The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

IF 13.3 Q1 MEDICINE, RESEARCH & EXPERIMENTAL

Med Pub Date : 2026-07-10 Epub Date: 2026-06-08 DOI:10.1016/j.medj.2026.101176

Yusheng Guo, Xiaona Fu, Tianxiang Li, Ning Wang, Shanshan Jiang, Shanmei Li, Xiaofang Guo, Rundong Wang, Shichao Long, Mengsi Li, Qiuping Liu, Kai Zhao, Yangyang Xie, Xuejun Chen, Lixia Wang, Chuansheng Zheng, Lian Yang

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引用次数: 0

Abstract

Background: Morphological changes of abdominal organs in hepatocellular carcinoma (HCC) remain uncharacterized. This study aimed to automatically quantify these changes using deep learning, assess their treatment-related outcome associations, and evaluate prognostic value.

Methods: Abdominal computed tomography (CT) images from 2,747 patients with HCC and 2,869 healthy controls across 15 cohorts from 10 centers (8 Chinese and 2 international) were analyzed. The patients included those receiving immune checkpoint inhibitors (ICIs), transarterial chemoembolization (TACE), or surgical resection. A deep learning algorithm automatically segmented the spleen, liver, kidneys, pancreas, and adrenal glands. Organ volumes and height-normalized indexes (volume/height²) were calculated. Propensity score matching balanced baseline differences. Cox regression assessed associations with overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS), with subgroup and interaction analyses.

Findings: Compared with healthy controls, patients with HCC showed significant organ remodeling, with enlarged spleen, liver, kidneys, and adrenal glands (all p < 0.001). Multivariable analysis showed that in the ICI cohort, left kidney volume/index, right kidney index, and left adrenal gland volume/index predicted longer OS and PFS; in the TACE cohort, spleen volume/index and left kidney volume predicted OS and PFS; and in the surgical cohort, spleen volume, left kidney volume, left adrenal gland volume/index, and liver index were independent predictors. Restricted cubic spline analysis suggested nonlinear relationships between adrenal and kidney volumes and survival.

Conclusions: HCC is associated with systemic abdominal organ remodeling. Automated CT-based multi-organ quantification offers reproducible, non-invasive prognostic biomarkers, particularly in cases involving adrenal glands, spleen, and kidneys, supporting personalized treatment and prognosis assessment.

Funding: This work was funded by the National Natural Science Foundation of China.

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肝细胞癌患者腹部器官重构图谱：基于人工智能的多中心影像学研究。

背景：肝细胞癌（HCC）腹部器官的形态学改变尚不明确。本研究旨在使用深度学习自动量化这些变化，评估它们与治疗相关的结果关联，并评估预后价值。方法：分析来自10个中心（8个中国中心和2个国际中心）15个队列的2747例HCC患者和2869例健康对照者的腹部计算机断层扫描（CT）图像。这些患者包括接受免疫检查点抑制剂（ICIs）、经动脉化疗栓塞（TACE）或手术切除的患者。深度学习算法自动分割脾脏、肝脏、肾脏、胰腺和肾上腺。计算器官体积和高度归一化指数（volume/height2）。倾向得分匹配平衡基线差异。Cox回归评估了总生存期（OS）、无进展生存期（PFS）和无病生存期（DFS）的相关性，并进行了亚组和相互作用分析。结果：与健康对照相比，HCC患者表现出明显的器官重塑，脾脏、肝脏、肾脏和肾上腺肿大（均p < 0.001）。多变量分析显示，在ICI队列中，左肾体积/指数、右肾体积/指数和左肾上腺体积/指数预测更长的OS和PFS；在TACE队列中，脾脏体积/指数和左肾体积预测OS和PFS；在手术队列中，脾脏体积、左肾体积、左肾上腺体积/指数和肝脏指数是独立的预测因子。限制三次样条分析表明肾上腺和肾脏体积与生存之间存在非线性关系。结论：肝细胞癌与全身腹部器官重构有关。基于ct的自动化多器官量化提供了可重复的、无创的预后生物标志物，特别是在涉及肾上腺、脾脏和肾脏的病例中，支持个性化治疗和预后评估。基金资助：本工作由国家自然科学基金资助。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Med MEDICINE, RESEARCH & EXPERIMENTAL-

CiteScore

17.70

自引率

0.60%

发文量

102

期刊介绍： Med is a flagship medical journal published monthly by Cell Press, the global publisher of trusted and authoritative science journals including Cell, Cancer Cell, and Cell Reports Medicine. Our mission is to advance clinical research and practice by providing a communication forum for the publication of clinical trial results, innovative observations from longitudinal cohorts, and pioneering discoveries about disease mechanisms. The journal also encourages thought-leadership discussions among biomedical researchers, physicians, and other health scientists and stakeholders. Our goal is to improve health worldwide sustainably and ethically. Med publishes rigorously vetted original research and cutting-edge review and perspective articles on critical health issues globally and regionally. Our research section covers clinical case reports, first-in-human studies, large-scale clinical trials, population-based studies, as well as translational research work with the potential to change the course of medical research and improve clinical practice.