Müller Lukas, Mähringer-Kunz Aline, Auer Timo Alexander, Fehrenbach Uli, Gebauer Bernhard, Haubold Johannes, Schaarschmidt Benedikt Michael, Kim Moon-Sung, Hosch René, Nensa Felix, Kleesiek Jens, Diallo Thierno D, Eisenblätter Michel, Kuzior Hanna, Roehlen Natascha, Bettinger Dominik, Steinle Verena, Mayer Philipp, Zopfs David, Pinto Dos Santos Daniel, Kloeckner Roman
Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Department of Radiology, Charité - University Medicine Berlin, Berlin, Germany.
JHEP Rep. 2024 May 25;6(8):101125. doi: 10.1016/j.jhepr.2024.101125. eCollection 2024 Aug.
BACKGROUND & AIMS: Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing transarterial chemoembolization (TACE).
This retrospective multicenter study included a total of 754 treatment-naïve patients with HCC who underwent TACE at six tertiary care centers between 2010-2020. Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition was performed to assess skeletal muscle volume (SM), total adipose tissue (TAT), intra- and intermuscular adipose tissue, visceral adipose tissue, and subcutaneous adipose tissue (SAT) on pre-intervention computed tomography scans. BCA parameters were normalized to the slice number of the abdominal cavity. We assessed the influence of BCA parameters on median overall survival and performed multivariate analysis including established estimates of survival.
Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (0.001), high TAT volume ( = 0.013), and high SAT volume ( = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor ( = 0.039), while TAT and SAT volumes no longer showed predictive ability. This predictive role of SM was confirmed in a subgroup analysis of patients with BCLC stage B.
SM is an independent prognostic factor for survival prediction. Thus, the integration of SM into novel scoring systems could potentially improve survival prediction and clinical decision-making. Fully automated approaches are needed to foster the implementation of this imaging biomarker into daily routine.
Body composition assessment parameters, especially skeletal muscle volume, have been identified as relevant prognostic factors for many diseases and treatments. In this study, skeletal muscle volume has been identified as an independent prognostic factor for patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Therefore, skeletal muscle volume as a metaparameter could play a role as an opportunistic biomarker in holistic patient assessment and be integrated into decision support systems. Workflow integration with artificial intelligence is essential for automated, quantitative body composition assessment, enabling broad availability in multidisciplinary case discussions.
身体成分评估（BCA）参数最近被确定为肝细胞癌（HCC）患者的相关预后因素。在此，我们旨在研究BCA参数在接受经动脉化疗栓塞术（TACE）的HCC患者预后预测中的作用。
这项回顾性多中心研究共纳入了754例未经治疗的HCC患者，他们于2010年至2020年期间在6家三级医疗中心接受了TACE治疗。在干预前的计算机断层扫描上，采用基于人工智能的全自动定量3D腹腔组织成分容积测量法，评估骨骼肌容积（SM）、总脂肪组织（TAT）、肌内和肌间脂肪组织、内脏脂肪组织以及皮下脂肪组织（SAT）。BCA参数根据腹腔切片数量进行标准化。我们评估了BCA参数对中位总生存期的影响，并进行了多变量分析，包括已确立的生存估计值。
单变量生存分析显示，低SM（P = 0.001）、高TAT容积（P = 0.013）和高SAT容积（P = 0.006）可预测中位总生存期受损。在多变量生存分析中，SM仍然是一个独立的预后因素（P = 0.039），而TAT和SAT容积不再显示出预测能力。SM的这种预测作用在BCLC B期患者的亚组分析中得到了证实。
SM是生存预测的独立预后因素。因此，将SM纳入新的评分系统可能会改善生存预测和临床决策。需要全自动方法来促进这种影像生物标志物在日常实践中的应用。
身体成分评估参数，尤其是骨骼肌容积，已被确定为许多疾病和治疗的相关预后因素。在本研究中，骨骼肌容积已被确定为接受经动脉化疗栓塞术的肝细胞癌患者的独立预后因素。因此，骨骼肌容积作为一个元参数，可在整体患者评估中作为一种机会性生物标志物发挥作用，并纳入决策支持系统。与人工智能的工作流程整合对于自动化、定量的身体成分评估至关重要，可在多学科病例讨论中广泛应用。
