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Diagnostics, Volume 14, Issue 1 (January-1 2024) – 120 articles

Cover Story (view full-size image): The use of handheld point-of-care (POCUS) systems has increased rapidly throughout emergency care and hospital medicine. Studies of cart-based POCUS systems have shown improvements in patient care, and for specific use cases, handheld POCUS systems using traditional piezoelectric crystals to generate an image have also performed well. Newer non-piezoelectric systems that instead use a chip array to generate images are generally less expensive, but little is known about how these devices perform in daily use conditions in an emergency setting. After one year of continuous use in an emergency department and trauma center, we retrospectively evaluated the performance of a non-piezoelectric handheld POCUS system to characterize its diagnostic performance for emergent and urgent diagnoses. View this paper
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17 pages, 1460 KiB  
Article
A Sequent of Gram-Negative Co-Infectome-Induced Acute Respiratory Distress Syndrome Are Potentially Subtle Aggravators Associated to the SARS-CoV-2 Evolution of Virulence
by Kamaleldin B. Said, Ahmed Alsolami, Khalid F. Alshammari, Fawaz Alshammari, Sulaf A. Alhallabi, Shahad F. Alafnan, Safia Moussa, Abdelhafiz I. Bashir, Kareemah S. Alshurtan, Rana Aboras, Ehab K. Sogeir, Alfatih M. A. Alnajib, Abdullah D. Alotaibi and Ruba M. Elsaid Ahmed
Diagnostics 2024, 14(1), 120; https://doi.org/10.3390/diagnostics14010120 - 4 Jan 2024
Viewed by 1584
Abstract
Acute respiratory distress syndrome (ARDS) is one of the major problems in COVID-19 that is not well understood. ARDS is usually complicated by co-infections in hospitals. Although ARDS is inherited by Europeans and Africans, this is not clear for those from the Middle [...] Read more.
Acute respiratory distress syndrome (ARDS) is one of the major problems in COVID-19 that is not well understood. ARDS is usually complicated by co-infections in hospitals. Although ARDS is inherited by Europeans and Africans, this is not clear for those from the Middle East. There are severe limitations in correlations made between COVID-19, ARDS, co-infectome, and patient demographics. We investigated 298 patients for associations of ARDS, coinfections, and patient demographics on COVID-19 patients’ outcomes. Of the 149 patients examined for ARDS during COVID-19, 16 had an incidence with a higher case fatality rate (CFR) of 75.0% compared to those without ARDS (27.0%) (p value = 0.0001). The co-infectome association showed a CFR of 31.3% in co-infected patients; meanwhile, only 4.8% of those without co-infections (p value = 0.01) died. The major bacteria were Acinetobacter baumannii and Escherichia coli, either alone or in a mixed infection with Klebsiella pneumoniae. Kaplan–Meier survival analysis of COVID-19 patients with and without ARDS revealed a significant difference in the survival time of patients with ARDS (58.8 +/− 2.7 days) and without ARDS (41.9 +/− 1.8 days) (p value = 0.0002). These findings prove that increased hospital time was risky for co-infectome-induced SDRS later on. This also explained that while empiric therapy and lethal ventilations delayed the mortality in 75% of patients, they potentially did not help those without co-infection or ARDS who stayed for shorter times. In addition, the age of patients (n = 298) was significantly associated with ARDS (72.9 +/− 8.9) compared to those without it (56.2 +/− 15.1) and was irrespective of gender. However, there were no significant differences neither in the age of admitted patients before COVID-19 (58.5 +/− 15.3) and during COVID-19 (57.2 +/− 15.5) nor in the gender and COVID-19 fatality (p value 0.546). Thus, Gram-negative co-infectome potentially induced fatal ARDS, aggravating the COVID-19 outcome. These findings are important for the specific differential diagnosis of patients with and without ARDS and co-infections. Future vertical investigations on mechanisms of Gram-negative-induced ARDS are imperative since hypervirulent strains are rapidly circulating. This study was limited as it was a single-center study confined to Ha’il hospitals; a large-scale investigation in major national hospitals would gain more insights. Full article
(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)
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<p>Comparison of survival analysis in COVID-19 subjects with no ARDS versus those with it.</p>
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<p>Comparison of survival analysis in COVID-19–ARDS patients with or without bacterial co-infection.</p>
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<p>Comparison of survival analysis in COVID-19 subjects with or without bacterial co-infection in subjects without ARDS.</p>
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<p>Association of admitted patients’ age with ARDS incidence rates in the study population in Ha’il, Saudi Arabia.</p>
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<p>Kaplan–Meier survival analysis of COVID-19 patients with and without ARDS.</p>
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15 pages, 2739 KiB  
Article
Temporal Trend of the SARS-CoV-2 Omicron Variant and RSV in the Nasal Cavity and Accuracy of the Newly Developed Antigen-Detecting Rapid Diagnostic Test
by Daisuke Tamura, Yuji Morisawa, Takashi Mato, Shin Nunomiya, Masaki Yoshihiro, Yuta Maehara, Shizuka Ito, Yasushi Ochiai, Hirokazu Yamagishi, Toshihiro Tajima, Takanori Yamagata and Hitoshi Osaka
Diagnostics 2024, 14(1), 119; https://doi.org/10.3390/diagnostics14010119 - 4 Jan 2024
Viewed by 1545
Abstract
The aim of this work is to analyze the viral titers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and respiratory syncytial virus (RSV) at the anterior nasal site (ANS) and nasopharyngeal site (NS), evaluate their virological dynamics, and validate the usefulness of [...] Read more.
The aim of this work is to analyze the viral titers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and respiratory syncytial virus (RSV) at the anterior nasal site (ANS) and nasopharyngeal site (NS), evaluate their virological dynamics, and validate the usefulness of a newly developed two-antigen-detecting rapid antigen diagnostic test (Ag-RDT) that simultaneously detects SARS-CoV-2 and RSV using clinical specimens. This study included 195 asymptomatic to severely ill patients. Overall, 668 specimens were collected simultaneously from the ANS and NS. The cycle threshold (Ct) values calculated from real-time polymerase chain reaction were used to analyze temporal changes in viral load and evaluate the sensitivity and specificity of the Ag-RDT. The mean Ct values for SARS-CoV-2-positive, ANS, and NS specimens were 28.8, 28.9, and 28.7, respectively. The mean Ct values for RSV-positive, ANS, and NS specimens were 28.7, 28.8, and 28.6, respectively. SARS-CoV-2 and RSV showed the same trend in viral load, although the viral load of NS was higher than that of ANS. The sensitivity and specificity of the newly developed Ag-RDT were excellent in specimens collected up to 10 days after the onset of SARS-CoV-2 infection and up to 6 days after the onset of RSV infection. Full article
(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)
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<p>Flowchart for the selection of the study population.</p>
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<p>Comparison of cycle threshold (Ct) values for all specimens, anterior nasal, and nasopharyngeal specimens for coronavirus disease-2019. Mean Ct values are indicated by horizontal bars.</p>
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<p>(<b>A</b>) Changes over time in thresholds (Ct) of nasopharyngeal and anterior nasal specimens in all coronavirus disease-2019; (<b>B</b>) changes over time in the cycle threshold (Ct) of nasopharyngeal and anterior nasal specimens in patients with mild and moderate to severe coronavirus disease-2019; (<b>C</b>) comparison of cycle threshold (Ct) values for all specimens, anterior nasal, and nasopharyngeal specimens taken from asymptomatic patients for coronavirus disease-2019. Mean Ct values are indicated by horizontal bars.</p>
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<p>(<b>A</b>) Changes over time in thresholds (Ct) of nasopharyngeal and anterior nasal specimens in all coronavirus disease-2019; (<b>B</b>) changes over time in the cycle threshold (Ct) of nasopharyngeal and anterior nasal specimens in patients with mild and moderate to severe coronavirus disease-2019; (<b>C</b>) comparison of cycle threshold (Ct) values for all specimens, anterior nasal, and nasopharyngeal specimens taken from asymptomatic patients for coronavirus disease-2019. Mean Ct values are indicated by horizontal bars.</p>
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<p>Comparison of cycle threshold (Ct) values for all specimens, anterior nasal, and nasopharyngeal specimens for the respiratory syncytial virus. Mean Ct values are indicated by horizontal bars.</p>
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<p>Changes over time in thresholds (Ct) of nasopharyngeal and anterior nasal specimens in respiratory syncytial virus.</p>
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<p>Ct values of respiratory syncytial virus (RSV) specimens by date of onset and determination of RapidTesta RSV and SARS-CoV-2.</p>
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10 pages, 1188 KiB  
Article
Prediction Model for the Clearance of Hepatitis B Surface Antigen in Patients with Chronic Hepatitis B before Interferon Therapy: A Prospective Case–Control Study
by Nan Geng, Lina Ma, Yi Jin, Junfeng Lu, Yanhong Zheng, Junli Wang, Xiaoxiao Wang and Xinyue Chen
Diagnostics 2024, 14(1), 118; https://doi.org/10.3390/diagnostics14010118 - 4 Jan 2024
Viewed by 1397
Abstract
To evaluate the prediction model comprised of patients’ laboratory results and single-nucleotide polymorphism (SNP) markers of host gene for the clearance of hepatitis B surface antigen (HBsAg) in patients with chronic hepatitis B (CHB) who underwent interferon (IFN)-α therapy, this prospective case–control study [...] Read more.
To evaluate the prediction model comprised of patients’ laboratory results and single-nucleotide polymorphism (SNP) markers of host gene for the clearance of hepatitis B surface antigen (HBsAg) in patients with chronic hepatitis B (CHB) who underwent interferon (IFN)-α therapy, this prospective case–control study enrolled 131 patients with CHB who underwent IFN-α-based regimens in our hospital between January 2015 and September 2019. Among them, 56 cases were without HBsAg clearance, while the other 75 cases had HBsAg clearance. Multivariable logistic regression analysis showed that CYP27B1 rs4646536 (odd ratio [OR] = 0.155, 95% CI: 0.030–0.807, p = 0.027), PAK4 rs9676717 (OR = 11.237, 95% CI: 1.768–71.409, p = 0.010), IL28B rs12979860 (OR = 0.059, 95% CI: 0.006–0.604, p = 0.017), baseline HBsAg (OR = 0.170, 95% CI: 0.040–0.716, p = 0.016), and HBeAg status (OR = 3.971, 95% CI: 1.138–13.859, p = 0.031) were independently associated with HBsAg clearance. The model that included rs3077, rs4646536, rs9676717, rs2850015, rs12979860, baseline HBsAg, HBeAg status, and HBV DNA had the best prediction performance for HBsAg clearance prediction, with AUC = 0.877, 80% sensitivity, and 81% specificity. In conclusion, laboratory results and gene polymorphisms before treatment might have a good predictive value for HbsAg clearance after IFN-α treatment in CHB. Full article
(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)
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<p>Polymorphism distributions in the HBsAg clearance and non-clearance groups. For most polymorphisms, there were frequencies of three genotypes in each group, with a sum of 1.0 (100%). For IL28B 12979860, there were two genotypes in each group, also with a sum of 1.0 (100%). Different colors indicate the frequencies of the genotypes for a given polymorphism.</p>
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<p>The prediction model was analyzed by logistic regression and shown by the receiver operating characteristics (ROC) curve in predicting responses of chronic hepatitis B (CHB) patients treated with interferon (IFN)-α. (<b>A</b>) The combination of potential factors from the multivariable analysis was analyzed by logistic regression, and the accuracy was shown using a ROC curve. (<b>B</b>) More factors displaying the differences in clinical characteristics and polymorphism analysis were incorporated into the logistic regression, and the prediction effect is shown using a ROC curve.</p>
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12 pages, 4760 KiB  
Article
Improving Prenatal Diagnosis Precision for Congenital Clubfoot by Using Three-Dimensional Ultrasonography
by Yoo-min Kim, Ji Su Seong, Ji Hoi Kim, Na Mi Lee, In Ho Choi, Yejin Jo, Gina Nam and Gwang Jun Kim
Diagnostics 2024, 14(1), 117; https://doi.org/10.3390/diagnostics14010117 - 4 Jan 2024
Viewed by 2255
Abstract
Prenatal diagnosis of clubfoot traditionally relied on two-dimensional ultrasonography. To enhance diagnosis and predict postnatal outcomes, we examined the parameters that differentiate pathological clubfoot using three-dimensional ultrasonography. In our retrospective study, we examined the findings of prenatal ultrasound and the postnatal outcomes of [...] Read more.
