Ignite Creation Date:
2025-12-24 @ 10:46 PM
Ignite Modification Date:
2026-01-02 @ 6:30 PM
Study NCT ID:
NCT01887769
Status:
UNKNOWN
Last Update Posted:
2017-01-06
First Post:
2013-02-13
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Body Composition Analysis for Patient With Lung Cancer Using Computed Tomography Image Analysis
Sponsor:
Centre de Recherche de l'Institut Universitaire de Cardiologie et de Pneumologie de Quebec
Organization:
Study Overview
Official Title:
None
Status:
UNKNOWN
Status Verified Date:
2017-01
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
BAT-SCAN
Brief 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.
Detailed Description:
None
Study Oversight
Has Oversight DMC:
True
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: