Don’t Judge a Body by Its Cover – Body Composition Profiling in Clinical Trials

Life Sciences, Clinical Trials, Medical Device, Medical Device Diagnostics,
  • Thursday, June 18, 2020

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.


Jennifer Linge, AMRA Medical

Jennifer Linge, MSc, Lead Scientist, Personalized Medicine, AMRA Medical

Jennifer Linge is a biostatistical analyst and clinical science lead for personalized medicine at AMRA Medical. Her main focus is on the development of individual-centric solutions and body composition phenotypes utilizing large MRI datasets. Her background is in engineering mathematics, specializing in medical modelling and data mining. She is responsible for AMRA’s scientific efforts and early product development in the metabolic space. She is pursuing her PhD in health economics focused on emerging diagnostic technologies.

Message Presenter

Who Should Attend?

  • Chief Medical Officer
  • Chief Executive Officer
  • Principal Investigator
  • Medical Director
  • Research Nurse
  • Clinical Director
  • Clinical Project Manager
  • Imaging Specialist
  • Clinical Operations
  • Clinical Development Manager
  • Procurement Manager
  • Statistician
  • Data Manager
  • Regulatory Coordinator
  • Business Development

What You Will Learn

In this webinar, attendees will learn:

  • Why measure multiple fat compartments?
  • How body composition profiling can be used to describe the heterogeneity within metabolic disorders
  • How large datasets can enhance the description of individuals with sarcopenia-related problems
  • What a virtual control group is and how it can be used to strengthen the interpretation of clinical study data

Xtalks Partner


AMRA is a ground-breaking international digital health company at the forefront of medical imaging and precision medicine. The company has developed a new global standard in body composition assessment, the ability to automatically produce multiple fat and muscle biomarkers with unrivaled precision and accuracy, as well as contextual disease insights – all from a single, rapid, whole-body MRI. AMRA was founded in 2010 as a spin-off of Linköping University, Sweden, with the aim to support transformative care and vital decision-making from clinical research to health and wellness.

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