Prenatal diagnosis of clubfoot traditionally relied on two-dimensional ultrasonography. To enhance diagnosis and predict postnatal outcomes, we examined the parameters that differentiate pathological clubfoot using three-dimensional ultrasonography. In our retrospective study, we examined the findings of prenatal ultrasound and the postnatal outcomes of pregnancies with suspected congenital clubfoot between 2018 and 2021. Based on the three-dimensional perspective, we measured the angles of varus, equinus, calcaneopedal block, and forefoot adduction and compared the sonographic variables between the postnatal treated and non-treated groups. We evaluated 31 pregnancies (47 feet) with suspected clubfoot using three-dimensional ultrasonography. After delivery, a total of 37 feet (78.7%) underwent treatment involving serial casting only or additional Achilles tenotomy. The treated group showed significantly greater hindfoot varus deviation (60.5° vs. 46.6°, p = 0.026) and calcaneopedal block deviation (65.6° vs. 26.6°, p < 0.05) compared to the non-treated group. The calcaneopedal block had an area under the curve of 0.98 with a diagnostic threshold of 46.2 degrees (sensitivity of 97%, specificity of 90%, positive predictive value of 97%, and negative predictive value of 90%). During prenatal evaluation of clubfoot using three-dimensional ultrasonography, the calcaneopedal block deviation has the potential to predict postnatal treatment. Full article
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<p>Two-dimensional sonographic view (<b>A</b>) Normal fetus: the tibia (green line) and the fibula (yellow line) are observed in the frontal coronal plane as talus (red colored), but the foot is not observed. (<b>B</b>) Suspected clubfoot: the tibia and fibula are observed in the coronal plane as the lateral aspect of the foot, with the foot extended and inverted.</p>
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<p>The three-dimensional assessment of deviation between foot and calf and plantar deviation of the foot (<b>A</b>) Equinus deviation in the sagittal plane (<b>B</b>) Varus deviation in the frontal plane (<b>C</b>) Derotation around the talus calcaneo-forefoot in the coronal plane (<b>D</b>) Adduction forefoot on forefoot in the horizontal plane.</p>
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<p>The measurement of calf volume and circumference using 3D US. The green dotted line shown in the top left picture indicates tibia. The green circular dotted line shown in the remaining five pictures indicates the calf circumference.</p>
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<p>The diagnostic thresholds of angle provided by ROC curve analysis for prediction of congenital clubfoot using 3D USG. The green line demonstrated the ROC curve of the calcaneopedal block angle. The red line demonstrates the ROC curve of the varus angle. The blue line demonstrated the ROC curve of the sum of the varus and calcaneopedal block angle. ROC curve, receiver operating characteristic curve; 3D, three-dimensional; US, ultrasonography; AUC, the area under the curve.</p>
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<p>Discordancy in calf volume and calf circumference between the treated and non-treated groups. (<b>A</b>) Unilateral clubfoot (<b>B</b>) Bilateral clubfoot.</p>
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10 pages, 1405 KiB  
Article
Examining the Forearm Intersection through Palpation and Ultrasonography
by Esperanza Naredo, Jorge Murillo-González, José Ramón Mérida Velasco, Otto Olivas Vergara, Robert A. Kalish, Cristina Gómez-Moreno, Eva García-Carpintero Blas, Gema Fuensalida-Novo and Juan J. Canoso
Diagnostics 2024, 14(1), 116; https://doi.org/10.3390/diagnostics14010116 - 4 Jan 2024
Viewed by 2020
Abstract
Background: Forearm intersection syndrome causes pain, swelling, and a rub at the dorsal distal forearm where the first extensor compartment muscles intersect with the second compartment tendons. Although primary care settings tend to treat mild cases, high-performance athletes may suffer from severe symptoms [...] Read more.
Background: Forearm intersection syndrome causes pain, swelling, and a rub at the dorsal distal forearm where the first extensor compartment muscles intersect with the second compartment tendons. Although primary care settings tend to treat mild cases, high-performance athletes may suffer from severe symptoms that require surgery. This proof-of-concept study aims to help detect the anatomical substrate of forearm intersection syndrome using palpation and ultrasonography when available. Methods: Five individuals were studied using independent palpation and ultrasonography to identify the first dorsal compartment muscles and the second dorsal compartment tendons. The distances between the dorsal (Lister’s) tubercle of the radius and the ulnar and radial edges of the first dorsal compartment muscles were measured to determine the location and extent of the muscle–tendon intersection. The palpatory and ultrasonographic measurements were compared using descriptive statistics and the paired t-test. Results: The mean distances from the dorsal tubercle of the radius to the ulnar and radial borders of the first dorsal compartment muscles were 4.0 cm (SE 0.42) and 7.7 cm (SE 0.56), respectively, based on palpation. By ultrasonography, the corresponding distances were 3.5 cm (SD 1.05, SE 0.47) and 7.0 cm (SD 1.41, SE 0.63). Both methods showed a similar overlap length. However, ultrasonography revealed a shorter distance between the dorsal tubercle of the radius and the ulnar border of the first compartment than palpation (p = 0.0249). Conclusions: Our findings indicate that a basic knowledge of anatomy should help health professionals diagnose forearm intersection syndrome through palpation and, if available, ultrasonography. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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<p>The landmarks used for palpation were the second and third metacarpal bases (2ndM, 3rdM), where extensor carpi radialis longus and extensor carpi radialis brevis are inserted. a, dorsal tubercle of the radius of radius; b, ulnar edge of extensor pollicis brevis; c, radial edge of abductor pollicis longus. Blue arrows indicate the distances between the dorsal tubercle of the radius and the ulnar and radial borders of the 1st compartment muscles.</p>
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<p>Ultrasound scanning of the second dorsal compartment tendons and the first dorsal compartment muscles, short-axis view. (<b>A</b>) Extensor carpi radialis brevis (ECRB) and extensor carpi radialis longus (ECRL) at distal dorsal tubercle of the radius level (arrowhead). (<b>B</b>) Crossing between the second dorsal compartment tendons (ECRB, ECRL) and the extensor pollicis brevis (EPB) muscle. R, radius. (<b>C</b>) Crossing between the second dorsal compartment tendons (ECRB, ECRL) and the abductor pollicis longus (APL) muscle. R, radius. (<b>D</b>) Musculotendinous junction of the ECRB and ECRL. R, radius.</p>
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<p>Dorsal dissection of the distal forearm and wrist. a, horizontal line indicating dorsal tubercle (DT) of the radius; b, horizontal line indicating the ulnar edge of the extensor pollicis brevis (EPB); c, horizontal line indicating the radial border of the abductor pollicis longus (APL); ab, distance from DT to the ulnar edge of EPB; ac, distance from DT to the radial edge of APL; bc, the overlap between the muscles of the first compartment (APL, EPB) and the tendons of the second compartment (ECRL, extensor carpi radialis longus; ECRB, extensor carpi radialis brevis). ECU, extensor carpi ulnaris; ED, extensor digitorum; EDM, extensor digiti minimi; EPL, extensor pollicis longus; ER, extensor retinaculum.</p>
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16 pages, 1424 KiB  
Review
Left Ventricular Non-Compaction in Children: Aetiology and Diagnostic Criteria
by Emanuele Monda, Gianantonio De Michele, Gaetano Diana, Federica Verrillo, Marta Rubino, Annapaola Cirillo, Adelaide Fusco, Federica Amodio, Martina Caiazza, Francesca Dongiglio, Giuseppe Palmiero, Pietro Buono, Maria Giovanna Russo and Giuseppe Limongelli
Diagnostics 2024, 14(1), 115; https://doi.org/10.3390/diagnostics14010115 - 4 Jan 2024
Cited by 1 | Viewed by 1794
Abstract
Left ventricular non-compaction (LVNC) is a heterogeneous myocardial disorder characterized by prominent trabeculae protruding into the left ventricular lumen and deep intertrabecular recesses. LVNC can manifest in isolation or alongside other heart muscle diseases. Its occurrence among children is rising due to advancements [...] Read more.
Left ventricular non-compaction (LVNC) is a heterogeneous myocardial disorder characterized by prominent trabeculae protruding into the left ventricular lumen and deep intertrabecular recesses. LVNC can manifest in isolation or alongside other heart muscle diseases. Its occurrence among children is rising due to advancements in imaging techniques. The origins of LVNC are diverse, involving both genetic and acquired forms. The clinical manifestation varies greatly, with some cases presenting no symptoms, while others typically manifesting with heart failure, systemic embolism, and arrhythmias. Diagnosis mainly relies on assessing heart structure using imaging tools like echocardiography and cardiac magnetic resonance. However, the absence of a universally agreed-upon standard and limitations in diagnostic criteria have led to ongoing debates in the scientific community regarding the most reliable methods. Further research is crucial to enhance the diagnosis of LVNC, particularly in early life stages. Full article
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<p>Echocardiographic images of a patient with LVNC. On the (<b>left</b>), apical 4-chamber view; on the (<b>right</b>), parasternal short-axis view.</p>
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<p>Comparison of the echocardiographic diagnostic criteria for children with LVNC [<a href="#B7-diagnostics-14-00115" class="html-bibr">7</a>,<a href="#B13-diagnostics-14-00115" class="html-bibr">13</a>,<a href="#B15-diagnostics-14-00115" class="html-bibr">15</a>,<a href="#B26-diagnostics-14-00115" class="html-bibr">26</a>].</p>
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<p>Cardiac magnetic resonance image of a patient with LVNC.</p>
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10 pages, 1073 KiB  
Article
Determining Pneumocystis jirovecii Colonisation from Infection Using PCR-Based Diagnostics in HIV-Negative Individuals
by Anna Louise Watson, John Woodford, Sumudu Britton, Rita Gupta, David Whiley and Kate McCarthy
Diagnostics 2024, 14(1), 114; https://doi.org/10.3390/diagnostics14010114 - 4 Jan 2024
Viewed by 1395
Abstract
Background: Pneumocystis jirovecii pneumonia is increasingly diagnosed with highly sensitive PCR diagnostics in immunocompromised, HIV-negative individuals. We assessed the performance of our in-house quantitative PCR with the aim to optimise interpretation. Methods: Retrospective audit of all positive P. jirovecii qPCRs on induced sputum [...] Read more.
Background: Pneumocystis jirovecii pneumonia is increasingly diagnosed with highly sensitive PCR diagnostics in immunocompromised, HIV-negative individuals. We assessed the performance of our in-house quantitative PCR with the aim to optimise interpretation. Methods: Retrospective audit of all positive P. jirovecii qPCRs on induced sputum or BAL fluid at a single centre from 2012 to 2023. Medical and laboratory records were analysed and people with HIV were excluded. Cases were categorised as colonisation, high-probability PCP or uncertain PCP infection against a clinical gold standard incorporating clinico-radiological data. Quantitative PCR assay targeting the 5s gene was utilised throughout the time period. Results: Of the 82 positive qPCRs, 28 were categorised as high-probability PCP infection, 30 as uncertain PCP and 24 as colonisation. There was a significant difference in qPCR values stratified by clinical category but not respiratory sample type. Current assay performance with a cutoff of 2.5 × 105 copies/mL had a sensitivity of 50% (95% CI, 30.65–69.35%) and specificity of 83.33% (95% CI, 62.62–95.26%). Youden Index calculated at 6.5 × 104 copies/mL had a sensitivity of 75% (56.64–87.32%, 95% CI) and specificity of 66.67% (46.71–82.03%, 95% CI). High and low cutoffs were explored. Significant variables associated with infection were age > 70 years old, the presence of fever, hypoxia or ground glass changes. Conclusions: A single qPCR cutoff cannot reliably determine P. jirovecii infection from colonisation. Low and high cutoffs are useful, however, a large “possible infection” cohort will remain where interpretation of clinic-radiological factors remains essential. Standardisation of assays with prospective validation in specific immunocompromised groups will allow greater generalisability and allow large-scale prospective assay validation to be performed. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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<p>Heatmap of study population comorbidities stratified by clinical diagnosis. Each vertical column represents 1 individual, with purple indicating present and blue indicating absent.</p>
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<p>qPCRs on any sample stratified by diagnosis. Bars at median. Kruskall–Wallis Test. Dotted line is existing cutoff.</p>
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<p>qPCR value stratified by diagnosis and sample type.</p>
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<p>(<b>A</b>,<b>B</b>) ROC curves for the differentiation of Pneumocystis high-probability PCP infection and colonisation using (<b>A</b>) qPCR values alone (<b>B</b>) multivariate model of clinical, radiographic and laboratory factors (age, sex, prophylaxis, fever, ground glass changes, sample type and qPCR).</p>
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13 pages, 2170 KiB  
Systematic Review
Diagnostic Accuracy of MRI in Detecting the Perineural Spread of Head and Neck Tumors: A Systematic Review and Meta-Analysis
by Umida Abdullaeva, Bernd Pape and Jussi Hirvonen
Diagnostics 2024, 14(1), 113; https://doi.org/10.3390/diagnostics14010113 - 4 Jan 2024
Cited by 1 | Viewed by 1922
Abstract
The purpose of this study was to review the diagnostic accuracy of MRI in detecting perineural spreading (PNS) of head and neck tumors using histopathological or surgical evidence from the afflicted nerve as the reference standard. Previous studies in the English language published [...] Read more.
