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Objective. The accuracy of material decomposition in spectral computed tomography (CT) depends on the information quality captured in image acquisition, a factor that cannot be adequately assessed using conventional image quality metrologies due to the multi-energy nature of spectral CT. This work used metrologies specific to spectral CT to evaluate the impact of acquisition conditions on the quality of spectral CT images and accuracy of material decomposition techniques. Approach. Computational phantoms were created with cylindrical shapes and variable sizes (20–40 cm), containing inserts of iodine and gadolinium (1–8 mg ml−1). The phantoms were imaged using a validated CT simulator modeling a clinical photon-counting CT scanner. The acquisitions were done at different detector energy thresholds (50–90 keV) and tube currents (25–250 mAs). The images were used to develop and train a data-driven material identification and quantification algorithm. Two spectral metrologies, multivariate contrast-to-noise ratio (CNR) and separability index, were used to characterize the impact of energy threshold, tube current, phantom size, and material concentration on signal quality. The results were interpreted in terms of figures of merit of accuracy for classification and mean absolute error (MAE) and root mean squared error (RMSE) for regression. Main results. Signal quality for iodine and gadolinium was maximized with a low energy threshold, high tube current, and small phantom size. While conventional CNR terms predicted variable image quality for two-thirds of all conditions, multivariate CNR was above 10 for half of those. Separability index showed that for a phantom size greater than 30 cm, a minimum of 75–110 mAs is required to separate 2 mg ml−1 of iodine and gadolinium. For both classification and regression tasks, a random forest model with a local statistics dataset provided the best performance. Across conditions, classification performance was 0.66–0.99 for I accuracy, 0.72–0.99 for Gd accuracy. Regression performance was 0.02–0.91 mg ml−1 I and 0.02–0.59 mg ml−1 Gd for MAE and 0.11–1.08 mg ml−1 I and 0.07-0.76 mg ml−1 Gd for RMSE. Significance. Multivariate CNR and separability index metrologies can predict material decomposition performance. Theses metrics demonstrated that the decomposition of iodine and gadolinium have higher separability when the acquisition is done at a lower energy threshold, with a higher tube current, and when the imaged object has a smaller size. Object size had the largest impact on metrics and decomposition performance. [ABSTRACT FROM AUTHOR]

Introduction.: Given the impetus to improve accessibility for diverse learners seeking physical therapist education, it is critical that all entry points to access information have minimal barriers. This study identified Web site accessibility barriers among Doctor of Physical Therapy (DPT) programs in the United States. Review of Literature.: Web site accessibility has been evaluated among many institutions of higher education, but none focused on DPT education. Individuals with disabilities may be adversely affected by Web site accessibility barriers. Subjects.: This cross-sectional study included 262 DPT programs in the United States. Doctor of Physical Therapy program characteristics collected were geographic region, institutional control type (public/private), medical school affiliation, accreditation status, total institutional enrollment, and DPT class size. Methods.: The Web Accessibility Evaluation (WAVE) Tool assessed data related to accessibility barriers among DPT program homepage Uniform Resource Locators. Three primary outcomes from the WAVE Tool included WAVE Total Errors, Error Density, and Total Alerts. Results.: Web site homepage accessibility barriers varied among programs for WAVE Total Errors (range 0–150), Error Density (range 0–14.6%), and Total Alerts (range 1–331). Median Total Errors were greater among private (9.0) versus public (5.0) institution Web sites (P <.001). Median Total Errors were greater among those institutions not affiliated with a medical school (9.0) compared with those that had an affiliated medical school (7.0) (P =.04). No differences in accessibility barriers were identified according to geographic region or accreditation status (P >.05). Median Total Errors were significantly different between institutional enrollment quartiles (H[3] = 17.9, P <.001), with no differences noted between DPT class size quartiles for any outcome (P >.05). Generally, weak–fair inverse correlations were observed between student enrollment for the institution and Web site accessibility barrier outcomes. Discussion and Conclusion.: Homepage accessibility barriers varied greatly among DPT programs in the United States. Factors, including being a private institution, no medical school affiliation, and lower institutional enrollment, were related to increased accessibility barriers. [ABSTRACT FROM AUTHOR]

