0.998–0.998 and 2.8–3.3% for VF. Time to analyze 30 Background: Computed tomography (CT) has been cases was 70–100 min and 150–180 min using Body- increasingly used to quantify abdominal muscle and fat CompSlicer and Slice-O-Matic, respectively. in clinical research studies, and multiple studies have Conclusion: BodyCompSlicer is comparable to Slice-O- shown importance of body composition in predicting Matic for CT body composition analysis. clinical outcome. The purpose of study is to compare newly developed semi-automated software (BodyComp- Key words: Computed tomography—Body Slicer) to commercially available validated software composition—Sarcopenia—Cachexia (Slice-O-Matic) for CT body composition analysis. Methods: CT scans of abdomen at L3 level in 30 patients were analyzed by two reviewers and using two softwares Computed tomography (CT) has been increasingly used (BodyCompSlicer and Slice-O-Matic). Body composition to quantify abdominal muscle and fat in clinical research analysis using BodyCompSlicer was semi-automated. studies, and multiple studies have shown importance of The program automatically segmented subcutaneous fat body composition in predicting clinical outcome. Low (SF), skeletal muscle (SM), and visceral fat (VF) areas. skeletal muscle mass, which, in its severe form, is de- Reviewers manually corrected the segmentation using computer–mouse interface as necessary. Body composi- scribed as sarcopenia has been shown to
Abdominal Radiology – Springer Journals
Published: Apr 7, 2017
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