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WO2012069965A1 - Corrections interactives de cartes de déformation - Google Patents

Corrections interactives de cartes de déformation Download PDF

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Publication number
WO2012069965A1
WO2012069965A1 PCT/IB2011/055145 IB2011055145W WO2012069965A1 WO 2012069965 A1 WO2012069965 A1 WO 2012069965A1 IB 2011055145 W IB2011055145 W IB 2011055145W WO 2012069965 A1 WO2012069965 A1 WO 2012069965A1
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WO
WIPO (PCT)
Prior art keywords
planning
planning image
locations
ooi
image set
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PCT/IB2011/055145
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English (en)
Inventor
Karl Antonin Bzdusek
Stephane Allaire
Nicholas Gordon Lance Hardcastle
Wolfgang Axel Tome
Original Assignee
Koninklijke Philips Electronics N.V.
University Of Wisconsin
University Health Network
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Application filed by Koninklijke Philips Electronics N.V., University Of Wisconsin, University Health Network filed Critical Koninklijke Philips Electronics N.V.
Publication of WO2012069965A1 publication Critical patent/WO2012069965A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/103—Treatment planning systems
    • A61N5/1031—Treatment planning systems using a specific method of dose optimization
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/103—Treatment planning systems
    • A61N5/1038—Treatment planning systems taking into account previously administered plans applied to the same patient, i.e. adaptive radiotherapy

Definitions

  • the following relates to the medical diagnostic imaging arts, radiation therapy arts, medical arts, radiation therapy planning arts, image processing arts, and related arts.
  • diagnostic images are taken from time to time to monitor progress of a treatment regimen, advancement of a medical condition, or plan a treatment course.
  • diagnostic image For example, in radiation therapy, using information from diagnostic image as a guide, spatially targeted dosages of ionizing radiation are applied to a tumor or other region containing cancerous or malignant tissue.
  • the applied radiation preferentially kills cancerous or malignant tissue. Because ionizing radiation is harmful to both malignant and healthy cells, precise spatial targeting of the radiation is important for applying effective radiation therapy to the malignancy while limiting collateral damage to healthy tissue.
  • the radiation beam is applied at angular positions around the subject in a manner that combines to produce a targeted total radiation dosage spatial distribution that is concentrated on the tumor or other region to be treated, while keeping the integrated exposure of certain radiation-sensitive critical organs below a safety threshold.
  • Angular coverage can be achieved by using a plurality of stationary radiation sources distributed around the subject, or by rotating a single radiation source such as a linear accelerator (LINAC) around the subject.
  • the radiation therapy is planned in advance for a specific subject, based on imaging data acquired of that subject.
  • CT computed tomography
  • MR magnetic resonance
  • PET positron emission tomography
  • SPECT single photon emission CT
  • ultrasound ultrasound
  • MR magnetic resonance
  • SPECT single photon emission CT
  • Radiation plan parameters are provided by the oncologist or other medical personnel.
  • the radiation therapy plan parameters typically include a minimum or target dose to be delivered to the malignant tumor, and maximum permissible dosages for the risk organs or regions.
  • contoured targets and organs at risk together with the radiation therapy plan parameters and known information about radiation attenuation or absorption characteristics of the various tissues serve as inputs to optimize the radiation beam spatial profile and intensities to concentrate the radiation in the target while limiting exposure of risk organs in a deformation map.
  • Deformable image registration is mapping of individual volume elements from one image to another image using non-rigid translation and/or rotations. That is, each volume element of the image is mapped separately.
  • Deformable image registration is required when anatomical differences exist between images that are beyond rigid translation/rotation.
  • Some applications of deformable image registration include propagation of Object(s) of Interest (OOIs) such as contours or Region(s) of Interest (ROIs) and landmarks or Point(s) of Interest (POIs), deforming PET/CT studies to a CT acquired for treatment planning for contouring and evaluation, and/or accumulation of dose computed on multiple image sets of the same patient.
  • OOIs Object(s) of Interest
  • ROIs contours or Region(s) of Interest
  • POIs Point(s) of Interest
  • Deformable image registration can be used for cases such as, but not limited to, adaptive planning for a patient during the course of therapy, 4-D planning/optimization, composite planning, and multimodality treatment plan generation.
