Search

PURPOSE: To develop a deep learning algorithm capable of extracting pectoralis muscle and adipose measurements and to longitudinally investigate associations between these measurements and incident heart failure (HF) in participants from the Multi-Ethnic Study of Atherosclerosis (MESA). MATERIALS AND METHODS: MESA is a prospective study of subclinical cardiovascular disease characteristics and risk factors for progression to clinically overt disease approved by institutional review boards of six participating centers (ClinicalTrials.gov identifier: NCT00005487). All participants with adequate imaging and clinical data from the fifth examination of MESA were included in this study. Hence, in this secondary analysis, manual segmentations of 600 chest CT examinations (between the years 2010 and 2012) were used to train and validate a convolutional neural network, which subsequently extracted pectoralis muscle and adipose (intermuscular adipose tissue (IMAT), perimuscular adipose tissue (PAT), extramyocellular lipids and subcutaneous adipose tissue) area measurements from 3031 CT examinations using individualized thresholds for adipose segmentation. Next, 1781 participants without baseline HF were longitudinally investigated for associations between baseline pectoralis muscle and adipose measurements and incident HF using crude and adjusted Cox proportional hazards models. The full models were adjusted for variables in categories of demographic (age, race, sex, income), clinical/laboratory (including physical activity, BMI, and smoking), CT (coronary artery calcium score), and cardiac MRI (left ventricular ejection fraction and mass (% of predicted)) data. RESULTS: In 1781 participants (median age, 68 (IQR,61, 75) years; 907 [51%] females), 41 incident HF events occurred over a median 6.5-year follow-up. IMAT predicted incident HF in unadjusted (hazard ratio [HR]:1.14; 95% CI: 1.03-1.26) and fully adjusted (HR:1.16, 95% CI: 1.03-1.31) models. PAT also predicted incident HF in crude (HR:1.19; 95% CI: 1.06-1.35) and fully adjusted (HR:1.25; 95% CI: 1.07-1.46) models. CONCLUSION: The study demonstrates that fast and reliable deep learning-derived pectoralis muscle and adipose measurements are obtainable from conventional chest CT, which may be predictive of incident HF.©RSNA, 2023.

PURPOSE: To assess the perception of equity and respect in the workplace and within the SSR. We hypothesized that responses would differ by gender and minorities underrepresented in medicine (URiM) status. METHODS: An electronic survey was sent to 1,531 SSR members between January 2020 and March 2020 to determine perception of equity and respect. Descriptive statistics were calculated, and analysis of differences in response by gender/minority status was performed using the Fishers exact test. The study was exempt from IRB approval. RESULTS: There were 176 responses (11.5%). Most respondents (61.9%) were between 30 and 50 years. Members identified as male (M) in 74.4%, as female (F) in 25.0%, and as other in 0.6%. URiM comprised 9.1% of members. Women worked more commonly in academia (p = 0.005), had the perception of unequal opportunities for leadership positions within the institution (p = 0.006), and emphasized the importance of having a mentor of the same gender (p = 0.001). URiM members were less likely to hold a leadership position (p = 0.1, trend), had a perception of unequal opportunities for leadership positions within the institution (p = 0.06, trend), and reported the importance of having a mentor of the same race (p = 0.06, trend). There were no significant differences between gender or URiM status and perception of the SSR to provide an inclusive environment and leadership opportunities (p ≥ 0.39). CONCLUSION: While survey participation was limited and potentially biased, respondents perceived that women and minorities have fewer opportunities and are treated with lower regard in the workplace compared to male, non-minority colleagues.

Background: Glucocorticoid metabolites are associated with body composition measures and are altered with weight status. Metabolic and bariatric surgery (MBS) results in significant changes in weight and body composition. However, MBS effects on glucocorticoid metabolites are unknown. Objective: To evaluate (i) changes in the cortisol/cortisone ratio in youth with obesity 12 months after sleeve gastrectomy (SG) compared with nonsurgical controls with obesity (NS), and (ii) associations of these changes with body composition changes. Methods: A total of 38 participants 13–25 years old with obesity (29 female) were followed for 12 months. Half underwent SG, and the other half were followed with routine care (nonsurgical, NS). Fasting blood was assessed for cortisol and cortisone using liquid chromatography-mass spectroscopy as part of metabolomic analysis, and the cortisol/cortisone ratio was calculated. A single-slice MRI of the abdomen was performed to assess subcutaneous and visceral adipose tissue (SAT, VAT). Hepatic steatosis was assessed by computed tomography (CT). Results: SG did not differ from NS for baseline clinical characteristics, other than the mean age (SG 18.0 ± 0.46 vs. NS 16.6 ± 0.50 years, P = 0.041), BMI (BMI, 47.23 ± 1.5 vs. 41.32 ± 1.1 kg/m2, P = 0.003) weight and VAT, which were higher in SG. Significant reductions were noted over 12 months in BMI, BMI z-score, VAT, and SAT within the SG versus NS groups (P ≤ 0.001). Over 12 months, groups did not differ for changes in cortisol/cortisone ratio after controlling for age at baseline (P = 0.293). The ratio trended to decrease within the SG group [−1.40 (−5.08, 0.06), P = 0.080], particularly among those that had completed puberty (P = 0.048). No associations were found between changes in the cortisol/cortisone ratio and changes in body composition. Conclusions: The cortisol/cortisone ratio trended to decrease 12 months following SG. However, no associations were found between changes in the cortisol/cortisone ratio and changes in body composition. Studies with larger numbers of participants are necessary to confirm these findings. [ABSTRACT FROM AUTHOR]