The purpose of this study was to review the diagnostic accuracy of MRI in detecting perineural spreading (PNS) of head and neck tumors using histopathological or surgical evidence from the afflicted nerve as the reference standard. Previous studies in the English language published in the last 30 years were searched from PubMed and Embase databases. We included studies that used magnetic resonance imaging (MRI) (with and without contrast enhancement) to detect PNS, as well as the histological or surgical confirmation of PNS, and that reported the exact numbers of patients required for assessing diagnostic accuracy. The outcome measures were sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Heterogeneity was assessed with the Higgins inconsistency test (I2). P-values smaller than 0.05 were considered statistically significant. A total of 11 retrospective studies were found, reporting 319 nerve samples from 245 patients. Meta-analytic estimates and their 95% confidence intervals were as follows: sensitivity 0.85 (0.70–0.95), specificity 0.85 (0.80–0.89), PPV 0.86 (0.70–0.94), and NPV 0.85 (0.71–0.93). We found statistically significant heterogeneity for sensitivity (I2 = 72%, p = 0.003) and PPV (I2 = 70%, p = 0.038), but not for NPV (I2 = 65%, p = 0.119) or specificity (I2 = 12%, p = 0.842). The most frequent MRI features of PNS were nerve enlargement and enhancement. Squamous cell carcinoma and adenoid cystic carcinoma were the most common tumor types, and the facial and trigeminal nerves were the most commonly affected nerves in PNS. Only a few studies provided examples of false MRI diagnoses. MRI demonstrated high diagnostic accuracy in depicting PNS of cranial nerves, yet this statement was based on scarce and heterogeneous evidence. Full article
(This article belongs to the Special Issue Advances in Diagnostic Imaging of Head and Neck Tumors: 2nd Edition)
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<p>PRISMA flowchart of systematic review and meta-analysis.</p>
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<p>Forest plots of the sensitivity (<b>A</b>) and specificity (<b>B</b>) values from individual studies and their model-based estimates. Bars represent 95% confidence intervals, and dotted lines represent the model-based estimates. Data shown from original publications: (<b>A</b>) [<a href="#B19-diagnostics-14-00113" class="html-bibr">19</a>,<a href="#B21-diagnostics-14-00113" class="html-bibr">21</a>,<a href="#B22-diagnostics-14-00113" class="html-bibr">22</a>,<a href="#B28-diagnostics-14-00113" class="html-bibr">28</a>,<a href="#B30-diagnostics-14-00113" class="html-bibr">30</a>], (<b>B</b>) [<a href="#B16-diagnostics-14-00113" class="html-bibr">16</a>,<a href="#B19-diagnostics-14-00113" class="html-bibr">19</a>,<a href="#B20-diagnostics-14-00113" class="html-bibr">20</a>,<a href="#B21-diagnostics-14-00113" class="html-bibr">21</a>].</p>
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<p>Forest plots of the PPV (<b>A</b>) and NPV (<b>B</b>) values from individual studies and their model-based estimates. Bars represent 95% confidence intervals, and the dotted lines represent the model-based estimates. Data shown from original publications: (<b>A</b>) [<a href="#B16-diagnostics-14-00113" class="html-bibr">16</a>,<a href="#B19-diagnostics-14-00113" class="html-bibr">19</a>,<a href="#B20-diagnostics-14-00113" class="html-bibr">20</a>,<a href="#B21-diagnostics-14-00113" class="html-bibr">21</a>], (<b>B</b>) [<a href="#B19-diagnostics-14-00113" class="html-bibr">19</a>,<a href="#B21-diagnostics-14-00113" class="html-bibr">21</a>,<a href="#B30-diagnostics-14-00113" class="html-bibr">30</a>].</p>
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<p>Frequency distribution of primary tumor histologies associated with PNS across studies.</p>
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<p>Frequency distribution of cranial nerves afflicted with PNS across studies.</p>
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<p>Frequency distribution of MRI features reportedly associated with PNS across studies.</p>
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18 pages, 1930 KiB  
Review
Hereditary Thoracic Aortic Diseases
by Gaia Spaziani, Francesca Chiara Surace, Francesca Girolami, Francesco Bianco, Valentina Bucciarelli, Francesca Bonanni, Elena Bennati, Luigi Arcieri and Silvia Favilli
Diagnostics 2024, 14(1), 112; https://doi.org/10.3390/diagnostics14010112 - 4 Jan 2024
Viewed by 1843
Abstract
Advances in both imaging techniques and genetics have led to the recognition of a wide variety of aortic anomalies that can be grouped under the term ‘hereditary thoracic aortic diseases’. The present review aims to summarize this very heterogeneous population’s clinical, genetic, and [...] Read more.
Advances in both imaging techniques and genetics have led to the recognition of a wide variety of aortic anomalies that can be grouped under the term ‘hereditary thoracic aortic diseases’. The present review aims to summarize this very heterogeneous population’s clinical, genetic, and imaging characteristics and to discuss the implications of the diagnosis for clinical counselling (on sports activity or pregnancy), medical therapies and surgical management. Full article
(This article belongs to the Special Issue Vascular Malformations: Diagnosis and Management)
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<p>Phenotypes of the most common genetic syndromes associated with aortic dilation. (Panel <b>A</b>): Marfan syndrome characterized by long bone overgrowth, arachnodactyly scoliosis, pectus deformities, and tall stature. (Panel <b>B</b>): Turner syndrome characterized by short stature, webbed neck, broad chest and widely spaced nipples, and low hairline. (Panel <b>C</b>): Loyes–Dietz syndrome characterized by hypertelorism, scoliosis, bifid uvula, club feet, loose joints, and longer fingers. (Panel <b>D</b>): Vascular Ehlers–Danlos syndrome characterized by small joint hypermobility and thin, translucent skin.</p>
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<p>Echocardiographic images of a one-year-old boy with suspected LDS/MS presenting with an isolated dilatation of the ascending aorta. Subcostal view of the aorta (Panel <b>A</b>); parasternal long axis view (Panel <b>B</b>). Legend: left ventricle (Lv); right ventricle (Rv); aorta (Ao); left atrium (La).</p>
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<p>CCT images of four-year-old girl with MS that underwent previous aortic valve replacement due to severe aortic regurgitation. Coronal section (Panel <b>A</b>); sagittal section (Panel <b>B</b>); axial section (Panel <b>C</b>). The asterisk indicates the dilated ascending aorta. Legend: aorta (Ao); pulmonary artery (Plm).</p>
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<p>CMR imaging of a 30-years old woman with MS presenting with an acute aortic dissection diagnosed during a routine exam. Angio-MRI with post contrast-enhanced sequence (Panel <b>A</b>); cine-SSFP sagittal and axial images (Panels <b>B</b>,<b>D</b>); T1-weighted axial images (Panel <b>C</b>). The asterisks indicate the true lumen and the arrows the false lumen. Legends: aorta (Ao); steady-state free precession (SSFP).</p>
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10 pages, 423 KiB  
Article
Early Assessment of Voice Problems in Post-Thyroidectomy Syndrome Using Cepstral Analysis
by Yeso Choi, Bo Ram Keum, Ju Eun Kim, Joong Seob Lee, Seok Min Hong, IL-Seok Park and Heejin Kim
Diagnostics 2024, 14(1), 111; https://doi.org/10.3390/diagnostics14010111 - 4 Jan 2024
Viewed by 1455
Abstract
Post-thyroidectomy syndrome (PTS), characterized by voice issues after thyroidectomy without recurrent laryngeal nerve injury, was investigated in this study. The Voice Fatigue Index (VFI) and cepstral analysis were employed for subjective and objective voice evaluation. Retrospective analysis involved 96 patients (37 males, 59 [...] Read more.
Post-thyroidectomy syndrome (PTS), characterized by voice issues after thyroidectomy without recurrent laryngeal nerve injury, was investigated in this study. The Voice Fatigue Index (VFI) and cepstral analysis were employed for subjective and objective voice evaluation. Retrospective analysis involved 96 patients (37 males, 59 females) who underwent thyroidectomy without nerve injury from April 2018 to June 2022. Assessments pre- and post-thyroidectomy included the Voice Handicap Index (VHI) and VFI, along with auditory perceptual, acoustic (including cepstral), aerodynamic, and glottal vibration analyses. In females, although the GRBAS scale showed no significant change, both VHI and VFI increased post-thyroidectomy. Significant correlations were observed between the VHI and VFI in females. Acoustic analysis indicated a decrease in the cepstral peak prominence (CPP) of vowels (/a/) and sentences in females, with significant correlations between changes in the CPP/a/ and VHI/VFI. The maximum fundamental frequency (F0max) exhibited a significant decrease, correlating with the VHI and VFI changes. The VFI demonstrated effectiveness in subjective PTS voice evaluation, comparable to the VHI. The present study highlights the potential of cepstral analysis as an index reflecting subjective voice discomfort, suggesting its promise for a comprehensive PTS voice evaluation. Full article
(This article belongs to the Special Issue Recent Advances in Thyroid Carcinoma)
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<p>Comparison of subjective voice discomfort (K-VHI and K-VFI) before and after thyroidectomy by gender: (<b>A</b>) K-VHI differences between pre- and post-thyroidectomy were significant in females (<span class="html-italic">p =</span> 0.001), whereas males did not show any differences (<span class="html-italic">p =</span> 0.052). (<b>B</b>) K-VFI scores showed significant differences in females after thyroidectomy (<span class="html-italic">p &lt;</span> 0.001) rather than in males (<span class="html-italic">p</span> = 0.125).</p>
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5 pages, 1009 KiB  
Interesting Images
An Ectopic Parathyroid Adenoma of the Retropharynx in a Patient with Primary Hyperparathyroidism and Papillary Thyroid Cancer—A Rare Case
by Youngjae Lee, Wonyong Baek, Jiwoong Cho and Jeonghyun Oh
Diagnostics 2024, 14(1), 110; https://doi.org/10.3390/diagnostics14010110 - 4 Jan 2024
Cited by 1 | Viewed by 1522
Abstract
The frequency of concurrent thyroid cancer in patients with primary hyperparathyroidism (pHPT) varies. While the pathological association between thyroid and parathyroid disorders is frequently noted, the co-occurrence of parathyroid adenoma and papillary thyroid cancer is exceptionally rare. Furthermore, an ectopic parathyroid adenoma in [...] Read more.
The frequency of concurrent thyroid cancer in patients with primary hyperparathyroidism (pHPT) varies. While the pathological association between thyroid and parathyroid disorders is frequently noted, the co-occurrence of parathyroid adenoma and papillary thyroid cancer is exceptionally rare. Furthermore, an ectopic parathyroid adenoma in the retropharyngeal space is exceedingly rare. Therefore, anatomical variations through the utilization of relevant diagnostic tools play a crucial role in guiding decisions pertaining to clinical manifestations, diagnostic methods, surgical interventions, and operative strategies for parathyroid tumors. We present a case of a 51-year-old female patient with papillary thyroid carcinoma in the right thyroid lobe and an ectopic parathyroid adenoma in the retropharyngeal space confirmed through surgical intervention. The elevated preoperative levels of serum calcium and parathyroid hormone, along with low serum phosphate, returned to normal ranges after surgery. This case sheds light on the unusual occurrence of an ectopic parathyroid adenoma in the retropharyngeal region within a thyroid cancer patient, providing valuable insights into the realm of thyroid malignancies. Full article
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<p>Preoperative enhanced neck CT shows an approximately 2.6 cm well-defined mass in the right retropharyngeal space (axial view, left blue arrow). The suspicious lesion in the retropharynx is located at the level of the upper thyroid cartilage (sagittal view, right blue arrow).</p>
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<p>[99m Tc]Tc-MIBI single-photon emission computed tomography combining computed tomography (SPECT/CT) scintigraphy showing the right retropharyngeal lesion with sustained radiotracer uptake on the delayed images (<b>A</b>,<b>B</b>) (orange arrow). Maximum-intensity projection image (<b>C</b>) (orange arrow).</p>
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<p>Histopathological examination confirmed the final diagnosis of parathyroid adenoma. Microscopic findings of the parathyroid gland show large cells with small irregular nuclei and dense acidophilic granules (H&amp;E staining; original magnification, ×5) (<b>A</b>) and follicular structures predominantly composed of chief cells (H&amp;E staining; original magnification, ×10) (<b>B</b>).</p>
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38 pages, 1586 KiB  
Systematic Review
A Systematic Review and Meta-Analysis of Artificial Intelligence Tools in Medicine and Healthcare: Applications, Considerations, Limitations, Motivation and Challenges
by Hussain A. Younis, Taiseer Abdalla Elfadil Eisa, Maged Nasser, Thaeer Mueen Sahib, Ameen A. Noor, Osamah Mohammed Alyasiri, Sani Salisu, Israa M. Hayder and Hameed AbdulKareem Younis
Diagnostics 2024, 14(1), 109; https://doi.org/10.3390/diagnostics14010109 - 4 Jan 2024
Cited by 36 | Viewed by 16201
Abstract
Artificial intelligence (AI) has emerged as a transformative force in various sectors, including medicine and healthcare. Large language models like ChatGPT showcase AI’s potential by generating human-like text through prompts. ChatGPT’s adaptability holds promise for reshaping medical practices, improving patient care, and enhancing [...] Read more.