  • a radiation planning module is configured to update a first radiation therapy plan (RTP) generated with a first planning image set that has been segmented to define locations of Object(s) of Interest (OOIs), including contours delineating Region(s) of Interest (ROIs) and/or landmarks indicating Point(s) of Interest (POIs).
  • RTP radiation therapy plan
  • the planning module receives a second planning image from an imaging device and registers the first and second planning images and generates a first transform deformation map which transforms one of the planning image sets into alignment with the other.
  • the OOI locations are operated on with the deformation map to propagate the 001 locations onto the second planning image set.
  • the deformation map is corrected in accordance with deviations between the propagated OOI locations and locations of the corresponding OOIs in the second planning image set.
  • the first radiation therapy plan is replicated and the replication adjusted with the corrected deformation map to generate an updated radiation therapy plan for the second planning image set.
  • a method of updating a first radiation therapy plan generated from a first planning image set that has been segmented to define locations of Object(s) of Interest (OOIs), including contours delineating Region(s) of Interest (ROIs) and/or landmarks indicating Point(s) of Interest (POIs) is provided.
  • a second planning image set is received and the first and second planning image sets are registered with a computer-implemented algorithm to generate a first deformation map which transforms one of the planning image sets into alignment with the other.
  • the deformation map operates on the object of interest locations to propagate the object of interest locations onto the second planning image set.
  • the deformation map is corrected in accordance with a deviation between the propagated OOIs and locations of the
  • the first radiation therapy plan is replicated and the replication adjusted with the corrected deformation map to generate an updated radiation therapy plan for the second planning image set.
  • a radiation planning module is configured to contain a first planning image that has been segmented to define locations of Object(s) of Interest (OOIs), including contours delineating Region(s) of Interest (ROIs) and/or landmarks indicating Point(s) of Interest (POIs).
  • the planning module receives an image pair where both images are in the same coordinate frame.
  • the planning module registers the first planning image with one of the images from the image pair and generates a first transform deformation map that transforms the planning image set into alignment with the other images.
  • the OOI locations are operated on with the deformation map to propagate the OOI locations onto the second planning image set.
  • the deformation map is corrected in accordance with deviations between the propagated OOI locations and locations of the corresponding OOIs in the second planning image set. Both images in the image pair are operated on with the deformation map to generate deformed images such that all three images are in the same coordinate frame.
  • One advantage resides in providing a deformation map for a treatment plan with less deformation errors.
  • Another advantage resides in providing more accurate mapping for treatment dose planning and tracking.
  • Another advantage resides in providing a radiologist or other medical professional to generate an improved deformation map.
  • Another advantage resides in providing a radiologist or other medical professional to generate an improved deformed image for contouring and analysis.
  • FIGURE 1 diagrammatically shows a radiation therapy system including a radiation therapy planning module
  • FIGURE 2 diagrammatically shows a radiation therapy planning method suitably performed by the radiation therapy planning module of the system of FIGURE 1;
  • FIGURES 3 and 4 diagrammatically show a region that diagrammatically illustrates selected operations of the method of FIGURE 2.
  • a radiation therapy system includes an imaging modality 10 suitable for acquiring planning images for planning radiation therapy.
  • the imaging modality 10 is a computed tomography (CT) scanner.
  • CT computed tomography
  • the CT scanner has a large patient aperture, 85 cm for example, which is large enough to accommodate the patient arranged in typical radiation therapy positions.
  • Other CT scanners can be used instead, as well as other imaging modalities such as positron emission tomography (PET), magnetic resonance (MR), single photon emission computed tomography (SPECT), and so forth.
  • PET positron emission tomography
  • MR magnetic resonance
  • SPECT single photon emission computed tomography
  • Acquired images are stored in an image memory 12, which may be in a central electronic records storage system.
  • the planning image is typically acquired of the subject scheduled to undergo the radiation therapy.
  • the subject may be an oncology patient, or a veterinary subject, or the like.
  • planning image in this context relates to the images that are used to plan radiation therapy sessions.
  • the planning images (or set of planning images), for example, generated at two different times, are used in generating deformation maps, which describe the deformations that transform or deform the planning image generated at one time into a common coordinate system and registered with the planning image taken at a different time.
