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

IF 2.2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Tomography Pub Date : 2024-11-20 DOI:10.3390/tomography10110134

Wen Li, Nu N Le, Rohan Nadkarni, Natsuko Onishi, Lisa J Wilmes, Jessica E Gibbs, Elissa R Price, Bonnie N Joe, Rita A Mukhtar, Efstathios D Gennatas, John Kornak, Mark Jesus M Magbanua, Laura J Van't Veer, Barbara LeStage, Laura J Esserman, Nola M Hylton

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引用次数: 0

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 (p < 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 (p < 0.001) and from 0.65 ± 0.06 to 0.73 ± 0.06 (p < 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.

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预测乳腺癌新辅助化疗早期不良反应的肿瘤形态学：一项多中心回顾性研究

研究背景这项多中心回顾性研究探讨了治疗前（T0）和早期治疗时间点（T1）的功能性肿瘤体积（FTV）肿瘤掩膜得出的肿瘤形态学特征在预测接受新辅助化疗的乳腺癌患者病理结果方面的附加价值：多中心 I-SPY 2 试验共纳入 910 例患者。通过动态对比增强（DCE）磁共振成像计算FTV和肿瘤形态特征。不良反应的定义是手术切除时残留癌负荷（RCB）达到 III 级（RCB-III）。接收者操作特征曲线下面积（AUC）用于评估预测性能。分析在整个队列和按激素受体（HR）和人表皮生长因子受体2（HER2）状态分层的各个子队列中进行：在整个队列中，使用 FTV 比值和临床病理数据的 AUC 为 0.64 ± 0.03（平均值 ± SD [标准差]）。根据形态学特征，AUC 显著增加到 0.76 ± 0.04（p < 0.001）。T0 和 T1 之间的表面积与体积比是贡献最大的特征。所有贡献最大的特征都来自 T1。在HR+/HER2-和三阴性亚组中也观察到了改善。增加形态特征后，AUC 分别从 0.56 ± 0.05 显著增加到 0.70 ± 0.06（p < 0.001），从 0.65 ± 0.06 显著增加到 0.73 ± 0.06（p < 0.001）：结论：与在早期治疗时间点仅使用 FTV 相比，肿瘤形态特征可提高 RCB-III 的预测效果。

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

Tomography Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

2.70

自引率

10.50%

发文量

222

期刊介绍： TomographyTM publishes basic (technical and pre-clinical) and clinical scientific articles which involve the advancement of imaging technologies. Tomography encompasses studies that use single or multiple imaging modalities including for example CT, US, PET, SPECT, MR and hyperpolarization technologies, as well as optical modalities (i.e. bioluminescence, photoacoustic, endomicroscopy, fiber optic imaging and optical computed tomography) in basic sciences, engineering, preclinical and clinical medicine. Tomography also welcomes studies involving exploration and refinement of contrast mechanisms and image-derived metrics within and across modalities toward the development of novel imaging probes for image-based feedback and intervention. The use of imaging in biology and medicine provides unparalleled opportunities to noninvasively interrogate tissues to obtain real-time dynamic and quantitative information required for diagnosis and response to interventions and to follow evolving pathological conditions. As multi-modal studies and the complexities of imaging technologies themselves are ever increasing to provide advanced information to scientists and clinicians. Tomography provides a unique publication venue allowing investigators the opportunity to more precisely communicate integrated findings related to the diverse and heterogeneous features associated with underlying anatomical, physiological, functional, metabolic and molecular genetic activities of normal and diseased tissue. Thus Tomography publishes peer-reviewed articles which involve the broad use of imaging of any tissue and disease type including both preclinical and clinical investigations. In addition, hardware/software along with chemical and molecular probe advances are welcome as they are deemed to significantly contribute towards the long-term goal of improving the overall impact of imaging on scientific and clinical discovery.