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Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients

机译:乳腺MRI辐射射清,用于节点阳性乳腺癌患者对新辅助化疗的反应预处理预测

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The purpose of this study was to evaluate breast MRI radiomics in predicting, prior to any treatment, the response to neoadjuvant chemotherapy (NAC) in patients with invasive lymph node-positive breast cancer for 2 tasks: 1) prediction of pathologic complete response and 2) prediction of post-NAC lymph node (LN) status. Our study included 158 patients with 19 showing post-NAC complete pathologic response (pathologic TNM stage TO,NO,MX) and 139 showing incomplete response, 42 patients were post-NAC LN-negative and 116 were post-NAC LN-positive. Only pre-NAC MRIs underwent computer analysis, initialized by an expert breast radiologist indicating index cancers and metastatic axillary sentinel lymph nodes on DCE-MRI images. Forty-nine radiomic features were extracted, both for the primary cancers and for the metastatic sentinel lymph nodes. Since the dataset contained MRIs acquired at 1.5T and at 3.0T, we eliminated features affected by magnet strength as demonstrated in the Mann-Whitney U-test by rejection of the null-hypothesis that samples were selected from populations having the same distribution. ROC analysis was used to assess performance of individual features in the 2 classification tasks. Eighteen features appeared unaffected by magnet strength, of which only a single pre-NAC tumor feature outperformed random guessing in predicting pathologic complete response. On the other hand, 13 and 10 pre-NAC lymph node features were able to predict pathologic complete response and post-NAC LN-status, respectively, with as most promising feature the standard deviation within the LN at the first post-contrast DCE-MRI time-point (areas under the ROC curve: 0.79 (standard error 0.06) and 0.70 (0.05), respectively).
机译:本研究的目的是评估在任何治疗之前预测乳房MRI射线组学,在侵入性淋巴结阳性乳腺癌患者中对新辅助化疗(NAC)的反应2任务:1)预测病理完全反应和2 )预测NAC淋巴结(LN)状态。我们的研究包括158例,19例患者显示NAC后完全病理反应(病理TNM阶段,不,MX)和139,显示不完全反应,42名患者是NAC LN阴性,116例均为NAC LN阳性。只有NAC前的MRIS接受了计算机分析,由专家乳房放射科医师初始化,指示DCE-MRI图像上的指数癌症和转移性腋窝哨淋巴结。提取四十九个射粒特征,用于初前癌症和转移哨淋巴结淋巴结。由于数据集包含在1.5T和3.0T时获得的MRI,因此我们通过抑制来自具有相同分布的群体的零假设来消除受磁体强度影响的磁体强度影响的特征。 ROC分析用于评估2个分类任务中的个别功能的性能。由磁体强度不受影响的十八个特征,其中只有单一的NAC肿瘤特征在预测病理完全反应方面只能猜测随机猜测。另一方面,13和10个前NAC淋巴结特征能够分别预测病理完全响应和后NAC后状态,因为最有希望的特征在第一个与对比度后的第一个对比度的LN内的标准偏差MRI时间点(ROC曲线下的区域:0.79(标准误差0.06)和0.70(0.05))。

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