PURPOSE: To investigate the relationship between marrow fat and cortical bone thickness in β-thalassemia and to identify key determinants influencing these variables.

STUDY TYPE: Prospective.

SUBJECTS: Thirty-five subjects in four subject groups of increasing disease severity: 6 healthy control (25.0 ± 5.3 years, 2 male), 4 β-thalassemia minor, 13 intermedia, and 12 major (29.1 ± 6.4 years, 15 male).

FIELD STRENGTH/SEQUENCE: 3.0 T, 3D fast low angle shot sequence and T1-weighted turbo spin echo.

ASSESSMENT: Analyses on proton density fat fraction (PDFF) and R2* values in femur subregions (femoral head, greater trochanter, intertrochanteric, diaphysis, distal) and cortical thickness (CBI) of the subjects' left femur. Clinical data such as age, sex, body mass index (BMI), and disease severity were also included.

STATISTICAL TESTS: One-way analysis of variance (ANOVA), mixed ANOVA, Pearson correlation and multiple regression. P-values <0.05 were considered significant.

RESULTS: Bone marrow PDFF significantly varied between the femur subregions, F(2.89,89.63) = 44.185 and disease severity, F(1,3) = 12.357. A significant interaction between subject groups and femur subregions on bone marrow PDFF was observed, F(8.67,89.63) = 3.723. Notably, a moderate positive correlation was observed between PDFF and CBI (r = 0.33-0.45). Multiple regression models for both PDFF (R2 = 0.476, F(13,151) = 10.547) and CBI (R2 = 0.477, F(13,151) = 10.580) were significant. Significant predictors for PDFF were disease severity (βTMi = 0.36, βTMa = 0.17), CBI (β = 0.24), R2* (β = -0.32), and height (β = -0.29) while for CBI, the significant determinants were sex (β = -0.27), BMI (β = 0.55), disease severity (βTMi = 2.15), and PDFF (β = 0.25).

DATA CONCLUSION: This study revealed a positive correlation between bone marrow fat fraction and cortical bone thickness in β-thalassemia with varying disease severity, potentially indicating a complex interplay between bone health and marrow composition.

METHOD: Prospective cohort study on CWE age 7-18 years old with no comorbidities. Epilepsy education was delivered using Epigame. CWE completed AKA questionnaire before (time point 1 [TP1]), immediately after (TP2), 3 months (TP3) after provision of Epigame. Child self-report Health-Related Quality of Life Measurement for Children with Epilepsy (CHEQOL-25) questionnaire was completed at TP1 and TP3.

METHODS: A systematic review on the classification and assessment techniques to measure breast ptosis was carried out based on the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias was assessed using the modified Newcastle-Ottawa scale for observational studies, whereas the Revised Cochrane risk-of-bias tool for randomized trials (RoB2) was used to evaluate randomized studies.

RESULTS: Of 2550 articles identified in the literature search, 16 observational and 2 randomized studies describing the classification and assessment techniques of breast ptosis were included in the review. A total of 2033 subjects were involved. Half of the total observational studies had a Newcastle-Ottawa scale score of 5 and above. In addition, all randomized trials recorded a low overall bias.

METHODS: In total, 154 patients (wild-type EGFR, 72 patients; Del19 mutation, 45 patients; and L858R mutation, 37 patients) were retrospectively enrolled and randomly divided into 92 training and 62 test cases. Two support vector machine (SVM) models to distinguish between wild-type and mutant EGFR (mutation [M] classification) as well as between the Del19 and L858R subtypes (subtype [S] classification) were trained using 3DBN features. These features were computed from 3DBN maps by using histogram and texture analyses. The 3DBN maps were generated using computed tomography (CT) images based on the Čech complex constructed on sets of points in the images. These points were defined by coordinates of voxels with CT values higher than several threshold values. The M classification model was built using image features and demographic parameters of sex and smoking status. The SVM models were evaluated by determining their classification accuracies. The feasibility of the 3DBN model was compared with those of conventional radiomic models based on pseudo-3D BN (p3DBN), two-dimensional BN (2DBN), and CT and wavelet-decomposition (WD) images. The validation of the model was repeated with 100 times random sampling.

RESULTS: The mean test accuracies for M classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.810, 0.733, 0.838, 0.782, and 0.799, respectively. The mean test accuracies for S classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.773, 0.694, 0.657, 0.581, and 0.696, respectively.

METHODS: The review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Literature search was conducted in Pubmed, Web of Science and Scopus database up to 23 October 2021. To evaluate risk and bias applicability, the Cochrane risk-of bias tool and GRADE was used. The review was registered under PROSPERO CRD42021265303.

RESULTS: A total of 2921 articles were identified. 104 full texts were examined and 26 studies included in systematic review. 11 studies performed on native kidneys and 15 studies on transplanted kidney. A wide range of impact factors was found that affect the accuracy of SWE of renal fibrosis in adult patients.

CONCLUSIONS: Compared to point SWE, two-dimensional SWE with elastogram could enable better selection of the region of interest in kidneys, leading to reproducible results. Tracking waves were attenuated as the depth from skin to region of interest increased, therefore, SWE is not recommended for overweight or obese patients. Variable transducer forces might also affect SWE reproducibility, thus, training of operators to ensure consistent operator-dependent transducer forces may be helpful.

METHODS: Staff members of a teaching hospital medical imaging department were invited to complete the generic short version of the Safety Attitude Questionnaire (SAQ). Internal consistency and reliability were evaluated using Cronbach's α. Confirmatory factor analysis (CFA) was conducted to examine model fit. A cut-off of 60% was used to define the percentage positive responses (PPR). PPR values were compared between occupational groups.

RESULTS: A total of 300 complete responses were received and the response rate was 75.4%. In reliability analysis, the Cronbach's α for the original 32-item SAQ was 0.941. Six subscales did not demonstrate good fit with CFA. A modified five-subscale, 22-item model (SAQ-MI) showed better fit (goodness-to-fit index ≥0.9, comparative fit index ≥ 0.9, Tucker-Lewis index ≥0.9 and root mean square error of approximation ≤0.08). The Cronbach's α for the 22 items was 0.921. The final five subscales were safety and teamwork climate, job satisfaction, stress recognition, perception of management and working condition, with PPR of 62%, 68%, 57%, 61% and 60%, respectively. Statistically significant differences in PPR were observed between radiographers, doctors and others occupational groups.

METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation.

RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM.