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Chepelev et al.

3D Printing in Medicine (2018) 4:11


https://doi.org/10.1186/s41205-018-0030-y

RESEARCH Open Access

Radiological Society of North America


(RSNA) 3D printing Special Interest Group
(SIG): guidelines for medical 3D printing
and appropriateness for clinical scenarios
Leonid Chepelev1†, Nicole Wake2,3†, Justin Ryan4†, Waleed Althobaity1†, Ashish Gupta1†, Elsa Arribas5†,
Lumarie Santiago5†, David H Ballard6, Kenneth C Wang7, William Weadock8, Ciprian N Ionita9, Dimitrios Mitsouras1,
Jonathan Morris10, Jane Matsumoto10, Andy Christensen1, Peter Liacouras11, Frank J Rybicki1*, Adnan Sheikh1
and RSNA Special Interest Group for 3D Printing

Abstract
Medical three-dimensional (3D) printing has expanded dramatically over the past three decades with growth in
both facility adoption and the variety of medical applications. Consideration for each step required to create
accurate 3D printed models from medical imaging data impacts patient care and management. In this paper, a
writing group representing the Radiological Society of North America Special Interest Group on 3D Printing (SIG)
provides recommendations that have been vetted and voted on by the SIG active membership. This body of work
includes appropriate clinical use of anatomic models 3D printed for diagnostic use in the care of patients with
specific medical conditions. The recommendations provide guidance for approaches and tools in medical 3D
printing, from image acquisition, segmentation of the desired anatomy intended for 3D printing, creation of a
3D-printable model, and post-processing of 3D printed anatomic models for patient care.
Keywords: 3D printing, Appropriateness, Guideline, Quality, Radiology, Additive manufacturing, Anatomic model

Background Printing) described for proposed new billing codes, in-


In 2016, the Radiological Society of North America cluding those for the American Medical Association.
(RSNA) approved a proposal to create the Special Inter- These practice parameters and recommendations are
est Group on 3D Printing (SIG). This document fulfills not intended as comprehensive standards but do reflect
two of the original SIG goals: to provide recommenda- several salient aspects of clinical anatomic modeling and
tions towards consistent and safe production of 3D appropriateness. The guidelines subcommittee of the
printed models derived from medical images, and to de- SIG will maintain and devote the time and effort neces-
scribe a set of clinical scenarios for 3D printing is appro- sary to continually develop and update these recommen-
priate for the intended use of caring for patients with dations. This subcommittee is comprised of volunteer
those medical conditions. This project also fills a previ- members of the SIG who form the writing group of this
ously unmet need for practice parameters/guidelines re- document.
garding the clinical service of anatomic modeling (3D In its current state, medical 3D printing [1–576] has
been performed for a variety of patients, but without
* Correspondence: frybicki@toh.ca evidence-based appropriateness guidelines. For many

Leonid Chepelev, Nicole Wake, Justin Ryan, Waleed Althobaity, Ashish body parts, this document includes a comprehensive as-
Gupta, Elsa Arribas and Lumarie Santiago contributed equally to this work.
1
Department of Radiology and The Ottawa Hospital Research Institute, sessment of appropriateness from the medical literature,
University of Ottawa, Ottawa, ON, Canada supplemented by expert opinion (SIG members) when
Full list of author information is available at the end of the article

© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made.
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 2 of 38

there is a paucity of peer-review data. After the clinical approach at scoring. Consensus among members is used
decision to use 3D printing for patient care, there are when there is a paucity of evidence.
many subsequent steps, as reviewed in prior literature Each category was led by a separate writing group,
[563, 566, 577]. These include image acquisition, image composed of a small group of experts in that domain of
segmentation (demarcation of the desired 3D anatomy), medical imaging and 3D printing. The SIG Executive
creating 3D-printable file types for each segmented part, committee, led by the Guidelines Chairperson, formed
printing, and post processing of 3D medical models. the review panel. Ratings were generated via by a vote of
This document differs from existing works, including Special Interest Group members at in-person meetings.
case reports, small and larger studies, and 3D printing The results of the ratings follow the following 1–9 for-
review articles in the literature. This is not a review art- mat (with 9 being the most appropriate):
icle; instead of reviewing the literature or providing data
regarding the clinical utility of medical 3D printing, the 1–3, red, rarely appropriate: There is a lack of a clear
RSNA SIG has assembled a group of experts to begin to benefit or experience that shows an advantage over
provide consensus recommendations on the practice of usual practice.
medical modeling and 3D printing, particularly for prac- 4–6, yellow, maybe appropriate: There may be times
tice within healthcare facilities. 3D printing of anatomical when there is an advantage, but the data is lacking, or
models within a hospital has recently become recognized the benefits have not been fully defined.
as point-of-care manufacturing. These recommendations 7–9, green, usually appropriate: Data and experience
create a foundational outline to provide practice recom- shows an advantage to 3D printing as a method to
mendations for those steps required for medical 3D print- represent and/or extend the value of data contained in
ing, including image acquisition, segmentation, printing, the medical imaging examination.
post-processing, and model verification.
The supporting evidence was obtained through struc-
tured PubMed searches, as detailed in the Appendix. In
Methods
rare circumstances, supporting literature was recom-
Consensus methodology recommendations
mended directly by the members of the committee and
The recommendations regarding medical image acquisi-
was explicitly identified outside of the structured
tion, image data preparation and manipulation, generation
PubMed search results.
of 3D printed models, quality control, communication
A subset of applications of 3D printing, including in
with referring physicians, preoperative planning using 3D
congenital heart, vascular, craniomaxillofacial, musculo-
printed models, and considerations regarding materials
skeletal, genitounirary, and breast pathologies was se-
were discussed and summarized by members of the RSNA
lected for detailed review. All final components of this
Special Interest Group for 3D Printing during several
section were vetted and approved by vote of Special
meetings, including on August 31 (Silver Spring, MD) and
Interest Group members at several face-to-face meetings
December 1, 2017 (Chicago, IL) after review of the rele-
including on August 31 (Silver Spring, MD) and Decem-
vant medical 3D printing literature [1–576] and the local
ber 1, 2017 (Chicago, IL) as well as via internal posting
clinical practice of representative members of the Special
on the SIG member intranet.
Interest Group. Relevant recommendations were further
exposed to internal online discussion and summarized by
Results
a focused taskforce. The final recommendations were
Consensus methodology recommendations
reviewed and vetted by all RSNA 3D printing SIG
Medical image acquisition
members.
The most common medical imaging modalities for 3D
printing are computed tomography (CT) and magnetic
Appropriateness consensus guideline generation resonance imaging (MRI); however, any 3D imaging data-
The Special Interest Group has initiated the quality and set including sonography (e.g., echocardiography) may be
safety scholarship to identify those clinical situations for utilized as input data for segmentation. The international
which 3D Printing is considered an appropriate, and not standard format for these imaging files is Digital Imaging
appropriate, representation of the data contained in a and Communications in Medicine (DICOM). At this time,
medical imaging examination. These documents highlight DICOM images are not routinely sent directly to a 3D
appropriateness of medical 3D printing for clinical printer for printing, so medical images are segmented and
utilization, research, scientific, and informational pur- converted to a file type that is recognized by 3D printers.
poses. This work is loosely modeled after the American Common file types include Standard Tessellation Lan-
College of Radiology Appropriateness Criteria® [553, 554] guage (STL), OBJ, VRML/WRL, AMF, 3MF, and X3D.
in that the guidelines committee uses an evidence-based Once this functionality is implemented by 3D printing
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 3 of 38

vendors, picture archiving and communication system higher SNR, all else being equal, implies more trust-
(PACS) vendors, and at the point of care facility, it will worthy data for 3D printing. The CNR is the relationship
allow 3D files in the form of STLs, for example, to be of the signal intensity differences (the contrast) between
stored in a patient’s medical record. two regions, scaled to noise. High contrast between vari-
ous organs in the body is an important feature of med-
Spatial resolution and slice thickness Medical imaging ical imaging and is necessary to delineate structures for
data should have sufficient spatial resolution to accur- 3D printing. The SNR and CNR of images used for 3D
ately represent the anatomy to be modeled. The spatial printing should be comparable to, or superior to,
resolution of an imaging method refers to the smallest those for “3D visualization”, defined as the compre-
resolvable distance between two different objects or two hensive ensemble of manipulation of a volumetric
different features of the same object. Low spatial reso- data set for viewing on a 2D surface such as a com-
lution techniques will be unable to differentiate two ad- puter monitor [563].
jacent structures that are close together and have similar If the SNR and/or CNR are inconsistent, or subopti-
tissue properties. When the intent to produce a 3D mal, the risks of inaccurate segmentation must be
model is known prior to a medical imaging procedure, weighed against those of rescanning the patient. Regard-
the image acquisition should be tailored so that the anat- ing high noise data, a judgment call must be made to de-
omy in the intended 3D model can be adequately visual- termine whether the segmentation operator is capable of
ized. The optimal spatial resolution will depend on the delineating the data (e.g. in the case of a cone beam CT
anatomy being imaged. image series).
Slice thickness, which influences the spatial resolution In CT, the X-ray tube voltage may also be adjusted to
and image noise (discussed in the next section), can also be maximize the signal. A lower kV can be used to increase
optimized depending on the intended use. In general, this the enhancement of iodine contrast when building vas-
means that the smallest anatomy of interest should be cap- cular models. In addition, the raw data reconstruction
tured on multiple sequential DICOM images of a particular parameters selected may affect the appearance of specific
series. For example, if the anatomy of interest measures anatomical structures. For example, the reconstruction
3 mm, it would be desirable for this anatomy to be cap- kernel (image filter) impacts both the spatial resolution
tured on at least 3 sequential image slices; therefore, the and image noise, which must be balanced, based on the
slice thickness should be no greater than 1 mm, and prefer- application. Typically, kernel options range from “sharp”
ably smaller. If images are acquired with a large slice thick- to “smooth.” Sharpening filters increase edge sharpness
ness, stair-step boundaries may be seen in the 3D model. at a cost of increasing noise while smoothing filters re-
For CT, in combination with scan distance, consider- duce noise content in images by also decrease edge
ation may be given regarding collimation (the thickness sharpness. For models with fine structures, such as the
of the X-ray beam) and overlap. Typically, the scan dis- temporal bone, a sharp kernel is preferred; and for lar-
tance and collimation are the same; however, if the slice ger, low contrast models, a smooth kernel is more ap-
distance is smaller than the collimation, there will be an propriate. CT is considered the imaging modality of
overlap which may lead to improved results. Cone Beam choice for bone imaging and is often used to produce
CT has technical differences with conventional CT, and 3D anatomical models of hard tissue structures such as
often results in a lower patient radiation exposure and bone. In MRI, the SNR may be improved by performing
subsequently less image contrast that typical clinical CT a volume acquisition (at the expense of time), decreasing
images. Image artifacts and consistency of SNR through- noise by reducing the bandwidth, altering the echo time
out the scan can also limit studies. For MRI, voxels may or repeat time, increasing the FOV, decreasing the
be isotropic or rectangular solids and the resolution may matrix size, or increasing the slice thickness.
be different in the three dimensions. The size of the
voxel depends on the matrix size, the field of view Image artifact The sub-volume of the imaging dataset
(FOV), and the slice thickness. that will be 3D printed is defined in this document as
In some clinical scenarios, there are patients for which the printing Region of Interest (ROI). All medical images
suboptimal imaging data is available, but a separate ac- contain artifact, and image processing steps should be
quisition is contraindicated. If superior spatial resolution taken to minimize artifact. The ROI should be small
is preferred and CT data is required, that benefit should enough to enable confident segmentation for 3D print-
be weighed against the risk of delivering more radiation ing. There are cases for which medical interpretation is
to the patient. possible (see Image interpretation Section), but 3D
printing can be limited by the presence of artifact, mo-
Signal to Noise Ratio (SNR) and Contrast to Noise tion, or other spatial or noise limitations in DICOM im-
Ratio (CNR) The SNR is a metric of image quality. A ages. When this is the case, we recommend that the
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 4 of 38

model be annotated with documentation of those parts SIG recommends that software used for segmentation is
of the ROI where segmentation quality may be limited. FDA cleared to produce 3D Printed models suitable for
diagnostic use, specifically using the FDA definition of
Image interpretation Medical images acquired for a diagnostic use and noting that FDA cleared software for
clinical indication should be interpreted with the inter- 3D printed models will also include machines and mate-
pretation being incorporated into the patient medical rec- rials validated for this intended use. At the time of
ord. The interpretation should include the ROI being manuscript submission, the FDA has approved one
considered for printing. Often, interpretation of the ROI complete system, consisting of software through the
incorporates 3D visualization to enable or enhance diag- printing process, for medical model production.
nosis. Examples of 3D visualization include multi-planar
reformatting, maximum intensity projections, and volume File storage and descriptors
rendering. Such interpretations are currently billable in Files stored within a repository should contain or be
the United States under CPT codes 76376 and 76377. linked to a set of corresponding descriptors, including
those pertaining to image acquisition and further im-
Image data preparation and manipulation aging processing. Descriptors should be supported by
Image segmentation standardized terminology from a consensus vocabu-
Image segmentation is necessary to create 3D printable lary; the SIG acknowledges that this vocabulary repre-
files from medical images. The segmentation process, sents a current, unmet need. If the descriptors are
which subdivides medical images into anatomical re- not within digital files, this information should be
gions, typically begins by importing a set of DICOM im- otherwise archived.
ages into dedicated image post-processing software.
Anatomical regions are selected using a combination of Reference to file manipulation and alteration
automated and semi-automated tools. Once the desired Data from medical images undergo alterations in the
ROI for 3D printing has been selected, data is interpo- design of the physical model. These changes have
lated and a surface-based 3D model which describes the been categorized into Minor and Major alterations
3D geometry of that volume is calculated. To date, the [578], with the latter generally representing changes
most common, widely used, and accepted file format for that could impact clinical care. When modifications
medical 3D printed objects is the STL file. include major changes, the operator should verify that
STL files are composed of triangular faces, and the both the digital file and 3D printed model is labeled/
number of these faces can affect anatomical accuracy of identified appropriately.
a model. Each lab should determine the appropriate
number of faces/triangles for their medical models to Generation of 3D printed model
adequately represent anatomy. Operators should be 3D printing
aware of any reduction, smoothing, or further file ma- There are many different 3D printing technologies, each
nipulation or optimization within the segmentation soft- differing in the way that the final 3D printed model is
ware when creating and exporting the STL file. created. When 3D printed models are generated from
The contours of the STL file should be routinely medical images, the resolution of the 3D printer should
checked against the source medical imaging data; typical be equal to, or superior to that of the clinical images
segmentation software packages allow the final STL to used to segment the model. Similar to the DICOM ac-
be re-imported and its contours displayed over the ori- quisition stage, it is preferable that printed layers be a
ginal DICOM images. This option can be used to verify multiplier of the smallest geometry of interest. For ex-
the surface accuracy of an anatomical model STL file. ample, if the smallest anatomical object of interest on
Additional file formats noted above should also meet the the 3D model is 1 mm, this object should be printed on
same criteria. at least 3 layers of the model. Due to the nature of med-
ical models, and the need for sub-millimeter accuracy, a
Segmentation and Computer Aided Design (CAD) software layer thickness of no more than one-third of a milli-
Medical image processing software is required to gener- meter is recommended, and preferably less than or equal
ate a file format amenable to 3D printing. The RSNA 3D to one-eighth of a millimeter. In addition to the layer
printing SIG concurs with the FDA that software that thickness of the 3D printing hardware, the in-plane (x-y)
has been favorably evaluated by the FDA be used to resolution should be known, with a target of less than
translate medical images into formats amenable to 3D one-quarter of a millimeter. The values above are global
printing for all aspects of patient care, defined by the recommendations may not be applicable in all cases. If a
SIG as all interactions with healthcare professionals, or model requires a higher or lower accuracy, these param-
patients and their families, related to medical care. The eters should be modified accordingly.
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 5 of 38