Background: Pathology grading is an essential step for the treatment and evaluation of the prognosis in patients with clear cell renal cell carcinoma (ccRCC). Purpose: To investigate the utility of texture analysis in evaluating Fuhrman grades of renal tumors in patients with Von Hippel–Lindau (VHL)‐associated ccRCC, aiming to improve non‐invasive diagnosis and personalized treatment. Study Type: Retrospective analysis of a prospectively maintained cohort. Population: One hundred and thirty‐six patients, 84 (61%) males and 52 (39%) females with pathology‐proven ccRCC with a mean age of 52.8 ± 12.7 from 2010 to 2023. Field Strength and Sequences: 1.5 and 3 T MRIs. Segmentations were performed on the T1‐weighted 3‐minute delayed sequence and then registered on pre‐contrast, T1‐weighted arterial and venous sequences. Assessment: A total of 404 lesions, 345 low‐grade tumors, and 59 high‐grade tumors were segmented using ITK‐SNAP on a T1‐weighted 3‐minute delayed sequence of MRI. Radiomics features were extracted from pre‐contrast, T1‐weighted arterial, venous, and delayed post‐contrast sequences. Preprocessing techniques were employed to address class imbalances. Features were then rescaled to normalize the numeric values. We developed a stacked model combining random forest and XGBoost to assess tumor grades using radiomics signatures. Statistical Tests: The model's performance was evaluated using positive predictive value (PPV), sensitivity, F1 score, area under the curve of receiver operating characteristic curve, and Matthews correlation coefficient. Using Monte Carlo technique, the average performance of 100 benchmarks of 85% train and 15% test was reported. Results: The best model displayed an accuracy of 0.79. For low‐grade tumor detection, a sensitivity of 0.79, a PPV of 0.95, and an F1 score of 0.86 were obtained. For high‐grade tumor detection, a sensitivity of 0.78, PPV of 0.39, and F1 score of 0.52 were reported. Data Conclusion: Radiomics analysis shows promise in classifying pathology grades non‐invasively for patients with VHL‐associated ccRCC, potentially leading to better diagnosis and personalized treatment. Level of Evidence: 1 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

To determine which methods of assessment of splenic size most accurately represent the actual spleen volume in patients with Chronic Lymphocytic Leukemia (CLL). The Abdominal Computed Tomography images of 48 patients with CLL enrolled on a phase 2 clinical trial at two time-points before and after 2-months of continuous acalabrutinib treatment were analyzed. Linear one-dimensional measurements of the spleen were taken in different planes. Two-dimensional and three-dimensional measurements were calculated from the linear measurements using mathematical formulae. The spleen volume was determined by manual segmentation as the ground truth. Data derived were analyzed using Pearson correlation and statistical significance was set at p < 0.05. Among the single-dimensional measurements, the strongest correlation with the segmented splenic volume was the sagittal long axis diameter (LAD) (r = 0.89, p < 0.05), followed closely by Coronal LAD (r = 0.87, p < 0.05) and cephalocaudal length (iwCLL) (r = 0.84, p < 0.05). For the two-dimensional indices, the sum of LAD and short axis diameter (SAD) of the spleen in axial plane showed good correlation with the splenic volume (r = 0.77, p < 0.05). Among the three-dimensional indices, the splenic index (0.523 x axial LAD x axial SAD x coronal height) and a formula for volume (30 + 0.58 x axial LAD x axial SAD x coronal height) had the strongest correlation (both r = 0.92, p < 0.05) with the spleen volume. The three-dimensional formulae showed the strongest correlation with volumetric reference spleen measurement. Among unidimensional measurements, the sagittal LAD had the best correlation with the actual splenic volume. The two-dimensional calculation methods were less reliable. [ABSTRACT FROM AUTHOR]