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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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