The medical model should include a patient identifier inaccuracies. Some examples of quantitative inspections
or an internal unique identification number that can be could include measurements of a test specimen, mea-
tracked back to the patient and date of the image acqui- surements of the model, or scanning and comparing the
sition. Labels can be incorporated (3D printed) into the model back to the original DICOM data sets.
model itself. Labels should be externally attached to the
model if size or location does not allow for printed label- The U.S. Food and Drug Administration (FDA)
ing. Printed models are assumed to be of anatomic size The U.S. Food and Drug Administration (FDA) en-
(1:1) unless a scaling factor is otherwise noted. Add- sures the safety and efficacy of personalized devices
itional identifiers such as model sidedness (left, right) in the United States of America. 3D Printing falls
should be noted, as appropriate. Institutional guidelines under the auspices of The Center for Devices and
should be used to verify models are free of protected Radiological Health (CDRH). There have been four
health information, or models are handled appropriately FDA benchmarks related to 3D printing and medical
in accordance to Health Insurance Portability and Ac- devices from 2014 to 2018.
countability Act (HIPAA) guidelines. First, in October 2014, the FDA held a public work-
shop entitled “Additive Manufacturing of Medical De-
Post-processing printed models vices: An Interactive Discussion on the Technical
Post-processing steps should not alter the intended Considerations of 3D Printing”. Second, the FDA pub-
morphology and desired accuracy of the part, but in- lished “Additively Manufactured Medical Products –
stead should only enhance the utility (including clarity The FDA Perspective” [579]. Third, in December 2017,
and transparency) and/or durability of the model. It the FDA published “Technical Considerations for Addi-
should be noted that finishing may slightly alter the di- tive Manufactured Devices” [580]. This perspective in-
mensional accuracy of a part, but this variation should cluded insights regarding 3D printing data manipulation
be minimal (or within the desired global accuracy of the and hardware for modeling patient-specific anatomy.
part) and the benefits (for example: strength and clarity) Fourth, the FDA commented on the publication “Main-
should outweigh the dimensional change. All support taining Safety and Efficacy for 3D Printing in Medicine”
materials and residual manufacturing materials and/or [578]. This paper uses a similar, logical 3-step format of
substances should be removed as completely as possible. these consensus recommendations, and then develops
If all supporting material is not capable of being re- different suggestions for regulatory models that depend
moved, this should be noted and presented to the on how much, if at all, the anatomical data is modified
requesting provider. Should the model be damaged ei- before 3D printing. On August 31st, 2017, the RSNA
ther during or after post-processing and cleaning, repairs SIG and the FDA engaged in a joint meeting to discuss
should be performed in a manner that reconstitutes the 3D printed anatomic models. The intended output of
quality to which the original model adhered. If these re- this meeting is a co-published white paper that will form
pairs are not possible, the model should be reprinted. Any the next benchmark.
damage should be noted to the provider and the option to
reprint should be presented. Cleaning solution concentra- Quality control program
tion and saturation levels should be monitored and main- Due to environmental factors and material properties,
tained in accordance to manufacture recommendations. model morphology is expected to change over time. As
part of a complete quality control program, 3D printers
Model inspection should undergo regular accuracy testing, including test
The model should be inspected by the 3D printing la- prints, preventative maintenance, and recalibration [581,
boratory before clinical use. For cases where the model 582]. Laboratories may develop a process using a
may be limited by a known image artifact, the model will phantom to ensure regular quality standards for their
be noted with any areas of concern. Qualitative and/or printers. If the reference standard is known or assumed,
quantitative measures to confirm that the 3D printed mathematical operations [583] can be applied equally to
model matches the desired input data will be taken, in- those volumes in the ROI to determine the overall ac-
cluding but not limited to expert subjective assessment curacy of the model, including not only potential manual
and objective fitting to the original volume submitted errors from segmentation, but also generation of the
for printing. This can be done on a per part basis, per final data set including digital post-processing steps such
build basis, or in accordance with an additional internal as smoothing.
protocol of the 3D lab. Some examples of qualitative as-
sessments could include comparing the model to a Delivery and discussion with referring physicians
digital representation or printed picture of the model 3D printed models represent an advanced form of com-
and inspecting the model for printing imperfections or munication of the data in medical images, and may
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 6 of 38

include the summation of data from multiple sources. peer-review data, to define and support the use of 3D
Extensive multidisciplinary teaching opportunities for printing for patients with a variety of conditions, in-
3D printing have been realized [584–586]. Physicians cluding congenital heart, vascular, craniomaxillofacial,
should have an opportunity to discuss the salient fea- musculoskeletal, genitounirary, and breast pathologies
tures and intended use of all models. Any concerns (Table 1).
about the model or segmentation process, if not dis-
cussed previously, should be noted to the provider at the Discussion
time of delivery. Where possible, annotations detailing Reviews that include the types of 3D printers commonly
critical points of model anatomy should be stored both used in medicine have been published [563, 584]. Re-
within the digital record of the model, and physically garding image post-processing and software, several tu-
placed on the 3D printed model. One example is annota- torials are available for step-by-step training. The
tion of a subtle fracture that may not otherwise be following discussion includes the specific descriptions
represented in either or both, the segmented, or the 3D from the SIG writing group for each clinical group of
printed model. clinical scenarios considered for appropriateness.

Pre-operative planning Congenital heart disease


“Pre-operative planning” with 3D printing refers to vir- Congenital heart diseases (CHD) are the most common
tual surgical planning (also called digital templating, significant birth defects. Substantial literature supports
digital surgical planning, virtual planning, computerized the benefit of 3D printing for patients with congenital
planning, computer-assisted surgical simulation). This heart disease [1–7]. Regarding improved outcomes, pre-
detailed planning of the intervention occurs in the cise preoperative understanding of the complex anatomy
digital space. There are times when the simulation itself from a printed model may obviate or shorten lengthy ex-
is the end product, and the interventionist acquires valu- ploration, and therefore operation and cardiopulmonary
able information regarding patient anatomy and medical bypass time can be reduced.
devices to be used to increase confidence and knowledge These recommendations utilize and conform to the
before surgery. For these cases the digital plan is trans- CHD nomenclature defined by the European Association
ferred to patient care by way of 3D printed templates, for Cardio-Thoracic Surgery / Society of Thoracic Sur-
guides, or models. This type of planning usually involves gery (EACTS-STS) version of the International Pediatric
major changes to the digital model while utilizing ori- and Congenital Cardiac Code (IPCCC), except as where
ginal patient contours. This necessitates the systematic noted otherwise. The clinical scenarios defined by the
application of the 3D printing recommendations out- IPCCC include the following: Septal Defects, Pulmonary
lined above to the models used for virtual surgical plan- Venous Anomalies, Cor Triatriatum, Pulmonary Venous
ning as a minimum requirement. Stenosis, Right Heart Lesions, Left Heart Lesions, Single
Ventricle, Transposition of the Great Arteries, DORV,
Material biocompatibility, cleaning, and sterilization DOLV.
For anatomical models and surgical guides/templates/ Structured searches were performed using the US Na-
jigs potentially entering a surgical field, material biocom- tional Library of Medicine (PubMed), which enabled the
patibility, cleaning, and sterilization are vitally important. querying and retrieval of appropriate clinical documents
The details are beyond the scope of this document. supporting the appropriateness of 3D printing-enabled
However, biocompatibility of materials depends on sev- technologies for each specific diagnosis. The search re-
eral factors including base material, the 3D printing sults were reviewed by experts and some references were
process (and any variations), any post-processing tech- removed and some were relocated to different categor-
niques, and hospital cleaning and sterilization methods ies. As noted above, references outside of the structured
and requirements. Manufacturers should provide clean- searches were added but noted and approved by the
ing recommendations and specifications for materials writing group. As a general rule, the benefits of 3D
which have been formally tested for biocompatibility and printing to define and rehearse an intervention increase
sterility, and these specifications should be followed by with the overall degree of complexity of disease.
the facility. Additional internal sterilization policies may
exist depending on the hospital. Craniomaxillofacial pathologies
The International Classification of Diseases, Tenth Revision
Appropriateness of 3D printing (anatomic modeling) for (ICD-10) [555] descriptions and categorization were used
selected clinical scenarios to categorize the clinical scenarios for rating craniomaxillo-
This section provides evidence-based guidelines, supple- facial conditions. Four major groups were used as the start-
mented by expert opinion when there is a paucity of ing point; 1) Craniomaxillofacial Trauma, 2) Congenital
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 7 of 38

Table 1 Ratings Summary: Appropriateness Guidelines (scoring system defined in Methods) for patients who present with a variety
of medical conditions, and for whom 3D Printing is often considered
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 8 of 38

Table 1 Ratings Summary: Appropriateness Guidelines (scoring system defined in Methods) for patients who present with a variety
of medical conditions, and for whom 3D Printing is often considered (Continued)
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 9 of 38

Malformations, 3) Acquired/Developmental Deformities planning combined with patient-matched implants or


and 4) Neoplasms. Further sub-groups were formed under- templating is playing.
neath the major groupings. Additional clarification for
“simple” versus “complex” diagnoses within a particular Genitourinary pathologies
group was given based on inherent differences in appropri- The genitourinary conditions have been organized ana-
ateness ratings between subgroups of patients in these tomically, recognizing that common genitourinary inter-
groups. Further language describing each diagnostic group- ventions are largely based on anatomic considerations.
ing helps describe the difference between a simple and a The complication rate after major genitourinary surger-
complex case in each subcategory. ies is reflected in the complexity of the lesion. For
Structured searches were performed using the US example, more complex kidney tumors are associated
National Library of Medicine (PubMed), which en- with longer operative times, warm ischemia times, and
abled the querying and retrieval of appropriate clinical greater blood loss [559]. High kidney tumor complexity
documents supporting the appropriateness of 3D can also be correlated to the risk of major postoperative
printing-enabled technologies for a specific condition. complications requiring a secondary intervention [560].
The search results were reviewed by experts and There is a growing body of literature that supports the
some references were removed because they were not benefits to patients from 3D printed models. Specifically,
relevant. A small number of references were added 3D printed models may improve comprehension of anat-
because they were found to be relevant, but not omy and facilitate pre-surgical planning for complex sur-
appearing using the stated search string. As noted gical cases, ultimately reducing operation times and
above, these were vetted by the writing group before improving patient outcomes.
inclusion. Clinical scenarios that were only dental or This document describes and provides rating for the
only brain have not been included. The authors clinical scenarios related to 3D printing of genitourinary
recognize that these include many important clinical pathology [561, 562]. Structured searches were per-
scenarios of for 3D printing, and the goal is to in- formed using the US National Library of Medicine
clude them in upcoming documents. (PubMed), which enabled the querying and retrieval of
Craniomaxillofacial (CMF) conditions for the purposes appropriated clinical documents supporting the appro-
of this document encompass several different surgical priateness of 3D printing for a specific diagnosis. As a
specialties all working in the head and neck area with general rule, the benefits of 3D printing to define and re-
both pediatric and adult patients. These include oral and hearse a genitourinary intervention increases with the
maxillofacial surgery, craniofacial surgery, plastic sur- overall degree of complexity of the pathology that is rep-
gery, microvascular surgery, pediatric neurosurgery and resented by the physical model based on a medical im-
otolaryngology. Use of 3D printing-enabled technologies aging study performed in a radiology department.
to aid clinical care in the craniomaxillofacial area has
been seen from the very advent of 3D printing in the late Musculoskeletal pathologies
1980s [556, 557]. Even before the commercialization of The role of 3D printed models in addressing musculo-
stereolithography there were surgeons, engineers and re- skeletal pathologies can vary depending on a specific
searchers figuring out more manual ways of converting clinical scenario, ranging from aiding in informed con-
medical imaging datasets into 3D models [558]. The fit sent to use in preoperative planning. Custom fixation
seems clear, CMF surgery has both a functional compo- plates, surgical osteotomy guides and implants can also
nent, and for most cases an aesthetic component, where be generated from 3D data, allowing for virtual surgery
the form carries importance along with the functional and design of a custom implant that is modeled after the
restoration. In the CMF arena, the use of anatomical contralateral healthy side. In addition, mock surgeries
models of anatomy is primarily derived from CT and can be performed on the physical 3D models, allowing
MRI datasets, and also from an increasing volume of for more intuitive problem solving and measurements
cone beam CT datasets. Patient-specific anatomical preoperatively. Such planning alters surgical manage-
models are the baseline, but for many of these applica- ment for some patients, either by delaying intervention,
tions the value of these technologies has been found in or by suggesting an alternative approach. Pre-surgical
either, a) patient-matched implants (for instance tem- planning can also decrease operating room time and the
poromandibular joint reconstruction), or b) virtual sur- number of devices and tools that need to be tried and
gery combined with templates and guides (for instance subsequently wasted and/or re-sterilized. In this sense,
orthognathic surgery). The scenarios to follow were 3D printing has proven useful for demonstrating muscu-
thought of in this way, with some of them relying heavily loskeletal pathology and for planning interventions.
on anatomical models alone and some of them relying Based on the accumulating evidence, the use of 3D
with increasing importance on the role that digital printed models can positively impact numerous metrics
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 10 of 38

