An Apparent Diffusion Coefficient Histogram Method Versus a Traditional 2-Dimensional Measurement Method for Identifying Non–Puerperal Mastitis From Breast Cancer at 3.0 T

医学 有效扩散系数 峰度 感兴趣区域 核医学 接收机工作特性 直方图 百分位 乳腺癌 再现性 曼惠特尼U检验 偏斜 放射科 癌症 数学 统计 人工智能 磁共振成像 内科学 图像(数学) 计算机科学
作者
Qi Tang,Qiang Li,Dong Xie,Ketao Chu,Lidong Liu,Chengcheng Liao,Yunying Qin,Zheng Wang,Danke Su
出处
期刊:Journal of Computer Assisted Tomography [Ovid Technologies (Wolters Kluwer)]
卷期号:42 (5): 776-783 被引量:9
标识
DOI:10.1097/rct.0000000000000758
摘要

Purpose This study aimed to investigate the utility of a volumetric apparent diffusion coefficient (ADC) histogram method for distinguishing non–puerperal mastitis (NPM) from breast cancer (BC) and to compare this method with a traditional 2-dimensional measurement method. Materials and Methods Pretreatment diffusion-weighted imaging data at 3.0 T were obtained for 80 patients (NPM, n = 27; BC, n = 53) and were retrospectively assessed. Two readers measured ADC values according to 2 distinct region-of-interest (ROI) protocols. The first protocol included the generation of ADC histograms for each lesion, and various parameters were examined. In the second protocol, 3 freehand (TF) ROIs for local lesions were generated to obtain a mean ADC value (defined as ADC-ROI TF ). All of the ADC values were compared by an independent-samples t test or the Mann-Whitney U test. Receiver operating characteristic curves and a leave-one-out cross-validation method were also used to determine diagnostic deficiencies of the significant parameters. Results The ADC values for NPM were characterized by significantly higher mean, 5th to 95th percentiles, and maximum and mode ADCs compared with the corresponding ADCs for BC (all P < 0.05). However, the minimum, skewness, and kurtosis ADC values, as well as ADC-ROI TF , did not significantly differ between the NPM and BC cases. Conclusions Thus, the generation of volumetric ADC histograms seems to be a superior method to the traditional 2-dimensional method that was examined, and it also seems to represent a promising image analysis method for distinguishing NPM from BC.
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