Abstract #0127

Texture Feature Analysis of Quantitative and Semi-Quantitative DCE-MRI Metrics for Early Prediction of Breast Cancer Therapy Response

Guillaume Thibault¹, Alina Tudorica², Aneela Afzal², Stephen Chui², Arpana Naik², Megan Troxell³, Kathleen Kemmer², Karen Oh², Nicole Roy², Megan Holtorf², Wei Huang², and Xubo Song²

¹BME, OHSU, Portland, OR, United States, ²OHSU, Portland, OR, United States, ³OHSU, portland, OR, United States

36 breast cancer patients underwent research DCE-MRI before and after one cycle of neoadjuvant chemotherapy. 3D tumor imaging texture features were extracted from parametric maps of quantitative pharmacokinetic (PK) and semi-quantitative DCE-MRI parameters, and correlated with pathologically measured post-therapy residual cancer burden (RCB). Texture features from quantitative PK parameters were found to be more useful than those from semi-quantitative metrics for early prediction of therapy response, while the features from the SSM PK parameters were superior to the SM counterparts for prediction of response.

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