associated with musculoskeletal interventions, including patient specific 3D model for suitability before being de-
patient and physician satisfaction, operative time, blood ployed in patients.
loss, and the various direct and indirect costs associated Aortic surgeries, especially in the region of aortic arch
with patient-centered decision making regarding man- and upper abdominal aorta can be quite challenging due
agement of complex disease. At present, the musculo- to origin of branches, angulation and complex aneurysm
skeletal pathologies with potential and established 3D neck anatomy. 3D printed models have shown to im-
printing-enabled management have been broadly catego- prove surgeons’ understanding of anatomy and help pre-
rized into fractures, chronic osseous abnormalities, de- operative planning [485]. Further, 3D printed models
generative disorders, neoplastic pathologies, scoliosis, can potentially also be used to plan and simulate surgical
and miscellaneous specific applications including liga- and endovascular interventions on visceral aneurysms
mentous injury and heterotopic ossification. [502, 503]. These models can also be used for designing
[486] and testing [568, 576] endovascular devices like
Vascular pathologies catheters, coils, balloons, and stents.
3D printing has been shown to be useful for understand-
ing the vascular anatomy, evaluation of hemodynamics,
Breast pathologies
treatment planning (surgical and endovascular) as well
Breast cancer is the most common solid malignancy in
as preclinical testing of devices. It has also been used for
women in the United States [570]. The overall lifetime
medical education and procedural training on vascular
risk of developing breast cancer for women in the
models [563–566]. There are several clinical scenarios
United States is 12.4%. Advancements in diagnostic tests
for which 3D printing has been used in the care of pa-
and treatments have led to decreasing death rates of
tients with vascular disease. Because of the nature of
1.8% per year from 2005 to 2014 [570, 571]. Understand-
vascular pathology, dissection, aneurysm, and stenosis
ing the extent of disease at the time of diagnosis allows
are often treated with medical management and “watch-
appropriate staging and determination of prognosis and
ful waiting”; most patients follow this algorithm, and
survival, in addition to selection of suitable surgical op-
there is little to no role for 3D printing. However, some
tions [572]. Benefits from 3D printed models and its role
patients have a clinical presentation and non-invasive
as an aid to clinical care has been increasingly described
tests that warrant intervention, while others progress
in the literature. 3D printed models have the ability of
from watchful waiting to planned intervention. For many
depicting the extent of disease and relationships of sensi-
of these patients, 3D printing is appropriate. Of note,
tive anatomy, thereby possibly reducing operating time,
coronary 3D printing, and cardiac printing in general
enhancing utilization of new oncoplastic techniques, and
falls outside the scope of this document. These clinical
improving patient outcomes.
scenarios will be discussed in future documents.
Benign breast diseases are common and include a wide
Most aortic dissections are treated medically, and for
range of entities [573]. The most common of these en-
these patients there is no indication for 3D printing.
tities, fibrocystic change, is clinically observed in up to
However, 3D printing may be appropriate for planning
50% of women and found histologically in 90% of
intervention in complex dissections, and in particular
women [573]. Fibroadenomas are the next most com-
dissections that also have enlargement. Models have
mon benign breast disease occurring in 15–23% of
been used for planning and simulation of stent deploy-
women [574]. Surgical management of these entities
ment [495]. Simulation on models can help in identify-
may be needed in cases where cosmesis is altered or
ing the best projections for angiography, best catheter
when symptom relief is needed. Surgical management
and wire combinations to navigate the anatomy, in for
may impact developing breast tissue in young women
determining appropriate balloon and stent size as well as
leading to alterations in its proper development [575].
position.
Therefore, careful understanding of the anatomy may
Endovascular repair of complex aortic aneurysm in-
minimize the deleterious effects of surgery in benign
volving the origin of branches, extreme angulations,
breast disease.
complex neck anatomy, and short landing zones can be
quite challenging. Use of 3D printed models can aid un-
derstanding of complex anatomy, device selection, and Conclusions
design of prosthesis best suited for patient’s anatomy. 3D printing will play an increasingly important role in en-
These models have shown to be useful in planning pro- abling precision medicine. This document addresses the
cedures and increase operator confidence [491]. 3D clinical scenarios where pathology complexity necessitates
printed models have also been used to precisely place a transformation of clinical imaging data into a physical
fenestrations on stent grafts to treat complex aneurysms model. Adoption of common clinical standards regarding
[479, 567]. In addition, graft replicas can be tested on appropriate use, information and material management,
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 11 of 38

and quality control are needed to ensure the greatest pos- PubMed search: ((3D printing) AND truncus) OR
sible clinical benefit from3D printing. ((rapid prototyping) AND truncus)
This work provides the first comprehensive Results: None
literature-based guideline document regarding the im- Partial Anomalous Pulmonary Venous Connection
plementation of 3D printing in clinical practice and de- (PAPVR)
tails the appropriate scenarios for numerous clinical PubMed search: ((3D printing) AND (Anomalous pul-
applications of 3D printing. It is anticipated that this monary)) OR ((rapid prototyping) AND (Anomalous
consensus guideline document, created by the members pulmonary)) OR ((3D printing) AND TAPVR) OR
of the RSNA 3D printing special group, will provide the ((rapid prototyping) AND TAPVR) OR ((3D printing)
initial reference for method and clinical application AND PAPVR) OR ((rapid prototyping) AND PAPVR)
standardization. The document and will be substantially Results: None
expanded and refined, based on expanding clinical Total Anomalous Pulmonary Venous Connection
applications. (TAPVR)
PubMed search: ((3D printing) AND (Anomalous pul-
monary)) OR ((rapid prototyping) AND (Anomalous
Appendix pulmonary)) OR ((3D printing) AND TAPVR) OR
Search Methodology and Search Results ((rapid prototyping) AND TAPVR) OR ((3D printing)
Structured searches were performed using the US Na- AND PAPVR) OR ((rapid prototyping) AND PAPVR)
tional Library of Medicine (PubMed), which enabled the Results: None
querying and retrieval of appropriated clinical docu- Cor Triatriatum
ments regarding the appropriateness of 3D printing in PubMed search: ((3D printing) AND (Cor Triatria-
each of the scenarios. tum)) OR ((rapid prototyping) AND (Cor Triatriatum))
Congenital Heart Disease (Retrieved August 2017) Results: None
Atrial Septal Defect (ASD): Large; small or spontan- Pulmonary Venous Stenosis
eously closed PubMed search: ((3D printing) AND (pulmonary ven-
PubMed Search: ((3D printing) AND (ASD)) OR ous stenosis)) OR ((rapid prototyping) AND ((pulmonary
((rapid prototyping) AND (ASD)) OR ((3D printing) venous stenosis)) OR ((3D printing) AND (pulmonary
AND (atrial septal defect)) OR ((rapid prototyping) vein stenosis)) OR ((rapid prototyping) AND ((pulmon-
AND (atrial septal defect)) ary vein stenosis))
Results: [1–7] Results: None
Ventricular Septal Defect (VSD): complex; large Tetralogy of Fallot (TOF): NOS; accompanied with
(noncomplex); small major aortopulmonary collateral arteries
PubMed Search: ((3D printing) AND (VSD)) OR PubMed search: ((3D printing) AND TOF) OR ((rapid
((rapid prototyping) AND (VSD)) OR ((3D printing) prototyping) AND TOF) OR ((3D printing) AND tetral-
AND (ventricular septal defect)) OR ((rapid prototyping) ogy) OR ((rapid prototyping) AND tetralogy)
AND (ventricular septal defect)) Results: [11, 17] Outside of Search, suggested by SIG
Results: [8–16] Members: [18]
Atrioventricular Canal (AV Canal) Tricuspid Valve Disease and Ebstein’s Anomaly
PubMed Search: ((3D printing) AND (AVSD)) OR PubMed search: ((3D printing) AND ebstein) OR ((rapid
((rapid prototyping) AND (AVSD)) OR ((3D printing) prototyping) AND ebstein) OR ((3D printing) AND
AND (atrioventricular septal defect)) OR ((rapid proto- ebsteins) OR ((rapid prototyping) AND ebsteins) OR ((3D
typing) AND (atrioventricular septal defect)) OR ((3D printing) AND ebstein’s) OR ((rapid prototyping) AND
printing) AND (AV Canal)) OR ((rapid prototyping) ebstein’s) OR ((3D printing) AND (tricuspid valve disease))
AND (AV Canal)) OR ((3D printing) AND (atrioven- OR ((rapid prototyping) AND (tricuspid valve disease))
tricular canal)) OR ((rapid prototyping) AND (atrioven- Results: None
tricular canal)) RVOT Obstruction and/or Pulmonary Stenosis
Results: None PubMed search: ((3D printing) AND (RVOT obstruc-
Aortopulmonary window (AP Window) tion)) OR ((rapid prototyping) AND (RVOT obstruc-
PubMed Search: ((3D printing) AND (AP window)) tion)) OR ((3D printing) AND (pulmonary stenosis)) OR
OR ((rapid prototyping) AND (AP Window)) OR ((3D ((rapid prototyping) AND (pulmonary stenosis))
printing) AND (aortopulmonary window)) OR ((rapid Results: [12, 16]
prototyping) AND (aortopulmonary window)) Hypoplastic Left Heart Syndrome
Results: None PubMed search: ((3D printing) AND HLHS) OR
Truncus Arteriosus ((rapid prototyping) AND HLHS) OR ((3D printing)
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 12 of 38

AND (hypoplastic left)) OR ((rapid prototyping) AND Results: [23, 28]


(hypoplastic left)) Transposition of the Great Arteries (dextro-TGA)
Results: [9–11, 19–24] PubMed search: ((3D printing) AND (D-TGA)) OR
Shone’s Syndrome ((rapid prototyping) AND (D-TGA)) OR ((3D printing)
PubMed search: ((3D printing) AND shones) OR AND DTGA) OR ((rapid prototyping) AND DTGA) OR
((rapid prototyping) AND shones) OR ((3D printing) ((3D printing) AND (dextro-transposition)) OR ((rapid
AND shone’s) OR ((rapid prototyping) AND shone’s) prototyping) AND (dextro-transposition)) OR ((3D
Results: None printing) AND (d-transposition)) OR ((rapid prototyp-
Double Inlet Left Ventricle ing) AND (d-transposition))
PubMed search: ((3D printing) AND DILV) OR ((rapid Results: [29]
prototyping) AND DILV) OR ((3D printing) AND Double Outlet Right Ventricle
(double inlet left)) OR ((rapid prototyping) AND (double PubMed search: ((3D printing) AND DORV) OR
inlet left)) ((rapid prototyping) AND DORV) OR ((3D printing)
Results: None AND (double outlet)) OR ((rapid prototyping) AND
Double Inlet Right Ventricle (double outlet))
PubMed search: ((3D printing) AND DIRV) OR Results: [9–12, 19, 20, 23, 24, 30]
((rapid prototyping) AND DIRV) OR ((3D printing) Double Outlet Left Ventricle
AND (double inlet right)) OR ((rapid prototyping) AND PubMed search: ((3D printing) AND DOLV) OR
(double inlet right)) ((rapid prototyping) AND DOLV) OR ((3D printing)
Results: None AND (double outlet left)) OR ((rapid prototyping) AND
Mitral atresia (double outlet left))
PubMed search: ((3D printing) AND (mitral atresia)) Results: None
OR ((rapid prototyping) AND (mitral atresia)) Craniomaxillofacial (Retrieved August 2017)
Results: None Skull Fractures: Fractures of the cranium include the
Tricuspid atresia frontal bone, frontal sinus, parietal, sphenoid, temporal,
PubMed search: ((3D printing) AND (tricuspid atre- occipital and mastoid bone. Simple fractures would be
sia)) OR ((rapid prototyping) AND (tricuspid atresia)) non-displaced and may not need surgery. Complex frac-
Results: None tures may be comminuted and most likely require sur-
Unbalanced AV canal gery early for decompression and/or later for cranial
PubMed search: ((3D printing) AND unbalanced) OR reconstruction. Any violation of the dura or brain re-
((rapid prototyping) AND unbalanced) quires immediate surgery. ICD-10: S02.0 Fracture of
Results: None Vault of Skull, S02.1 Fracture of Base of Skull
Single ventricle (general) PubMed Search: ((3D Printing) AND (Skull Fracture))
PubMed search: ((3D printing) AND SV) OR ((rapid OR ((Rapid Prototyping) AND (Skull Fracture))
prototyping) AND SV) OR ((3D printing) AND (single ven- Results: [31–43]
tricle)) OR ((rapid prototyping) AND (single ventricle)) Facial Fractures: Description: Facial fractures include
Results: [25–27] fractures of the maxilla, zygoma, nasal bones, and frontal
Congenitally Corrected TGA (levo-TGA) bone in addition to the orbit, which is composed of the
PubMed search: ((3D printing) AND (L-TGA)) OR orbital surface of the maxillary bone, lamina papyracea
((rapid prototyping) AND (L-TGA)) OR ((3D printing) of the ethmoid bone, lacrimal bone, greater and lesser
AND LTGA) OR ((rapid prototyping) AND LTGA) OR wings of the sphenoid bone, orbital process of the zygo-
((3D printing) AND (levo-transposition)) OR ((rapid matic bone, the orbital process of the palatine bone, and
prototyping) AND (levo-transposition)) OR ((3D print- the pars orbitalis of the frontal bone. Non-displaced
ing) AND (l-transposition)) OR ((rapid prototyping) fractures often heal uneventfully and may be managed
AND (l-transposition)) OR ((3D printing) AND CCTG non-surgically. Displaced fractures---either linear or
A) OR ((rapid prototyping) AND CCTGA) OR ((3D comminuted---generally require operative repair to
printing) AND (CC-TGA)) OR ((rapid prototyping) avoid functional or esthetic complications. High energy
AND (CC-TGA)) OR ((3D printing) AND (congenitally injuries, such as those seen with unrestrained motor ve-
corrected transposition)) OR ((rapid prototyping) AND hicle collisions or gunshot wounds, often result in
(congenitally corrected transposition)) OR ((3D printing) greater three-dimensional disruption and displacement
AND (congenitally corrected transposition)) OR ((rapid than low energy injuries, which are often the result of
prototyping) AND (congenitally corrected transpos- assaults and ground level falls. Patient-matched implants
ition)) OR ((3D printing) AND (CC-transposition)) OR may be required for reconstruction of complex injuries,
((rapid prototyping) AND (CC-transposition)) particularly those involving the orbit and zygoma.
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 13 of 38