  • Modeling anatomical shape change as deformation uses landmarks, features, surfaces, and the like in 3-D to define a mapping (transformation) between two images or sets of images (e.g., of the same anatomy) into the same coordinate frame or frame of reference.
  • Various algorithms are available for performing these mappings or transformations among sets of images. Once landmark and/or features and/or surfaces are identified and paired between the images, these points are used to compute a coordinate transformation that maps every coordinate location in one image to a corresponding location in the other image and align them accordingly into one coordinate system, which is called image registration.
  • a planning module 20 receives planning images at various times during a radiation therapy process.
  • the module 20 updates an earlier radiation therapy plan (RTP) and its cumulative dose map to compensate for anatomical changes, e.g., shrinking, expanding, shifting, etc, during prior therapy sessions.
  • RTP radiation therapy plan
  • a first planning image is generated and a first RTP is generated. After one or a series of therapy sessions, a subsequent planning image is generated and the module 20 updates the RTP.
  • the planning module 20 includes automatic segmentation tools 22 and manual segmentation and editing tools 24.
  • Model based segmentation or other methods are used to modify a representation of the ROI boundaries, such as by contours, binary mask, or mesh vertices therein and/or the POI positions.
  • the segmentation tools are used to delineate, e.g., with superimposed contours and/or dots, target Object(s) of Interest (OOIs) including Region(s) of Interest (ROIs) and/or Point(s) of Interest (POIs) and other adjoining ROIs, OOIs, and/or POIs particularly at risk regions in which radiation dose is to be limited.
  • OOIs target Object(s) of Interest
  • ROIs Region(s) of Interest
  • POIs Point(s) of Interest
  • the manual segmentation tools include editing tools, which allow the user to manually adjust image features, particularly the segmentation contours and/or the landmark positions when the images are displayed on a display 26.
  • Manual inputs 28, such as a keyboard or mouse, enable the user to use various virtual tools to push or pull the OOIs to change their shapes and positions to conform more accurately to the image content.
  • the radiation target region may be a cancerous tumor
  • the one or more risk regions may include neighboring vital organs or tissue whose radiation exposure should be kept below a maximum value.
  • the radiation therapy planning is responsive to dose plan parameters that are indicative of dosage or dosage constraints for the radiation target region and the one or more risk regions.
  • An accumulated dose map is generated which shows the cumulative radiation dose which the treatment plan delivers to each region.
  • the planning module 20 also includes a deformable or elastic registration module which can implement one or more deformable, elastic registration algorithms 30.
  • deformable registration algorithms compare two images of a common area of the same subject to determine the differences between them and generate a transform, such as a deformation map, which can be applied to one of the images to transform it into alignment or registration with the other.
  • transform such as a deformation map
  • One of the ways to determine the accuracy of the mapping is to analyze the propagated OOI locations.
  • the editing tool module 24 is utilized to adjust contour points and/or features on the OOI locations propagated onto the second image.
  • the specialist can adjust the OOI locations manually using contour or mesh editing, for example.
  • the same or a different algorithm of the deformation image registration algorithm module 30 is then used to generate a new or corrected deformation map based on corresponding points of the locations of the original or first planning image set and the edited locations on the second image.
  • the planning module 20 also includes a radiation therapy planning module or algorithm 32 which can generate an initial RTP and update the RTP including the accumulated dose each time a subsequent planning image is generated.
  • a radiation therapy planning module or algorithm 32 can generate an initial RTP and update the RTP including the accumulated dose each time a subsequent planning image is generated.
  • the corrected deformation map is applied to the subsequent plan to conform the OOIs and their dose to the planning image for a second treatment session. In this manner, the accumulated radiation in each OOI is accurately determined over a plurality of treatment sessions even as OOIs shift, shrink, expand, change shape, or the like.
  • a deformable image registration can be used, for example, when a radiologist compares images acquired before and after administration of a contrast enhancing pharmaceutical that highlights malignant masses. If a tumor was shrunk by the therapy, the tumor is smaller and the surrounding OOIs have relaxed back closer to their normal location. Comparison of images before and after an intervention, such as radiation therapy, is performed. A simple change in position can cause apparent deformation of a breast, for example, which further complicates the comparison. Matching or image mapping is therefore performed to eliminate the deformation. The differences remaining between the original 3-D images and the non-ideally corrected images can be determined by subtracting the two images and taking an absolute value of the result.