Artificial intelligence (AI) has emerged as a transformative force in various sectors, including medicine and healthcare. Large language models like ChatGPT showcase AI’s potential by generating human-like text through prompts. ChatGPT’s adaptability holds promise for reshaping medical practices, improving patient care, and enhancing interactions among healthcare professionals, patients, and data. In pandemic management, ChatGPT rapidly disseminates vital information. It serves as a virtual assistant in surgical consultations, aids dental practices, simplifies medical education, and aids in disease diagnosis. A total of 82 papers were categorised into eight major areas, which are G1: treatment and medicine, G2: buildings and equipment, G3: parts of the human body and areas of the disease, G4: patients, G5: citizens, G6: cellular imaging, radiology, pulse and medical images, G7: doctors and nurses, and G8: tools, devices and administration. Balancing AI’s role with human judgment remains a challenge. A systematic literature review using the PRISMA approach explored AI’s transformative potential in healthcare, highlighting ChatGPT’s versatile applications, limitations, motivation, and challenges. In conclusion, ChatGPT’s diverse medical applications demonstrate its potential for innovation, serving as a valuable resource for students, academics, and researchers in healthcare. Additionally, this study serves as a guide, assisting students, academics, and researchers in the field of medicine and healthcare alike. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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<p>Categories and groups covered by all studies of the review. G1: treatment and medicine, G2: buildings and equipment, G3: parts of the human body and areas of the disease, G4: patients, G5: citizens, G6: cellular imaging, radiology, pulse, and medical images, G7: doctors and nurses, and G8: tools, devices and administration.</p>
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<p>No. of databases/publishers.</p>
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<p>Distribution by type of articles to number of articles.</p>
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<p>Flowchart for selecting studies with specific query and eligibility criteria.</p>
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<p>Challenges of healthcare and the medical fields.</p>
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4 pages, 1764 KiB  
Interesting Images
Pedicle Screw Pseudofracture on Computed Tomography Secondary to Metal Artifact Reduction
by Shuliang Ge, Naresh Kumar and James Thomas Patrick Decourcy Hallinan
Diagnostics 2024, 14(1), 108; https://doi.org/10.3390/diagnostics14010108 - 3 Jan 2024
Viewed by 1000
Abstract
Metal artifact reduction (MAR) algorithms are commonly used in computed tomography (CT) scans where metal implants are involved. However, MAR algorithms also have the potential to create new artifacts in reconstructed images. We present a case of a screw pseudofracture due to MAR [...] Read more.
Metal artifact reduction (MAR) algorithms are commonly used in computed tomography (CT) scans where metal implants are involved. However, MAR algorithms also have the potential to create new artifacts in reconstructed images. We present a case of a screw pseudofracture due to MAR on CT. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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<p>Axial (<b>a</b>) and sagittal (<b>b</b>) CT bone reconstructions with MAR showing a linear dark band across the mid-section of the right L3 pedicle screw. Axial CT bone reconstruction without MAR (<b>c</b>) at the same L3 level showing intact screws.</p>
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<p>Anterior–posterior and lateral radiographs of the implants were taken a few days after the CT scan and showed intact pedicle screws.</p>
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16 pages, 3895 KiB  
Article
Establishing Normative Values for Acromion Anatomy: A Comprehensive MRI-Based Study in a Healthy Population of 996 Participants
by Anne Prietzel, Theo Languth, Robin Bülow, Till Ittermann, René Laqua, Lyubomir Haralambiev, Georgi Iwan Wassilew, Axel Ekkernkamp and Mustafa Sinan Bakir
Diagnostics 2024, 14(1), 107; https://doi.org/10.3390/diagnostics14010107 - 3 Jan 2024
Cited by 1 | Viewed by 1343
Abstract
Shoulder pain is a common issue often linked to conditions such as subacromial impingement or rotator cuff lesions. The role of the acromion in these symptoms remains a subject of debate. This study aims to establish standardized values for commonly used acromion dimensions [...] Read more.
Shoulder pain is a common issue often linked to conditions such as subacromial impingement or rotator cuff lesions. The role of the acromion in these symptoms remains a subject of debate. This study aims to establish standardized values for commonly used acromion dimensions based on whole-body MRI scans of a large and healthy population and to investigate potential correlations between acromion shape and influencing factors such as sex, age, BMI, dominant hand, and shoulder pain. The study used whole-body MRI scans from the Study of Health in Pomerania, a German population-based study. Acromion index, acromion tilt, and acromion slope were measured. Interrater variability was tested with two independent, trained viewers on 100 MRI sequences before actual measurements started. Descriptive statistics and logistic regression were used to evaluate the results. We could define reference values based on a shoulder-healthy population for each acromion parameter within the 2.5 to 97.5 percentile. No significant differences were found in acromion slope, tilt, and index between male and female participants. No significant correlations were observed between acromion morphology and anthropometric parameters such as height, weight, or BMI. No significant differences were observed in acromion parameters between dominant and non-dominant hands or stated pain intensity. This study provides valuable reference values for acromion-related parameters, offering insight into the anatomy of a healthy shoulder. The findings indicate no significant differences in acromion morphology based on sex, weight, BMI, or dominant hand. Further research is necessary to ascertain the clinical implications of these reference values. The establishment of standardized reference values opens new possibilities for enhancing clinical decision making regarding surgical interventions, such as acromioplasty. Full article
(This article belongs to the Special Issue Advanced MRI in Clinical Diagnosis)
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<p>Schematic 3D reconstruction of the glenohumeral joint in anterior–posterior view, illustrating the measurement technique for the acromion index AI = GA/GH. GA indicates the distance between glenoid surface and lateral edge of the acromion, GH the distance between glenoid surface and lateral edge of the humeral head.</p>
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<p>How to measure acromion index: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point G1 indicates the lower end of the glenoid.</p>
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<p>How to measure acromion index: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point G2 indicates the upper end of the glenoid.</p>
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<p>How to measure acromion index: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point H indicates the lateral edge of the humeral head.</p>
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<p>How to measure acromion index: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point A indicates the lateral edge of the acromion.</p>
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<p>Schematic 3D reconstruction of the glenohumeral joint in anterior–posterior view, illustrating the measurement technique for the acromion tilt (α). A1 indicates the ventral end of the acromion’s bottom, A2 the dorsal end of the acromion’s bottom, B1 the lower end of the coracoid process.</p>
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<p>How to measure acromion tilt: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point A1 indicates the ventral end of the acromion’s bottom.</p>
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<p>How to measure acromion tilt: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point A2 indicates the dorsal end of the acromion’s bottom.</p>
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<p>How to measure acromion tilt: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point B1 indicates the lower end of the coracoid process.</p>
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<p>Schematic 3D reconstruction of the glenohumeral joint in anterior–posterior view, illustrating the measurement technique for the acromion slope (α). A1 indicates the ventral end of the acromion’s bottom, A2 the dorsal end of the acromion’s bottom, M the middle of the acromion’s bottom.</p>
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<p>How to measure acromion slope: Axial MRI of the thorax depicting the shoulder joint in T1 weighting (3D-GRE VIBE sequence), with a slice thickness of 3 mm. Point M indicates the middle of the acromion’s bottom.</p>
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<p>(<b>a</b>–<b>c</b>). Bland–Altman plots for interrater variability: (<b>a</b>) Acromion slope (AS, <span class="html-italic">n</span> = 60), (<b>b</b>) Acromion tilt (AT, <span class="html-italic">n</span> = 85), (<b>c</b>) Acromion index (<span class="html-italic">n</span> = 60).</p>
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<p>(<b>a</b>–<b>c</b>). Bland–Altman plots for interrater variability: (<b>a</b>) Acromion slope (AS, <span class="html-italic">n</span> = 60), (<b>b</b>) Acromion tilt (AT, <span class="html-italic">n</span> = 85), (<b>c</b>) Acromion index (<span class="html-italic">n</span> = 60).</p>
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<p>Amount and Composition of Measured MRIs.</p>
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12 pages, 494 KiB  
Review
The Genetic Landscape of Sleep Disorders in Parkinson’s Disease
by Kallirhoe Kalinderi, Vasileios Papaliagkas and Liana Fidani
Diagnostics 2024, 14(1), 106; https://doi.org/10.3390/diagnostics14010106 - 3 Jan 2024
Cited by 4 | Viewed by 2134
Abstract
Parknson’s disease (PD) is the second most common neurodegenerative disease, affecting 1% of people aged over 60. PD is characterized by a wide range of motor symptoms, however the clinical spectrum of PD covers a wide range of non-motor symptoms, as well. Sleep [...] Read more.
Parknson’s disease (PD) is the second most common neurodegenerative disease, affecting 1% of people aged over 60. PD is characterized by a wide range of motor symptoms, however the clinical spectrum of PD covers a wide range of non-motor symptoms, as well. Sleep disorders are among the most common non-motor symptoms of PD, can occur at any stage of the disease and significantly affect quality of life. These include rapid eye movement sleep behavior disorder (RBD), restless legs syndrome (RLS), excessive daytime sleepiness (EDS), insomnia, obstructive sleep apnea (OSA) and circadian rhythm disturbances. One of the main challenges in PD research is identifying individuals during the prodromal phase of the disease. Combining genetic and prodromal data may aid the early identification of individuals susceptible to PD. This review highlights current data regarding the genetic component of sleep disorders in PD patients, focusing on genes that have currently been associated with this PD co-morbidity. Full article
(This article belongs to the Special Issue Advances in the Diagnosis of Nervous System Diseases—2nd Edition)
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<p>Genes and sleep disorders in PD.</p>
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19 pages, 23995 KiB  
Article
Retinal Disease Diagnosis Using Deep Learning on Ultra-Wide-Field Fundus Images
by Toan Duc Nguyen, Duc-Tai Le, Junghyun Bum, Seongho Kim, Su Jeong Song and Hyunseung Choo
Diagnostics 2024, 14(1), 105; https://doi.org/10.3390/diagnostics14010105 - 3 Jan 2024
Cited by 3 | Viewed by 2572
Abstract
Ultra-wide-field fundus imaging (UFI) provides comprehensive visualization of crucial eye components, including the optic disk, fovea, and macula. This in-depth view facilitates doctors in accurately diagnosing diseases and recommending suitable treatments. This study investigated the application of various deep learning models for detecting [...] Read more.
