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Purpose The United States Medical Licensing Examination (USMLE) is an examination series required for allopathic physician licensure in the United States (US). USMLE content is created and maintained by the National Board of Medical Examinations (NBME). The specialty composition of the USMLE and NBME taskforce members involved in the creation of examination content is currently unknown. Methods Using the 2021 USMLE and 2021 NBME Committees and Task Forces documents, we determined each member’s board-certified primary specialty and involvement in test material development committees who we dubbed “test writers”. Total active physicians by primary specialty were recorded from the 2020 Physician Specialty Data Report published by the Association of American Medical Colleges (AAMC). Descriptive statistics and chi-square analysis were used to analyze the cohorts. Results The USMLE and NBME test writer primary specialty composition was found to be significantly different compared to the US active physician population (USMLE χ 2 [32] = 172, p  < .001 and NBME χ 2 [32] = 200, p  < .001). Only nineteen specialties were represented within USMLE test writers, with three specialties being proportionally represented. Two specialties were represented within NBME test writers. Obstetrics and Gynecology physicians were proportionally represented in USMLE but not within NBME test writers. Internal Medicine (IM) accounts for the largest percentage of all USMLE test writers (60/197, 30%) with an excess representation of 31 individuals. Conclusions There is an imbalance in the specialty representation of USMLE and NBME test writers compared to the US active physician population. These findings may have implications for the unbiased and accurate portrayal of topics in such national examinations; thus, future investigation is warranted.

Purpose The value of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)-positron emission tomography (PET)-radiomics in the outcome assessment of patients with recurrent glioblastoma (rGBM) has not been evaluated until now. The aim of this study was to evaluate whether a prognostic model based on FET-PET radiomics features (RF) is feasible and can identify rGBM patients that would most benefit from re-irradiation. Methods We prospectively recruited rGBM patients who underwent FET-PET before re-irradiation (GLIAA-Pilot trial, DRKS00000633). Tumor volume was delineated using a semi-automatic method with a threshold of 1.8 times the standardized-uptake-value of the background. 135 FET-RF (histogram parameters, shape and texture features) were extracted. The analysis involved the characterization of tumor and non-tumor tissue with FET-RF and the evaluation of the prognostic value of FET-RF for time-to-progression (TTP), overall survival (OS) and recurrence location (RL). Results Thirty-two rGBM patients constituted our cohort. FET-RF discriminated significantly between tumor and non-tumor. The texture feature Small-Zone-Low-Gray-Level-Emphasis (SZLGE) showed the best performance for the prediction of TTP ( p  = 0.001, satisfying Bonferroni-multiple-test significance level). Additionally, two radiomics signatures could predict TTP (TTP-radiomics-signature, p  = 0.001) and OS (OS-radiomics-signature, p  = 0.038). SZLGE and the TTP-radiomics-signature additionally predicted RL. Specifically, high values for TTP-radiomics-signature and for SZLGE indicated not only earlier progression, but also a RL within the initial FET-PET active volume. Conclusion Our findings suggest that FET-PET radiomics could contribute to the prognostic assessment and selection of rGBM-patients benefiting from re-irradiation. Trial registration DRKS00000633. Registered on 8th of December in 2010. https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00000633 .

Prior studies suggest lymphopenia, systemic immune-inflammatory index, and tumor response all impact clinical outcomes in Stage III NSCLC. We hypothesized that tumor response after CRT would be associated with hematologic metrics and might predict clinical outcomes. Patients with stage III NSCLC treated at a single institution between 2011 and 2018 were retrospectively reviewed. Pre-treatment gross tumor volume (GTV) was recorded then reassessed at 1-4 months post-CRT. Complete blood counts before, during and after treatment were recorded. Systemic immune-inflammation index (SII) was defined as neutrophil × platelet/lymphocyte. Overall survival (OS) and progression free survival (PFS) were calculated using Kaplan-Meier estimates, and compared with Wilcoxon tests. A multivariate analysis of hematologic factors impacting restricted mean survival was then performed using pseudovalue regression, accounting for other baseline factors. 106 patients were included. After median follow-up of 24 months, median PFS and OS were 16 and 40 months, respectively. Within the multivariate model, baseline SII was associated with OS (p = 0.046) but not PFS (p = 0.09), and baseline ALC correlated with both PFS and OS (p = 0.03 and p = 0.02, respectively). Nadir ALC, nadir SII, and recovery SII were not associated with PFS or OS. In this cohort of patients with stage III NSCLC, baseline hematologic factors were associated with clinical outcomes including baseline ALC, baseline SII and recovery ALC. Disease response was not well correlated with hematologic factors or clinical outcomes.

