• Michelle V Dietz, Karteek Popuri, Lars Janssen, Mushfiqus Salehin, Da Ma, Vincent Tze Yang Chow, Hyunwoo Lee, Cornelis Verhoef, Eva V E Madsen, Mirza F Beg, and van VugtJeroen L AJLADepartment of Surgical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands; Department of Surgery, University Medical Center Groningen, Groningen, The Netherlands. Electronic address: j.l.a.van.vugt@umcg.nl..
• Department of Surgical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
• Nutrition. 2025 Jan 1; 129: 112592112592.

IntroductionBody composition evaluation can be used to assess patients' nutritional status to predict clinical outcomes. To facilitate reliable and time-efficient body composition measurements eligible for clinical practice, fully automated computed tomography segmentation methods were developed. The aim of this study was to evaluate automated segmentation by Data Analysis Facilitation Suite in an independent dataset.Materials And MethodsPreoperative computed tomography images were used of 165 patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy from 2014 to 2019. Manual and automated measurements of skeletal muscle mass (SMM), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intramuscular adipose tissue (IMAT) were performed at the third lumbar vertebra. Segmentation accuracy of automated measurements was assessed using the Jaccard index and intra-class correlation coefficients.ResultsAutomatic segmentation provided accurate measurements compared to manual analysis, resulting in Jaccard score coefficients of 94.9 for SMM, 98.4 for VAT, 99.1 for SAT, and 79.4 for IMAT. Intra-class correlation coefficients ranged from 0.98 to 1.00. Automated measurements on average overestimated SMM and SAT areas compared to manual analysis, with mean differences (±2 standard deviations) of 1.10 (-1.91 to 4.11) and 1.61 (-2.26 to 5.48) respectively. For VAT and IMAT, automated measurements on average underestimated the areas with mean differences of -1.24 (-3.35 to 0.87) and -0.93 (-5.20 to 3.35), respectively.ConclusionsCommercially available Data Analysis Facilitation Suite provides similar results compared to manual measurements of body composition at the level of third lumbar vertebra. This software provides accurate and time-efficient body composition measurements, which is necessary for implementation in clinical practice.Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

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