Ultra-wide-field fundus imaging (UFI) provides comprehensive visualization of crucial eye components, including the optic disk, fovea, and macula. This in-depth view facilitates doctors in accurately diagnosing diseases and recommending suitable treatments. This study investigated the application of various deep learning models for detecting eye diseases using UFI. We developed an automated system that processes and enhances a dataset of 4697 images. Our approach involves brightness and contrast enhancement, followed by applying feature extraction, data augmentation and image classification, integrated with convolutional neural networks. These networks utilize layer-wise feature extraction and transfer learning from pre-trained models to accurately represent and analyze medical images. Among the five evaluated models, including ResNet152, Vision Transformer, InceptionResNetV2, RegNet and ConVNext, ResNet152 is the most effective, achieving a testing area under the curve (AUC) score of 96.47% (with a 95% confidence interval (CI) of 0.931–0.974). Additionally, the paper presents visualizations of the model’s predictions, including confidence scores and heatmaps that highlight the model’s focal points—particularly where lesions due to damage are evident. By streamlining the diagnosis process and providing intricate prediction details without human intervention, our system serves as a pivotal tool for ophthalmologists. This research underscores the compatibility and potential of utilizing ultra-wide-field images in conjunction with deep learning. Full article
(This article belongs to the Special Issue Artificial Intelligence in Biomedical Image Analysis)
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<p>Comparative view of ultra-wide-field fundus imaging (UFI, left) versus conventional fundus imaging (CFI, right), showcasing the extent of retinal coverage and detail resolution. UFI captures a comprehensive field of view, revealing the fovea, macula, and optic disk alongside peripheral retinal details that are not visible in the narrower field of CFI, which focuses on central retinal structures with greater detail. This contrast highlights the diagnostic advantages of UFI in assessing peripheral retinal pathology and the detailed visualization of central retinal features by CFI.</p>
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<p>Deep learning-aided eye disease diagnosis system. The images first undergo augmentation and preprocessing. Next, the preprocessed images are fed into deep learning neural networks to learn feature representations. The model then outputs the predictions as normal or abnormal eyes.</p>
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<p>Different core blocks of the proposed deep learning models. ResNet152 employs convolution layers of size 1 and 3, RegNet introduces a design space with additional convolution layers of <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>×</mo> <mn>1</mn> </mrow> </semantics></math>, and ConVNext introduces a depth-wise convolution. Vision Transformer comprises Multi-head Self-attention (MHSA) and multilayer perceptron (MLP).</p>
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<p>AUC score of ResNet152, Vision Transformer, InceptionResNetV2, RegNet and ConVNext.</p>
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<p>Training losses of ResNet152, Vision Transformer, InceptionResNetV2, RegNet and ConVNext. The transparent lines represent the raw training loss for each epoch, while the solid lines show the smoothed training loss with a smoothing factor of 0.6.</p>
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<p>Heatmaps generated from each deep learning model. The first-row images display abnormal eyes, and the second-row images represent normal eyes.</p>
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<p>Feature map generated from each deep learning model after each convolution layer (or after each block of attention, in the case of Vision Transformer).</p>
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<p>t-SNE visualization for each deep learning model, generated from 400 samples (200 for each class).</p>
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<p>Examples of ResNet152 model predictions, given an input image.</p>
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<p>Inference time for each model (average time taken for each model to generate a prediction, given an input image).</p>
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Article
Radiological Features of Male Breast Neoplasms: How to Improve the Management of a Rare Disease
by Luca Nicosia, Luciano Mariano, Anna Carla Bozzini, Filippo Pesapane, Vincenzo Bagnardi, Samuele Frassoni, Chiara Oriecuia, Valeria Dominelli, Antuono Latronico, Simone Palma, Massimo Venturini, Federico Fontana, Francesca Priolo, Ida Abiuso, Claudia Sangalli and Enrico Cassano
Diagnostics 2024, 14(1), 104; https://doi.org/10.3390/diagnostics14010104 - 3 Jan 2024
Cited by 1 | Viewed by 1393
Abstract
The primary aim of our study was to assess the main mammographic and ultrasonographic features of invasive male breast malignancies. The secondary aim was to evaluate whether a specific radiological presentation would be associated with a worse receptor profile. Radiological images (mammography and/or [...] Read more.
The primary aim of our study was to assess the main mammographic and ultrasonographic features of invasive male breast malignancies. The secondary aim was to evaluate whether a specific radiological presentation would be associated with a worse receptor profile. Radiological images (mammography and/or ultrasound) of all patients who underwent surgery for male invasive breast cancer in our institution between 2008 and 2023 were retrospectively analyzed by two breast radiologists in consensus. All significant features of radiological presentation known in the literature were re-evaluated. Fifty-six patients were selected. The mean age at surgery of patients was 69 years (range: 35–81); in 82% of cases (46 patients), the histologic outcome was invasive ductal carcinoma. A total of 28 out of 56 (50%) patients had preoperative mammography; in 9/28 cases (32%), we found a mass with microcalcifications on mammography. The mass presented high density in 25 out of 28 patients (89%); the mass showed irregular margins in 15/28 (54%) cases. A total of 46 out of 56 patients had preoperative ultrasounds. The lesion showed a solid mass in 41/46 (89%) cases. In 5/46 patients (11%), the lesion was a mass with a mixed (partly liquid–partly solid) structure. We did not find any statistically significant correlation between major types of radiological presentation and tumor receptor arrangement. Knowledge of the main radiologic presentation patterns of malignant male breast neoplasm can help better manage this type of disease, which is rare but whose incidence is increasing. Full article
(This article belongs to the Special Issue Recent Advances in Breast Imaging)
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<p>Flowchart diagram of the study inclusion and exclusion criteria.</p>
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<p>Disease-free survival (median FU (Q1–Q3) in years: 4.0 (1.1–7.0), N = 56).</p>
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<p>(<b>a</b>) (mediolateral oblique projection), (<b>b</b>) (cranio caudal projiection) 60-year-old man with a palpable mass of the upper sectors on the right breast (arrow).</p>
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<p>(<b>a</b>) (mediolateral oblique projection), (<b>b</b>) (cranio caudal projiection 75-year-old man with a palpable mass on the right breast (arrow).</p>
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<p>A 79-year-old man with a palpable mass on the right breast (arrow).</p>
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<p>Typical differences between gynecomastia and breast neoplasm (primary differential diagnosis): (<b>a</b>) A 45-year-old patient with a retroareolar, palpable, and mobile right mass (arrow). (<b>b</b>) A 70-year-old patient with a solid mass (arrow) and left nipple retraction (arrowhead).</p>
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<p>A 75-year-old man with a palpable lump and blood secretion of the right breast.</p>
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<p>67-year-old man with a palpable mass of the right breast.</p>
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Review
Does Frontal Recess Cell Variation Associate with the Development of Frontal Sinusitis? A Narrative Review
by Tariq Al Habsi, Eiman Al-Ajmi, Mohammed Al Washahi, Maitham Al Lawati, Shihab Al Maawali, Amit Mahajan and Srinivasa Rao Sirasanagandla
Diagnostics 2024, 14(1), 103; https://doi.org/10.3390/diagnostics14010103 - 3 Jan 2024
Viewed by 2110
Abstract
Chronic rhinosinusitis (CRS) can have a significant impact on quality of life. With persistent symptoms and the failure of initial medical treatments, surgical management is indicated. Despite the excellent results of endoscopic sinus surgery for persistent CRS, it is quite a challenging procedure [...] Read more.
Chronic rhinosinusitis (CRS) can have a significant impact on quality of life. With persistent symptoms and the failure of initial medical treatments, surgical management is indicated. Despite the excellent results of endoscopic sinus surgery for persistent CRS, it is quite a challenging procedure for frontal sinusitis given the complex anatomy and location of the frontal sinus. Frontal recess cells significantly contribute to the complexity of the frontal sinus, and numerous studies have sought to establish their association with sinusitis. This review offers a comprehensive understanding of frontal recess cells, their different classifications, their prevalence among different populations, and their relationship to sinusitis. After an extensive review of the current literature, the International Frontal Sinus Anatomy Classification (IFAC) is the most recent classification method and a preferred practical preoperative assessment tool. Although the agger nasi cell is the most prevalent cell among all reported populations, ethnic variations are still influencing the other cells’ distribution. Studies are inconsistent in reporting a relationship between frontal recess cells and sinusitis, and that is mainly because of the differences in the classification methods used. More research using a standardized classification method is needed to understand the association between frontal recess cells and sinusitis. Full article
(This article belongs to the Special Issue The Role of Anatomy in Medical Diagnosis and Pathology Analysis)
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<p>Modified Kuhn classification of frontal recess cells [<a href="#B15-diagnostics-14-00103" class="html-bibr">15</a>].</p>
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<p>International Frontal Sinus Anatomy Classification (IFAC) [<a href="#B7-diagnostics-14-00103" class="html-bibr">7</a>].</p>
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<p>IFAC cell types using computed tomography. Different cell types according to IFAC on CT using sagittal, axial and coronal planes for each cell type: (<b>A</b>–<b>C</b>) aggar nasi cell, (<b>D</b>–<b>F</b>) supra aggar cell, (<b>G</b>–<b>I</b>) supra aggar frontal cell, (<b>J</b>–<b>L</b>) supra bulla cell, (<b>M</b>–<b>O</b>) supra bulla frontal cell, (<b>P</b>–<b>R</b>) supraorbital ethmoid cell, and (<b>S</b>–<b>U</b>) frontal septal cell.</p>
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10 pages, 1089 KiB  
Case Report
Fetal Hyperthyroidism with Maternal Hypothyroidism: Two Cases of Intrauterine Therapy
by Lu Hong, Mary Hoi Yin Tang, Ka Wang Cheung, Libing Luo, Cindy Ka Yee Cheung, Xiaoying Dai, Yanyan Li, Chuqin Xiong, Wei Liang, Wei Xiang, Liangbing Wang, Kelvin Yuen Kwong Chan and Shengmou Lin
Diagnostics 2024, 14(1), 102; https://doi.org/10.3390/diagnostics14010102 - 3 Jan 2024
Cited by 2 | Viewed by 3026
Abstract
Fetal hyperthyroidism can occur secondary to maternal autoimmune hyperthyroidism. The thyroid-stimulating hormone receptor antibody (TRAb) transferred from the mother to the fetus stimulates the fetal thyroid and causes fetal thyrotoxicosis. Fetuses with this condition are difficult to detect, especially after maternal Graves disease [...] Read more.
Fetal hyperthyroidism can occur secondary to maternal autoimmune hyperthyroidism. The thyroid-stimulating hormone receptor antibody (TRAb) transferred from the mother to the fetus stimulates the fetal thyroid and causes fetal thyrotoxicosis. Fetuses with this condition are difficult to detect, especially after maternal Graves disease therapy. Here, we present two cases of fetal hyperthyroidism with maternal hypothyroidism and review the assessment and intrauterine therapy for fetal hyperthyroidism. Both women were referred at 22+ and 23+ weeks of gestation with abnormal ultrasound findings, including fetal heart enlargement, pericardial effusion, and fetal tachycardia. Both women had a history of Graves disease while in a state of hypothyroidism with a high titer of TRAb. A sonographic examination showed a diffusely enlarged fetal thyroid with abundant blood flow. Invasive prenatal testing revealed no significant chromosomal aberration. Low fetal serum TSH and high TRAb levels were detected in the cord blood. Fetal hyperthyroidism was considered, and maternal oral methimazole (MMI) was administered as intrauterine therapy, with the slowing of fetal tachycardia, a reduction in fetal heart enlargement, and thyroid hyperemia. During therapy, maternal thyroid function was monitored, and the dosage of maternal levothyroxine was adjusted accordingly. Both women delivered spontaneously at 36+ weeks of gestation, and neonatal hyperthyroidism was confirmed in both newborns. After methimazole and propranolol drug treatment with levothyroxine for 8 and 12 months, both babies became euthyroid with normal growth and development. Full article
(This article belongs to the Special Issue Fetal Medicine: From Basic Science to Prenatal Diagnosis and Therapy)
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<p>Ultrasonographic cardiac scan of Case One during the 23rd gestational week. (<b>A</b>) Fetal cardiac enlargement, pericardial effusion, and cardiac hypertrophy; (<b>B</b>) Fetal mild exophthalmos and palpebral oedema; (<b>C</b>) Enlarged thyroid with diffusely abundant blood flow.</p>
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<p>(<b>A</b>) Severely enlarged heart with increased cardiothoracic ratio and pericardial effusion at the 23rd gestational week in Case Two; (<b>B</b>) Mild fetal ascites; (<b>C</b>) Mild fetal palpebral oedema; (<b>D</b>) Fetal thyromegaly and congestion; (<b>E</b>) Decreased fetal cardiothoracic ratio at 31 weeks.</p>
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13 pages, 2780 KiB  
Article
Functional and Morphological Outcomes after Trabeculectomy and Deep Sclerectomy—Results from a Monocentric Registry Study
by Valentin Pfeiffer, Pascal Aurel Gubser, Xiao Shang, Joel-Benjamin Lincke, Nathanael Urs Häner, Martin Sebastian Zinkernagel and Jan Darius Unterlauft
Diagnostics 2024, 14(1), 101; https://doi.org/10.3390/diagnostics14010101 - 2 Jan 2024
Viewed by 1000
Abstract
The aim of this study was to compare the effectiveness of trabeculectomy (TE) and deep sclerectomy (DS) in lowering intraocular pressure (IOP) and thereby preserving visual field and peripapillary retinal nerve fiber layer (RNFL) tissue in primary open-angle glaucoma (POAG) cases. IOP, number [...] Read more.