  • a control processor 34 controls the modules and algorithms to perform the method described in conjunction with FIGURE 2.
  • the radiation therapy plan generated by the radiation therapy planning module 20 after adjustment of any propagated OOIs is stored in a radiation therapy plan memory 50.
  • a radiation therapy apparatus 52 is employed to deliver therapeutic radiation to the subject controlled by a radiation therapy control system 54 in accordance with the radiation therapy plan stored in the memory 50.
  • the radiation therapy delivery apparatus 52 is a tomotherapy linear accelerator (LINAC), and the radiation therapy control system 54 operates multi-leaf collimator (MLC) or other radiation beam profile-shaping apparatus of the LINAC 52 to modulate beam intensity and profile as the linear accelerator is moved around the subject, so as to deliver a radiation dose distribution into the subject that provides the desired integrated radiation dosage to the target feature while suitably limiting or constraining radiation exposure of sensitive critical features in accordance with the radiation therapy plan.
  • LINAC tomotherapy linear accelerator
  • MLC multi-leaf collimator
  • the radiation therapy planning module 20 can be embodied by a single digital processor, two or more digital processors, computers, application-specific integrated circuitry (ASIC), or so forth.
  • the radiation therapy planning including editing tools for generating deformation maps may be embodied by a storage medium storing instructions executable by a digital processor to perform the planning.
  • the storage medium may be a hard disk or other magnetic storage medium, an optical disk or other optical storage medium, a random access memory (RAM), read-only memory (ROM), FLASH memory, or other electronic storage medium, various combinations thereof, or so forth.
  • a first planning image is generated and/or displayed.
  • the initial first planning image is segmented 62 to define initial segmentation contours of the target and other OOIs.
  • the operation 62 can employ initial contouring utilizing automatic segmentation of the planning image, a semi-automatic segmentation, or manual segmentation of the OOIs.
  • a radiation therapy planning (RTP) operation is calculated 63.
  • the radiation therapy plan is generated using commercially available software. In other embodiments, the RTP plan is generated semi-automatically or manually.
  • any image segmentation operation 62 and RTP operation 63 can be performed using the radiation therapy planning module 20.
  • the initial radiation therapy plan is implemented to treat the patient.
  • the LINAC 52 is used to irradiate the patient over one or a series of therapy sessions.
  • a second planning image or image set is generated at an operation 64.
  • the first and second sets of planning images e.g. 1st and 2nd 3-D images
  • a deformation algorithm to determine a transform, usually a deformation map 66, which brings the first and second planning image sets into registration or alignment.
  • a deformation algorithm to determine a transform, usually a deformation map 66, which brings the first and second planning image sets into registration or alignment.
  • a deformation algorithm for example, a constant volume, 3-D, second order Taylor series propagation or warp to the original images can be performed, (see, Davis, Malcolm H., "A Physics-Based Coordinate Transformation for 3-D Image Matching" in IEEE Transactions on Medical Imaging, Vol. 16, No. 3 (1997).
  • Other types of deformable image registration algorithms are also envisioned by the presented disclosure as one of ordinary skill in the art will appreciate, such as demons, b-spline, level set and the like.
  • the deformation map can be generated by various transformations, such as spline algorithms, for example, a thin plate spline transform based on corresponding mesh vertices of the segmented contours or features.
  • a set of images is used in order to perform image registration of the OOIs in a patient, for example.
  • Image registration allows the comparison or integration of data points obtained from different measurements at various times.
  • multi-dimensional splines e.g., a thin plate spline, or the like
  • a volume spline e.g., elastic spline, or other imaging registration algorithms may be used in generating a deformed planning image.
  • the locations of the OOIs including ROI contours and/or POI positions of the first planning image set are propagated or warped 67 with the deformation map and overlaid on the second planning image set for display 68 with propagated OOIs.
  • the difference between the propagated OOI locations and the actual 001 locations is determined and corrected in a local OOI correction operation 70, including ROI contour corrections and/or POI position shifting, to bring the OOIs into coincidence with the image contents.
  • the correction can be automatic, semi-automatic, or manual.
