The American Cancer Society Research Scholar Grant supports investigator-initiated proposals that and pursue questions across the cancer research that align with ACS Priority Research Areas.
Understanding the metabolic complexities of cancer cachexia (CC) in individuals of all weight and BMI classes is paramount as CC is associated with decreased survival and reduced treatment tolerance. Current diagnostic criteria for CC rely on total body weight loss or body mass index (BMI) to assess wasting, which is unable to accurately assess both muscle quantity and muscle quality especially in individuals with an elevated BMI. Growing evidence for the development of CC support a signaling crosstalk between skeletal muscle and adipose tissue. The project aims to identify imaging thresholds diagnostic of CC for muscle, fat, and other tissues that are independent of body weight utilizing AI-based CT tools. This directly aligns with the Obesity/Healthy Eating and Active Living (HEAL) ACS research priority as it addresses how body composition (particularly muscle and fat mass) impact the diagnosis and progression of CC. Further, we intend to determine the prognostic impact of these imaging thresholds on outcomes including treatment tolerance and survival (Screening & Diagnosis).
It is known, and appreciated, that individuals with cancer will often experience muscle loss during disease progression and corresponding treatments. This muscle loss is termed cancer cachexia (CC) and is massive contributor to decreased quality of life and difficulty maintaining normal activities, but notably is also highly associated with increased risk of death. Up until this point, diagnosis of CC occurs when individuals lose a certain amount of their body weight or have a low BMI. However, muscle loss and body weight loss are not one in the same. An individual with cancer may be losing a significant amount of muscle mass, but maintaining their body weight (often due to increasing fat stores or fat entering muscle) and thereby may be missed by this traditional definition of CC. Even when CC is appropriately detected, our current understanding of CC makes it nearly impossible to treat.
Based on our previous work, we propose utilizing non-invasive imaging techniques like magnetic resonance imaging (MRI) and CT to measure how muscle and fat stores change over time in people with cancer and asking the following questions. Which CT imaging parameters can most strongly predict an individual’s risk of poor outcomes? How do MR and CT imaging parameters compare when looking at different tissues (like muscle and fat)? Based on these imaging parameters, can we identify a measure and a threshold to identify individuals who are at increased risk of ?
By looking at CT and MR scans, both at diagnosis and over time, we can determine imaging thresholds that clinicians can use to quickly, effectively, and noninvasively diagnosis cancer cachexia in individuals of all body sizes. There are no current methods that allow clinicians to accurately assess CC for individuals of varying body sizes so this development would greatly increase equity of care. The proposed strategy would also leverage imaging workflows that are presently standard of care during treatment, like computed tomography (CT). Therefore, clinicians could gain more information from required procedures and without additional expense or time for the patient. By identifying CC earlier, treatment strategies would shift to potential interventions that help maintain muscle mass rather than attempting to regain muscle after loss has occurred; a critical change, and likely a more successful way, to address cancer cachexia. The impact of this work extends to family, friends, and caregivers of loved ones with cancer as the implications of earlier cancer cachexia diagnosis and intervention include not only improved quality of life and ability to maintain engagement in their normal activities, with the ultimate goal of longer life.