Computed Tomography Image Analysis in Assessing Body CompositionCommunity Oral Topic ● Kaitlin Charette ● 02/04/2015

Why Is Accurate Assessment of Body Composition Challenging?

Muscle loss is generally recognized to be of greater concern than adipose tissue loss 10

Body weight change may not accurately show shifts between lean and adipose tissue 1,3

Skeletal muscle wasting may be masked by increase in fat mass 2,3

Using body weight to measure nutritional status in patients with specific clinical conditions can be misleading, especially when involving edema or ascites 1

Why Is Accurate Assessment of Body Composition Important?

Recognition of sarcopenia (reduced quality of skeletal muscle) as clinically important is increasing 1

Sarcopenia is associated with loss of physical function, disability, risk of fractures and falls, increased hospital stays, infections, and decreased survival in nonmalignant diseases 2,1

Sarcopenic obesity (excess fat mass with loss of lean soft tissue mass) is on the rise and is associated with greater physical disability and increased mortality and combines the health risks of both obesity and depleted lean mass 2,6,9

Cachexia (“ a complex metabolic syndrome associated with underlying illness …characterized by loss of muscle with or without loss of fat mass”) is also associated with increased morbidity and mortality7

Effective diagnosis and treatment of cachexia is key to improving morbidity, mortality, and quality of life7

How Can CT Imaging Help?

CT imaging has been identified as a gold-standard method for analyzing body composition4

It allows for differentiation of bone, skeletal muscle, adipose tissue, and visceral organs4

CT Imaging comes with high cost and high radiation dose- but when patients have CT imaging as part of their medical diagnosis or care, they may be used for body composition assessment without additional risk to the patient1

CT imaging is often available for patients with cancer, respiratory failure, and trauma ICU patients 1

Recent studies also discuss the use of CT imaging in detecting LST depletion in patients with respiratory failure, COPD, HIV, Alzheimer disease, and traumatic injuries 1

How Does CT Image Analysis Work?

Analysis software such as SliceOmatic is used to identify demarcations between specific tissue types on a third-lumbar vertebra cross-section1

The third lumbar vertebra cross-section has been demonstrated to best correlate with total-body muscle volume5

Individuals may be directly compared based on adipose tissue, muscle, and lean tissue mass in L3 cross-sections

This information can also be used to approximate whole-body tissue masses using regression equations2,5

2

2

The UAMC Device Patient Lean Body Mass Project

UAMC Medical Imaging and Nutrition researchers are beginning a study utilizing CT scans to assess lean body mass in cardiac device patients

Cardiac device heart failure patients:o Have a higher risk of poor outcomes and readmissions when they are malnourishedo Require adequate nutrition for optimal wound healing following device placement or

transplantationo Are challenging subjects for nutritional assessment due to fluid retentiono Often receive CT imaging as part of cardiac transplant work-ups

The UAMC study aims to use imaging already available to:o “Demonstrate that changes in lean body mass obtained from cross-sectional imaging

studies correlate with nitrogen balance calculated from 24-hour urine urea nitrogen”o “Demonstrate that patients with preserved or increased lean body mass over time have

better outcomes (fewer admissions, fewer infections, less wound complications, lower mortality) in heart failure patients”

Future goals include:o Using lean body mass analysis from CT imaging to provide baseline nutritional

assessment for patients with heart failureo Guiding future nutritional interventions leading to better outcomes in this population12

Other Future Directions:

CT scans may be used to assess the impact of nutrition support in body composition changes and to detect the causal link between nutrition support, nutrition status, and outcomes in different populations, providing solid data to guide nutrition practice11

In Summary:

CT imaging has been demonstrated to be a precise way to assess lean soft tissue mass in many populations and thus can be a valuable tool in assessing nutritional status and nutritional and medical risk. 1 An upcoming UAMC study hopes to show a link between lean body mass preservation and better outcomes in heart failure device patients. CT scans may be a valuable tool for guiding nutrition interventions in many patient populations in the future.

Sources:

1. Prado CM, Heymsfield SB. Lean tissue imaging: a new era for nutritional assessment and intervention. JPEN J Parenter Enteral Nutr. 2014;38(8):940-53.

2. Baracos V. Measurement of lean body mass using CT scans. The 110th Abbott Nutrition Research Conference. Columbus, Ohio: Abbott Nutrition Health Institute 2009: 1-26.

3. Moisey LL, Mourtzakis M, Cotton BA, et al. Skeletal muscle predicts ventilator-free days, ICU-free days, and mortality in elderly ICU patients. Crit Care. 2013;17(5):R206.

4. Ross R, Janssen I. Computed tomography and magnetic resonance imaging. In: Heymsfield SB, Lohman T, Wang Z, Going S, eds. Human Body Composition. 2nd ed. Champaign, IL: Human Kinetics; 2005:89-108.

5. Shen W, Punyanitya M, Wang Z, et al. Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. J Appl Physiol. 2004;97(6):2333-2338.

6. Prado CM, Wells JC, Smith SR, Stephan BC, Siervo M. Sarcopenic obesity: a critical appraisal of the current evidence. Clin Nutr. 2012;31(5):583-601.

7. Evans WJ, Morley JE, Argilés J, et al. Cachexia: a new definition. Clin Nutr. 2008;27(6):793-9.

8. Cosquéric G, Sebag A, Ducolombier C, Thomas C, Piette F, Weill-engerer S. Sarcopenia is predictive of nosocomial infection in care of the elderly. Br J Nutr. 2006;96(5):895-901.

9. Prado, Carla MM et al. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. The Lancet Oncology. 9(7): 629-635.

10. Baracos VE, Reiman T, Mourtzakis M, Gioulbasanis I, Antoun S. Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis. Am J Clin Nutr. 2010;91(4):1133S-1137S.

11. Yost G, Gregory M, Bhat G. Short-form nutrition assessment in patients with advanced heart failure evaluated for ventricular assist device placement or cardiac transplantation. Nutr Clin Pract. 2014;29(5):686-91.

12. Jokerst C, Urbina S. Application for retrospective records review. The University of Arizona Medical Center. 2014: 1-12.