Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
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DOI：
10.1002/jmri.26701
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发表时间：
2019-10
期刊：
影响因子：
--
通讯作者：
Xu K
中科院分区：
文献类型：
--
作者：
Chai R;Ma H;Xu M;Arefan D;Cui X;Liu Y;Zhang L;Wu S;Xu K
腋窝淋巴结状态对乳腺癌分期和个体化治疗计划至关重要。目的：评估乳腺mri放射特征对腋窝淋巴结（ALN）转移的鉴别作用，并比较不同mri序列的鉴别能力。回顾。120例乳腺癌患者经病理证实，有ALN转移59例，无转移61例。3所示。0T扫描仪，包括t1加权成像、t2加权成像、弥散加权成像和动态对比增强（DCE）序列。从动态增强序列的T1WI、T2WI、DWI和对比后第二阶段（CE2） 4个序列中提取出肿瘤的典型形态和纹理特征。从所有DCE序列（1个造影前和7个造影后阶段）中提取额外的对比度增强动力学特征。当使用单个序列或组合序列的特征来区分ALN转移状态时，建立线性判别分析分类器并进行比较。进行Mann-Whitney u检验、Fisher精确检验、最小绝对收缩选择算子（LASSO）回归和受试者工作特征分析。4个序列对T1WI、CE2、T2WI和DWI的准确率/AUC分别为79%/0.87、77%/0.85、74%/0.79和79%/0.85。当加入动力学特征增强CE2时，模型达到了最高的性能（精度= 0.86,AUC = 0.91）。当四个序列的所有特征和动力学相结合时，它没有导致性能的进一步提高（P = 0.48）。乳腺肿瘤术前乳腺MRI序列放射学特征与ALN转移状态相关，其中CE2期和对比增强动力学特征的分类效果最高。
The axillary lymph node status is critical for breast cancer staging and individualized treatment planning. 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. Retrospective. In all, 120 breast cancer patients, 59 with ALN metastasis and 61 without metastasis, all confirmed by pathology. 3 .0T scanner with T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced (DCE) sequences. Typical morphological and texture features of the segmented tumor were extracted from four sequences, ie, T1WI, T2WI, 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. Mann–Whitney U-test, Fisher’s exact test, least absolute shrinkage selection operator (LASSO) regression, and receiver operating characteristic analysis were performed. The accuracy/AUC of the four sequences was 79%/0.87, 77%/0.85, 74%/0.79, and 79%/0.85 for the T1WI, CE2, T2WI, 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). 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.
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影响因子：
19.7
作者：
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通讯作者：
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