The aim of this study was to compare the effectiveness of trabeculectomy (TE) and deep sclerectomy (DS) in lowering intraocular pressure (IOP) and thereby preserving visual field and peripapillary retinal nerve fiber layer (RNFL) tissue in primary open-angle glaucoma (POAG) cases. IOP, number of IOP-lowering medications, visual acuity, mean defect of standard automated perimetry, and mean peripapillary RNFL thickness were retrospectively collected and followed up for 3 years after surgery. TE was performed in 104 eyes and DS in 183 eyes. Age, gender, laterality, IOP, number of medications, visual acuity, perimetry mean defect, and peripapillary RNFL thickness were equally distributed at baseline. Mean IOP decreased from 23.8 ± 1.4 mmHg and 23.1 ± 0.4 mmHg to 13.4 ± 0.6 mmHg (p < 0.001) and 15.4 ± 0.7 mmHg (p = 0.001) in the TE and DS groups, respectively. Mean defect remained stable (TE: −11.5 ± 0.9 dB to −12.0 ± 1.1 (p = 0.090); DS: −10.5 ± 0.9 dB to −11.0 ± 1.0 dB (p = 0.302)), while mean peripapillary RNFL thickness showed further deterioration during follow-up (TE group: 64.4 ± 2.1 μm to 59.7 ± 3.5 μm (p < 0.001); DS group: 64.9 ± 1.9 μm to 58.4 ± 2.1 μm (p < 0.001)). Both TE and DS were comparably effective concerning postoperative reduction in IOP and medication. However, glaucoma disease further progressed during follow-up. Full article
(This article belongs to the Special Issue Structure–Function Relationship in Retinal Diseases, Second Edition)
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<p>Mean IOP development over the course of 3 years after TE or DS: TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Development of the mean number of necessary IOP-lowering medications over the course of 3 years after TE or DS: TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Course of the mean BCVA over the 3 years of follow-up after TE or DS: TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Distribution of SAP mean deviation in groups undergoing TE or DS at baseline before surgery: TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Course of the visual field mean deviation over the 3 years of follow-up after TE or DS: TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Course of the mean RNFL thickness measured using peripapillary OCT scan over the 3 years of follow-up after TE or DS: RNFL, retinal nerve fiber layer; OCT, optical coherence tomography; TE, trabeculectomy; DS, deep sclerectomy.</p>
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<p>Scattergrams of pre- and postoperative IOP results in the TE (<b>a</b>) and DS (<b>b</b>) groups 3 years after the respective surgery: TE, trabeculectomy; DS, deep sclerectomy; IOP, intraocular pressure.</p>
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13 pages, 4867 KiB  
Case Report
Diagnostic Methods in Forensic Pathology: Autoptic Findings and Immunohistochemical Study in Cases of Sudden Death Due to a Colloid Cyst of the Third Ventricle
by Angelo Montana, Francesco Paolo Busardò, Giovanni Tossetta, Gaia Goteri, Pasqualina Castaldo, Giuseppe Basile and Giulia Bambagiotti
Diagnostics 2024, 14(1), 100; https://doi.org/10.3390/diagnostics14010100 - 1 Jan 2024
Viewed by 2023
Abstract
The colloid cyst is a non-malignant tumor growth made of a gelatinous material covered by a membrane of epithelial tissue. It is usually located posterior to the foramen of Monro, in the anterior aspect of the third ventricle of the brain. Due to [...] Read more.
The colloid cyst is a non-malignant tumor growth made of a gelatinous material covered by a membrane of epithelial tissue. It is usually located posterior to the foramen of Monro, in the anterior aspect of the third ventricle of the brain. Due to its location, it can cause obstructive hydrocephalus, increased intracranial pressure, and sudden cardiac death, catecholamine-mediated, through hypothalamus compression. All the mechanisms are still controversial, but the role of catecholamine has been confirmed with histological findings that highlighted myocardial injury (coagulative myocytolysis and contraction band necrosis, CBN). This study presents a case of sudden death in a previously healthy 22-year-old male due to a colloid cyst of the third ventricle. A complete autopsy was performed, highlighting in the brain an abundant quantity of cerebrospinal fluid (CSF) and a 2 cm pale grayish-green rounded cyst formation partially filling and distending the third ventricle. The diagnosis was confirmed through immunohistochemical investigation: positivity for Periodic acid-Schiff (PAS) staining and CK7 expression. In cases such as the one reported here, a combined approach of autopsy, histology, and immunohistochemistry is mandatory in order to identify the neoformation’s location and morpho-structural characteristics for a correct differential diagnosis, as well as to identify the cause of death. Full article
(This article belongs to the Special Issue Forensic Diagnosis)
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<p>Localization of the cyst in the third ventricle (<b>A</b>). The cyst was wedged between the splayed columns of the fornix, not obstructing the left foramen of Monro (<b>B</b>). A viscous substance hardened after formalin fixation with a thin fibrous capsule was observed when the cyst was sectioned (<b>C</b>,<b>D</b>).</p>
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<p>Cystic lesion, filled with a strongly PAS-positive amorphous content (<b>A</b>) and covered by hypocellular fibrous wall lined by simple columnar epithelium with variable cilia or mucin, flattened without squamous metaplasia (<b>B</b>). Columnar, ciliated epithelial cells compose the cyst wall. There was no abnormal increase in goblet cells or any cellular atypia or thickening of the wall. Cyst content consisted of a mucoid material with detached epithelial cell clusters (<b>A</b> ×40, <b>B</b> ×80).</p>
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<p>Immunohistochemical staining of CK7 using a human-specific anti-Cytokeratin 7 antibody. The cyst epithelium (arrows) is positive for CK7 (×40, ×80).</p>
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<p>Hypercontracted myofibrils fragmentation and hypercontracted or coagulated sarcomeres (arrows) band formation. Absence of edema, hemorrhage, and myofiber vacuolization (H&amp;E × 40).</p>
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<p>Combined double mechanisms underlying the sudden death due to a colloid cyst of the third ventricle.</p>
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18 pages, 1131 KiB  
Systematic Review
Artificial Intelligence in Predicting Microsatellite Instability and KRAS, BRAF Mutations from Whole-Slide Images in Colorectal Cancer: A Systematic Review
by Theo Guitton, Pierre Allaume, Noémie Rabilloud, Nathalie Rioux-Leclercq, Sébastien Henno, Bruno Turlin, Marie-Dominique Galibert-Anne, Astrid Lièvre, Alexandra Lespagnol, Thierry Pécot and Solène-Florence Kammerer-Jacquet
Diagnostics 2024, 14(1), 99; https://doi.org/10.3390/diagnostics14010099 - 31 Dec 2023
Cited by 3 | Viewed by 2426
Abstract
Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), KRAS, and BRAF mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to [...] Read more.
Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), KRAS, and BRAF mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to predict tumor status. In this systematic review, we evaluated the role of AI in predicting MSI status, KRAS, and BRAF mutations in colorectal cancer. Studies published in PubMed up to June 2023 were included (n = 17), and we reported the risk of bias and the performance for each study. Some studies were impacted by the reduced number of slides included in the data set and the lack of external validation cohorts. Deep learning models for the d-MMR/MSI status showed a good performance in training cohorts (mean AUC = 0.89, [0.74–0.97]) but slightly less than expected in the validation cohort when available (mean AUC = 0.82, [0.63–0.98]). Contrary to the MSI status, the prediction of KRAS and BRAF mutations was less explored with a less robust methodology. The performance was lower, with a maximum of 0.77 in the training cohort, 0.58 in the validation cohort for KRAS, and 0.82 AUC in the training cohort for BRAF. Full article
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<p>Flowchart.</p>
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<p>Overview of the AUC (area under the curve) for each MSI study between intern and extern validation [<a href="#B20-diagnostics-14-00099" class="html-bibr">20</a>,<a href="#B21-diagnostics-14-00099" class="html-bibr">21</a>,<a href="#B22-diagnostics-14-00099" class="html-bibr">22</a>,<a href="#B23-diagnostics-14-00099" class="html-bibr">23</a>,<a href="#B24-diagnostics-14-00099" class="html-bibr">24</a>,<a href="#B25-diagnostics-14-00099" class="html-bibr">25</a>,<a href="#B26-diagnostics-14-00099" class="html-bibr">26</a>,<a href="#B27-diagnostics-14-00099" class="html-bibr">27</a>,<a href="#B28-diagnostics-14-00099" class="html-bibr">28</a>,<a href="#B30-diagnostics-14-00099" class="html-bibr">30</a>,<a href="#B31-diagnostics-14-00099" class="html-bibr">31</a>,<a href="#B32-diagnostics-14-00099" class="html-bibr">32</a>,<a href="#B33-diagnostics-14-00099" class="html-bibr">33</a>,<a href="#B35-diagnostics-14-00099" class="html-bibr">35</a>,<a href="#B36-diagnostics-14-00099" class="html-bibr">36</a>].</p>
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<p>QUADAS 2 overview evaluating the risk of MSI studies.</p>
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12 pages, 2295 KiB  
Review
Navigation and Robotics in Interventional Oncology: Current Status and Future Roadmap
by Georgios Charalampopoulos, Reto Bale, Dimitrios Filippiadis, Bruno C. Odisio, Bradford Wood and Luigi Solbiati
Diagnostics 2024, 14(1), 98; https://doi.org/10.3390/diagnostics14010098 - 31 Dec 2023
Cited by 5 | Viewed by 2235
Abstract
Interventional oncology (IO) is the field of Interventional Radiology that provides minimally invasive procedures under imaging guidance for the diagnosis and treatment of malignant tumors. Sophisticated devices can be utilized to increase standardization, accuracy, outcomes, and “repeatability” in performing percutaneous Interventional Oncology techniques. [...] Read more.
Interventional oncology (IO) is the field of Interventional Radiology that provides minimally invasive procedures under imaging guidance for the diagnosis and treatment of malignant tumors. Sophisticated devices can be utilized to increase standardization, accuracy, outcomes, and “repeatability” in performing percutaneous Interventional Oncology techniques. These technologies can reduce variability, reduce human error, and outperform human hand-to-eye coordination and spatial relations, thus potentially normalizing an otherwise broad diversity of IO techniques, impacting simulation, training, navigation, outcomes, and performance, as well as verification of desired minimum ablation margin or other measures of successful procedures. Stereotactic navigation and robotic systems may yield specific advantages, such as the potential to reduce procedure duration and ionizing radiation exposure during the procedure and, at the same time, increase accuracy. Enhanced accuracy, in turn, is linked to improved outcomes in many clinical scenarios. The present review focuses on the current role of percutaneous navigation systems and robotics in diagnostic and therapeutic Interventional Oncology procedures. The currently available alternatives are presented, including their potential impact on clinical practice as reflected in the peer-reviewed medical literature. A review of such data may inform wiser investment of time and resources toward the most impactful IR/IO applications of robotics and navigation to both standardize and address unmet clinical needs. Full article
(This article belongs to the Special Issue Imaging-Guided Techniques in Interventional Oncology)
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<p>A 58-year-old male patient with a mass in the left adrenal gland. Biopsy was performed using an electromagnetic navigation device.</p>
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<p>Case of a stereotactic radiofrequency ablation (SRFA) in an 85-year-old male with a sub-cardiac HCC (4.8 cm): (<b>A</b>) Arterial phase planning CT; (<b>B</b>) Portal-venous phase planning CT; (<b>C</b>) MIP of the control CT, showing in total 7 inserted coaxial needles; (<b>D</b>) Screenshot of the frameless stereotactic navigation system: Superposition of the needle control CT on the planning CT, with the pathways showing precise placement of all needles; (<b>E</b>) Contrast-enhanced control CT (portalvenous phase), showing the large ablation zone covering the HCC, including a sufficient safety margin, which was confirmed by image fusion.</p>
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<p>An 82-year-old female RCC patient with multiple metastatic lesions was treated with percutaneous cryoablation of a soft tissue mass in the posterior paravertebral muscles for pain palliation. (<b>A</b>) The ablation procedure was performed under CT guidance using a robotic navigation device. (<b>B</b>) Four cryoprobes were placed under CT guidance using the robotic navigation device. (<b>C</b>) Axial CT scan during ablation illustrating the ice ball and a sterile glove filled with warm water placed on the skin for protection.</p>
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<p>A 73-year-old male HCC patient was treated with percutaneous radiofrequency ablation in segment VIII. The ablation procedure was performed under CT guidance using an AR navigation device. (<b>A</b>) The small HCC (red circle) is visible in arterial phase. (<b>B</b>) AR guidance from the physician’s point of view. The liver is in red; the bones of thoracic case are in white; the liver vessels are in light-blue, and the lesion is in green. The green line shows the trajectory that connects the tip of the needle to the center of the target in real time. (<b>C</b>) Axial CT scan showing the tip of the needle (red circle) precisely located in the center of the lesion after the guidance by AR.</p>
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15 pages, 1199 KiB  
Article
Application of a 21-Gene Recurrence Score in a Swiss Single-Center Breast Cancer Population: A Comparative Analysis of Treatment Administration before and after TAILORx
by Elena Diana Chiru, Anton Oseledchyk, Andreas Schoetzau, Christian Kurzeder, Raphael Mosimann, Marcus Vetter and Cvetka Grašič Kuhar
Diagnostics 2024, 14(1), 97; https://doi.org/10.3390/diagnostics14010097 - 31 Dec 2023
Cited by 1 | Viewed by 1454
Abstract
In patients with hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2−) negative breast cancer (BC), the TAILORx study showed the benefit of adding chemotherapy (CHT) to endocrine therapy (ET) in a subgroup of patients under 50 years with an intermediate Oncotype DX [...] Read more.
