Body composition profiling in clinical trials – can large scale body composition data enhance the understanding of your study participants?
The heterogeneity of disorders such as diabetes type II, coronary heart disease, non-alcoholic fatty liver disease, neuromuscular disorders and obesity is a major problem when evaluating new treatments. A successful treatment for one patient might not be as effective in another. The current paradigms for selecting patients for treatment usually results in a broad spectrum of patient phenotypes, complicating the investigation of treatment efficacy.
Magnetic Resonance Imaging (MRI) is regarded as the gold standard for soft-tissue imaging (such as muscles, organs and fat). Lately, large population imaging studies, like the UK Biobank, have enabled the creation of standardized, large-scale reference data sets, allowing for the development of personalized body composition assessment. Body composition profiling is an emerging concept, using large data resources, enabling the investigation of the interplay between different body tissues and compartments and the definition of novel body composition phenotypes.
This webinar begins with a short introduction to MRI-based body composition profiling and will thereafter review recent research on the development of novel body composition phenotypes applied in various metabolic and wasting disorders such as sarcopenia. Multiple adipose tissue compartments and their different associations to metabolic disorders will be discussed while highlighting the importance of understanding skewness in body fat distribution. Recent research on how large data sets can be used to enhance the description of the individual and to create personalized virtual control groups to strengthen the interpretation of clinical study data will be presented.