Objective In this study we examined the correlation between standardized uptake value (SUV) of [ 18 F]fluorodeoxyglucose (FDG) and apparent diffusion coefficient (ADC) within the gross tumor volume (GTV) of patients with head and neck squamous cell carcinoma (HNSCC). In addition, we assessed the comparability of cell density ( ρ ) estimates obtained from FDG PET and MRI data. Methods Twenty-one HNSCC patients from a prospective FMISO imaging trial underwent pre-treatment PET/CT and MRI. We assessed correlations between FDG SUV (mean, max) and ADC (mean, min) within the GTV using Pearson’s correlation coefficient. The tumor cell density within the GTV was calculated from FDG SUV and from ADC maps. For the estimation of ADC-based cell density, we used a published tumor cell volume fraction ( v TC ). Agreement between FDG- and ADC-derived cell density estimates was assessed. The best-fitting v TC * was computed to achieve equal mean ρ ADC and ρ FDG for each patient and was compared to the literature. Results The SUV and ADC metrics showed up to moderate negative correlations, but none of them were statistically significant at p  < 0.05. The correlation of SUV mean vs. ADC mean with Pearson’s correlation coefficient r  = −0.426 and p  = 0.054 and SUV max vs. ADC min with r  = −0.414 and p  = 0.062 suggested a weak negative trend. The average and standard deviation of mean ρ FDG and ρ ADC across our cohort were (1.8 ± 0.6) × 10 8 cells/ml and (3.3 ± 0.2) × 10 8 cells/ml. The difference between the mean ρ FDG and ρ ADC was statistically significant ( p  < 0.001). To achieve equal mean ρ ADC and ρ FDG for each patient, the mean optimal v TC * with standard deviation was 0.29 ± 0.09. Although significantly lower than the published mean v TC ​ (0.54), v TC * lies within the published range of v TC for HNSCCs (0.28 to 0.75). Conclusion ADC and SUV metrics exhibited moderate but marginally insignificant correlation in this dataset. Although not directly interchangeable, the two methods provide comparable, clinically relevant cell density estimates, offering flexibility to use the most accessible modality for individualized treatment planning. Trial registration Registered at German Clinical Trials Register on 20/08/2015 (DRKS00003830).

BackgroundThe recent phase III VISION-trial confirms the treatment efficacy of radioligand therapy with [177Lu]PSMA-617 (PSMA-RLT) in metastatic castration-resistant prostate cancer (mCRPC). In PSMA-RLT, the relatively low absorbed bone marrow dose allows for multiple therapy cycles with relatively low risk of haematological adverse events (hAE). However, as disease progression itself may be a cause of bone marrow impairment, the aim of this study was to assess potential relations between impairment of haematological status and response to PSMA-RLT.MethodsIn this retrospective analysis, haematological parameters (HP) of 64 patients with mCRPC were systematically acquired over two cycles (12–16 weeks) of PSMA-RLT from baseline to restaging. Changes in HP were analysed qualitatively (CTCAE 5.0) and quantitatively. The HP changes from baseline were compared to quantitative and qualitative biochemical and imaging response, using PCWG3 and PROMISE criteria.ResultsAll grade 3/4 hAE observed were associated with disseminated or diffuse bone involvement as well as biochemical non-response at restaging. Quantitatively, at baseline, HP inversely correlated with biochemical and volumetric (on PET) tumour burden as well as bone involvement pattern (p ≤ 0.043). Among patients with disseminated or diffuse bone involvement, percentage changes in HP (%HP) at restaging inversely correlated with serological and imaging tumour burden (p ≤ 0.017). Biochemical non-responders showed a significant decrease in %HP (p ≤ 0.001) while HP in biochemical responders remained stable (p ≥ 0.079).ConclusionDuring early cycles of PSMA-RLT, qualitative and quantitative bone marrow impairment appears to be closely associated with osseous tumour burden as only patients with advanced bone involvement and non-response to therapy exhibited high-grade haematological adverse events, showing a significant decline of haematological parameters. This implies that in patients with advanced mCRPC, non-response to PSMA-RLT may be a major cause of bone marrow impairment during early treatment cycles.German Clinical Trial Register DRKS00013665. Registered 28 December 2017, retrospectively registered (www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00013665)

