基于磁共振成像的乳腺癌新辅助治疗个性化模型

MRI-Based Model for Personalizing Neoadjuvant Treatment in Breast Cancer.

作者信息

Li Wen, Onishi Natsuko, Gibbs Jessica E, Wilmes Lisa J, Le Nu N, Metanat Pouya, Price Elissa R, Joe Bonnie N, Kornak John, Yau Christina, Wolf Denise M, Magbanua Mark Jesus M, LeStage Barbara, van 't Veer Laura J, DeMichele Angela M, Esserman Laura J, Hylton Nola M

机构信息

Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94158, USA.

Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA.

出版信息

Tomography. 2025 Feb 27;11(3):26. doi: 10.3390/tomography11030026.

DOI:10.3390/tomography11030026

PMID:40137566

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11946387/

Abstract

BACKGROUND

Functional tumor volume (FTV), measured from dynamic contrast-enhanced MRI, is an imaging biomarker that can predict treatment response in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). The FTV-based predictive model, combined with core biopsy, informed treatment decisions of recommending patients with excellent responses to proceed to surgery early in a large NAC clinical trial.

METHODS

In this retrospective study, we constructed models using FTV measurements. We analyzed performance tradeoffs when a probability threshold was used to identify excellent responders through the prediction of pathology complete response (pCR). Individual models were developed within cohorts defined by the hormone receptor and human epidermal growth factor receptor 2 (HR/HER2) subtype.

RESULTS

A total of 814 patients enrolled in the I-SPY 2 trial between 2010 and 2016 were included with a mean age of 49 years (range: 24 to 77). Among these patients, 289 (36%) achieved pCR. The area under the ROC curve (AUC) ranged from 0.68 to 0.74 for individual HR/HER2 subtypes. When probability thresholds were chosen based on minimum positive predictive value (PPV) levels of 50%, 70%, and 90%, the PPV-sensitivity tradeoff varied among subtypes. The highest sensitivities (100%, 87%, 45%) were found in the HR-/HER2+ sub-cohort for probability thresholds of 0, 0.62, and 0.72; followed by the triple-negative sub-cohort (98%, 52%, 4%) at thresholds of 0.13, 0.58, and 0.67; and HR+/HER2+ (78%, 16%, 8%) at thresholds of 0.34, 0.57, and 0.60. The lowest sensitivities (20%, 0%, 0%) occurred in the HR+/HER2- sub-cohort.

CONCLUSIONS

Predictive models developed using imaging biomarkers, alongside clinically validated probability thresholds, can be incorporated into decision-making for precision oncology.

摘要

背景

通过动态对比增强磁共振成像测量的功能性肿瘤体积（FTV）是一种成像生物标志物，可预测接受新辅助化疗（NAC）的乳腺癌患者的治疗反应。基于FTV的预测模型，结合核心活检，在一项大型NAC临床试验中为推荐反应良好的患者尽早进行手术的治疗决策提供了依据。

方法

在这项回顾性研究中，我们使用FTV测量构建模型。我们通过预测病理完全缓解（pCR）分析了使用概率阈值识别优秀反应者时的性能权衡。在由激素受体和人表皮生长因子受体2（HR/HER2）亚型定义的队列中开发个体模型。

结果

2010年至2016年期间纳入I-SPY 2试验的814例患者，平均年龄49岁（范围：24至77岁）。在这些患者中，289例（36%）实现了pCR。各HR/HER2亚型的ROC曲线下面积（AUC）在0.68至0.74之间。当根据50%、70%和90%的最小阳性预测值（PPV）水平选择概率阈值时，PPV-敏感性权衡在各亚型之间有所不同。在HR-/HER2+亚组中，概率阈值为0、0.62和0.72时，敏感性最高（分别为100%、87%、45%）；其次是三阴性亚组（分别为98%、52%、4%），阈值分别为0.13、0.58和0.67；HR+/HER2+亚组（分别为78%、16%、8%），阈值分别为0.34、0.57和0.60。最低敏感性（分别为20%、0%、0%）出现在HR+/HER2-亚组中。