ICD-10: S02.2 Fracture of Nasal Bones, S02.3 Fracture of Printing) AND (Hypertelorism)) OR ((Rapid Prototyping)
Orbital Floor, S02.4 Fracture of Malar, Maxillary and AND (Hypertelorism)) OR ((3D Printing) AND (Plagioce-
Zygoma Bones phaly)) OR ((Rapid Prototyping) AND (Plagiocephaly)) OR
PubMed Search: ((3D Printing) AND (Facial Fracture)) ((3D Printing) AND (Facial Asymmetry)) OR ((Rapid
OR ((Rapid Prototyping) AND (Facial Fracture)) Prototyping) AND (Facial Asymmetry))
Results: [31–43] Results: [32, 33, 53, 60, 88–122]
Mandible Fractures: Mandible fractures include frac- Cleft Lip & Palate: Cleft lip and cleft palate are birth
tures to the condyle, ramus, coronoid process, mandibu- defects that affect the upper lip, nose, alveolus, soft and
lar angle, body of the mandible or symphysis. Linear or hard palate. The problem can range from a small
fractures are likely to be less three-dimensional as com- notch in the lip (simple) to a unilateral or bilateral
pared to comminuted fractures, which are often signifi- complete or incomplete involvement of lip, alveolar
cantly displaced. Depending on the complexity of the bone, soft and hard palate with displacement of the pal-
fracture, the degree of dislocation and the location, open atal muscles. The functional problems associated with
reduction and internal fixation with titanium plates and cleft lip and/or palate include problems with eating,
screws may be required. Secondary reconstruction of speech, and eustachian tube malfunction and middle ear
complex post-traumatic deformity may also require effusion requiring grommet tube insertion into the ear
patient-matched implants. ICD-10: S02.6 Fracture of drum. Growth may be abnormal requiring jaw surgery.
Mandible (body), S02.61 Fracture of Condylar Process of Surgery involves alveolar bone grafting, lip and nose re-
Mandible, S02.62 Fracture of Subcondylar Process of pair, palate repair including palatal muscle repair and
Mandible, S02.63 Fracture of Coronoid Process of Man- closure of the palatal cleft. Later secondary surgery may
dible, S02.64 Fracture of Ramus of Mandible, S02.65 be necessary. ICD-10: Q35.1 Cleft Hard Palate, Q35.3
Fracture of Angle of Mandible, S02.66 Fracture of Sym- Cleft Soft Palate, Q35.5 Cleft Hard Palate and Cleft Soft
physis of Mandible Palate, Q36.0 Cleft Lip, Bilateral, Q36.1 Cleft Lip, Me-
PubMed Search: ((3D Printing) AND (Mandible Frac- dian, Q36.9 Cleft Lip, Unilateral
ture)) OR ((Rapid Prototyping) AND (Mandible Fracture)) PubMed Search: ((3D Printing) AND (Cleft Palate))
Results: [32, 35–37, 44–69] OR ((Rapid Prototyping) AND (Cleft Palate)) OR ((3D
Congenital Malformations of Skull & Facial Bones: Printing) AND (Cleft Lip)) OR ((Rapid Prototyping)
Syndromal or non-syndromal cases characterized mainly by AND (Cleft Lip))
anomalies which may vary from mild to severe and may Results: [123–135]
present with asymmetric involvement of the skull and facial Ear Malformations: Malformations of the ear can in-
bones. In simple craniosynostosis one or more sutures may clude missing portions of the ear, misshapen portions of
be involved. In complex or syndromal craniosynostosis pa- the ear, malpositioned ears, large ears (macrotia) or
tients may be programmed genetically to grow abnormally small/missing ears (microtia). Simple cases may require
and require repeated surgical operations until growth is surgical excision of extra tissue or a procedure to restrict
complete including cranial vault, facial-orbital advancement prominence. Complex cases are typically very complex
including maxillae and mandible surgery after eruption of surgical cases and may require total auricular recon-
the secondary dentition. Congenital birth defects character- struction with autogenous tissues. ICD-10: Q17.1
ized by incomplete development or absence of face struc- Macrotia, Q17.2 Microtia
tures, usually affecting one side of the face. Simple cases PubMed Search: ((3D Printing) AND (Microtia)) OR
would include those such as positional plagiocephaly which ((Rapid Prototyping) AND (Microtia)) OR ((3D Print-
most likely involve non-surgical treatment. Complex cases ing) AND (Macrotia)) OR ((Rapid Prototyping) AND
for facial reconstruction (for craniofacial macrosomia or (Macrotia))
hypertelorism, for instance) or total vault reconstruction in Results: [136–146]
an infant require extensive planning and surgical care. Osteochondroplasias: Osteogenesis imperfecta (OI) is
Secondary reconstruction in the growing child or adult a genetic disorder in which bones break easily. Fibrous
may require continued surgical care as the skeleton de- Dysplasia of the craniomaxillofacial skeleton may result
velops further before reaching skeletal maturity. ICD-10: in benign overgrowth of tissue which is fibrous and lack-
Q75.0 Craniosynostosis, Q75.1 Craniofacial Dysostosis, ing calcium. Fibrous dysplasia may impact skeletal ap-
Q75.2 Hypertelorism, Q75.3 Macrocephaly, Q75.4 pearance but the complex cases begin to compromise
Mandibulofacial Dysostosis, Q75.5 Oculomandibular other vital structures/organs such as the optic nerve and
Dysostosis, Q67.0 Congenital Facial Asymmetry, Q67.3 the brain. Simple cases of OI may include bony fractures
Plagiocephaly which will be handled such as in the Trauma (Group A,
PubMed Search: ((3D Printing) AND (craniosynostosis)) II or III classification). Complex fibrous dysplasia cases
OR ((Rapid Prototyping) AND (craniosynostosis)) OR ((3D can be very difficult surgically and require three-
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 14 of 38

dimensional removal/sculpting of the mass while paying simple excision. Complicated and destructive lesions
close attention to close-by vital structures. Surgical re- may involve segmental resection of the mandible or
placement of tumor resection can be very complex. maxilla and reconstruction, typically with autogenous
ICD-10: Q78.0 Osteogenesis Imperfecta, Q78.1 Polyos- tissues supported by rigid fixation. Secondary recon-
totic Fibrous Dysplasia struction with patient-matched implants or further free
PubMed Search: ((3D Printing) AND (Osteogenesis flaps may be required for complex cases. ICD-10: M27.1
Imperfecta)) OR ((Rapid Prototyping) AND (Osteogenesis Giant Cell Granuloma, Central, M27.2 Inflammatory
Imperfecta)) OR ((3D Printing) AND (Fibrous Dysplasia)) Conditions of Jaws (osteoradionecrosis, osteomyelitis,
OR ((Rapid Prototyping) AND (Fibrous Dysplasia)) others), M27.3 Alveolitis of Jaws
Results: [53, 147–156] PubMed Search: ((3D Printing) AND (Giant Cell
Dentofacial Anomalies Including Malocclusion: Granuloma Jaw)) OR ((Rapid Prototyping) AND (Giant
Dentofacial anomalies can include over or undergrowth Cell Granuloma Jaw)) OR ((3D Printing) AND (Osteora-
of either the upper jaw (maxilla) or the lower jaw (man- dionecrosis)) OR ((Rapid Prototyping) AND (Osteora-
dible). Malocclusion happens when the teeth are not ap- dionecrosis)) OR ((3D Printing) AND (Osteomyelitis))
proximating in a way that allows for normal function OR ((Rapid Prototyping) AND (Osteomyelitis)) OR ((3D
and can be any combination of one jaw being smaller, Printing) AND (Alveolitis)) OR ((Rapid Prototyping)
larger or asymmetric as compared to the other. Simple AND (Alveolitis))
cases may involve surgical repositioning of only one of Results: [150, 202–207]
the jaws and typically symmetrical movements. Complex Temporomandibular Joint Disorders: Temporoman-
cases typically involve bimaxillary surgery with highly dibular joint disorders relate to a variety of conditions
complex movements of both jaws based upon the clin- affecting the anatomic and functional characteristics of
ical and radiographic examination. ICD-10: M26.01 the temporomandibular joint. Factors contributing to
Maxillary hyperplasia, M26.02 Maxillary hypoplasia, the complexity of temporomandibular diseases are its re-
M26.03 Mandibular hyperplasia, M26.04 Mandibular hy- lation to dentition and mastication and the symptomatic
poplasia, M26.05 Macrogenia, M26.06 Microgenia, effects in other areas which account for referred pain to
M26.07 Excessive tuberosity of jaw, M26.1 Anomalies of the joint. Common diseases are developmental abnor-
Jaw-Cranial Base Relationship, M26.11 Maxillary asym- malities, trauma, subluxation, luxation, arthritis, and
metry, M26.211 Malocclusion Angle Class I, M26.212 neoplasia. Simple cases may not need surgical interven-
Malocclusion Angle Class II, M26.213 Malocclusion tion or may require arthroscopy. Cases that involve loss
Angle Class III, M26.22 Open Occlusal Relationship, or gain of vertical dimension in the condyle and result
M26.220 Open Anterior Occlusal Relationship, M26.221 in loss of jaw function (malocclusion or range of mo-
Open Posterior Occlusal Relationship tion) may require joint total joint replacement and will
PubMed Search: ((3D Printing) AND (Orthognathic often rely on patient-matched implants for reconstruc-
Surgery)) OR ((Rapid Prototyping) AND (Orthognathic tion of the joint(s). Complex conditions such as
Surgery)) OR ((3D Printing) AND (Maxillary Hyperpla- ankylosis of the joint require careful surgical interven-
sia)) OR ((Rapid Prototyping) AND (Maxillary Hyperpla- tion to avoid surrounding vital structures such as nerves
sia)) OR ((3D Printing) AND (Maxillary Asymmetry)) and vasculature. ICD-10: M26.601 Right temporoman-
OR ((Rapid Prototyping) AND (Maxillary Asymmetry)) dibular joint disorder, unspecified, M26.602 Left tem-
OR ((3D Printing) AND (Malocclusion)) OR ((Rapid poromandibular joint disorder, unspecified, M26.603
Prototyping) AND (Malocclusion)) OR ((3D Printing) Bilateral temporomandibular joint disorder, unspecified
AND (Anterior Open Bite)) OR ((Rapid Prototyping) PubMed Search: ((3D Printing) AND (Temporoman-
AND (Anterior Open Bite)) OR ((3D Printing) AND dibular Joint)) OR ((Rapid Prototyping) AND (Temporo-
(Posterior Open Bite)) OR ((Rapid Prototyping) AND mandibular Joint)) OR ((Stereolithography) AND
(posterior open bite)) OR ((3D Printing) AND (virtual (Temporomandibular Joint)) OR ((CAD-CAM) and
surgical planning)) OR ((Rapid Prototyping) AND (vir- (Temporomandibular Joint))
tual surgical planning)) Results: [32, 36, 208–243]
Results: [36, 53, 79, 81, 92, 93, 98, 99, 101–103, 107, Benign Neoplasms (Bone): Bony benign neoplasms of
108, 110, 117, 120, 123, 157–201] the craniomaxillofacial area may involve the skull, max-
Other Diseases of Jaws: Other diseases of jaws in- illa, orbit, sinuses and mandible. These can range from
clude inflammatory, infectious, vascular or iatrogenic simple cases where excision of a mass may be required
processes in which bone is remodeled or eroded, such as to very complex cases requiring three-dimensional surgi-
osteoradionecrosis and osteomyelitis. Bony lesions such cal excision and reconstruction. Reconstruction for com-
as giant cell lesions and benign cysts may require partial plex cases may require autogenous tissue or a free flap
resection of the jaw. Uncomplicated cases may require and may at times also require patient-matched implants
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 15 of 38

or fixation plates. ICD-10: D16.4 Benign neoplasm of the area to be resected/reconstructed, the three-dimen-
bones of skull and face, D16.5 Benign neoplasm of lower sionality of the affected area or its approximation to vital
jaw bone structures. Reconstruction for complex cases most times
PubMed Search: ((3D Printing) AND (Benign Facial require a free flap and may at times also require
Neoplasm)) OR ((Rapid Prototyping) AND (Benign Fa- patient-matched implants or patient-matched rigid fix-
cial Neoplasm)) OR ((3D Printing) AND (Benign Jaw ation. ICD-10: C41.0 Malignant neoplasm of bones of
Neoplasm)) OR ((Rapid Prototyping) AND (Benign Jaw skull and face, C41.1 Malignant neoplasm of mandible
Neoplasm)) PubMed Search: ((3D Printing) AND (Malignant Neo-
Results: [244, 245] plasm Skull)) OR ((Rapid Prototyping) AND (Malignant
Benign Neoplasms (Soft Tissue): Benign soft tissue Neoplasm Skull)) OR ((3D Printing) AND (Malignant
neoplasms of the craniomaxillofacial area include lesions Neoplasm Mandible)) OR ((Rapid Prototyping) AND
of parotid or salivary glands, the lip, the floor of mouth, (Malignant Neoplasm Mandible)) OR ((virtual surgical
other parts of the mouth, tonsil, oropharynx, nasophar- planning) AND (Malignant Neoplasm Mandible)) OR
ynx and hypopharynx. Other cutaneous lesions include ((patient matched implant) AND (Malignant Neoplasm
neurofibromas, gliomas, dermoids, hemangiomas, lym- Mandible))
phangiomas and many other rarer tumors. Diagnosis Results: [36, 55, 72, 73, 82, 88, 107, 111, 114, 161,
and excision is indicated in all these lesions when pos- 202–205, 246–300]
sible. Complex cases can include resection and recon- Malignant Neoplasms (Soft Tissue): Malignant neo-
struction of soft tissue and hard tissue concomitantly. plasms of the soft tissue within the craniomaxillofacial
Reconstruction for complex cases may require autogen- region include cancers of the oral cavity (e.g. tongue,
ous tissue or a free flap and may at times also require floor of mouth maxillary and mandibular gingiva), oro-
patient-matched implants or rigid fixation. ICD-10: pharynx, hypopharynx, orbit, skull base and larynx. Simple
D11.0 Benign neoplasm of parotid gland, D11.7 Benign cases may only require biopsy while complex cases can in-
neoplasm of other major salivary glands, D10.0 Benign clude composite resection and reconstruction of soft tis-
neoplasm of lip, D10.1 Benign neoplasm of tongue, sue and hard tissue concomitantly. Reconstruction for
D10.2 Benign neoplasm of floor of mouth, D10.3 Benign complex cases may require autogenous tissue or a free flap
neoplasm of other and unspecified parts of mouth, and may at times also require patient-matched implants
D10.4 Benign neoplasm of tonsil, D10.5 Benign neo- or rigid fixation. ICD-10: C00 Malignant Neoplasm of Lip,
plasm of other parts of oropharynx, D10.6 Benign neo- C01 Malignant Neoplasm of Base of Tongue, C04 Malig-
plasm of nasopharynx, D10.7 Benign neoplasm of nant Neoplasm of Floor of Mouth, C05 Malignant Neo-
hypopharynx, D10.9 Benign neoplasm of pharynx, plasm of Palate, C30 Malignant neoplasm of nasal cavity
unspecified and middle ear, C31 Malignant neoplasm of accessory si-
PubMed Search: ((3D Printing) AND (Benign Parotid nuses, C32 Malignant neoplasm of larynx, C33 Malignant
Neoplasm)) OR ((Rapid Prototyping) AND (Benign Par- neoplasm of trachea, D00.0 Carcinoma in situ of lip, oral
otid Neoplasm)) OR ((3D Printing) AND (Benign Saliv- cavity and pharynx, D00.1 Carcinoma in situ of esophagus
ary Gland Neoplasm)) OR ((Rapid Prototyping) AND PubMed Search: ((3D Printing) AND (Malignant Neo-
(Benign Salivary Gland Neoplasm)) OR ((3D Printing) plasm Lip)) OR ((Rapid Prototyping) AND (Malignant
AND (Benign Neoplasm Tonsil)) OR ((Rapid Prototyp- Neoplasm Lip)) OR ((3D Printing) AND (Malignant
ing) AND (Benign Neoplasm Tonsil)) OR ((3D Printing) Neoplasm Tongue)) OR ((Rapid Prototyping) AND (Ma-
AND (Benign Neoplasm Oropharynx)) OR ((Rapid lignant Neoplasm Tongue)) OR ((3D Printing) AND
Prototyping) AND (Benign Neoplasm Oropharynx)) OR (Malignant Neoplasm Palate)) OR ((Rapid Prototyping)
((3D Printing) AND (Benign Neoplasm Nasopharynx)) AND (Malignant Neoplasm Palate)) OR ((3D Printing)
OR ((Rapid Prototyping) AND (Benign Neoplasm Naso- AND (Malignant Neoplasm Sinus)) OR ((Rapid Proto-
pharynx)) OR ((3D Printing) AND (Benign Neoplasm typing) AND (Malignant Neoplasm Sinus)) OR ((3D
Hypopharynx)) OR ((Rapid Prototyping) AND (Benign Printing) AND (Malignant Neoplasm Larynx)) OR
Neoplasm Hypopharynx)) ((Rapid Prototyping) AND (Malignant Neoplasm Lar-
Results: No Relevant Papers ynx)) OR ((3D Printing) AND (Malignant Neoplasm
Malignant Neoplasms (Bone): Malignant neoplasms Trachea)) OR ((Rapid Prototyping) AND (Malignant
of bone which can occur in the craniomaxillofacial re- Neoplasm Trachea)) OR ((3D Printing) AND (Carcin-
gion almost always require complex surgical interven- oma Lip)) OR ((Rapid Prototyping) AND (Carcinoma
tion. Many times bone and soft tissue are involved in Lip)) OR ((3D Printing) AND (Carcinoma Pharynx)) OR
these cases and the resections encompass a margin of ((Rapid Prototyping) AND (Carcinoma Pharynx)) OR
uninvolved tissue to prevent recurrence. The difference ((3D Printing) AND (Carcinoma esophagus)) OR ((Rapid
between simple and complex may relate to the size of Prototyping) AND (Carcinoma Esophagus)) OR ((3D
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 16 of 38

