Abstract #1134

Quantitative transport mapping for classifying malignant breast lesion: Comparison with kinetic modeling and enhancement characteristics

Qihao Zhang¹, Michele B Drotman¹, Christine Chen¹, Thanh Nguyen¹, Pascal Spincemaille¹, and Yi Wang²

¹Weill Cornell Medical College, New York, NY, United States, ²Cornell University, New York, NY, United States

We evaluate quantitative transport mapping (QTM) based on the inversion of transport equation without any arterial input function (AIF) for automatically postprocessing dynamic contrast enhanced MRI (DCE-MRI) to differentiate malignant and benign breast tumors using biopsy pathology as reference and comparing with traditional Kety’s method and enhancement curve characteristics (ECC). Automated QTM velocity was found to be the most accurate, then ECC enhancement amplitude with manual ROI, and lastly Kety’s K^trans with a manual AIF for differentiating malignant from benign breast tumor.

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