Lukas Müller , Aline Mähringer-Kunz , Timo Alexander Auer , Uli Fehrenbach , Bernhard Gebauer , Johannes Haubold , Benedikt Michael Schaarschmidt , Moon-Sung Kim , René Hosch , Felix Nensa , Jens Kleesiek , Thierno D. Diallo , Michel Eisenblätter , Hanna Kuzior , Natascha Roehlen , Dominik Bettinger , Verena Steinle , Philipp Mayer , David Zopfs , Daniel Pinto Dos Santos , Roman Kloeckner
{"title":"一项多中心研究将 AI 衍生的身体成分参数作为接受 TACE 的 HCC 患者的预后因素","authors":"Lukas Müller , Aline Mähringer-Kunz , Timo Alexander Auer , Uli Fehrenbach , Bernhard Gebauer , Johannes Haubold , Benedikt Michael Schaarschmidt , Moon-Sung Kim , René Hosch , Felix Nensa , Jens Kleesiek , Thierno D. Diallo , Michel Eisenblätter , Hanna Kuzior , Natascha Roehlen , Dominik Bettinger , Verena Steinle , Philipp Mayer , David Zopfs , Daniel Pinto Dos Santos , Roman Kloeckner","doi":"10.1016/j.jhepr.2024.101125","DOIUrl":null,"url":null,"abstract":"<div><h3>Background & Aims</h3><p>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).</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (<em>p <</em>0.001), high TAT volume (<em>p</em> = 0.013), and high SAT volume (<em>p</em> = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (<em>p</em> = 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.</p></div><div><h3>Conclusions</h3><p>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.</p></div><div><h3>Impact and implications:</h3><p>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.</p></div>","PeriodicalId":14764,"journal":{"name":"JHEP Reports","volume":"6 8","pages":"Article 101125"},"PeriodicalIF":9.5000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589555924001290/pdfft?md5=8f81f815539c9b7127ef027a6c9b8f47&pid=1-s2.0-S2589555924001290-main.pdf","citationCount":"0","resultStr":"{\"title\":\"AI-derived body composition parameters as prognostic factors in patients with HCC undergoing TACE in a multicenter study\",\"authors\":\"Lukas Müller , Aline Mähringer-Kunz , Timo Alexander Auer , Uli Fehrenbach , Bernhard Gebauer , Johannes Haubold , Benedikt Michael Schaarschmidt , Moon-Sung Kim , René Hosch , Felix Nensa , Jens Kleesiek , Thierno D. Diallo , Michel Eisenblätter , Hanna Kuzior , Natascha Roehlen , Dominik Bettinger , Verena Steinle , Philipp Mayer , David Zopfs , Daniel Pinto Dos Santos , Roman Kloeckner\",\"doi\":\"10.1016/j.jhepr.2024.101125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background & Aims</h3><p>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).</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (<em>p <</em>0.001), high TAT volume (<em>p</em> = 0.013), and high SAT volume (<em>p</em> = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (<em>p</em> = 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.</p></div><div><h3>Conclusions</h3><p>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.</p></div><div><h3>Impact and implications:</h3><p>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.</p></div>\",\"PeriodicalId\":14764,\"journal\":{\"name\":\"JHEP Reports\",\"volume\":\"6 8\",\"pages\":\"Article 101125\"},\"PeriodicalIF\":9.5000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2589555924001290/pdfft?md5=8f81f815539c9b7127ef027a6c9b8f47&pid=1-s2.0-S2589555924001290-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JHEP Reports\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589555924001290\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JHEP Reports","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589555924001290","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景& 目的最近发现，身体成分评估（BCA）参数是肝细胞癌（HCC）患者的相关预后因素。方法这项回顾性多中心研究纳入了2010-2020年间在6个三级医疗中心接受TACE治疗的754例未经治疗的HCC患者。对腹腔组织成分进行了基于人工智能的全自动三维容积定量分析，以评估干预前计算机断层扫描上的骨骼肌体积（SM）、总脂肪组织（TAT）、肌内和肌间脂肪组织、内脏脂肪组织和皮下脂肪组织（SAT）。BCA 参数根据腹腔切片数进行归一化处理。我们评估了BCA参数对中位总生存期的影响，并进行了包括既定生存期估计值在内的多变量分析。结果单变量生存期分析显示，低SM（p <0.001）、高TAT体积（p = 0.013）和高SAT体积（p = 0.006）可预测中位总生存期受损。在多变量生存分析中，SM 仍是一个独立的预后因素（p = 0.039），而 TAT 和 SAT 容量则不再具有预测能力。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。因此，将 SM 纳入新型评分系统可能会改善生存预测和临床决策。影响和意义：身体成分评估参数，尤其是骨骼肌体积，已被确定为许多疾病和治疗的相关预后因素。在这项研究中，骨骼肌体积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，骨骼肌体积作为一种元参数，可在患者整体评估中发挥机会性生物标志物的作用，并可整合到决策支持系统中。与人工智能相结合的工作流程对于自动、定量的身体成分评估至关重要，可广泛应用于多学科病例讨论。
AI-derived body composition parameters as prognostic factors in patients with HCC undergoing TACE in a multicenter study
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).
Methods
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.
Results
Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (p <0.001), high TAT volume (p = 0.013), and high SAT volume (p = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (p = 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.
Conclusions
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.
Impact and implications:
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.
期刊介绍：
JHEP Reports is an open access journal that is affiliated with the European Association for the Study of the Liver (EASL). It serves as a companion journal to the highly respected Journal of Hepatology.
The primary objective of JHEP Reports is to publish original papers and reviews that contribute to the advancement of knowledge in the field of liver diseases. The journal covers a wide range of topics, including basic, translational, and clinical research. It also focuses on global issues in hepatology, with particular emphasis on areas such as clinical trials, novel diagnostics, precision medicine and therapeutics, cancer research, cellular and molecular studies, artificial intelligence, microbiome research, epidemiology, and cutting-edge technologies.
In summary, JHEP Reports is dedicated to promoting scientific discoveries and innovations in liver diseases through the publication of high-quality research papers and reviews covering various aspects of hepatology.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