There is a paucity of formalized exposure to Radiation Oncology (RO) for preclinical medical students across the United States as well as barriers to implementation within undergraduate medical education curriculum at many institutions. We present a novel approach to implementing an introductory RO didactic lecture to second-year medical students by interweaving associated oncological and ionizing radiation content represented on the United States Medical Licensing Exam® (USMLE®) Step 1 examination. Students had synchronous and asynchronous opportunities to engage with the 1.0-h didactic lecture administered by an attending Radiation Oncologist faculty member. Students were electronically invited to anonymously rank the effectiveness of the lecture materials on a 5-point Likert scale. Performance on standardized board-style questions regarding radiation biology and radiation side effects was recorded before and after the lecture and compared to the historic performance of previous institutional second-year medical student cohorts. The lecture material effectiveness received a mean score of 4.50 on a 5-point Likert scale. There was a statistically significant improvement in student performance on a board-style radiation side effect question from 39% on a pretest to 76% on a posttest. A USMLE® topic-based approach may be an effective way to implement a formalized introduction to RO to preclinical medical students while simultaneously improving performance on relevant standardized board-style questions. Providing evidence that RO topics appear on the USMLE® Step 1 examination curriculum was a powerful incentive for implementation when negotiating with curriculum offices.

Radiation therapy (RT) is a critical component of multidisciplinary cancer care, but has inconsistent curricular exposure. We characterize the radiation oncology (RO) content on the standardized undergraduate medical examinations by comparing its context and prevalence with other domains in oncology. National Board of Medical Examiners (NBME) self-assessments and sample questions for the United States Medical Licensing Exam (USMLE) Steps 1–3 and NBME clinical science shelf examinations were accessed ( n  = 3878). Questions were inductively analyzed for content pertaining to oncology and treatment modalities of RT, systemic therapy (ST), and surgical intervention (SI). Questions were coded using USMLE Physician Tasks/Competencies and thematic analysis. Descriptive statistics and analyses using the Kruskal–Wallis test are reported. A total of 337 questions (8.6%) within the USMLE and shelf exams included oncology content, with 101 questions (2.6%) referencing at least one cancer treatment modality ( n  = 35 RT, 45 ST, 57 SI). Treatment questions were more common on USMLE Step 2 CK ( n  = 35/101, 32%) compared to Step 1 ( n  = 23/101, 23%) and Step 3 ( n  = 8/101, 8%) ( p  < 0.001). RT was significantly less likely to be the correct answer (2/35, 6%) compared to ST (4/45, 9%) and SI (18/57, 32%) ( p  = 0.003). Therapeutic oncology questions are uncommon on the examination material, with an under-representation of radiation-related content, and contextual bias favoring surgical approaches. We advocate for greater RO involvement in the content creation of such examinations to help trainees better understand multidisciplinary cancer care.

INTRODUCTION We investigated whether age of patients with Alzheimer‘s disease (AD) at first visit to a memory clinic predicts biomarker findings along the amyloid beta deposition, pathologic tau, and neurodegeneration (ATN) scheme and moderates the association between ATN biomarkers and cognition. METHODS We evaluated [11C]Pittsburgh compound B positron emission tomography (PET), florzolotau (18F) PET, [18F]fluorodeoxyglucose PET, T1‐weighted magnetic resonance imaging, and cognitive assessments (N = 190/63/252/687/2198) of a total of 2355 AD patients. We assessed direct and moderating effects of age. RESULTS Tau burden and hypometabolism were more severe in younger AD patients. Gray matter volume of the medial temporal lobe (MTL) was reduced to a greater extent in older patients. Relationships between different imaging modalities or between single imaging modalities and cognition were not moderated by age. DISCUSSION In contrast to more severe tau burden and hypometabolism in younger patients, MTL atrophy was more pronounced in older patients. Relationships between markers of pathology and those of neurodegeneration were not associated with age. Highlights Amyloid beta load as a biomarker of pathology burden was not associated with age at first visit to a memory clinic. Tau burden was higher, and glucose metabolism was lower in younger Alzheimer's disease (AD) patients. By contrast, medial temporal lobe atrophy was less severe in younger AD patients. Younger AD patients showed more severe memory deficits with respect to age‐appropriate normative data. Age had no moderating effect on relationships between different imaging variables or between single imaging variables and cognition.