Printing) AND (Carcinoma Oral Cavity)) OR ((Rapid abnormal development of the renal parenchyma, or
Prototyping) AND (Carcinoma Oral Cavity)) OR ((vir- inherited, due to abnormal cilium signaling in tubular
tual surgical planning) AND (Malignant Neoplasm Base epithelial cells [561]. Inherited cystic renal diseases are
of Tongue)) OR ((patient matched implant) AND (Ma- now included in the group of diseases termed ciliopa-
lignant Neoplasm Base of Tongue)) thies. Renal cysts are characterized based on the Bos-
Results: [55, 150, 204, 247–250, 278, 279, 287, 290, niak classification system which divides cystic renal
301, 302] masses into five categories based on imaging charac-
Genitourinary (Retrieved August 2017) teristics. Simple cysts are considered Bosniak 1, min-
Urolithiasis, Surgical or Medical Management: Cal- imally complex are Bosniak 2, intermediate are
culi or stones that form in the urinary tract, affecting the Bosniak 3, and malignant are Bosniak 4. Bosniak 3
kidneys, ureters, bladder or urethra is common and in- and 4 lesions undergoing surgical treatment such as
creasing in prevalence due to a variety of proposed fac- partial nephrectomy or radiofrequency ablation should
tors including obesity, dietary changes, and global be grouped in the renal cancer group described in
warming. Terms associated with urolithiasis include kid- the previous section.
ney stones, renal stones, renal calculus disease, nephro- PubMed Search: (3D printing AND Bosniak cystic le-
lithiasis, calculi. sions) or (rapid prototyping AND Bosniak cystic lesions)
PubMed Search: (3D printing AND urolithiasis) OR OR (3D printing AND Bosniak) OR (rapid prototyping
(3D printing AND kidney stones) OR (3D printing AND AND Bosniak) OR (3D printing AND renal cysts) OR
renal stones) OR (3D printing AND renal calculus dis- (rapid prototyping AND renal cysts) OR (3D printing
ease) OR (3D printing AND nephrolithiasis) OR (3D AND kidney cyst) OR (rapid prototyping AND kidney
printing AND calculi) OR (rapid prototyping AND uro- cyst) OR (3D printing AND, cystic renal dysplasia) OR
lithiasis) OR (rapid prototyping AND kidney stones) OR (rapid prototyping AND cystic renal dysplasia) OR (3D
(rapid prototyping AND renal stones) OR (rapid proto- printing AND polycystic kidney disease) OR (rapid
typing AND renal calculus disease) OR (rapid prototyp- prototyping AND polycystic kidney disease)
ing AND nephrolithiasis) OR (rapid prototyping AND Results: None
calculi) Lower Tract Tumors (bladder and urethra) and
Results: [303–309] Upper Tract Tumors (pyelocaliceal cavities and ur-
Renal Cancer: Renal cancer is common, with renal eter): Urothelial carcinomas can be located in the lower
cell carcinoma (RCC) accounting for approximately 3.5% (bladder and urethra) or the upper (pyelocalyceal cavities
of all malignancies [562]. In the US, there is predicted to and ureter) urinary tract. Bladder cancer accounts for
be 63,990 new diagnoses of RCC and 14,400 kidney can- the majority of urothelial malignancies. In 2017, there
cer related deaths in 2017. Surgical resection is the are estimated to be 79,030 new cases of bladder cancer
standard of care for RCC, with minimally invasive partial in the United States, 60,490 in men, making it the 4th
nephrectomy the treatment of choice for localized le- most prevalent cancer in men [562]. Cancer of the ur-
sions [561]. eter is uncommon and occurs most often in older adults
PubMed Search: (3D printing AND kidney cancer) OR who have been previously treated for bladder cancer.
(rapid prototyping and kidney cancer) OR (3D printing Transitional cell carcinoma is the most common hist-
AND renal cancer) OR (rapid prototyping AND renal ology observed.
cancer) OR (3D printing AND renal mass) OR (3D PubMed Search: 3D printing AND urothelial malig-
printing AND kidney mass) OR (rapid prototyping nancy OR rapid prototyping AND urothelial malignancy,
AND renal mass) OR (rapid prototyping AND kidney 3D printing AND urothelial malignancies OR rapid
mass) OR (3D printing AND renal cell carcinoma) prototyping AND urothelial malignancies, 3D printing
OR (3D printing AND RCC) OR (rapid prototyping AND urothelial carcinoma OR rapid prototyping AND
AND renal cell carcinoma) OR (rapid prototyping urothelial carcinoma, 3D printing AND transitional cell
AND RCC) carcinoma OR rapid prototyping AND transitional cell
Results: [308, 310–324] carcinoma, 3D printing AND bladder malignancy OR
The terms renal lymphoma, angiomyolipoma (AML) rapid prototyping AND bladder malignancy, 3D printing
and renal oncocytoma generated no results when AND bladder malignancies OR rapid prototyping AND
searched with 3D printing or rapid prototyping. bladder malignancies, (3D printing AND bladder cancer
Renal Cysts: Renal cysts are common; they are hetero- OR rapid prototyping AND bladder cancer, 3D printing
geneous in both origin and pathogenesis; and most are AND bladder neoplasm OR rapid prototyping AND
simple and are usually of little clinical significance. Cys- bladder neoplasm, 3D printing AND bladder mass OR
tic renal disease may be sporadic, from congenital anom- rapid prototyping AND bladder mass
alies of the kidney and urinary tract that result in Results: None Relevant
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 17 of 38

PubMed Search: (3D printing AND ureteral malig- prototyping AND polycystic ovarian disease) OR (rapid
nancy) OR (3D printing AND ureteral malignancies) OR prototyping AND PCOD)
(rapid prototyping AND ureteral malignancy) OR (rapid Results: None
prototyping and ureteral malignancies) OR (3D printing Uterine and Cervical Disease: The uterine corpus is
AND intrarenal collecting system malignancies) OR composed of endometrial mucosa and the underlying
(rapid prototyping AND intrarenal collecting system ma- smooth muscle myometrium. Frequent and significant
lignancies) OR (3D printing AND pyelocaliceal) OR uterine disorders include endometriosis, adenomyosis,
(rapid prototyping AND pyelocaliceal) OR (3D printing abnormal uterine bleeding, and lesions of the endomet-
AND pyelocalyceal) OR (rapid prototyping AND rium and myometrium including endometrial hyperpla-
pyelocalyceal) sia, endometrial carcinomas, endometrial polyps, and
Results: None Relevant smooth muscle tumors.
Adrenal Disease: The adrenal glands may be affected PubMed Search: (3D printing AND uterine cancer)
by a variety of pathologies, the majority of which are be- OR (rapid prototyping AND uterine cancer) OR (3D
nign. Causes of adrenal gland disorders include genetic printing AND cervical cancer) OR (rapid prototyping
mutations, tumors, infections, regulatory pathologies, or AND cervical cancer)
certain medications. Results: [335–342]
PubMed search: (3D printing AND adrenal disease) The terms endometrial adenocarcinoma, leiomyoma
OR (rapid prototyping AND adrenal disease) OR (3D (uterine fibroids), leiomyosarcoma, and endometrial
printing AND adrenal gland) OR (rapid prototyping stromal sarcoma generated no results when searched
AND adrenal gland) with 3D printing or rapid prototyping.
Results: [325] PubMed Search: (3D printing AND endometriosis) OR
Penile Cancer: Cancer of the penis is an uncommon (rapid prototyping AND endometriosis)
lesion occurring almost entirely in uncircumcised men. Results: [342]
An important pathological process in penile cancer, is PubMed Search: (3D printing AND endometritis) OR
squamous cell carcinoma, which is caused by the human (3D printing AND adenomyosis) OR (3D printing AND
papillomavirus (HPV). uterine bleeding) OR (rapid prototyping AND endomet-
PubMed Search: (3D printing AND penile cancer) OR ritis) OR (rapid prototyping AND adenomyosis) OR
(rapid prototyping AND penile cancer) (rapid prototyping) AND (uterine bleeding)
Results: None Results: None
Testicular Cancer: The majorities (95%) of testicular Vaginal Cancer
tumors are derived from germ cells and all masses of PubMed Search: 3D printing AND vaginal tumor OR
the testes are considered malignant until proven rapid prototyping AND vaginal tumor OR 3D printing
otherwise [562]. AND vaginal cancer OR rapid prototyping AND vaginal
PubMed Search: (3D printing AND testicular cancer) cancer
OR (rapid prototyping AND testicular cancer) Results: [339, 343]
Results: None Genitourinary Reconstruction: Genitourinary recon-
Prostate Cancer: Prostate cancer is the most common struction encompasses a broad range of surgical proce-
cancer in American men, accounting for almost 1 in 5 dures whose purpose is to correct congenital or acquired
new diagnoses [583]. Men diagnosed with prostate can- abnormalities. Terms: genitourinary conditions, genito-
cer have three primary treatment options including ac- urinary disorders, genitourinary anomalies, genitourinary
tive surveillance, surgery, and radiation. abnormalities, genital conditions, genital disorders, geni-
PubMed Search: (3D printing AND prostate cancer) tal anomalies, genital abnormalities.
OR (rapid prototyping AND prostate cancer) PubMed Search: (3D printing AND genitourinary re-
Results: [326–334] construction) OR (rapid prototyping AND genitourinary
Ovarian Disease: Ovarian disease includes ovarian reconstruction) OR (3D printing AND genitourinary dis-
cancer and ovarian cysts, as well as polycystic ovarian orders) OR (rapid prototyping AND genitourinary disor-
syndrome. ders) OR (3D printing AND genitourinary disorder) OR
PubMed Search: (3D printing AND ovarian tumor) (rapid prototyping AND genitourinary disorder) OR (3D
OR (rapid prototyping AND ovarian tumor) OR (3D printing AND genitourinary anomaly) OR (rapid proto-
printing AND ovarian cancer) OR (rapid prototyping typing AND genitourinary anomaly) OR (3D printing
AND ovarian cancer) AND genitourinary anomalies) OR (rapid prototyping
Results: None Relevant AND genitourinary anomalies) OR (3D printing AND
PubMed Search: (3D printing AND polycystic ovarian genitourinary abnormalities) OR (rapid prototyping
disease) OR (3D printing AND PCOD) OR (rapid AND genitourinary abnormalities) OR (3D printing
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 18 of 38

