Understanding the implications of sarcopenia in heart failure using multi-modality imaging and genetics

Heart failure (HF) is a condition that occurs due to the heart not efficiently pumping blood around the body. It is a major cause of disability and death worldwide. A growing area of research is the link between HF and sarcopenia, which is the gradual loss of muscle mass and strength. Sarcopenia is usually thought of as an ageing problem, but it is now recognised in up to 1 in 3 people with HF. This overlap matters because the relationship goes both ways. On the one hand, HF leads to inflammation, hormonal changes, and metabolic problems that promote muscle wasting. On the other hand, sarcopenia worsens frailty, reduces physical activity, and doubles the risk of dying within a year for HF patients. In short, sarcopenia is not just a consequence of HF—it may actively make the disease worse.
 
Muscles in the legs, such as the quadriceps, carry the body’s weight and weaken through loss of muscle mass early in illness. By contrast, chest muscle mass, though still related to leg muscles, may serve as a more stable indicator of illness. Among them, the pectoralis major muscle has emerged as a particularly promising indicator of overall muscle health and heart function. Research shows that the size of this muscle, measured using routine chest scans, is strongly linked to survival in people with and without HF.
 
Currently, there are major limitations in how sarcopenia is measured. Common techniques, such as bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DEXA) scans, only provide indirect estimates of muscle mass, mostly in the arms and legs. These methods can be inaccurate in people with HF because they often have swelling of their extremities which can distort measurements. Conversely, magnetic resonance imaging (MRI) or computed tomography (CT) scans both provide a direct and precise way to measure muscle mass. As it stands, muscle analysis is not yet standardised within routine heart or chest scans, meaning that valuable information is potentially being missed. This creates a significant opportunity. Around 400 million CT scans and 150 million MRI scans are performed globally every year. With modern advances in artificial intelligence, it is now possible to automatically analyse these images with near-human accuracy. This means sarcopenia could be measured at scale, without extra scans or burden for patients, simply by extracting more information from existing images.
 
The proposed project will harness this opportunity by developing automatic methods to measure chest muscles in CT and MRI scans, alongside quality-control systems to ensure reliability. These muscle measurements will then be studied in relation to lifestyle factors, genetics, and cardiovascular disease, especially in HF. By using large datasets such as the UK Biobank (which includes genetic and imaging data from around half a million people) and the Barts Health Data Platform (one of the NHS’s largest collections of patient scans and records), researchers will be able to explore both the biological mechanisms and the clinical importance of sarcopenia. Ultimately, this work aims to clarify how much sarcopenia contributes to worsening HF, to develop a practical imaging biomarker that can be used from existing scans, and to improve the ability to predict which patients are most at risk. This could lead to more targeted treatments, better patient outcomes, and reduced healthcare costs.