Three‐dimensional body composition parameters using automatic volumetric segmentation allow accurate prediction of colorectal cancer outcomes

Author:

Bimurzayeva Aiya1,Kim Min Jung123ORCID,Ahn Jong‐Sung1,Ku Ga Yoon1,Moon Dokyoon1,Choi Jinsun1,Kim Hyo Jun1,Lim Han‐Ki12,Shin Rumi14,Park Ji Won123,Ryoo Seung‐Bum12,Park Kyu Joo12,Chung Han‐Jae5,Kim Jong‐Min5,Park Sang Joon56,Jeong Seung‐Yong123

Affiliation:

1. Department of Surgery Seoul National University College of Medicine Seoul Republic of Korea

2. Colorectal Cancer Center Seoul National University Cancer Hospital Seoul Republic of Korea

3. Cancer Research Institute Seoul National University Seoul Republic of Korea

4. Department of Surgery Seoul Metropolitan Government‐Seoul National University Boramae Medical Center Seoul Republic of Korea

5. Research and Science Division MEDICAL IP Co., Ltd. Seoul Republic of Korea

6. Department of Radiology Seoul National University College of Medicine Seoul Republic of Korea

Abstract

AbstractBackgroundParameters obtained from two‐dimensional (2D) cross‐sectional images have been used to determine body composition. However, data from three‐dimensional (3D) volumetric body images reflect real body composition more accurately and may be better predictors of patient outcomes in cancer. This study aimed to assess the 3D parameters and determine the best predictive factors for patient prognosis.MethodsPatients who underwent surgery for colorectal cancer (CRC) between 2010 and 2016 were included in this study. Preoperative computed tomography images were analysed using an automatic segmentation program. Body composition parameters for muscle, muscle adiposity, subcutaneous fat (SF) and abdominal visceral fat (AVF) were assessed using 2D images at the third lumbar (L3) level and 3D images of the abdominal waist (L1–L5). The cut‐off points for each parameter were determined using X‐tile software. A Cox proportional hazards regression model was used to identify the association between the parameters and the treatment outcomes, and the relative influence of each parameter was compared using a gradient boosting model.ResultsOverall, 499 patients were included in the study. At a median follow‐up of 59 months, higher 3D parameters of the abdominal muscles and SF from the abdominal waist were found to be associated with longer overall survival (OS) and disease‐free survival (all P < 0.001). Although the 3D parameters of AVF were not related to survival outcomes, patients with a high AVF volume and mass experienced higher rate of postoperative complications than those with low AVF volume (27.4% vs. 18.7%, P = 0.021, for mass; 27.1% vs. 19.0%, P = 0.028, for volume). Low muscle mass and volume (hazard ratio [HR] 1.959, P = 0.016; HR 2.093, P = 0.036, respectively) and low SF mass and volume (HR 1.968, P = 0.008; HR 2.561, P = 0.003, respectively), both in the abdominal waist, were identified as independent prognostic factors for worse OS. Along with muscle mass and volume, SF mass and volume in the abdominal waist were negatively correlated with mortality (all P < 0.001). Both AVF mass and volume in the abdominal waist were positively correlated with postoperative complications (P < 0.05); 3D muscle volume and SF at the abdominal waist were the most influential factors for OS.Conclusions3D volumetric parameters generated using an automatic segmentation program showed higher correlations with the short‐ and long‐term outcomes of patients with CRC than conventional 2D parameters.

Funder

Seoul National University Hospital

Publisher

Wiley

Subject

Physiology (medical),Orthopedics and Sports Medicine

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