AND genitourinary abnormality) OR (rapid prototyping No results for PubMed search with 3D printing OR
AND genitourinary abnormality) OR (3D printing AND rapid prototyping AND the following: urinary tract in-
genital condition) OR (rapid prototyping AND genital fection, UTI, or pyelonephritis
condition) OR (3D printing AND genital anomaly) OR Pediatric Retroperitoneal Genitourinary Tumors:
(rapid prototyping AND genital anomaly) OR (3D print- The terms included Wilms tumor, nephroblastoma, and
ing AND genital anomalies) OR (rapid prototyping AND genitourinary tumor.
genital anomalies) OR (3D printing AND genitourinary PubMed Search: (3D printing AND pediatric genito-
abnormalities) OR (rapid prototyping AND genitouri- urinary tumor) OR (rapid prototyping AND pediatric
nary abnormalities) OR (3D printing AND genitourinary genitourinary tumor) OR (3D printing AND Wilms
abnormality) OR (rapid prototyping AND genitourinary tumor) OR (rapid prototyping AND Wilms tumor) OR
abnormality) (3D printing AND nephroblastoma) OR (rapid prototyp-
Results: None Relevant ing AND nephroblastoma)
Genitourinary Trauma: Injury to the genitourinary Results: None Relevant
tract is a common occurrence after both blunt and pene- Musculoskeletal (Retrieved February 2017)
trating trauma. Terms: genitourinary injury, urinary tract Fracture: Simple, Acute Complex Long Bone, Acute
trauma, renal trauma, kidney trauma (renal lacerations, Complex Intraarticular, Complex, Acetabular,
renal collecting system injury, renal vascular injury), ur- Non-Pathological Vertebral, Pathological Vertebral,
eteral trauma, bladder trauma, urethral trauma, adrenal Fracture Malunion.
trauma, scrotal trauma. PubMed Search: ((“printing, three-dimensional”[MeSH
PubMed Search: (3D printing AND genitourinary Terms] OR (“printing”[All Fields] AND “three-dimensio-
trauma) OR (rapid prototyping AND genitourinary nal”[All Fields]) OR “three-dimensional printing”[All
trauma) OR (3D printing AND genitourinary injury) OR Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
(additive manufacturing AND genitourinary injury) OR OR “3d printing”[All Fields]) OR (rapid[All Fields] AND
(3D printing AND urinary tract trauma) OR (additive prototyping[All Fields])) AND ((“fractures, bone”[MeSH
manufacturing AND urinary tract trauma) OR (3D Terms] OR (“fractures”[All Fields] AND “bone”[All
printing AND renal trauma) OR (rapid prototyping Fields]) OR “bone fractures”[All Fields] OR “fracture”[All
AND renal trauma) OR (3D printing AND kidney Fields]) OR malunion[All Fields])
trauma) OR (rapid prototyping AND kidney trauma) OR Results: [345–406]
(3D printing AND renal laceration) OR (rapid prototyp- Heterotopic Ossification
ing AND renal laceration) OR (3D printing AND renal PubMed Search: ((“printing, three-dimensional”[MeSH
collecting system injury) OR (rapid prototyping AND Terms] OR (“printing”[All Fields] AND “three-dimensio-
renal collecting system injury) OR (3D printing AND nal”[All Fields]) OR “three-dimensional printing”[All
renal vascular injury) OR (rapid prototyping AND renal Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
vascular injury) OR (3D printing AND ureteral trauma) OR “3d printing”[All Fields]) OR (rapid[All Fields] AND
OR (additive manufacturing AND ureteral trauma) OR prototyping[All Fields])) AND (“ossification, heteroto-
(3D printing AND ureteral injury) OR (additive manu- pic”[MeSH Terms] OR (“ossification”[All Fields] AND
facturing AND ureteral injury) OR (3D printing AND “heterotopic”[All Fields]) OR “heterotopic ossification”[All
bladder injury) OR (rapid prototyping AND bladder in- Fields] OR (“heterotopic”[All Fields] AND “ossificatio-
jury) OR (3D printing AND bladder trauma) OR (rapid n”[All Fields]))
prototyping AND bladder trauma) OR (3D printing AND Results: None relevant
adrenal trauma AND rapid prototyping AND adrenal Ligamentous Injury
trauma) OR (3d printing AND adrenal injury) OR (3D PubMed Search: ((“printing, three-dimensional”[MeSH
printing AND scrotal trauma) OR (rapid prototyping Terms] OR (“printing”[All Fields] AND “three-dimensio-
AND scrotal trauma) OR (3d printing AND scrotal injury) nal”[All Fields]) OR “three-dimensional printing”[All
Results: None Relevant Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
Pediatric Infection and Reflux: Acute pyelonephritis OR “3d printing”[All Fields]) OR (rapid[All Fields] AND
is inflammation of the kidney, usually bacterial in origin. prototyping[All Fields])) AND ((“tendons”[MeSH
Terms: vesicoureteral reflux (VUR), urinary tract infec- Terms] OR “tendons”[All Fields] OR “tendon”[All
tion (UTI), acute pyelonephritis Fields]) OR (“ligaments”[MeSH Terms] OR “ligament-
PubMed search: (3D printing AND vesicoureteral re- s”[All Fields] OR “ligament”[All Fields]))
flux) OR (rapid prototyping AND vesicoureteral reflux) Results: [407, 408]
OR (3D printing AND VUR) OR (rapid prototyping Hip Dysplasia
AND VUR) PubMed Search: ((“printing, three-dimensional”[MeSH
Results: [344] Terms] OR (“printing”[All Fields] AND “three-
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 19 of 38

dimensional”[All Fields]) OR “three-dimensional printin- OR (“aortic”[All Fields] AND “dissection”[All Fields])


g”[All Fields] OR (“3d”[All Fields] AND “printing”[All OR “aortic dissection”[All Fields]) OR (“aortic aneur-
Fields]) OR “3d printing”[All Fields]) OR (rapid[All ysm”[MeSH Terms] OR (“aortic”[All Fields] AND
Fields] AND prototyping[All Fields])) AND (“hip dislo- “aneurysm”[All Fields]) OR “aortic aneurysm”[All
cation”[MeSH Terms] OR (“hip”[All Fields] AND “dislo- Fields]) OR ((“aorta”[MeSH Terms] OR “aorta”[All
cation”[All Fields]) OR “hip dislocation”[All Fields] OR Fields] OR “aortic”[All Fields]) AND (“stents”[MeSH
(“hip”[All Fields] AND “dysplasia”[All Fields]) OR “hip Terms] OR “stents”[All Fields] OR “stent”[All Fields]))
dysplasia”[All Fields]) OR ((“aorta”[MeSH Terms] OR “aorta”[All Fields] OR
Results: [389, 409–414] “aortic”[All Fields]) AND (“aneurysm, false”[MeSH
Bone or Soft Tissues Neoplasm: With or Without Terms] OR (“aneurysm”[All Fields] AND “false”[All
Joint and Neurovascular Involvement Fields]) OR “false aneurysm”[All Fields] OR “pseudoa-
PubMed Search: ((“printing, three-dimensional”[MeSH neurysm”[All Fields])))
Terms] OR (“printing”[All Fields] AND “three-dimensio- Results: [464–499]
nal”[All Fields]) OR “three-dimensional printing”[All Peripheral Aneurysm
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) PubMed Search: ((“printing, three-dimensional”[MeSH
OR “3d printing”[All Fields]) OR (rapid[All Fields] AND Terms] OR (“printing”[All Fields] AND “three-dimensio-
prototyping[All Fields])) AND (“bone neoplasms”[MeSH nal”[All Fields]) OR “three-dimensional printing”[All
Terms] OR (“bone”[All Fields] AND “neoplasms”[All Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
Fields]) OR “bone neoplasms”[All Fields] OR (“bone”[All OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND
Fields] AND “tumor”[All Fields]) OR “bone tumor”[All Prototyping[All Fields])) AND ((“arteries”[MeSH Terms]
Fields]) OR “arteries”[All Fields] OR “arterial”[All Fields]) AND
Results: [324, 353, 415–443] (“aneurysm”[MeSH Terms] OR “aneurysm”[All Fields]))
Arthritis, Not Otherwise Specified Results: [500–505]
PubMed Search: ((“printing, three-dimensional”[MeSH Stenosis, Arterial, Extracranial, for Patient-Specific
Terms] OR (“printing”[All Fields] AND “three-dimensio- Simulations
nal”[All Fields]) OR “three-dimensional printing”[All PubMed Search: ((“printing, three-dimensional”[MeSH
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) Terms] OR (“printing”[All Fields] AND “three-dimensio-
OR “3d printing”[All Fields]) OR (rapid[All Fields] AND nal”[All Fields]) OR “three-dimensional printing”[All
prototyping[All Fields])) AND (“arthritis”[MeSH Terms] Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
OR “arthritis”[All Fields]) OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND
Results: [358, 444–453] Prototyping[All Fields])) AND ((“constriction, patholo-
Scoliosis: Secondary to Congenital Vertebral Anom- gic”[MeSH Terms] OR (“constriction”[All Fields] AND
aly, Severe/Marked, Thoracic Kyphosis, None of the “pathologic”[All Fields]) OR “pathologic constriction”[All
Above Fields] OR “stenosis”[All Fields]) OR (“peripheral arterial
PubMed Search: ((“printing, three-dimensional”[MeSH disease”[MeSH Terms] OR (“peripheral”[All Fields]
Terms] OR (“printing”[All Fields] AND “three-dimensio- AND “arterial”[All Fields] AND “disease”[All Fields]) OR
nal”[All Fields]) OR “three-dimensional printing”[All “peripheral arterial disease”[All Fields]))
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) Results: [506–508]
OR “3d printing”[All Fields]) OR (rapid[All Fields] AND Vascular Malformations: Acquired, Congenital,
prototyping[All Fields])) AND (“scoliosis”[MeSH Terms] Rings, Slings, For Interventional Consideration – Ex-
OR “scoliosis”[All Fields]) cluding congenital heart disease and intracranial
Results: [438, 454–463] pathologies.
Vascular (Retrieved: Initial November 2017, Updated PubMed Search: ((“printing, three-dimensional”[MeSH
June 2018) Terms] OR (“printing”[All Fields] AND “three-dimensio-
Aortic Pathologies: Dissection, Aneurysm, Stenting, nal”[All Fields]) OR “three-dimensional printing”[All
Pseudoaneurysm Fields] OR (“3d”[All Fields] AND “printing”[All Fields])
PubMed Search: ((“printing, three-dimensional”[MeSH OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND
Terms] OR (“printing”[All Fields] AND “three-dimensio- Prototyping[All Fields])) AND ((“vascular malforma-
nal”[All Fields]) OR “three-dimensional printing”[All tions”[MeSH Terms] OR (“vascular”[All Fields] AND
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) “malformations”[All Fields]) OR “vascular malformation-
OR “3d printing”[All Fields]) OR (rapid[All Fields] AND s”[All Fields] OR (“vascular”[All Fields] AND “malforma-
prototyping[All Fields])) AND ((“aneurysm, dissecting”[- tion”[All Fields]) OR “vascular malformation”[All
MeSH Terms] OR (“aneurysm”[All Fields] AND “dissec- Fields]) OR (“vascular ring”[MeSH Terms] OR (“vascu-
ting”[All Fields]) OR “dissecting aneurysm”[All Fields] lar”[All Fields] AND “ring”[All Fields]) OR “vascular
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 20 of 38

ring”[All Fields]) OR (“vascular ring”[MeSH Terms] OR Benign breast lesions: Benign breast lesions include
(“vascular”[All Fields] AND “ring”[All Fields]) OR “vas- fibrocystic change, benign breast masses, inflammatory,
cular ring”[All Fields] OR (“vascular”[All Fields] AND and peripartum conditions.
“sling”[All Fields]) OR “vascular sling”[All Fields])) PubMed Search: ((3D printing) AND (fibrocystic
Results: [509] change)) OR ((3D printing) AND (benign breast
Varices: Peripheral for Medical Management, Retro- masses)) OR ((3D printing) AND (mastitis)) OR ((3D
peritoneal for Medical Management, Intervention printing) AND (galactocele)) OR ((rapid prototyping)
Planning AND (fibrocystic change)) OR ((rapid prototyping) AND
PubMed Search: ((“printing, three-dimensional”[MeSH (benign breast masses)) OR ((rapid prototyping) AND
Terms] OR (“printing”[All Fields] AND “three-dimensio- (mastitis) OR ((rapid prototyping) AND (galactocele))
nal”[All Fields]) OR “three-dimensional printing”[All Results: None
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) High risk breast lesions: High risk lesions include flat
OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND epithelial atypia, atypical ductal hyperplasia, lobular neo-
Prototyping[All Fields])) AND ((“varicose veins”[MeSH plasia, radial scar, papillary lesions and mucocele-like
Terms] OR (“varicose”[All Fields] AND “veins”[All lesions.
Fields]) OR “varicose veins”[All Fields] OR “varices”[All PubMed Search: ((3D printing) AND (flat epithelial
Fields]) OR (“varicose veins”[MeSH Terms] OR (“varico- atypia)) OR ((3D printing) AND (atypical ductal hyper-
se”[All Fields] AND “veins”[All Fields]) OR “varicose plasia)) OR ((3D printing) AND (lobular neoplasia)) OR
veins”[All Fields] OR “varix”[All Fields]) OR varicose[All ((3D printing) AND (radial scar)) OR ((3D printing)
Fields]) AND (papillary lesions) OR ((3D printing) AND
Results: None (mucocele-like lesions)) OR ((rapid prototyping) AND
Carotid Pathologies: Stenosis, Dissection, Pseudoa- (flat epithelial atypia)) OR ((rapid prototyping) AND
neurysm, Post-Endarterectomy (atypical ductal hyperplasia)) OR ((rapid prototyping)
PubMed Search: ((“printing, three-dimensional”[MeSH AND (lobular neoplasia) OR ((rapid prototyping)
Terms] OR (“printing”[All Fields] AND “three-dimensio- AND (radial scar)) OR ((rapid prototyping) AND
nal”[All Fields]) OR “three-dimensional printing”[All (papillary lesions)) OR ((rapid prototyping) AND
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) (mucocele-like lesions))
OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND Results: No results found.
Prototyping[All Fields])) AND carotid[All Fields] Breast cancer: Malignant breast lesions included
Results: [510–514] ductal carcinoma in situ ductal (DCIS) and invasive
Intracranial Pathologies: Stenosis, Aneurysm, Dural breast carcinomas. Use in breast malignancies with chest
AV Fistula, Arteriovenous Malformation wall involvement and/or nipple-areolar complex involve-
PubMed Search: ((“printing, three-dimensional”[MeSH ment, evaluation of tumor-breast size ratio, and tumors
Terms] OR (“printing”[All Fields] AND “three-dimensio- where oncoplastic surgery is considered.
nal”[All Fields]) OR “three-dimensional printing”[All PubMed Search: ((3D printing) AND (breast cancer)
Fields] OR (“3d”[All Fields] AND “printing”[All Fields]) OR ((rapid prototyping) AND (breast cancer))
OR “3d printing”[All Fields]) OR (Rapid[All Fields] AND Results: [546–552]
Prototyping[All Fields])) AND ((“constriction, patholo-
gic”[MeSH Terms] OR (“constriction”[All Fields] AND
“pathologic”[All Fields]) OR “pathologic constriction”[All
Abbreviations
Fields] OR “stenosis”[All Fields]) OR (“aneurysm”[MeSH 3D: Three-dimensional; ACR: American College of Radiology; ASD: Atrial
Terms] OR “aneurysm”[All Fields]) OR (Dural[All septal defect; AV: Atrioventricular; CAD: Computer aided design;
CDRH: The center for devices and radiological health; CHD: Congenital
Fields] AND (“arteriovenous fistula”[MeSH Terms] OR
heart disease; CMF: Craniomaxillofacial; CNR: Contrast to noise ratio;
(“arteriovenous”[All Fields] AND “fistula”[All Fields]) CT: Computed tomography; DICOM: Digital imaging and
OR “arteriovenous fistula”[All Fields] OR (“av”[All communications in medicine; DOLV: Double-outlet left ventricle;
Fields] AND “fistula”[All Fields]) OR “av fistula”[All DORV: Double-outlet right ventricle; EACTS-STS: European Association for
Cardio-Thoracic Surgery / Society of Thoracic Surgery; FDA: The United
Fields])) OR (“arteriovenous malformations”[MeSH States Food and Drug Administration; FOV: Field of view; HIPAA: Health
Terms] OR (“arteriovenous”[All Fields] AND “malforma- Insurance Portability and Accountability Act; ICD-10: International
tions”[All Fields]) OR “arteriovenous malformations”[All Classification of Diseases, Tenth Revision; IPCCC: International Pediatric
and Congenital Cardiac Code; MRI: Magnetic resonance imaging;
Fields] OR (“arteriovenous”[All Fields] AND “malforma- NOS: Not otherwise specified; PACS: Picture archiving and
tion”[All Fields]) OR “arteriovenous malformation”[All communication system; PAPVR: Partial anomalous pulmonary venous
return; ROI: Region of interest; RSNA: Radiological Society of North
Fields]))
America; RVOT: Right ventricular outflow tract; SIG: Special Interest
Results: [501, 515–545] Group; SNR: Signal to noise ratio; STL: Standard tessellation language;
Breast (Retrieved November 2017) TAPVR: Total anomalous pulmonary venous return; TGA: Transposition of
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 21 of 38

