Abstract #1117

Characterization of Breast Tumor using Machine Learning based upon Multi-parametric MRI Features.

Snekha Thakran¹, Rakesh Kumar Gupta², and Anup Singh^1,3

¹Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, Delhi, India, ²Department of Radiology, Fortis Memorial Research Institute, Haryana, Gurgaon, India, Delhi, India, ³Department of Biomedical Engineering, All India Institute of Medical Science, New Delhi, India, Delhi, India

Multi-parametric MRI(mp-MRI) has shown promising outcomes with high sensitivity and accuracy in the characterization of breast tumor. Quantitative analysis of mp-MRI and texture features with machine learning approach have also shown potential in improving accuracy of breast tumor classification. The objective of this study was to differentiate low-grade vs. high-grade breast tumor using machine learning with optimized feature vector obtained from mp-MRI data. The study included mp-MRI data of 35 patients with breast cancer. The combination of support-vector-machine(SVM) with Wrapper method using Adaptive-Boosting(AdaBoost) technique resulted in high sensitivity(0.94±0.07), specificity(0.80±0.05), and accuracy(0.90±5.48) in classification of low-grade vs. high-grade tumors.

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