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Abstract #4334

Diagnostic Assessment of Breast Cancer in Non-Contrast MRI Images Through an Artificial Intelligence Machine Learning Algorithm

Craig Neal Detheridge1, Philip Saponara1, Jaspreet Bhangu1, Boris Nicholas Bloch2, and Kevin Thomas1

1Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, United States, 2Radiology, Boston Medical Center, Boston, MA, United States

Contrast-Enhanced Breast MRI is a common method for diagnosis of Breast Cancer. An Artificial Intelligence Machine Learning Algorithm was developed to analyze Non-Contrast Breast MRI scans and predict diagnoses. The algorithm was trained using MRI data that had pathological specimens to validate diagnoses, obtained from The Cancer Imaging Archive. The AI was found to be 95% accurate in classifying tissue as cancerous or benign. This algorithm could be used to assist diagnoses in clinical practice. Future work will assess the generalizability of the algorithm on data from other scan sites, and the potential for classifying specific subtypes of Breast Cancer.

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