肿瘤形态学预测乳腺癌新辅助化疗早期不良反应的多中心回顾性研究。

Tumor Morphology for Prediction of Poor Responses Early in Neoadjuvant Chemotherapy for Breast Cancer: A Multicenter Retrospective Study.

机构信息

Department of Radiology and Biomedical Imaging, University of California, 550 16th Street, San Francisco, CA 94158, USA.

Department of Surgery, University of California, San Francisco, 550 16th Street, San Francisco, CA 94158, USA.

出版信息

Tomography. 2024 Nov 20;10(11):1832-1845. doi: 10.3390/tomography10110134.

DOI:10.3390/tomography10110134

PMID:39590943

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11598075/

Abstract

BACKGROUND

This multicenter and retrospective study investigated the additive value of tumor morphologic features derived from the functional tumor volume (FTV) tumor mask at pre-treatment (T0) and the early treatment time point (T1) in the prediction of pathologic outcomes for breast cancer patients undergoing neoadjuvant chemotherapy.

METHODS

A total of 910 patients enrolled in the multicenter I-SPY 2 trial were included. FTV and tumor morphologic features were calculated from the dynamic contrast-enhanced (DCE) MRI. A poor response was defined as a residual cancer burden (RCB) class III (RCB-III) at surgical excision. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive performance. The analysis was performed in the full cohort and in individual sub-cohorts stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status.

RESULTS

In the full cohort, the AUCs for the use of the FTV ratio and clinicopathologic data were 0.64 ± 0.03 (mean ± SD [standard deviation]). With morphologic features, the AUC increased significantly to 0.76 ± 0.04 ( < 0.001). The ratio of the surface area to volume ratio between T0 and T1 was found to be the most contributing feature. All top contributing features were from T1. An improvement was also observed in the HR+/HER2- and triple-negative sub-cohorts. The AUC increased significantly from 0.56 ± 0.05 to 0.70 ± 0.06 ( < 0.001) and from 0.65 ± 0.06 to 0.73 ± 0.06 ( < 0.001), respectively, when adding morphologic features.

CONCLUSION

Tumor morphologic features can improve the prediction of RCB-III compared to using FTV only at the early treatment time point.

摘要

背景

本多中心回顾性研究探讨了治疗前（T0）和早期治疗时间点（T1）功能肿瘤体积（FTV）肿瘤掩模中肿瘤形态特征的附加价值，以预测接受新辅助化疗的乳腺癌患者的病理结果。

方法

共纳入多中心 I-SPY2 试验 910 例患者。从动态对比增强（DCE）MRI 计算 FTV 和肿瘤形态特征。残留癌负荷（RCB）为 III 级（RCB-III）定义为手术切除时的不良反应。受试者工作特征曲线下面积（AUC）用于评估预测性能。在全队列和按激素受体（HR）和人表皮生长因子受体 2（HER2）状态分层的亚队列中进行分析。

结果

在全队列中，FTV 比值和临床病理数据的 AUC 为 0.64 ± 0.03（平均值 ± SD）。使用形态特征，AUC 显著增加至 0.76 ± 0.04（<0.001）。发现 T0 和 T1 之间表面积与体积比的比值是最有贡献的特征。所有前 5 个贡献特征均来自 T1。在 HR+/HER2-和三阴性亚队列中也观察到了改善。当添加形态特征时，AUC 从 0.56 ± 0.05 显著增加至 0.70 ± 0.06（<0.001）和 0.65 ± 0.06 至 0.73 ± 0.06（<0.001）。