NCT01887769

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

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,000 (estimated)
• Sponsor: Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Quebec · Academic / Other
• Sex: All
• Age: 40 Years – 80 Years
• Healthy volunteers: Not accepted

Summary

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.

Conditions

• Lung Cancer

Timeline

• Start date: 2012-05-01
• Primary completion: 2017-07-01
• Completion: 2017-10-01
• First posted: 2013-06-27
• Last updated: 2017-01-06

Locations

1 site across 1 country: Canada