人工智能生成的三维身体成分可预测直肠癌新辅助化疗患者的剂量调整。

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer.

作者信息

Besson Alex, Cao Ke, Mardinli Ahmed, Wirth Lara, Yeung Josephine, Kokelaar Rory, Gibbs Peter, Reid Fiona, Yeung Justin M

机构信息

Department of Surgery - Western Precinct, The University of Melbourne, Melbourne, VIC, Australia.

Melbourne Academic Centre for Health, North Melbourne, Melbourne, VIC, Australia.

出版信息

J Cancer Res Clin Oncol. 2025 May 16;151(5):168. doi: 10.1007/s00432-025-06219-5.

DOI:10.1007/s00432-025-06219-5

PMID:40379920

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12084224/

Abstract

PURPOSE

Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition plays a crucial role in the pharmacokinetic and pharmacodynamic profile of cytotoxic agents and could inform optimal dosing. This study aims to assess how lumbosacral body composition influences adverse events in patients receiving neoadjuvant chemotherapy for rectal cancer.

METHODS

A retrospective study (February 2013 to March 2023) examined the impact of body composition on neoadjuvant treatment outcomes for rectal cancer patients. Staging CT scans were analysed using a validated AI model to measure lumbosacral skeletal muscle (SM), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue volume and density. Multivariate analyses explored the relationship between body composition and chemotherapy outcomes.

RESULTS

242 patients were included (164 males, 78 Females), median age 63.4 years. Chemotherapy dose reductions occurred more frequently in females (26.9% vs. 15.9%, p = 0.042) and in females with greater VAT density (-82.7 vs. -89.1, p = 0.007) and SM: IMAT + VAT volume ratio (1.99 vs. 1.36, p = 0.042). BSA was a poor predictor of dose reduction (AUC 0.397, sensitivity 38%, specificity 60%) for female patients, whereas the SM: IMAT + VAT volume ratio (AUC 0.651, sensitivity 76%, specificity 61%) and VAT density (AUC 0.699, sensitivity 57%, specificity 74%) showed greater predictive ability. Body composition didn't influence dose adjustment of male patients.

CONCLUSION

Lumbosacral body composition outperformed BSA in predicting adverse events in female patients with rectal cancer undergoing neoadjuvant chemotherapy.

摘要

目的

化疗给药是一项平衡工作，既要给予足够剂量以实现预期的肿瘤反应，又要限制不良反应。化疗剂量是基于体表面积（BSA）确定的。新出现的证据表明，身体组成在细胞毒性药物的药代动力学和药效学特征中起着关键作用，并且可以为优化给药提供依据。本研究旨在评估腰骶部身体组成如何影响接受直肠癌新辅助化疗患者的不良事件。

方法

一项回顾性研究（2013年2月至2023年3月）考察了身体组成对直肠癌患者新辅助治疗结果的影响。使用经过验证的人工智能模型分析分期CT扫描，以测量腰骶部骨骼肌（SM）、肌内脂肪组织（IMAT）、内脏脂肪组织（VAT）以及皮下脂肪组织的体积和密度。多变量分析探讨了身体组成与化疗结果之间的关系。

结果

纳入242例患者（164例男性，78例女性），中位年龄63.4岁。化疗剂量减少在女性中更频繁发生（26.9%对15.9%，p = 0.042），在VAT密度较高的女性中（-82.7对-89.1，p = 0.007）以及SM:IMAT + VAT体积比更高的女性中（1.99对1.36，p = 0.042）。对于女性患者，BSA是剂量减少的较差预测指标（AUC 0.397，敏感性38%，特异性60%），而SM:IMAT + VAT体积比（AUC 0.651，敏感性76%，特异性61%）和VAT密度（AUC 0.699，敏感性57%，特异性74%）显示出更强的预测能力。身体组成对男性患者的剂量调整没有影响。