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Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences

乳腺癌 医学 淋巴结 精确检验 转移 曼惠特尼U检验 磁共振成像 接收机工作特性 乳房磁振造影 腋窝淋巴结 前哨淋巴结 动态增强MRI 线性判别分析 放射科 核医学 癌症 乳腺摄影术 病理 内科学 计算机科学 人工智能
作者
Ruimei Chai,He Ma,Mingjie Xu,Dooman Arefan,Xiaoyu Cui,Yi Liu,Lina Zhang,Shandong Wu,Ke Xu
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:50 (4): 1125-1132 被引量:64
标识
DOI:10.1002/jmri.26701
摘要

Background The axillary lymph node status is critical for breast cancer staging and individualized treatment planning. Purpose To assess the effect of determining axillary lymph node (ALN) metastasis by breast MRI‐derived radiomic signatures, and compare the discriminating abilities of different MR sequences. Study Type Retrospective. Population In all, 120 breast cancer patients, 59 with ALN metastasis and 61 without metastasis, all confirmed by pathology. Field Strength/Sequence 3 .0T scanner with T 1 ‐weighted imaging, T 2 ‐weighted imaging, diffusion‐weighted imaging, and dynamic contrast‐enhanced (DCE) sequences. Assessment Typical morphological and texture features of the segmented tumor were extracted from four sequences, ie, T 1 WI, T 2 WI, DWI, and the second postcontrast phase (CE2) of the dynamic contrast‐enhanced sequences. Additional contrast enhancement kinetic features were extracted from all DCE sequences (one pre‐ and seven postcontrast phases). Linear discriminant analysis classifiers were built and compared when using features from an individual sequence or the combination of the sequences in differentiating the ALN metastasis status. Statistical Tests Mann–Whitney U ‐test, Fisher's exact test, least absolute shrinkage selection operator (LASSO) regression, and receiver operating characteristic analysis were performed. Results The accuracy/AUC of the four sequences was 79%/0.87, 77%/0.85, 74%/0.79, and 79%/0.85 for the T 1 WI, CE2, T 2 WI, and DWI, respectively. When CE2 was augmented by adding kinetic features, the model achieved the highest performance (accuracy = 0.86 and AUC = 0.91). When all features from the four sequences and the kinetics were combined, it did not lead to a further increase in the performance ( P = 0.48). Data Conclusion Breast tumor's radiomic signatures from preoperative breast MRI sequences are associated with the ALN metastasis status, where CE2 phase and the contrast enhancement kinetic features lead to the highest classification effect. Level of Evidence 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2019;50:1125–1132.
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