  • the second planning image set is overlaid with the propagated OOI locations.
  • the image content information and the user's knowledge are used to determine the accuracy of the propagated OOIs and modify these using editing tools if there is error.
  • Interactive software tools such as mesh editing, paint brush, or any method allowing the user to modify representations of ROIs, such as contours, binary making, or mesh vertices may be implemented.
  • the propagated OOIs would be automatically adjusted to the image content using an algorithm such as model based segmentation which may also incorporate shape priors or the like. Note that in an automatic OOI correction operation, previous display operation 68 may be skipped.
  • a corrected deformation map is generated from manual and/or automatic OOI correction operations.
  • corresponding landmark (POI) positions are used as well as corresponding points selected at locations distributed along the ROI contours.
  • ROI contour point selection vary from random selection through regular sampling to algorithms that determine boundary surface areas with large curvature, points that represent ROI extents, for example.
  • Various algorithms such as 3-D affine transformation, thin plate spline, volume spline, or elastic body spline, etc, may be used to generate a new
  • deformation map based on either the selected corresponding OOI points entirely or a combination of the selected corresponding OOI points and the original deformation transform or corresponding points.
  • the various algorithms and the like discussed above are used to achieve a global update or correction of the deformation map to account for local manual and/or automated OOI corrections in a previous operation 70. This may be performed iteratively 74 until all propagated OOI locations are corrected or until all planning criteria are met.
  • the display 26 displays the second planning image set overlaid with the OOI locations propagated from the first planning image.
  • the deformation map is applied by the radiation therapy plan and the accumulated dose map to generate an updated radiation dose map in an operation 76.
  • Applying the deformation map to the accumulated dose map transforms the OOIs and their accumulated doses into conformity with the OOIs of the planning map for calculating the RTP for the next therapy session.
  • the updated dose map is approved by the radiologist, the patient undergoes one or a series of therapy sessions 77.
  • a third planning image set is generated and the above-described steps are repeated. Additional planning images, updated deformation maps, updated radiation therapy plans and updated accumulated dose maps are generated as needed over the course of the therapy.
  • the second planning image or set could be registered to the first planning image set.
  • FIGURES 3 and 4 illustrate an example of the OOI correction operation 70 and the basis for deformation map correction operation 72.
  • An initial planning image is segmented to define an ROI contour 90 of a tumor, an organ at risk, or one or more other contoured ROIs or positioned landmark POIs or any OOIs, for example.
  • ROIs or POIs may be referred to herein, the disclosure is not limited to either one, and includes both in addition to OOIs of an image accordingly.
  • the first planning image is captured by a CT, MR, or other imaging modality 10. Operating on the first image with the initial deformation map in operation 67 propagates the ROI contour 90 to a propagated ROI contour 92 and the POI position 91 to a propagated POI position 93.
  • the propagated ROI contour 92 and the propagated POI position 93 are overlaid on the image contents of a new or second planning image, in which appears the desired shape 94 of the ROI, and the desired position 95 of the POI.
  • manual and/or automated OOI correction methods in operation 70 have produced the corrected ROI contour 92' and the corrected POI position 93' so as to bring these OOIs in coincidence with the desired locations 94 and 95 in the second planning image.
  • These local OOI corrections provide corrected points of correspondence 96' between the OOIs in the first planning image and the corrected OOI locations in the second planning image, which are used to correct the global deformation map.
  • applying the corrected deformation map to the first planning image would propagate the points of correspondence 96' of the re-propagated OOI locations 92' and 93' into better coincidence with the second planning image contents 94 and 95 (the correspondence 96' would be exactly satisfied in the case where the deformation map method relies on interpolation, whereas it would be better approximately satisfied in the case where the deformation map method relies on approximation).
  • the OOI corrections are carried out directly with the editing tools of editing sub-module 24 without any further calculation or algorithm being implemented before generating the corrected deformation map.
  • a region R in FIGURE 3 illustrates the difference between points of correspondence at the first propagated contour 92 and the structure ROI 94 in the second image. Radiation dose in region R could erroneously be attributed to the ROI defined by contour 94 rather than the adjacent ROI in the second planning image. Computer implemented algorithms can be used to reduce the difference to zero. Afterwards, the newly corrected deformation map is able to be applied to volumes, such as in a moving image, a dose volume, or any other desired volume and/or any other OOIs.
