Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment.

IF 5.6 Q1 ONCOLOGY Radiology. Imaging cancer Pub Date : 2023-07-01 DOI:10.1148/rycan.220126
Natsuko Onishi, Teffany Joy Bareng, Jessica Gibbs, Wen Li, Elissa R Price, Bonnie N Joe, John Kornak, Laura J Esserman, David C Newitt, Nola M Hylton
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Abstract

Purpose To investigate the impact of longitudinal variation in functional tumor volume (FTV) underestimation and overestimation in predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Materials and Methods Women with breast cancer who were enrolled in the prospective I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2) from May 2010 to November 2016 were eligible for this retrospective analysis. Participants underwent four MRI examinations during NAC treatment. FTV was calculated based on automated segmentation. Baseline FTV before treatment (FTV0) and the percentage of FTV change at early treatment and inter-regimen time points relative to baseline (∆FTV1 and ∆FTV2, respectively) were classified into high-standard or standard groups based on visual assessment of FTV under- and overestimation. Logistic regression models predicting pCR using single predictors (FTV0, ∆FTV1, and ∆FTV2) and multiple predictors (all three) were developed using bootstrap resampling with out-of-sample data evaluation with the area under the receiver operating characteristic curve (AUC) independently in each group. Results This study included 432 women (mean age, 49.0 years ± 10.6 [SD]). In the FTV0 model, the high-standard and standard groups showed similar AUCs (0.61 vs 0.62). The high-standard group had a higher estimated AUC compared with the standard group in the ∆FTV1 (0.74 vs 0.63), ∆FTV2 (0.79 vs 0.62), and multiple predictor models (0.85 vs 0.64), with a statistically significant difference for the latter two models (P = .03 and P = .01, respectively). Conclusion The findings in this study suggest that longitudinal variation in FTV estimation needs to be considered when using early FTV change as an MRI-based criterion for breast cancer treatment personalization. Keywords: Breast, Cancer, Dynamic Contrast-enhanced, MRI, Tumor Response ClinicalTrials.gov registration no. NCT01042379 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Ram in this issue.

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肿瘤体积估算纵向变化对磁共振成像指导下乳腺癌新辅助治疗个性化的影响
目的 研究功能性肿瘤体积(FTV)低估和高估的纵向变化对预测新辅助化疗(NAC)后病理完全反应(pCR)的影响。材料与方法 2010年5月至2016年11月期间参加前瞻性I-SPY 2 TRIAL(利用成像和分子分析预测治疗反应的系列研究2)的乳腺癌女性患者有资格参加此次回顾性分析。参与者在 NAC 治疗期间接受了四次 MRI 检查。FTV根据自动分割计算。根据对 FTV 低估和高估的目测评估,将治疗前的基线 FTV(FTV0)以及早期治疗和疗程间时间点相对于基线的 FTV 变化百分比(分别为 ∆FTV1 和 ∆FTV2)分为高标准组和标准组。采用引导重采样法(bootstrap resampling)建立了使用单一预测因子(FTV0、ΔFTV1 和 ΔFTV2)和多重预测因子(所有三个)预测 pCR 的逻辑回归模型,并对样本外数据进行了评估,每组的接收器操作特征曲线下面积(AUC)均为独立的。结果 本研究纳入了 432 名女性(平均年龄 49.0 岁 ± 10.6 [SD])。在 FTV0 模型中,高标准组和标准组的 AUC 相似(0.61 vs 0.62)。与标准组相比,高标准组在 ∆FTV1(0.74 vs 0.63)、∆FTV2(0.79 vs 0.62)和多重预测模型(0.85 vs 0.64)中的估计 AUC 更高,后两个模型的差异具有统计学意义(分别为 P = .03 和 P = .01)。结论 本研究结果表明,在使用早期 FTV 变化作为基于 MRI 的乳腺癌个性化治疗标准时,需要考虑 FTV 估计的纵向变化。关键词乳腺癌 动态对比增强 MRI 肿瘤反应 ClinicalTrials.gov registration no.本文有补充材料。© RSNA, 2023 另请参阅本期Ram的评论。
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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