the great arteries; VRML: Virtual reality markup language; VSD: Ventricular Daniel Davis, RT, BS, Denver, CO, United States
septal defect Daniel LaRussa, PhD, Department of Radiology, The University of Ottawa
Faculty of Medicine, Ottawa, ON, Canada
Acknowledgements Daniel S. Madsen, MD, Dept of Interventional Radiology, San Antonio Military
Med Ctr, Fort Sam Houston, TX, United States
RSNA SIG Faculty Members (July 15, 2018) Daniele Marin, MD, Cary, NC, United States
Abraham Levitin, MD, Beachwood, OH, United States Darshit Thakrar, MD, Dept of Pediatric Radiology, Childrens Hospital of
Adam C. Zoga, MD, Dept of Radiology, Thomas Jefferson University Hospital, Pittsburgh of UPMC, Pittsburgh, PA, United States
Philadelphia, PA, United States Dave Nuthals, Vital Images, Minnetonka, MN, United States
Alejandro A. Espinoza, PhD, Dept of Orthopedic Surgery, Rush University David Dreizin, MD, Dept of Radiology & Nuclear Medicine, University of
Medical Center, Chicago, IL, United States Maryland Medical Center, Baltimore, MD, United States
Alexander J. Chien, MD, Chino Hills, CA, United States David M. Hough, MD, Rochester, MN, United States
Amar B. Shah, MD, New York, NY, United States David MacCutcheon, TeraRecon, Foster City, MA, United States
Ambroise Mathurin Dzogang Temdemno, MD, CARIM, Yaounde, Cameroon Daya Vora, MD, Troy, MI, United States
Amin S. Chaoui, MD, Wellesley, MA, United States Deborah E. Starkey, RT, Medical Radiation Sciences, Queensland University of
Amy E. Alexander, MS, Dept of Radiology, Mayo Clinic, Rochester, MN, United States Technology, Brisbane, QLD, Australia
Anand V. Rao, MD, Brookfield, WI, United States Denis Samama, MD, Service d’Imagerie Medicale, Neuilly-sur-Seine, France
Anne Garcia, Opheart, Houston, TX, United States Derek L. West, MD, Dept of Radiology, Emory University, Atlanta, GA, United
Angel R Colon, MD, Mayaguez, PR, United States States
Antoine Leimgruber, MD, MS, Pully, VD, Switzerland Diane M. Twickler, MD, Dept of Radiology, Univ of Texas Southwestern
Antoine M. Vanderhofstadt, MD, Brussels, Belgium Medical Ctr, Dallas, TX, United States
Asra Khan-Bonenberger, MD, Orlando, FL, United States Donald S. Emerson, MD, Memphis, TN, United States
Attilio A. Guazzoni, MD, Dept of Radiology, San Biagio Hospital, Dong Xu, MD, PhD, Dept of Ultrasound, Zhejiang Cancer Hospital, Hangzhou,
Domodossola, VB, Italy Zhejiang, China
Barbara L. McComb, MD, Ponte Vedra, FL, United States Dorothy J. Shum, MD, Dept of Radiology, University of California San
Benjamin E. Tubb, MD, PhD, San Antonio, TX, United States Francisco, San Francisco, CA, United States
Benjamin Johnson, 3DSystems, Littleton, CO, United States Eddy D. Lucas, MD, Wichita, KS, United States
Benjamin M. Howe, MD, Dept of Radiology, Mayo Clinic, Rochester, MN, Eduardo M. Rosa, MD, Radiologica Los Volcanes, Puerto Montt, Decima
United States Region, Chile
Berdoudi Rabah, MD, Dept of Radiology, Imagerie Medicale du Charollais, Edward A. Del Grosso, MD, Granville, OH, United States
Paray-le-Monial, France Edward P. Quigley, III, MD, PhD, Salt Lake City, UT, United States
Bernadette M. Greenwood, BS, RT, Desert Medical Imaging, Indian Wells, CA, Edward Stefanowicz, MBA, RT, Dept of Radiology, Geisinger Health System,
United States Danville, PA, United States
Beth A. Ripley, MD, PhD, Dept of Radiology, University of Washington, Enrique R. Escobar, MD, Melilla, Spain
Seattle, WA, United States Eric M. Baumel, MD, Digital Imaging Diagnostics PLC, Wellington, FL, United
Beth M. Kline-Fath, MD, Dept of Radiology (MLC 5031), Children’s Hospital States
Medical Center, Cincinnati, OH, United States Eric Teil, MD, Tresserve, France
Brent Chanin, BEng, Mediprint.us, Chester, NY, United States Erik W. Stromeyer, MD, Miami Beach, FL, United States
Brian A. Tweddale, MD, Doylestown, PA, United States Ernest J. Ferris, MD, Little Rock, AR, United States
Brian McNamee, MD, Coeur D Alene, ID, United States Fabrizio D’Alessandro, MD, Massa, Ron, Italy
Bruce M. Barack, MD, Los Angeles, CA, United States Fadi Toonsi, MBBS, FRCPC, Jeddah, Saudi Arabia
Bruce M. Shuckett, MD, Toronto, ON, Canada Faisal M. Shah, MD, Scotch Plains, NJ, United States
Bryan Crutchfield, Materialise, Plymouth, MI, United States Fernando A. Alvarado Sr, MD, Dept of Radiology, Diagnos, Machala, El Oro,
Carina L. Butler, MD, Lexington, KY, United States Ecuador
Carlin A. Ridpath, MD, Springfield, MO, United States Francesco Potito, MD, Dept of MRI CT, Centro Radiologico Potito,
Carlos I. Hernandez Rojas, MD, Lima 27, Peru Campobasso, CB, Italy
Carlos Torres, MD, Ottawa, ON, Canada Frank S. Bonelli, MD, PhD, Rockford, IL, United States
Carolina A. Souza, MD, Ottawa, ON, Canada Freddy Drews, MD, Avon Lake, OH, United States
Chen C. Hoffmann, MD, Dept of Diagnostic Radiology, Ramat-Gan, Israel Gaetano T. Pastena, MD, MBA, Glenmont, NY, United States
Cheryl L. Kirby, MD, Cherry Hill, NJ, United States Gary W. Kerber, MD, Urbana, IL, United States
Ching-Lan Wu, MD, Dept of Radiology, Taipei Veterans General Hospital, Gene Kitamura, MD, Dept of Radiology, UPMC, Pittsburgh, PA, United States
Taipei, Taiwan George Antaki, MD, Riverview, FL, United States
Chris Letrong, RT, ARRT, San Jose, CA, United States Georgina A. Viyella, MD, Santo Domingo, Dominican Republic
Christina Kotsarini, MD, PhD, Glasgow, United Kingdom Gerard P. Farrar, MD, Hemlock, MI, United States
Christine J. Kim, MD, Dept of Neuroradiology, Brigham and Women’s Gloria M. Rapoport, MD, Forest Hills, NY, United States
Hospital, Boston, MA, United States Gul Moonis, MD, South Orange, NJ, United States
Christopher A. Swingle, DO, Saint Louis, MO, United States H. Henry Guo, MD, Fremont, CA, United States
Christopher E. Smith, MD, Rch Palos Vrd, CA, United States Halemane S. Ganesh, MD, Lexington, KY, United States
Christopher Wilke, MD, Dept of Radiation Oncology, Univ of Minnesota Han N. Ta, MD, Newport Coast, CA, United States
School of Medicine, Minneapolis, MN, United States Haraldur Bjarnason, MD, Dept of Vascular & Interventional Radiology, Mayo
Christopher Yurko, MD, Vallejo, CA, United States Clinic, Rochester, MN, United States
Claudio Silva, MD, Radiology Department, Clinica Alemana, Facultad de Hemant T. Patel, MD, Samved Hospital, Ahmedabad, India
Medicina Clinica Alemana Universidad del Desarrollo, Santiago, Chile Hongju Son, MD, Dept of Radiology, Einstein Healthcare Network,
Colin M. Wilson, MA, Dept of Radiology, University of New Mexico, Philadelphia, PA, United States
Albuquerque, NM, United States Hui J. Chen, MD, San Francisco, CA, United States
Craig S. Howard, MD, Hattiesburg, MS, United States Hyun-Ju Lee, MD, PhD, Dept of Radiology, Seoul National University Hospital,
Damodaran Arul Selvam, MD, Dept of Radiology, Malcolm Randall VA Seoul, Korea, Republic of
Medical Center, Gainesville, FL, United States Irini M. Youssef, MD, MPH, Hollidaysburg, PA, United States
Dana A. Fuller, MD, Dallas, TX, United States Jack M. Drew, MD, Littleton, CO, United States
Daniel A. Crawford, MSc, BSc, Dept of Medical 3D Printing, Axial3D, Belfast, Jaime Ribeiro Barbosa, MD, Instituto de Radiologia Pres Prudente, Presidente
Antrim, United Kingdom Prudente, SP, Brazil
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 22 of 38

James B. Allison, MD, Richmond, VT, United States Louis T. Kircos, DDS, PhD, San Rafael, CA, United States
James Shin, MD, MSc, New York, NY, United States Luc Lacoursiere, MD, FRCPC, Quebec, QC, Canada
Jared V. Grice, DMP, Nashville, TN, United States Luca Remonda, MD, Aarau, Aargau, Switzerland
Jaroslaw Ast, MD, Poznan, Wielkopolska, Poland Lucas M. Sheldon, MD, Niceville, FL, United States
Jayanthi Parthasarathy BDS, PhD, Nationwide Children’s Hospital, Columbus, Luigi Grazioli, MD, Servizio di Radiologia, University of Brescia/Spedali Civili
OH, United States Brescia, Brescia, BS, Italy
Jeffrey A. Haithcock, MD, Colleyville, TX, United States Luis A. Campos, MD, Lima 33, Lima, Peru
Jeffrey A. Sodergren, MD, Mountain Top, PA, United States Luis A. Rodriguez Palomares, MD, Delegacion: Benito Juarez, Mexico City,
Jeffrey D. Hirsch, MD, Lutherville, MD, United States Mexico
Jesus D. Buonomo, MD, Gurabo, PR, United States Mamdouh E. Rayan, MD, MSc, Chicago, IL, United States
Joaquim M. Farinhas, MD, Tampa, FL, United States Marc J. Gollub, MD, New York, NY, United States
Joel M. Stein, MD, PhD, Div of Neuroradiology, Hospital of the University of Margaret O. Brown, MD, Walton, KY, United States
Pennsylvania, Philadelphia, PA, United States Mariah N. Geritano, MSc, Brookline, MA, United States
Johannes Goerich, MD, Eberbach, Baden, Germany Mariam Thomas, MD, Los Angeles, CA, United States
John A. Skinner, MD, Dept of Radiology, Mayo Clinic, Rochester, MN, United Mariano Sturla, MD, Castelar, Buenos Aires, Argentina
States Mark A. Smith, MS, ARRT, Columbus, OH, United States
John G. O’Rourke, MBBS, Sydney, NSW, Australia Mark D. Alson, MD, Fresno, CA, United States
John Oh, MD, Las Vegas, NV, United States Mark E. Sharafinski Jr., MD, Madison, WI, United States
John P. Knoedler Jr., MD, North Oaks, MN, United States Marshall B. Hay, MD, Portage, MI, United States
Jonathan A. Aziza, MD, Thornhill, ON, Canada Mary Ellen Wickum, MS, Cambridge, MA, United States
Jonathan M. Ford, PhD, Dept of Radiology, University of South Florida Mary Hu, MD, MS, Flushing, NY, United States
College of Medicine, Tampa, FL, United States Mary L. Christie, Rockland, MA, United States
Jorge E. Salazar, MD, UT Medical Group Inc., Memphis, TN, United States Mashael K. Alrujaib, FRCR, FRCPC, Dept of Radiology (MBC-28), King Faisal
Jose A. Barriocanal, MD, PhD, Chattanooga, TN, United States Specialist Hospital, Riyadh, Central Region, Saudi Arabia
Jose A. Maldonado, MD, San Juan, PR, United States Matthew Allen, MD, Redding Cancer Treatment Center, Redding, CA, United
Joseph Johnnie, MS, BEng, Medivators, Conroe, TX, United States States
Joseph M. Aulino, MD, Brentwood, TN, United States Mayola C. Boykin, MD, Ashland, KY, United States
Josephine Pressacco, MD, PhD, Dept of Diagnostic Radiology (D5–113), Melanie Gillies, BSc, Coolangatta, QLD, Australia
MUHC/Montreal General Hospital, Montreal, QC, Canada Michael D. Maloney, MD, Yreka, CA, United States
Judy H. Song, MD, Medstar Georgetown University Hospital, Washington, DC, Michael Gaisford, Stratasys, Cambridge, MA, United States
United States Michael L. Richardson, MD, Dept of Radiology, University of Washington,
Juergen Brandt, MD, Arnsberg, Germany Seattle, WA, United States
Julie S. Lee, MD, Seattle, WA, United States Michael T. McGuire, MD, Jersey City, NJ, United States
Juling Ong I, MBBS, Dept of Plastic Surgery/3D Facility, Great Ormond Street Michael T. Miller, MD, Pittsford, NY, United States
Hospital for Children, London, United Kingdom Michael W. Itagaki, MD, MBA, Bellevue, WA, United States
Justin Sutherland, PhD, Department of Radiology, The University of Ottawa Michel Berube, MD, Chicoutimi, QC, Canada
Faculty of Medicine, Ottawa, ON, Canada Michel D. Dumas, MD, Abilene, TX, United States
Michelle L. Walker, MS, Clearwater, FL, United States
Karen K. Moeller, MD, Louisville, KY, United States
Mohammad Eghtedari, MD, PhD, San Diego, CA, United States
Katherine Weimer, 3D Systems - Healthcare, Littleton, CO, United States
Muge Ozhabes, MD, Marina Del Rey, CA, United States
Kathleen G. Oxner, MD, Greenville, SC, United States
Nathaniel Reichek, MD, Fort Salonga, NY, United States
Kathryn E. Pflug, MD, Dept of Radiology, Lakeview Regional Medical Center, Naveen K. Gowda, MD, Dept of Radiology, St. Lukes Hospital, Duluth, MN,
Covington, LA, United States United States
Kelly D. Smith, MD, Mitchell, SD, United States Nicholas C. Fraley, MD, Oro Valley, AZ, United States
Kelly Oppe, RT, Dept of Radiology, Carle Foundation Hospital, Urbana, IL, Nicholas G. Rhodes, MD, Rochester, MN, United States
United States Nopporn Beokhaimook, MD, Nonthaburi, Thailand
Kenneth A. Buckwalter, MD, Indiana University, Indianapolis, IN, United States Pamela A. Rowntree, RT, Medical Radiation Sciences, Queensland University
Kenneth L. Sandock, MD, Tucson, AZ, United States of Technology, Brisbane, Qld, Australia
Kent R. Thielen, MD, Department of Radiology, Mayo Clinic, Rochester, MN, Pascal Fontaine, DVM, MSc, Montreal, QC, Canada
United States Patricia A. Rhyner, MD, Atlanta, GA, United States
Kevin A. Lugo, MBA, ARRT, Raleigh, NC, United States Patrick Chang, MD, Dept of Radiology, Kaiser South San Francisco Medical
Kevin J. Roche, MD, New Hope, PA, United States Ctr, San Francisco, CA, United States
Kevin L. Pope, MD, Breast Center of Northwest Arkansas, Fayetteville, AR, Paul E. Lizotte, DO, MA, Valley Center, CA, United States
United States Paulo M. Bernardes, MD, Rio de Janeiro, RJ, Brazil
Keyur Mehta, MD, Montefiore Medical Center, Bronx, NY, United States Pedro E. Diaz, MD, Guaynabo, PR, United States
Kimberly Torluemke, 3D Systems, Healthcare, Littleton, CO, United States Pen-An Liao, MD, Taipei City, Taiwan
Kirby K. Wong, MBBS, MPH, Sydney, NSW, Australia Perla M. Salgado, MD, Cuernavaca, Morelos, Mexico
Klaus Kubin, MD, CT/MR Institutes, Medical Center Schallmoos, Salzburg, Peter M. Van Ooijen, MSc, PhD, Dept of Radiology, University Medical Center
Austria of Groningen, Groningen, Netherlands
Kranthi K. Kolli, PhD, MS, New York, NY, United States Peter Piechocniski, Memorial Sloan Kettering Cancer Center, New York City,
Kristi B. Oatis, MD, Lexington, KY, United States NY, United States
Kwok-chung Lai, MBChB, FRCR, Dept of Radiology & Imaging, Queen Philip S. Lim, MD, Dept of Radiology, Abington Memorial Hospital, Abington,
Elizabeth Hospital, Kowloon, Hong Kong PA, United States
Lance E. Reinsmith, MD, San Antonio, TX, United States Philipp Brantner, MD, Binningen, Switzerland
Lauralyn McDaniel, MBA, SME, Dearborn, MI, United States Philippe Grouwels, MD, Hasselt, Belgium
Leizle E. Talangbayan, MD, Long Branch, NJ, United States Phillip D. Baker, MD, PhD, Dept of Radiology, Legacy Good Samaritan
Leszek J. Jaszczak, MD, Williston, ND, United States Hospital, Portland, OR, United States
Ligia Cardona, MD, Santo Domingo, Distrito Nacional, Dominican Republic Prasad S. Dalvie, MD, Dept of Radiology, University of Wisconsin, Madison,
Lincoln Wong, MD, Omaha, NE, United States WI, United States
Liza Nellyta, MD, Department of Radiology, RS Awal Bros Pekanbaru, Qurashi M. Ali Fadlelseed, MD, PhD, National College for Med & Technical
Pekanbaru, Riau, Indonesia Studies, Kitarfoum, Sudan
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 23 of 38

