本研究的目的是评估新辅助化疗期间超快速动态对比增强磁共振成像（DCE-MRI）的时间趋势，并研究DCE-MRI参数的变化是否可以早期预测乳腺癌的病理完全缓解（pCR）。本纵向研究于2021年2月至2022年2月期间，连续招募乳腺癌患者，并在治疗前后两个、四个和六个新辅助化疗周期进行了超快速DCE-MRI检查。在每个时间点，测量了五个超快速DCE-MRI参数（最大斜率[MS]、达峰时间[TTP]、增强时间[TTE]、峰值增强强度[PEI]和初始60秒曲线下面积[iAUC]）以及肿瘤大小。还额外测量并比较了相邻时间点之间参数的变化情况。采用广义估计方程分析了纵向数据。利用接受者操作特征曲线下面积（AUC）评估预测pCR的性能。共纳入了67名女性（平均年龄50±8 [标准差]岁，年龄范围：25-69岁），其中19名患者实现了pCR。在新辅助化疗过程中，MS、PEI、iAUC和肿瘤大小均减小，而TTP增加（所有P < 0.001）。结合超快速DCE-MRI参数变化值（从时间点1到时间点2）和临床病理特征的模型的AUC（0.92；95%置信区间[CI]：0.83-0.97）高于临床模型的AUC（0.79；95% CI：0.68-0.88）以及与临床病理特征相结合的时间点2的超快速DCE-MRI参数模型的AUC（0.82；95% CI：0.71-0.90）（均P = 0.01和0.02）。新辅助化疗后超快速DCE-MRI参数的早期变化结合临床病理特征可以作为乳腺癌pCR的预测标志物。版权所有© 2023 Société française de radiologie。由Elsevier Masson SAS出版。保留所有权利。

The purpose of this study was to evaluate the temporal trends of ultrafast dynamic contrast-enhanced (DCE)-MRI during neoadjuvant chemotherapy (NAC) and to investigate whether the changes in DCE-MRI parameters could early predict pathologic complete response (pCR) of breast cancer.This longitudinal study prospectively recruited consecutive participants with breast cancer who underwent ultrafast DCE-MRI examinations before treatment and after two, four, and six NAC cycles between February 2021 and February 2022. Five ultrafast DCE-MRI parameters (maximum slope [MS], time-to-peak [TTP], time-to-enhancement [TTE], peak enhancement intensity [PEI], and initial area under the curve in 60 s [iAUC]) and tumor size were measured at each timepoint. The changes in parameters between each pair of adjacent timepoints were additionally measured and compared between the pCR and non-pCR groups. Longitudinal data were analyzed using generalized estimating equations. The performance for predicting pCR was assessed using area under the receiver operating characteristic curve (AUC).Sixty-seven women (mean age, 50 ± 8 [standard deviation] years; age range: 25-69 years) were included, 19 of whom achieved pCR. MS, PEI, iAUC, and tumor size decreased, while TTP increased during NAC (all P < 0.001). The AUC (0.92; 95% confidence interval [CI]: 0.83-0.97) of the model incorporating ultrafast DCE-MRI parameter change values (from timepoints 1 to 2) and clinicopathologic characteristics was greater than that of the clinical model (AUC, 0.79; 95% CI: 0.68-0.88) and ultrafast DCE-MRI parameter model at timepoint 2 when combined with clinicopathologic characteristics (AUC, 0.82; 95% CI: 0.71-0.90) (P = 0.01 and 0.02).Early changes in ultrafast DCE-MRI parameters after NAC combined with clinicopathologic characteristics could serve as predictive markers of pCR of breast cancer.Copyright © 2023 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.