Low thigh muscle strength in relation to myosteatosis in patients with type 2 diabetes mellitus.

This study aimed to investigate the association of thigh muscle fat infiltration by quantitative MRI with muscle strength in patients with type 2 diabetes mellitus (T2DM). Seventy T2DM patients and sixty control subjects (71 males; age: 52 ± 8 years) underwent 3.0T MRI and isokinetic muscle strength measurements to obtain the skeletal muscle index (SMI), intermuscular adipose tissue (IMAT) proton density fat fraction (PDFF), intramuscular fat (IMF) PDFF, peak torque (PT) and total work (TW) of knee extensors and flexors. The differences of measurements between T2DM patients and asymptomatic volunteers were compared. Multivariate regression analysis was used to determine significant predictors of thigh extension and flexion strength. The SMI, IMAT and IMF PDFF of thigh muscles in T2DM patients were higher than that in the control group (p < 0.001), while PT and TW were lower than those in the control subjects (p < 0.05). Both IMF and IMAT PDFF were negatively correlated with PT, TW in participants with T2DM (extensors: r = - 0.72, - 0.70, p < 0.001; r = - 0.62, - 0.56, p < 0.05. flexors: r = - 0.37, - 0.43, p < 0.05; r = - 0.39, - 0.46, p < 0.05). Moderate and strong correlations between HOMA-IR and muscle strength measurements, muscle PDFFs were observed in extensors and flexors. IMF PDFF and age were the statistically significant predictor of PT and TW of extensors of thigh in multivariate regression analysis. Therefore, the thigh muscle PDFF increased was associated with muscle strength decreased in T2DM patients beyond SMI. Age are also important factors influencing thigh muscle PDFF and strength in T2DM patients.

CT-based radiomics signature of visceral adipose tissue for prediction of disease progression in patients with Crohn's disease: A multicentre cohort study.

Background: Visceral adipose tissue (VAT) is involved in the pathogenesis of Crohn's disease (CD). However, data describing its effects on CD progression remain scarce. We developed and validated a VAT-radiomics model (RM) using computed tomography (CT) images to predict disease progression in patients with CD and compared it with a subcutaneous adipose tissue (SAT)-RM. Methods: This retrospective study included 256 patients with CD (training, n = 156; test, n = 100) who underwent baseline CT examinations from June 19, 2015 to June 14, 2020 at three tertiary referral centres (The First Affiliated Hospital of Sun Yat-Sen University, The First Affiliated Hospital of Shantou University Medical College, and The First People's Hospital of Foshan City) in China. Disease progression referred to the development of penetrating or stricturing diseases or the requirement for CD-related surgeries during follow-up. A total of 1130 radiomics features were extracted from VAT on CT in the training cohort, and a machine-learning-based VAT-RM was developed to predict disease progression using selected reproducible features and validated in an external test cohort. Using the same modeling methodology, a SAT-RM was developed and compared with the VAT-RM. Findings: The VAT-RM exhibited satisfactory performance for predicting disease progression in total test cohort (the area under the ROC curve [AUC] = 0.850, 95% confidence Interval [CI] 0.764-0.913, P < 0.001) and in test cohorts 1 (AUC = 0.820, 95% CI 0.687-0.914, P < 0.001) and 2 (AUC = 0.871, 95% CI 0.744-0.949, P < 0.001). No significant differences in AUC were observed between test cohorts 1 and 2 (P = 0.673), suggesting considerable efficacy and robustness of the VAT-RM. In the total test cohort, the AUC of the VAT-RM for predicting disease progression was higher than that of SAT-RM (AUC = 0.786, 95% CI 0.692-0.861, P < 0.001). On multivariate Cox regression analysis, the VAT-RM (hazard ratio [HR] = 9.285, P = 0.005) was the most important independent predictor, followed by the SAT-RM (HR = 3.280, P = 0.060). Decision curve analysis further confirmed the better net benefit of the VAT-RM than the SAT-RM. Moreover, the SAT-RM failed to significantly improve predictive efficacy after it was added to the VAT-RM (integrated discrimination improvement = 0.031, P = 0.102). Interpretation: Our results suggest that VAT is an important determinant of disease progression in patients with CD. Our VAT-RM allows the accurate identification of high-risk patients prone to disease progression and offers notable advantages over SAT-RM. Funding: This study was supported by the National Natural Science Foundation of China, Guangdong Basic and Applied Basic Research Foundation, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Nature Science Foundation of Shenzhen, and Young S&T Talent Training Program of Guangdong Provincial Association for S&T. Translation: For the Chinese translation of the abstract see Supplementary Materials section.