Purpose Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of radiation oncology, significantly advancing the precision of contouring practices. However, the adaptability of these algorithms across diverse scanners, institutions, and imaging protocols remains a considerable obstacle. This study aims to investigate the effects of incorporating institution-specific datasets into the training regimen of CNNs to assess their generalization ability in real-world clinical environments. Focusing on a data-centric analysis, the influence of varying multi- and single center training approaches on algorithm performance is conducted. Methods nnU-Net is trained using a dataset comprising 161 18 F-PSMA-1007 PET images collected from four distinct institutions (Freiburg: n = 96, Munich: n = 19, Cyprus: n = 32, Dresden: n = 14). The dataset is partitioned such that data from each center are systematically excluded from training and used solely for testing to assess the model's generalizability and adaptability to data from unfamiliar sources. Performance is compared through a 5-Fold Cross-Validation, providing a detailed comparison between models trained on datasets from single centers to those trained on aggregated multi-center datasets. Dice Similarity Score, Hausdorff distance and volumetric analysis are used as primary evaluation metrics. Results The mixed training approach yielded a median DSC of 0.76 (IQR: 0.64–0.84) in a five-fold cross-validation, showing no significant differences (p = 0.18) compared to models trained with data exclusion from each center, which performed with a median DSC of 0.74 (IQR: 0.56–0.86). Significant performance improvements regarding multi-center training were observed for the Dresden cohort (multi-center median DSC 0.71, IQR: 0.58–0.80 vs. single-center 0.68, IQR: 0.50–0.80, p < 0.001) and Cyprus cohort (multi-center 0.74, IQR: 0.62–0.83 vs. single-center 0.72, IQR: 0.54–0.82, p < 0.01). While Munich and Freiburg also showed performance improvements with multi-center training, results showed no statistical significance (Munich: multi-center DSC 0.74, IQR: 0.60–0.80 vs. single-center 0.72, IQR: 0.59–0.82, p > 0.05; Freiburg: multi-center 0.78, IQR: 0.53–0.87 vs. single-center 0.71, IQR: 0.53–0.83, p = 0.23). Conclusion CNNs trained for auto contouring intraprostatic GTV in 18 F-PSMA-1007 PET on a diverse dataset from multiple centers mostly generalize well to unseen data from other centers. Training on a multicentric dataset can improve performance compared to training exclusively with a single-center dataset regarding intraprostatic 18 F-PSMA-1007 PET GTV segmentation. The segmentation performance of the same CNN can vary depending on the dataset employed for training and testing.

Positron-emission tomography (PET) has improved identification of the primary tumor as well as occult nodal burden in cancer of the head and neck. Nevertheless, there are still patients where the primary tumor cannot be located. In these situations, the standard of care is comprehensive head and neck radiation therapy however it is unclear whether this is necessary. This study examines the effects of radiation treatment volume on outcomes among using data from two cancer centers in unknown primary carcinoma of the head and neck. Patients received unilateral (n = 34), or bilateral radiation (n = 28). Patient factors such as age, gender, smoking history, and patterns of failure were compared using Mann Whitney U and Chi Square. Overall survival (OS) and disease free survival (DFS) trends were estimated using Kaplan-Meier survival curves. Effect of treatment volume on survival was examined using multivariate cox proportional hazard regression model. No significant differences were observed in the frequency of local (p = 0.32), regional (p = 0.50), or distant (p = 0.76) failures between unilateral and bilateral radiation therapy. By Kaplan-Meier estimates, OS (3-year OS bilateral = 71.67%, unilateral = 77.90%, p = 0.50) and DFS (3-year DFS bilateral = 77.92%, unilateral = 69.43%, p = 0.63) were similar between the two treatment approaches. Lastly, multivariate analysis did not demonstrate any significant differences in outcome by treatment volumes (OS: HR = 0.74, 95% CI: 0.31, 1.81, p = 0.51; DFS: HR: 0.68, 95% CI: 0.24, 1.93, p = 0.47). Unilateral radiation therapy compared with bilateral produced similar survival.