In patients with hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2−) negative breast cancer (BC), the TAILORx study showed the benefit of adding chemotherapy (CHT) to endocrine therapy (ET) in a subgroup of patients under 50 years with an intermediate Oncotype DX recurrence score (RS 11–25). The aim of the present study was to determine if the TAILORx findings, including the changes in the RS categories, impacted CHT use in the intermediate RS (11–25) group in daily practice, as well as to identify the main factors for CHT decisions. We conducted a retrospective study on 326 BC patients (59% node-negative), of which 165 had a BC diagnosis before TAILORx (Cohort A) and 161 after TAILORx publication (Cohort B). Changes in the RS categories led to shifts in patient population distribution, thereby leading to a 40% drop in the low RS (from 60% to 20%), which represented a doubling in the intermediate RS (from 30% to 60%) and an increase of 5% in the high RS (from 8–10% to 15%). The overall CHT recommendation and application did not differ significantly between cohort B when compared with A (19% vs. 22%, resp., p = 0.763). In the intermediate RS (11–25), CHT use decreased by 5%, while in the high-risk RS category (>25), there was an increase of 13%. The tumor board recommended CHT for 90% of the patients according to the new RS guidelines in cohort A and for 85% in cohort B. The decision for CHT recommendation was based on age (OR 0.93, 95% CI 0.08–0.97, p = 0.001), nodal stage (OR 4.77, 95% CI 2.03–11.22, p < 0.001), and RS categories (RS 11–25 vs. RS 0–10: OR 0.06 (95% CI 0.02–0.17), p < 0.001; RS > 26 vs. RS 11–25: OR 618.18 95% CI 91.64–4169.91, p < 0.001), but did not depend on the cohort. In conclusion, while the tumor board recommendation for CHT decreased in the intermediate RS category, there was an increase being reported in the high RS category, thus leading to overall minor changes in CHT application. As expected, among the younger women with intermediate RS and unfavorable histopathological factors, CHT use increased. Full article
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<p>Distribution of the patients in Cohort A (before TAILORx) and Cohort B (after TAILORx) in each RS category (low, intermediate, and high) according to the different thresholds, as defined by the manufacturer recommendation (<b>part 1</b>) and by the TAILORx study design (<b>part 2</b>). RS = recurrence score. Note: percentages were rounded.</p>
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<p>The percentage of patients treated with endocrine therapy (ET) and chemotherapy followed by endocrine therapy (CHT-ET), and the distribution of ET and CHT-ET according to the three RS groups, as determined by tumor board (TB) recommendation. In addition, the percentage of patients who refused ET or CHT + ET (from the entire population). ET = endocrine therapy; CHT = chemotherapy. Note: percentages were rounded.</p>
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<p>Change in the chemotherapy use in Cohort B (pre-TAILORx) and Cohort B (post-TAILORx) according to the patient and tumor characteristics. CHT-ET = chemoendocrine therapy. Note: percentages were rounded.</p>
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<p>Comparison of endocrine therapy (ET) in patients in the two cohorts (pre- and post-TAILORx: Cohort A and Cohort B) and the observed changes in treatment. ET = endocrine therapy. Note: percentages were rounded.</p>
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15 pages, 5334 KiB  
Article
AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed Tomography
by Chulkyun Ahn and Jong Hyo Kim
Diagnostics 2024, 14(1), 96; https://doi.org/10.3390/diagnostics14010096 - 31 Dec 2023
Cited by 3 | Viewed by 1346
Abstract
Gaining the ability to audit the behavior of deep learning (DL) denoising models is of crucial importance to prevent potential hallucinations and adversarial clinical consequences. We present a preliminary version of AntiHalluciNet, which is designed to predict spurious structural components embedded in the [...] Read more.
Gaining the ability to audit the behavior of deep learning (DL) denoising models is of crucial importance to prevent potential hallucinations and adversarial clinical consequences. We present a preliminary version of AntiHalluciNet, which is designed to predict spurious structural components embedded in the residual noise from DL denoising models in low-dose CT and assess its feasibility for auditing the behavior of DL denoising models. We created a paired set of structure-embedded and pure noise images and trained AntiHalluciNet to predict spurious structures in the structure-embedded noise images. The performance of AntiHalluciNet was evaluated by using a newly devised residual structure index (RSI), which represents the prediction confidence based on the presence of structural components in the residual noise image. We also evaluated whether AntiHalluciNet could assess the image fidelity of a denoised image by using only a noise component instead of measuring the SSIM, which requires both reference and test images. Then, we explored the potential of AntiHalluciNet for auditing the behavior of DL denoising models. AntiHalluciNet was applied to three DL denoising models (two pre-trained models, RED-CNN and CTformer, and a commercial software, ClariCT.AI [version 1.2.3]), and whether AntiHalluciNet could discriminate between the noise purity performances of DL denoising models was assessed. AntiHalluciNet demonstrated an excellent performance in predicting the presence of structural components. The RSI values for the structural-embedded and pure noise images measured using the 50% low-dose dataset were 0.57 ± 31 and 0.02 ± 0.02, respectively, showing a substantial difference with a p-value < 0.0001. The AntiHalluciNet-derived RSI could differentiate between the quality of the degraded denoised images, with measurement values of 0.27, 0.41, 0.48, and 0.52 for the 25%, 50%, 75%, and 100% mixing rates of the degradation component, which showed a higher differentiation potential compared with the SSIM values of 0.9603, 0.9579, 0.9490, and 0.9333. The RSI measurements from the residual images of the three DL denoising models showed a distinct distribution, being 0.28 ± 0.06, 0.21 ± 0.06, and 0.15 ± 0.03 for RED-CNN, CTformer, and ClariCT.AI, respectively. AntiHalluciNet has the potential to predict the structural components embedded in the residual noise from DL denoising models in low-dose CT. With AntiHalluciNet, it is feasible to audit the performance and behavior of DL denoising models in clinical environments where only residual noise images are available. Full article
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<p>A flow diagram of AntiHalluciNet: structure-embedded noise simulation, AntiHalluciNet training, and auditing the behavior of DL denoising models.</p>
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<p>An example procedure of creating structure-embedded noise image. A pure noise image (<b>b</b>) was creating by applying a low-dose simulation technique to (<b>a</b>) the given CT image. High frequency component image (<b>d</b>) obtained by <span class="html-italic">DoG</span> filtering was multiplied by randomly placed circular masks (<b>e</b>) to produce spurious structural components (<b>f</b>). Then, the structure-embedded noise image (<b>c</b>) was obtained by combining the simulated pure noise images and structural components.</p>
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<p>Selected examples of pure noise images (<b>a</b>) generated by using the experimental procedure described above and corresponding heatmaps (<b>b</b>) generated with AntiHalluciNet. Typical noise appearances are well represented in (<b>a</b>), and heatmaps with mostly clean backgrounds are shown in (<b>b</b>).</p>
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<p>Selected examples of structure-embedded noise images (<b>a</b>) generated by using the experimental procedure described above and corresponding heatmaps (<b>b</b>) generated with AntiHalluciNet. Typical residual spurious structures are well represented in (<b>a</b>), and opaque colors are overlayed on the spots where spurious structures are located in (<b>b</b>).</p>
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<p>Comparison of low-dose image, standard-dose image, and denoised images from the three DL denoisers employed in this study. (<b>a</b>) Low-dose, (<b>b</b>) standard-dose, (<b>c</b>) RED-CNN, (<b>d</b>) CTformer, and (<b>e</b>) ClariCT.AI. The display window is [−160, 240] HU.</p>
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<p>An example of (<b>a</b>) residual noise and (<b>b</b>) structure prediction heat maps (<b>c</b>) overlaid on denoised images from the three DL denoisers.</p>
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16 pages, 3357 KiB  
Article
Histopathological Image Diagnosis for Breast Cancer Diagnosis Based on Deep Mutual Learning
by Amandeep Kaur, Chetna Kaushal, Jasjeet Kaur Sandhu, Robertas Damaševičius and Neetika Thakur
Diagnostics 2024, 14(1), 95; https://doi.org/10.3390/diagnostics14010095 - 31 Dec 2023
Cited by 8 | Viewed by 3127
Abstract
Every year, millions of women across the globe are diagnosed with breast cancer (BC), an illness that is both common and potentially fatal. To provide effective therapy and enhance patient outcomes, it is essential to make an accurate diagnosis as soon as possible. [...] Read more.
Every year, millions of women across the globe are diagnosed with breast cancer (BC), an illness that is both common and potentially fatal. To provide effective therapy and enhance patient outcomes, it is essential to make an accurate diagnosis as soon as possible. In recent years, deep-learning (DL) approaches have shown great effectiveness in a variety of medical imaging applications, including the processing of histopathological images. Using DL techniques, the objective of this study is to recover the detection of BC by merging qualitative and quantitative data. Using deep mutual learning (DML), the emphasis of this research was on BC. In addition, a wide variety of breast cancer imaging modalities were investigated to assess the distinction between aggressive and benign BC. Based on this, deep convolutional neural networks (DCNNs) have been established to assess histopathological images of BC. In terms of the Break His-200×, BACH, and PUIH datasets, the results of the trials indicate that the level of accuracy achieved by the DML model is 98.97%, 96.78, and 96.34, respectively. This indicates that the DML model outperforms and has the greatest value among the other methodologies. To be more specific, it improves the results of localization without compromising the performance of the classification, which is an indication of its increased utility. We intend to proceed with the development of the diagnostic model to make it more applicable to clinical settings. Full article
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<p>Medical imaging modalities for breast tissue: (<b>a</b>) ultrasound, (<b>b</b>) mammogram, and (<b>c</b>) MRI [<a href="#B10-diagnostics-14-00095" class="html-bibr">10</a>].</p>
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<p>Samples (<b>a</b>–<b>e</b>) are ductal carcinomas (DCs), while sample (<b>f</b>) is a phyllodes tumor carcinoma (PTC) from a woman with breast cancer. Each image is a 400× magnification from the BreakHis archive.</p>
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<p>Slides of breast ductal carcinoma from the same patient at (<b>a</b>) 40×, (<b>b</b>) 100×, (<b>c</b>) 200×, and (<b>d</b>) 400×. BreakHis has provided the images [<a href="#B20-diagnostics-14-00095" class="html-bibr">20</a>].</p>
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<p>The DML schema.</p>
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<p>Images from three publicly available datasets illustrating histopathology.</p>
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<p>Block diagram of the proposed methodology.</p>
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<p>ROC curve for the classification results using the BreakHis-200× dataset.</p>
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<p>ROC curve for the classification results using the BACH dataset.</p>
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<p>ROC curve for the classification results using the PUIH dataset.</p>
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<p>Comparison of the DML with the independent and DML-based training systems for accuracy.</p>
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<p>MA-MIDN model’s localization output on three publicly available datasets.</p>
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<p>Different attention processes’ localization outcomes on the BACH dataset.</p>
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<p>Evaluation of the DML and Grad-CAM for localization.</p>
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<p>Performance associations between the suggested methods and the other pooling methods.</p>
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13 pages, 1065 KiB  
Article
Explaining the Elusive Nature of a Well-Defined Threshold for Blood Transfusion in Advanced Epithelial Ovarian Cancer Cytoreductive Surgery
by Alexandros Laios, Evangelos Kalampokis, Marios-Evangelos Mamalis, Amudha Thangavelu, Yong Sheng Tan, Richard Hutson, Sarika Munot, Tim Broadhead, David Nugent, Georgios Theophilou, Robert-Edward Jackson and Diederick De Jong
Diagnostics 2024, 14(1), 94; https://doi.org/10.3390/diagnostics14010094 - 30 Dec 2023
Viewed by 2058
Abstract
There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. To address this, we devised a Machine Learning (ML)-driven prediction algorithm aimed at prompting and elucidating a communication alert for BT based on anticipated peri-operative events [...] Read more.
