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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