Last updated on February 2018

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

Brief description of study

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 Qubec (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.

Clinical Study Identifier: NCT01887769

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Didier Saey, PhD

Institut universitaire de cardiologie et de pneumologie de Qu bec
Québec, QC Canada
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Recruitment Status: Open

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