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Abstract #3827

Accurate Discrimination of Benign and Malignant Breast Cancer in Suspicious Tumors Based on Semi-Quantitative DCE-MRI Employing Support Vector Machine

Saeedeh Navaei Lavasani 1,2 , Masoomeh Gity 3 , Mahnaz Nabil 1,4 , Anahita Fathi Kazerooni 1,2 , and Hamidreza Saligheh Rad 1,2

1 Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran, 2 Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran, 3 Department of Radiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran, 4 Department of Statistics, Tarbiat Modares University, Tehran, Iran

Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI) is widely used as sensitive tool in breast tumor diagnosis. Interpretation of breast MRI requires focusing not only on morphologic changes, but also on the quantification of the areas with increased enhancement. In this setting, accurate selection of quantitative parameters and classification approach could result in reliable tumor differentiation. We propose an accurate approach, based on support vector machine classiļ¬cation of dynamic features of suspicious tumors within the breast to discriminate malignant or benign breast lesions.

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