INVESTigations of Muscle and Bone Health: Developing Automated Approaches for CT-Based Analyses

PROJECT SUMMARY Obesity is a common, serious, and costly condition among older adults. Weight loss (WL) is an effective strategy to combat obesity-related comorbidities; however, the safety of WL interventions for older adults remains controversial due to potential exacerbation of age-related muscle and bone loss that increases fracture risk.

Mechanical stimuli, such as resistance training (RT), can be effective in mitigating WL-associated bone loss, but there are many barriers to success of RT programs for older adults, including low adherence and accessibility. In response, our group has proposed that a weighted vest may serve as an alternative for maintaining mechanical

stress during intentional WL, but it is unclear whether this vest will have similar preservation effects on bone when compared to RT. Therefore, our ongoing 12-month WL trial of 150 older adults living with obesity, INVEST in Bone Health (NCT04076618) is exploring the effects of WL alone versus WL plus weighted vest use or WL

plus RT on indicators of bone health and fracture risk, with the primary outcome being 12-month change in total hip volumetric (vBMD) as measured by computed tomography (CT). This F31 proposal enhances the parent study by adding new analyses of the CT scans acquired for this study to investigate indicators of muscle health.

As WL-associated muscle loss often precedes bone loss, preserving muscle health may also have clinical relevance to the reduction of fracture risk. Aim 1 will develop an automated image analysis platform to process baseline, 6- and 12-month participant CT scans to measure muscle quantity and quality and assess intervention

effects. Aim 2 will utilize CT data for development of subject-specific finite element models to assess longitudinal bone strength and muscle-bone associations in response to WL. Taken together, completion of these aims will provide automated techniques to support future large-scale research projects and opportunistic CT assessments

of muscle in clinical care, while also furthering our understanding of the mechanistic relationship between WL- associated changes in muscle and bone. In addition to augmenting the suite of musculoskeletal outcomes in the INVEST trial, this fellowship will provide the predoctoral principal investigator (PI) with valuable training from an

experienced mentorship team in the areas of: 1) aging and clinical trials, 2) data management, interpretation, and biostatistics, 3) muscle and bone epidemiology, 4) machine learning and imaging informatics, and 5) computational biomechanics. This research will be conducted at Wake Forest University as an interdisciplinary

collaboration between the Departments of Biomedical Engineering, Health and Exercise Science, Radiology, and Statistical Sciences. Together, this collaborative environment and an expert team of mentors will support the PI’s training to achieve independency in her research career while successfully completing her doctoral

dissertation. This project, as an extension of the PI’s ongoing work with the INVEST trial, will refine her technical engineering and professional skillsets, and launch her career as an independent bioengineering researcher focused on developing and applying advanced image analyses to study musculoskeletal health in aging.