Body Composition Analysis for Patient With Lung Cancer Using Computed Tomography Image Analysis

Rationale: With 1.6 million new cases diagnosed each year and 1.3 million deaths, lung cancer is the leading cancer-related death worldwide and it represents a pressing health issue. Patients with lung cancer are more likely to experience cachexia, a severe debilitating disorder causing fatigue, weight loss, muscle wasting and associated with reduced physical function, increased chemotherapy toxicity and reduced survival. This syndrome occurring in about 80% of advanced cancer patients is the direct cause of death in about 20% of cases. However, despite the importance of cachexia in lung cancer, it has been mainly studied from several assessment methods which do not usually differentiate muscle from other tissues. Aim: To analyze body composition of patients with lung cancer at diagnosis using computed tomography (CT-Scan) image analysis. Methods: This is a retrospective study extending over a period of 3 years conducted at the Institut universitaire de cardiologie et de pneumologie de Québec (2009-2012). We listed patients newly diagnosed with lung cancer who had a thoraco-abdominal CT-scan performed in our institution. Following the collection of clinical data from patient records, we used SliceOmatic software to quantify muscle area, visceral fat area and subcutaneous fat area from a single abdominal cross-sectional image at the level of the third lumbar vertebra.

Sex

All

Minimum age

40 Years

Maximum age

80 Years

Inclusion Criteria:

* Men or women
* Between 40-80 years of age
* Primary lung cancer diagnosed between 2009 and 2012
* CT-Scan done at the time of the diagnosis

Exclusion Criteria:

* Chemotherapy, radiotherapy or surgery at the time of the first Ct-Scan image
* History of other cancer (during the last five years)