Pottsbentsen1771

To develop a 3D U-Net-based deep learning model for automated segmentation of kidney and renal mass, and detection of renal mass in corticomedullary phase of computed tomography urography (CTU).

Data on 882 kidneys obtained from CTU data of 441 patients with renal mass were used to learn and evaluate the deep learning model. The CTU data of 35 patients with small renal tumors (diameter ≤ 1.5 cm) were used for additional testing. The ground truth data for the kidney, renal tumor, and cyst were manually annotated on corticomedullary phase images of CTU. AZD1080 purchase The proposed segmentation model for kidney and renal mass was constructed based on a 3D U-Net. The segmentation accuracy was evaluated through the Dice similarity coefficient (DSC). The volume of the maximum 3D volume of interest of renal tumor and cyst in the predicted segmentation by the model was used as an identification indicator, while the detection performance of the model was evaluated by the area under the receiver operation characteristic curve.

lanning, etc.

• The segmentation model based on 3D U-Net showed high accuracy in segmentation of kidney and renal neoplasm, and good detection performance of renal neoplasm and cyst in corticomedullary phase of CTU. • The segmentation model based on 3D U-Net is a fully automated aided diagnostic tool that could be used to reduce the workload of radiologists and improve the accuracy of diagnosis. • The segmentation model based on 3D U-Net would be helpful to provide quantitative information for diagnosis, treatment, surgical planning, etc.

To develop a radiomics model using preoperative multiphasic CT for predicting distant metastasis after surgical resection in patients with localized clear cell renal cell carcinoma (ccRCC) and to identify key biological pathways underlying the predictive radiomics features using RNA sequencing data.

In this multi-institutional retrospective study, a CT radiomics metastasis score (RMS) was developed from a radiomics analysis cohort (n = 184) for distant metastasis prediction. Using a gene expression analysis cohort (n = 326), radiomics-associated gene modules were identified. Based on a radiogenomics discovery cohort (n = 42), key biological pathways were enriched from the gene modules. Furthermore, a multigene signature associated with RMS was constructed and validated on an independent radiogenomics validation cohort (n = 37).

The 9-feature-based RMS predicted distant metastasis with an AUC of 0.861 in validation set and was independent with clinical factors (p < 0.001). A gene module comprising 114th radiomics metastasis score predicted distant metastasis in localized ccRCC.

• Radiomics features from primary tumor in preoperative CT predicted distant metastasis after surgical resection in patients with localized ccRCC. • CT radiomics features predictive of distant metastasis were associated with key signaling pathways related to tumor progression and metastasis. • Gene signature associated with radiomics metastasis score predicted distant metastasis in localized ccRCC.

Sacral stress fractures are rare complications which can arise during pregnancy or in the early postpartum period. We report a case and discuss the findings of a confirmed postpartum sacral stress fracture in a 39-year-old multiparous woman and review previous case reports in the literature of sacral stress fracture related to pregnancy.

A review of the literature was conducted to examine the main characteristics of sacral stress fractures related to pregnancy. The Ovid/Medline, Embase and Google Scholar databases were searched with the inclusion criteria human studies, English language, intrapartum, postpartum (within 6months of parturition), sacrum and stress fracture. Our exclusion criteria included pubic fractures, vertebral fractures and non-English articles. The search terms included "stress fracture", "postpartum", "pregnancy", "atraumatic" and the wildcard "sacr*". Thirty-four cases were found and summarised in Table 2.

A total of 65% of patients had onset of symptoms postpartum. Most patients dvative management often produces good clinical outcomes.This study estimates causality of physical activity (PA) on bone mineral density (BMD) by conducting multivariable Mendelian randomization (MR). The findings suggest that habitual vigorous PA increases lumbar spine BMD, and higher overall acceleration average would improve forearm BMD. The results could promote PA intervention targeting individuals with optimized type.

Evidence from epidemiologic studies showed type, frequency, and duration of PA influenced BMD. However, these observational studies may be confounded by many factors, resulting in spurious associations. We aimed to conduct multivariable MR to estimate the causal effect of self-reported and device-measured PA on osteoporosis.

Three self-reported and two device-measured PA-related traits were selected as exposures. Outcomes were BMD at different skeletal sites femoral neck BMD (FN BMD), lumbar spine BMD (LS BMD), and forearm BMD (FA BMD). Exposure datasets were obtained from UK Biobank with total 377,234 subjects. Outcome datasets were obtained from GEFOS consortium with 53,236 subjects. Standard MR analysis and multivariable MR were conducted to assess the total and direct causal effect of PA on BMD.

For self-reported PA, inverse-normalized moderate-to-vigorous had a direct causal effect on FN BMD independently (β = - 1.116 (95% confidence interval, 95%CI - 2.210, - 0.023), P = 0.045); vigorous PA showed a direct effect (β = 3.592 (95%CI 0.310, 6.874), P = 0.032) on LS BMD independently. While overall acceleration average and fraction of accelerations both had a direct causal effect on FA BMD independently.

Habitual vigorous PA could increase LS BMD. Individuals with higher overall acceleration average would have a higher FA BMD.

Habitual vigorous PA could increase LS BMD. Individuals with higher overall acceleration average would have a higher FA BMD.

We examined changes in plasma creatine kinase (CK) activity, hydroxyproline and cell-free DNA (cfDNA) concentrations in relation to changes in maximum voluntary isometric contraction (MVIC) torque and delayed-onset muscle soreness (DOMS) following a session of volume-matched higher- (HI) versus lower-intensity (LI) eccentric cycling exercise.

Healthy young men performed either 5 × 1-min HI at 20% of peak power output (n = 11) or 5 × 4-min LI eccentric cycling at 5% of peak power output (n = 9). Changes in knee extensor MVIC torque, DOMS, plasma CK activity, and hydroxyproline and cfDNA concentrations before, immediately after, and 24-72h post-exercise were compared between groups.

Plasma CK activity increased post-exercise (141 ± 73.5%) and MVIC torque decreased from immediately (13.3 ± 7.8%) to 48h (6.7 ± 13.5%) post-exercise (P < 0.05), without significant differences between groups. DOMS was greater after HI (peak 4.5 ± 3.0 on a 10-point scale) than LI (1.2 ± 1.0). Hydroxyproline concentration increased 40-53% at 24-72h after both LI and HI (P < 0.