Myostatin inhibition improves insulin sensitivity in preclinical and clinical models; however, studies investigating the relationship between serum myostatin levels and insulin sensitivity are discrepant. Sensitive and specific myostatin LC–MS/MS assays are now available to accurately assess serum myostatin level in vivo. We sought to determine whether higher serum myostatin levels are independently associated with lower insulin sensitivity in adults with overweight/obesity. Participants included 74 adults, 20–65 years old, BMI ≥25 kg/m2 without type 2 diabetes. Appendicular lean mass (ALM) was measured by dual‐energy x‐ray absorptiometry; visceral adipose tissue (VAT) was measured by computed tomography. Main outcome measures were serum myostatin levels (LC–MS/MS) and insulin sensitivity (Matsuda index). Mean age was 48 ± 12 years, and BMI was 33.1 ± 5.6 kg/m2 (mean ± SD). Men had higher mean serum myostatin levels versus women (8.3 ± 1.9 vs. 7.2 ± 1.9 ng/mL, p = 0.01) and higher serum myostatin levels were associated with higher ALM (R = 0.34, p = 0.003). Higher serum myostatin levels were associated with lower Matsuda index (R = −0.44, p = 0.0004), which remained significant after controlling for BMI, VAT, ALM, and sex. In conclusion, higher serum myostatin levels are independently associated with lower insulin sensitivity in adults with overweight/obesity and may be a marker of or play a mechanistic role in the development of insulin resistance. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop a machine learning model to reconstruct time series kinematic and kinetic profiles of the ankle and knee joint across six different tasks using an ankle-mounted IMU. Four male collegiate basketball players performed repeated tasks, including walking, jogging, running, sidestep cutting, max-height jumping, and stop-jumping, resulting in a total of 102 movements. Ankle and knee flexion-extension angles and moments were estimated using motion capture and inverse dynamics and considered 'actual data' for the purpose of model fitting. Synchronous acceleration and angular velocity data were collected from right ankle-mounted IMUs. A time-series feature extraction model was used to determine a set of features used as input to a random forest regression model to predict the ankle and knee kinematics and kinetics. Five-fold cross-validation was performed to verify the model accuracy, and statistical parametric mapping was used to determine the difference between the predicted and experimental time series. The random forest regression model predicted the time-series profiles of the ankle and knee flexion-extension angles and moments with high accuracy (Kinematics: R2 ranged from 0.782 to 0.962, RMSE ranged from 2.19° to 11.58°; Kinetics: R2 ranged from 0.711 to 0.966, RMSE ranged from 0.10 Nm/kg to 0.41 Nm/kg). There were differences between predicted and actual time series for the knee flexion-extension moment during stop-jumping and walking. An appropriately trained feature-based regression model can predict time series knee and ankle joint angles and moments across a wide range of tasks using a single ankle-mounted IMU. [ABSTRACT FROM AUTHOR]

Introduction: The study aimed to pilot test a well-being curriculum for KL2 scholars to be used across the Clinical and Translational Science Award consortium. Methods: Between November 2022, and May 2023, 36 KL2 scholars from 25 hubs participated in the program. The General Well-Being Index for U.S. Workers and the Patient Reported Outcomes Measurement Information System (PROMIS-29) were completed by scholars before and after the program. Results: Postparticipation, there was a trend of improvement in the domains of well-being, sleep, anxiety, and fatigue. Conclusion: Implementing a virtual synchronous well-being curriculum allowed the scholars to connect across the consortium and improve their well-being. [ABSTRACT FROM AUTHOR]

ObjectivesThe Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials.MethodsA systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy.ResultsWB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility.ConclusionsWB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI.