3D assessment of skeletal muscle and adipose tissue for prognosis of hepatocellular carcinoma: A multicenter cohort study

IF 2.9 Q3 NUTRITION & DIETETICS

Clinical nutrition ESPEN Pub Date : 2025-04-03 DOI:10.1016/j.clnesp.2025.03.168

Jinxiong Zhang , Shuoling Zhou , Yurong Jiang , Wei Zhao , Weiguo Xu , Jiawei Zhang , Taixue An , Jianfeng Yan , Chongyang Duan , Xiaojun Wang , Sihui Yang , Tao Wang , Dandan Dong , Yuan Chen , Feixiang Zou , Xiangrong Yu , Meiyan Huang , Sirui Fu

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引用次数: 0

Abstract

Background

Changes in protein and lipid metabolism could provide additional prognostic information for hepatocellular carcinoma (HCC).This study aimed to explore whether 3D automatic assessment of skeletal muscle and adipose tissue can contribute to the precise prognosis for HCC.

Methods

The data of 458 HCC patients from 6 hospitals were divided into training and external validation datasets. Preoperative CT Images were used for this study. First, we tested the stability of the 2D factors. Second, we tested whether standardization for volume assessment was necessary. Third, we compared the clinical (Model^C), skeletal muscle and adipose tissue (Model^NSA), and combined (Model^C−NSA) models by discrimination and calibration to identify the optimal model. Subgroup analysis was performed for the optimal model.

Results

For the 16 2D factors, 13 factors were statistically different among the three 2D slices. Standardization of the volume factors was necessary. Among the three models, Model^C−NSA had a higher area under the curve [AUC] than Model^C and Model^NSA, both in the training dataset (0.809 vs. 0.649 vs. 0.797) and the validation dataset (0.770 vs. 0.718 vs. 0.719). For calibration, the performance of Model^C−NSA was similar to those of Model^C and Model^NSA. The performance of Model^C−NSA was not influenced by age (P = 0.753), sex (P = 0.781), treatments (P = 0.504), Barcelona Clinic Liver Cancer stage (P = 0.913), or Child-Pugh class (P = 0.580).

Conclusions

Compared to 2D evaluation, 3D assessment is more stable. 3D automatic assessment of skeletal muscle and adipose tissue can accurately predict progression in patients with HCC.

查看原文本刊更多论文

骨骼肌和脂肪组织对肝细胞癌预后的三维评估：一项多中心队列研究。

背景：蛋白质和脂质代谢的变化可以为肝细胞癌（HCC）的预后提供额外的信息。本研究旨在探讨骨骼肌和脂肪组织的3D自动评估是否有助于HCC的精确预后。方法：将来自6家医院的458例HCC患者的数据分为训练数据集和外部验证数据集。本研究使用术前CT图像。首先，我们测试了二维因子的稳定性。其次，我们检验了是否有必要对容积评估进行标准化。第三，我们比较了临床模型（ModelC）、骨骼肌和脂肪组织模型（ModelNSA），并通过判别和校准组合模型（ModelC- nsa），以确定最优模型。对最优模型进行亚组分析。结果：在16个2D因素中，有13个因素在3个2D切片中有统计学差异。体积因子的标准化是必要的。在三个模型中，ModelC- nsa在训练数据集（0.809 vs. 0.649 vs. 0.797）和验证数据集（0.770 vs. 0.718 vs. 0.719）的曲线下面积（AUC）均高于ModelC和ModelNSA。在校准方面，ModelC- nsa的性能与ModelC和ModelNSA相似。模型c - nsa的表现不受年龄（P=0.753）、性别（P=0.781）、治疗（P=0.504）、巴塞罗那临床肝癌分期（P=0.913）、Child-Pugh分级（P=0.580）的影响。结论：与二维评价相比，三维评价更加稳定。骨骼肌和脂肪组织的3D自动评估可以准确预测HCC患者的进展。

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

Clinical nutrition ESPEN NUTRITION & DIETETICS-

CiteScore

4.90

自引率

3.30%

发文量

512

期刊介绍： Clinical Nutrition ESPEN is an electronic-only journal and is an official publication of the European Society for Clinical Nutrition and Metabolism (ESPEN). Nutrition and nutritional care have gained wide clinical and scientific interest during the past decades. The increasing knowledge of metabolic disturbances and nutritional assessment in chronic and acute diseases has stimulated rapid advances in design, development and clinical application of nutritional support. The aims of ESPEN are to encourage the rapid diffusion of knowledge and its application in the field of clinical nutrition and metabolism. Published bimonthly, Clinical Nutrition ESPEN focuses on publishing articles on the relationship between nutrition and disease in the setting of basic science and clinical practice. Clinical Nutrition ESPEN is available to all members of ESPEN and to all subscribers of Clinical Nutrition.