There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. To address this, we devised a Machine Learning (ML)-driven prediction algorithm aimed at prompting and elucidating a communication alert for BT based on anticipated peri-operative events independent of existing BT policies. We analyzed data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. The estimated blood volume (EBV), calculated using the formula EBV = weight × 80, served for setting a 10% EBV threshold for individual intervention. Based on known estimated blood loss (EBL), we identified two distinct groups. The Receiver operating characteristic (ROC) curves revealed satisfactory results for predicting events above the established threshold (AUC 0.823, 95% CI 0.76–0.88). Operative time (OT) was the most significant factor influencing predictions. Intra-operative blood loss exceeding 10% EBV was associated with OT > 250 min, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score > 4. Certain sub-procedures including large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy demonstrated clear associations with an elevated interventional risk. Our findings emphasize the importance of obtaining a rough estimate of OT in advance for precise prediction of blood requirements. Full article
(This article belongs to the Special Issue Gynecological Oncology: Advanced Diagnosis and Management)
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<p>Flowchart of the study cohort.</p>
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<p>Performance of the XGBoost model for the risk prediction of blood transfusion at cytoreductive surgery (<b>A</b>) Receiver Operator Characteristic (ROC) curve. (<b>B</b>) Precision Recall (PR) curve.</p>
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<p>(<b>A</b>) Summary plot showing a set of feature distribution beeswarm plots for global (threshold) explainability of 10% EBV threshold prediction. (<b>B</b>) Feature importance bar plot of their SHAP values. PCI, Peritoneal Carcinomatosis Index; RD, Residual Disease; PDS, Primary Debulking surgery; IDS, Interval Debulking Surgery; PS, Performance Status.</p>
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<p>Kaplan Meier (KM) curve showing overall survivals between the &lt;10% EBV and &gt;10% EBV threshold cohorts of women undergoing cytoreduction for advanced epithelial ovarian cancer. No statistical significance was demonstrated.</p>
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<p>Schematic representation of our study. According to our concept, ML-based feature selection identified operative time out of an exhaustive list of patient, disease and operation-specific features as the top feature for the risk prediction of blood transfusion at cytoreductive surgery.</p>
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<p>Examples of SHAP value Dependence plots for global explainability features showing the impact of each feature value in the risk prediction of blood transfusion at cytoreductive surgery. (<b>A</b>) Pre-treatment. (<b>B</b>) Grade. (<b>C</b>) PS. (<b>D</b>) Serous vs. non-serous pathology. PS, Performance Status.</p>
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<p>Examples of SHAP value Dependence plots for global explainability features showing the impact of each feature value in the risk prediction of blood transfusion at cytoreductive surgery. (<b>A</b>) Operative time. (<b>B</b>) timing of cytoreduction. (<b>C</b>) Intra-operative mapping of ovarian cancer score. (<b>D</b>) Peritoneal Carcinomatosis Index. (<b>E</b>) Surgical Complexity Score. (<b>F</b>) Residual disease.</p>
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<p>Examples of SHAP value Dependence plots for global explainability features showing the impact of surgical sub-procedures in the risk prediction of blood transfusion at cytoreductive surgery. The important features include (<b>A</b>) stoma formation; (<b>B</b>) Bladder peritonectomy; (<b>C</b>) Para-aortic lymphadenectomy; (<b>D</b>) Ileo-caecal resection/right hemicolectomy; (<b>E</b>) Mesenteric resection; (<b>F</b>) Upper abdominal peritonectomy; (<b>G</b>) Large bowel resection; (<b>H</b>) Pelvic lymph node dissection. LND, lymph node dissection.</p>
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14 pages, 295 KiB  
Article
Analysis of Hand Function, Upper Limb Disability, and Its Relationship with Peripheral Vascular Alterations in Raynaud’s Phenomenon
by Rosa Mª Tapia-Haro, Mª Carmen García-Ríos, Adelaida Mª Castro-Sánchez, Sonia Toledano-Moreno, Antonio Casas-Barragán and Mª Encarnación Aguilar-Ferrándiz
Diagnostics 2024, 14(1), 93; https://doi.org/10.3390/diagnostics14010093 - 30 Dec 2023
Viewed by 1290
Abstract
This study aimed to compare vascular involvement, hand functionality, and upper limb disability between Raynaud’s phenomenon participants and controls. Also, we analyzed the relationships between vascular impairment, mobility, and strength with disability in this Raynaud population. We conducted a case–control study with fifty-seven [...] Read more.
This study aimed to compare vascular involvement, hand functionality, and upper limb disability between Raynaud’s phenomenon participants and controls. Also, we analyzed the relationships between vascular impairment, mobility, and strength with disability in this Raynaud population. We conducted a case–control study with fifty-seven participants. We registered sociodemographic and clinical data; vascular variables (temperature, cold test, blood flow, and oxygen saturation); functional variables (pinch strength, range of motion), and disability (Shortened Disabilities of the Arm, Shoulder and Hand Questionnaire) (Q-DASH). Raynaud participants present more disability in all Q-DASH subscales, lower hands’ temperature pre and post cold test, decreased blood flow on radial artery, decreased ranges of motions at passive extension of index finger, and active flexion and extension of thumb than the healthy controls. The multivariate regression analysis showed that extension of the index finger, lateral pinch strength, and oxygen saturation were significantly associated with disability in RP, almost the 55% of the total variance on the upper limb, 27% at sports/arts, and 42% at work. Our findings suggest that RP has a disabling effect on the upper extremities and a practice of activities in people who suffer it. Also, disability in Raynaud seems to be more related with hand mobility and strength impairment than vascular injury. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
17 pages, 4351 KiB  
Article
Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis
by Miriam C. Bassler, Mona Knoblich, Elena Gerhard-Hartmann, Ashutosh Mukherjee, Almoatazbellah Youssef, Rudolf Hagen, Lukas Haug, Miguel Goncalves, Agmal Scherzad, Manuel Stöth, Edwin Ostertag, Maria Steinke, Marc Brecht, Stephan Hackenberg and Till Jasper Meyer
Diagnostics 2024, 14(1), 92; https://doi.org/10.3390/diagnostics14010092 - 30 Dec 2023
Viewed by 1377
Abstract
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential [...] Read more.
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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<p>Schematic acquisition workflow for Raman imaging of parotid tissue cross-sections and data extraction. Raman images were recorded with the WITec Alpha 300 RA&amp;S using a 532 nm frequency-doubled Nd:YAG laser for excitation purposes (<b>a</b>). Initially, a suitable tissue region was chosen in an overview brightfield image, which was in accordance with the corresponding HE evaluation ((<b>b</b>), *** marks the sample). In this overview image, a 20 µm × 20 µm tissue area of interest ((<b>b</b>,<b>c</b>), yellow box) was determined and Raman imaged in a stepwise manner. The obtained Raman image (<b>d</b>) is composed of single Raman spectra (1–6) located at distinct x,y-positions. Raman spectra were extracted individually for PCA-DA model formation (<b>e</b>).</p>
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<p>Overall Raman mean spectra with corresponding 95% confidence intervals (light colors) of normal salivary gland tissue (green), Warthin tumor (blue) and pleomorphic adenoma (red), illustrated in a Raman shift region of 500–3500 cm<sup>−1</sup> (<b>a</b>). Main spectral differences were noticed between 900 and 1700 cm<sup>−1</sup>, which was analyzed in more detail (<b>b</b>). In this region, distinct Raman band assignments were performed (1–14). The spectra are vertically displayed. Corresponding molecular vibrations and causes are comprehensively listed in <a href="#diagnostics-14-00092-t001" class="html-table">Table 1</a>.</p>
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<p>PCA model for the differentiation of salivary gland, Warthin tumor and pleomorphic adenoma. The 3D scores plot is illustrated in (<b>a</b>), displaying PC1 (40%), PC2 (18%) and PC5 (4%). A successful separation of salivary gland (green circles), Warthin tumor (blue triangles) and pleomorphic adenoma (red squares) clusters is achieved with only minor group overlaps in the center. The corresponding loading plots are shown in (<b>b</b>), revealing the main influencing Raman shift of PC1, PC2 and PC5 for the group segregation. To demonstrate the clear differentiation between parotid tissue clusters by the PCA model, various perspectives on the 3D scores plot are shown in <a href="#app1-diagnostics-14-00092" class="html-app">Figure S2</a>. Additional 2D scores and respective loading plots of all model-included PCs are summarized in <a href="#app1-diagnostics-14-00092" class="html-app">Figure S3, Supplementary information</a>.</p>
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<p>Schematic description of the external PCA-DA validation. At first, histopathologically appropriate tissue regions were defined on the HE-stained cross-sections (1–5 tumor tissue, 1–5 salivary gland tissue in (<b>a</b>)). Afterwards, these regions were identified on the corresponding unstained cross-sections used for Raman imaging (1–5 tumor tissue, 1–5 salivary gland tissue in (<b>b</b>)). Raman images (<b>c</b>) and resulting Raman mean spectra (<b>d</b>) were acquired and calculated to be predicted by the PCA-DA model. The tested Raman mean spectra are either correctly (✓) or falsely (✕) classified by the model (<b>e</b>), which is evaluated by the initial HE diagnosis in step (<b>a</b>). Examples for the typical histomorphology of (<b>f</b>) a pleomorphic adenoma and (<b>g</b>) a Warthin tumor with adjacent healthy salivary gland tissue.</p>
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12 pages, 2694 KiB  
Article
Effectiveness of Single-Dose Oral Pilocarpine Administration in Patients with Sjögren’s Syndrome
by Aoi Komuro, Norihiko Yokoi, Chie Sotozono and Shigeru Kinoshita
Diagnostics 2024, 14(1), 91; https://doi.org/10.3390/diagnostics14010091 - 30 Dec 2023
Viewed by 1512
Abstract
In this study, we evaluated the effectiveness of a single-dose oral pilocarpine administration on tear film (TF), as well as dry eye and dry mouth symptoms, in 53 eyes of 27 Sjögren syndrome (SS) patients who were experiencing dry mouth. To evaluate the [...] Read more.
In this study, we evaluated the effectiveness of a single-dose oral pilocarpine administration on tear film (TF), as well as dry eye and dry mouth symptoms, in 53 eyes of 27 Sjögren syndrome (SS) patients who were experiencing dry mouth. To evaluate the changes in tear volume, a digital video-meniscometer was used to measure the radius of the lower central tear meniscus curvature (R, mm) of each eye at prior to the administration of 5 mg oral pilocarpine, and at 15 (R:(15)), 30 (R:(30)), and 60 (R:(60)) minutes after administration. The fluorescein breakup time (FBUT, seconds) and ocular and oral dryness symptoms were evaluated before and at 60 min after administration using a visual analogue scale (VAS, mm). A significant increase in R was observed at 15 and 30 min after administration compared to that at prior to administration. FBUT showed significant improvement at 60 min after administration, and the VAS score for ocular and oral dryness symptoms was found to have decreased significantly at 60 min after administration. A single-dose administration of 5 mg oral pilocarpine had a beneficial effect on TF, as well as on ocular and oral dryness symptoms, in patients with SS. Full article
(This article belongs to the Special Issue Diagnosis, Treatment and Management of Eye Diseases)
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<p>Mean visual analog scale (VAS) scores for the ocular dryness and oral dryness. Data are expressed as mean ± SD (* <span class="html-italic">p</span> &lt; 0.001, paired <span class="html-italic">t</span>-test). A <span class="html-italic">p</span>-value of &lt;0.05 is considered statistically significant.</p>
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<p>Charts illustrating the improvements of ocular dryness and oral dryness. Note: Due to rounding, percentages may not sum to 100%.</p>
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<p>Time-dependent changes in the radius of curvature of the tear meniscus after administration of single-dose oral pilocarpine. Each datapoint represents the mean ± standard error of the mean (* <span class="html-italic">p</span> = 0.0313, ** <span class="html-italic">p</span> = 0.0025, paired <span class="html-italic">t</span>-test).</p>
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<p>Correlation between Schirmer 1 test and ΔR. r: Spearman’s correlation coefficient; R: radius of the lower central tear meniscus curvature.</p>
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<p>Representative images of the central lower tear meniscus of a 49–year–old female patient (Schirmer 1 test: R 7 mm, L 8 mm; fluorescein score: R A2D2, L A2D2) obtained via meniscometry at baseline and at 15, 30, and 60 min after the administration of oral 5 mg pilocarpine.</p>
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<p>Graph showing the mean change of FBUT (in seconds) between before and at 60 min after administration of oral 5 mg pilocarpine. Data are expressed as mean ± SD (* <span class="html-italic">p</span> = 0.0002, paired <span class="html-italic">t</span>-test).</p>
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