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Abstract #0876

Differentiation Idiopathic Granulomatous Mastitis and Breast Carcinoma: Value of Whole-Lesion Histogram and Texture Analysis Using Quantitative ADC Map

Qiufeng Zhao1, Tianwen Xie2, Caixia Fu3, Qiong Li1, Mingqin Yan1, Shijie Zhang1, Fei Duan1, Huimei Chao1, Robert Grimm4, and Song Wang1

1Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China, 2Radiology, Fudan University Shanghai Cancer Center, Shanghai, China, 3MR Application Development, Siemens Shenzhen Magnetic Resonance, Shenzhen, China, 4MR Application Predevelopment, Siemens Healthcare, Erlangen, Germany

Recently, DWI has been increasingly used in distinguishing benign inflammation lesions and breast cancers. A total of 15 patients with invasive ductal carcinoma (IDC) and 10 patients with idiopathic granulomatous mastitis (IGM) were retrospectively evaluated. We extracted the whole-lesion histogram and textural features from the ADC map. Univariate and multivariate logistic regression analysis was performed. The area under the curve (AUC) at the best cut-off point was assessed. Using the three significant features (difference entropy, difference variance and entropy of ADC), we obtained an AUC of 0.953 (95% CI: 0.787, 0.998) for the differentiation between IGM group from tumor group.

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