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Body Composition Analysis for Patient With Lung Cancer Using Computed Tomography Image Analysis
Conditions
Lung Cancer
Conditions: official terms
Lung Neoplasms
Conditions: Keywords
Lung cancer, Body composition analysis, Ct-Scan, Muscle mass, Cachexia
Study Type
Observational
Study Phase
N/A
Study Design
Observational Model: Cohort, Time Perspective: Retrospective
Overall Status
Recruiting
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.
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.
Criteria for eligibility
Healthy Volunteers: No
Maximum Age: 80 Years
Minimum Age: 40 Years
Gender: Both
Criteria: 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)
- 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)
Location
Institut universitaire de cardiologie et de pneumologie de Québec
Québec, Quebec, Canada
Status: Recruiting
Contact: Didier Saey, PhD - 418-656-8711 - didier.saey@criucpq.ulaval.ca
Start Date
May 2012
Completion Date
May 2015
Sponsors
Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Quebec
Source
Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Quebec
Record processing date
ClinicalTrials.gov processed this data on July 28, 2015
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