  • the corrected points of correspondence are input to an automated segmentation/contouring algorithm, which allows for relaxation of the accuracy requirements of the automated algorithm.
  • the technician is informed of which areas of the initial contour delineation need to be improved.
  • the radiation target region is the prostate and the risk regions to be delineated typically include femur heads, the bladder, and the rectum.
  • Certain contour segments are unlikely to have high impact regardless of the accuracy of delineation, while other contour segments need to be very accurate.
  • a learned or pre-calculated impact values become part of (i.e., a priori knowledge included in) a model used for automated or model-based segmentation.
  • the impact values are used as an additional (probabilistic) feature to balance accuracy in areas where contours are difficult to delineate. In such embodiments the calculation of dose during the segmentation can optionally be avoided.

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Life Sciences & Earth Sciences (AREA)
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Abstract

L'invention concerne un système de planification de radiothérapie comprenant un module de planification (20) qui reçoit un premier ensemble d'images de planification d'un appareil d'imagerie de diagnostic (10) et qui utilise des outils de segmentation automatique (22) ou des outils de segmentation manuelle (24) et un système de planification de radiothérapie (32) destiné à produire un premier plan de radiothérapie. Après que le premier plan de radiothérapie a été appliqué lors d'une ou plusieurs sessions de thérapie, un second ensemble d'images de planification est produit. Le module de planification (20) utilise un algorithme d'alignement d'images déformables (30) afin d'aligner les ensembles d'images de planification et de générer une carte de déformation correspondante qui est appliquée à des objets à examiner segmentés (OOI, Objets Of Interest) du premier ensemble d'images de planification segmentées afin de propager les objets à examiner vers le second ensemble d'images de planification. La carte de déformation est corrigée conformément à des écarts entre les positions des objets à examiner propagés et effectifs en deux étapes : 1) des corrections manuelles et/ou automatisées des objets à examiner propagés sont effectuées, par exemple des corrections de contours de régions à examiner et/ou des positions de repères à examiner ; 2) une carte de déformation globale corrigée est générée à partir de ces corrections d'objets à examiner locaux. La carte de déformation corrigée est appliquée au premier plan de radiothérapie et une carte de rayonnement accumulé représentant le rayonnement accumulé dans chaque objet à examiner pendant la ou les session(s) de thérapie mise(s) en œuvre avec le premier plan de radiothérapie.
PCT/IB2011/055145 2010-11-23 2011-11-17 Corrections interactives de cartes de déformation WO2012069965A1 (fr)

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WO2014096993A1 (fr) * 2012-12-17 2014-06-26 Koninklijke Philips N.V. Thérapie par rayonnements avec calcul adaptatif de la dose en temps réel
EP3109824A1 (fr) 2015-06-24 2016-12-28 RaySearch Laboratories AB Système et méthode pour la manipulation des données d'image
WO2018055066A1 (fr) 2016-09-21 2018-03-29 Koninklijke Philips N.V. Appareil pour le contourage adaptatif d'une partie du corps
WO2018081537A1 (fr) * 2016-10-31 2018-05-03 Konica Minolta Laboratory U.S.A., Inc. Procédé et système de segmentation d'image à l'aide d'une rétroaction commandée
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EP3789085A1 (fr) * 2019-09-05 2021-03-10 Koninklijke Philips N.V. Enregistrement d'image déformable guidé par dose
EP3827883A3 (fr) * 2016-12-13 2021-07-21 ViewRay Technologies, Inc. Systèmes et méthodes de radiothérapie
WO2021184161A1 (fr) * 2020-03-16 2021-09-23 Shanghai United Imaging Healthcare Co., Ltd. Systèmes et procédés de génération de plan de radiothérapie adaptative
EP4249049A1 (fr) 2022-03-22 2023-09-27 RaySearch Laboratories AB Procédé et système de planification de traitement radiothérapeutique fiable pour les incertitudes de cartographie de dose
WO2023205984A1 (fr) * 2022-04-25 2023-11-02 广州科莱瑞迪医疗器材股份有限公司 Association de roi et procédé d'étiquetage

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