R. Scott Rader, PhD, GE Healthcare, Marlborough, MA, United States Vinicius V. Alves, Niteroi, RJ, Brazil
Rajaram E. Reddy, MD, St Catherines, ON, Canada W. Brian Hyslop, MD, PhD, Dept of Radiology, University of North Carolina,
Rami M. Shorti, PhD, Intermountain Healthcare, South Jordan, UT, United States Chapel Hill, NC, United States
Ramin Javan, MD, Washington, DC, United States Wael M. Abdalla, MD, Presby South Tower, Henderson, NV, United States
Randolph K. Otto, MD, Edmonds, WA, United States Walter A. Carpenter, MD, PhD, Atlanta, GA, United States
Raphael J. Alcuri, MD, Whitesboro, NY, United States Wellington Eddy Reynaldo Paez Zumarraga, MD, Quito, Ecuador
Rasim C. Oz, MD, Baltimore, MD, United States William D. Boswell Jr., MD, Dept of Diagnostic Radiology, City of Hope
Richard A. Levy, MD, Saugerties, NY, United States National Medical Center, Duarte, CA, United States
Richard E. Barlow, MD, Sandy Springs, GA, United States William Prows, Intermountain Healthcare, Murray, UT, United States
Richard K. Brown, MD, Dept of Nuclear Medicine, University of Michigan, Ann Xing-Jun Gao, MD, Department of Radiology, Xinyang Central Hospital,
Arbor, MI, United States Xinyang, Henan, China
Richard Shoenfeld, MD, Mountain Lks, NJ, United States Yeong Shyan Lee, MBBCh, Department of Diagnostic Radiology (Basement
Rikesh J. Makanji, MD, Tampa, FL, United States 1), Singapore, Singapore
Robert A. Posniak, MD, Windermere, FL, United States Yiwen Chen, PhD, Dept of 3D Printing Med Research, China Medical
Robert L. Falk, MD, Prospect, KY, United States University Hospital, Taichung City, Taiwan
Robert M. DeWitt, MD, APO, AE, United States Yoshimi Anzai, MD, Dept of Radiology, University of Utah, Salt Lake Cty, UT,
Robert S. Redlich, MD, Hudson, OH, United States United States
Robyn A. Pugash, MD, Dept of Medical Imaging, Sunnybrook HSC, Toronto, Zheng Jin, MS, New York, NY, United States
ON, Canada
Roy G. Bryan Jr., MD, MBA, Radiology, Santa Barbara Cottage Hospital, Santa Trainee Members (July 15, 2018)
Barbara, CA, United States Adrian A. Negreros-Osuna, MD, Massachusetts General Hospital, Boston, MA,
Salim S. Merchant, FRANZCR, Melbourne, VIC, Australia United States
Sang Joon Park, PhD, Seoul National University Hospital, Seoul, Korea, Andreas Giannopoulos, MD, University Hospital Zurich, Zurich, Switzerland
Republic of Andres Vasquez, MD, MSc, New York, NY, United States
Sang-Sun Han, MD, Dept of Oral & Maxillofacial Radiology, Yonsei University Boris Kumaev, DO, University of Florida, Jacksonville, FL, United States
College of Dentistry, Seoul, Korea, Republic of Carissa M. White, MD, Venice, CA, United States
Sanjay M. Mallya, DDS, PhD, Dept of Oral & Maxillofacial Radiology, UCLA Eduardo Hernandez-Rangel, MD, University of California, Santa Ana, CA,
School of Dentistry, Los Angeles, CA, United States United States
Sanjay P. Prabhu, MBBS, FRCR, Dept of Pediatric Neuroradiology, Childrens Elias Kikano, MD, Mayfield Heights, OH, United States
Hospital Boston, Boston, MA, United States Elisa Spoldi, DVM, University of Florida College of Veterinary Med, Gainesville,
Sankar P. Sinha, MBBS, FRCR, Nuneaton, Warwickshire, United Kingdom FL, United States
Sanket Chauhan, MD, Dept of Surgery, Baylor University Medical Center, Jessica D. Shand Smith, MBChB, Edinburgh, United Kingdom
Dallas, TX, United States Justin Kerby, II, MD, MS, Wichita, KS, United States
Satinder S. Rekhi Jr., MD, Manorville, NY, United States Kirk P. Langheinz, MD, Lafayette General Medical Center - Cancer Center of
Scott H. Faro, MD, Haddonfield, NJ, United States Acadiana, Lafayette, LA, United States
Scott T. Williams, MD, San Juan Capo, CA, United States Luis G. Ricardez, MD, Hospital Civil de Culiacan, Culiacan, Sinaloa, Mexico
Sepideh Sefidbakht, MD, Powel, OH, United States Michael Bartellas, MS, St Johns, NL, Canada
Sergio A. Gonzalez, MD, El Paso, TX, United States Narayana Vamyanmane Dhananjaya Kotebagilu, MBBS, MBA, Abhayahasta
Seth J. Berkowitz, MD, Brookline, MA, United States Multispeciality Hospital, Bengaluru, Karnataka, India
Shannon N. Zingula, MD, Dept of Radiology, Mayo Clinic, Rochester, MN, Sadia R. Qamar, MBBS, Vancouver General Hospital, UBC, Vancouver, BC,
United States Canada
Shannon R. Kirk, MD, Loma Linda University, Loma Linda, CA, United States Sherazad Islam, MD, Glenview, IL, United States
Sharon W. Gould, MD, Kemblesville, PA, United States Vasanthakumar Venugopal, MD, New Delhi, Delhi, India
Shuai Leng, PhD, Dept of Radiology, Mayo Clinic, Rochester, MN, United States Vjekoslav Kopacin, MD, Osijek, Croatia
Sidney D. Machefsky, MD, University Cy, MO, United States Yu-hui Huang, MS, Chicago, IL, United States
Sofiane Derrouis, MD, Neuchatel, Switzerland
Srini Malini, MD, Womens Specialists of Houston at TCH, Texas Childrens Affiliated Contributors (non-members of the Special Interest Group)
Hospital Pavilion for Women, Houston, TX, United States Jeffrey P Jacobs, MD, Division of Cardiovascular Surgery and Director of the
Stephane Khazoom, MD, Chambly, QC, Canada Andrews/Daicoff Cardiovascular Program, Johns Hopkins All Children’s Heart
Stephen E. Russek, PhD, NIST, Boulder, CO, United States Institute, St Petersburg, FL
Steven C. Horii, MD, Dept of Radiology, University of Pennsylvania Medical Kenneth E. Salyer, MD, World Craniofacial Foundation, Dallas, TX, US and
Center, Philadelphia, PA, United States Texas A&M University, Dallas, TX, US
Steven R. Parmett, MD, Teaneck, NJ, United States R. Bryan Bell, MD, DDS, Providence Head and Neck Cancer Program,
Sumit Pruthi, MBBS, Dept of Radiology, Vanderbilt Childrens Hospital, Providence Cancer Institute, Portland, OR, US and Head & Neck Surgical
Nashville, TN, United States Associates, Portland, OR, US
Summer J. Decker, PhD, Dept of Radiology, University of South Florida
College of Medicine, Tampa, FL, United States Authors’ contributions
Tan M. Nguyen, MD, Dept of Radiology, Sacramento, CA, United States All primary authors edited, reviewed, and approved this manuscript. All included
Terence J. O’Loughlin, MD, Provincetown, MA, United States special interest group member coauthors, listed in the Acknowledgements
Terry C. Lynch, MD, Dept of Radiology, San Francisco General Hospital, San section, were provided with the final manuscript for review and approved its
Francisco, CA, United States publication.
Timothy L. Auran, MD, San Luis Obispo, CA, United States
Todd Goldstein, PhD, Northwell Health, USA, NY, United States Competing interests
The primary authors declare no competing interests. RSNA Special Interest
Todd Pietila, Materialise, Plymouth, MI, United States
Group for 3D Printing includes a variety of industry representatives with
Tone Lindgren, MD, Pelham, NY, United States
voting privileges, including representatives from Materialise Inc., Stratasys,
Tracy S. Chen, DO, MPH, Carmel, CA, United States
3D Systems, and TeraRecon, as detailed in the Acknowledgements section.
Vartan M. Malian, MD, Roseville, CA, United States
Vicente Gilsanz, MD, PhD, Dept of Radiology, Childrens Hospital Los Angeles,
Los Angeles, CA, United States Publisher’s Note
Victor A. McCoy, MD, Prairieville, LA, United States Springer Nature remains neutral with regard to jurisdictional claims in published
Vijay Jayaram, MBBS, PhD, Enfield, Middlesex, United Kingdom maps and institutional affiliations.
Chepelev et al. 3D Printing in Medicine (2018) 4:11 Page 24 of 38

Author details 15. Sodian R, Weber S, Markert M, Rassoulian D, Kaczmarek I, Lueth TC, Reichart
1
Department of Radiology and The Ottawa Hospital Research Institute, B, Daebritz S. Stereolithographic models for surgical planning in congenital
University of Ottawa, Ottawa, ON, Canada. 2Center for Advanced Imaging heart surgery. Ann Thorac Surg. 2007;83(5):1854–7.
Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for 16. Valverde I, Gomez G, Gonzalez A, Suarez-Mejias C, Adsuar A, Coserria JF,
Biomedical Imaging, Department of Radiology, NYU School of Medicine, Uribe S, Gomez-Cia T, Hosseinpour AR. Three-dimensional patient-specific
New York, NY, USA. 3Sackler Institute of Graduate Biomedical Sciences, NYU cardiac model for surgical planning in Nikaidoh procedure. Cardiol Young.
School of Medicine, New York, NY, USA. 4Rady Children’s Hospital, San Diego, 2015;25(4):698–704.
CA, USA. 5Department of Diagnostic Radiology, Division of Diagnostic 17. Schievano S, Migliavacca F, Coats L, Khambadkone S, Carminati M, Wilson N,
Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, Deanfield JE, Bonhoeffer P, Taylor AM. Percutaneous pulmonary valve
USA. 6Mallinckrodt Institute of Radiology, Washington University School of implantation based on rapid prototyping of right ventricular outflow tract
Medicine, Saint Louis, MO, USA. 7Baltimore VA Medical Center, University of and pulmonary trunk from MR data. Radiology. 2007;242(2):490–7.
Maryland Medical Center, Baltimore, MD, USA. 8Department of Radiology and 18. Ryan JR, Moe TG, Richardson R, Frakes DH, Nigro JJ, Pophal S. A novel
Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA. approach to neonatal Management of Tetralogy of Fallot, with pulmonary
9
Department of Neurosurgery, State University of New York Buffalo, Buffalo, atresia, and multiple Aortopulmonary collaterals. JACC Cardiovasc Imaging.
NY, USA. 10Department of Radiology, Mayo Clinic, Rochester, MN, USA. 113D 2015;8(1):103–4.
Medical Applications Center, Walter Reed National Military Medical Center, 19. Bhatla P, Tretter JT, Chikkabyrappa S, Chakravarti S, Mosca RS. Surgical
Washington, DC, USA. planning for a complex double-outlet right ventricle using 3D printing.
Echocardiography. 2017;34(5):802–4.
Received: 7 August 2018 Accepted: 19 September 2018 20. Farooqi KM, Gonzalez-Lengua C, Shenoy R, Sanz J, Nguyen K. Use of a three
dimensional printed cardiac model to assess suitability for biventricular
repair. World J Pediatr Congenit Heart Surg. 2016;7(3):414–6.
21. Farooqi KM, Nielsen JC, Uppu SC, Srivastava S, Parness IA, Sanz J, Nguyen K.
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