基于磁共振成像的纹理分析在评估乳腺叶状肿瘤组织病理学分级中的预测价值

The Predictive Value of Magnetic Resonance Imaging-based Texture Analysis in Evaluating Histopathological Grades of Breast Phyllodes Tumor.

作者信息

Mao Yifei, Xiong Zhongtang, Wu Songxin, Huang Zhiqing, Zhang Ruoxian, He Yuqin, Peng Yuling, Ye Yang, Dong Tianfa, Mai Hui

机构信息

Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Department of Pathology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

出版信息

J Breast Cancer. 2022 Apr;25(2):117-130. doi: 10.4048/jbc.2022.25.e14.

DOI:10.4048/jbc.2022.25.e14

PMID:35506580

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9065359/

Abstract

PURPOSE

Knowing the distinction between benign and borderline/malignant phyllodes tumors (PTs) can help in the surgical treatment course. Herein, we investigated the value of magnetic resonance imaging-based texture analysis (MRI-TA) in differentiating between benign and borderline/malignant PTs.

METHODS

Forty-three women with 44 histologically proven PTs underwent breast MRI before surgery and were classified into benign (n = 26) and borderline/malignant groups (n = 18 [15 borderline, 3 malignant]). Clinical and routine MRI parameters (CRMP) and MRI-TA were used to distinguish benign from borderline/malignant PT. In total, 298 texture parameters were extracted from fat-suppression (FS) T2-weighted, FS unenhanced T1-weighted, and FS first-enhanced T1-weighted sequences. To evaluate the diagnostic performance, receiver operating characteristic curve analysis was performed for the K-nearest neighbor classifier trained with significantly different parameters of CRMP, MRI sequence-based TA, and the combination strategy.

RESULTS

Compared with benign PTs, borderline/malignant ones presented a higher local recurrence ( = 0.045); larger size ( < 0.001); different time-intensity curve pattern ( = 0.010); and higher frequency of strong lobulation ( = 0.024), septation enhancement ( = 0.048), cystic component ( = 0.023), and irregular cystic wall ( = 0.045). TA of FS T2-weighted images (0.86) showed a significantly higher area under the curve (AUC) than that of FS unenhanced T1-weighted (0.65, = 0.010) or first-enhanced phase (0.72, = 0.049) images. The texture parameters of FS T2-weighted sequences tended to have a higher AUC than CRMP (0.79, = 0.404). Additionally, the combination strategy exhibited a similar AUC (0.89, = 0.622) in comparison with the texture parameters of FS T2-weighted sequences.

CONCLUSION

MRI-TA demonstrated good predictive performance for breast PT pathological grading and could provide surgical planning guidance. Clinical data and routine MRI features were also valuable for grading PTs.

摘要

目的

了解良性与交界性/恶性叶状肿瘤（PTs）之间的区别有助于手术治疗过程。在此，我们研究了基于磁共振成像的纹理分析（MRI-TA）在鉴别良性与交界性/恶性PTs中的价值。

方法

43例经组织学证实患有44个PTs的女性在手术前行乳腺MRI检查，并分为良性组（n = 26）和交界性/恶性组（n = 18 [15个交界性，3个恶性]）。临床和常规MRI参数（CRMP）以及MRI-TA用于区分良性与交界性/恶性PT。总共从脂肪抑制（FS）T2加权、FS未增强T1加权和FS首次增强T1加权序列中提取了298个纹理参数。为评估诊断性能，对使用CRMP、基于MRI序列的TA和联合策略的显著不同参数训练的K近邻分类器进行了受试者操作特征曲线分析。

结果

与良性PTs相比，交界性/恶性PTs表现出更高的局部复发率（= 0.045）；更大的尺寸（< 0.001）；不同的时间-强度曲线模式（= 0.010）；以及更高的强分叶频率（= 0.024）、分隔增强（= 0.048）、囊性成分（= 0.023）和不规则囊壁（= 0.045）。FS T2加权图像的TA（0.86）显示曲线下面积（AUC）显著高于FS未增强T1加权图像（0.65，= 0.010）或首次增强期图像（0.72，= 0.049）。FS T2加权序列的纹理参数倾向于比CRMP具有更高的AUC（0.79，= 0.404）。此外，与FS T2加权序列的纹理参数相比，联合策略表现出相似的AUC（0.89，= 0.622）。