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Abstract #1106

Spatial Heterogeneity Analysis of DCE- and DW-MRI Using the Logistic Ridge Regression to Predict Breast Cancer Response to Neoadjuvant Therapy

Xia Li 1 , Hakmook Kang 1 , Lori R. Arlinghaus 1 , A. Bapsi Chakravarthy 1 , Richard G Abramson 1 , Vandana Abramson 1 , and Thomas E Yankeelov 1

1 Vanderbilt University, Nashville, Tennessee, United States

DCE- and DW-MRI have been used to predict the response of breast tumors to neoadjuvant chemotherapy (NAC). However, most studies quantify changes in parameters averaged over the tumor ROI and therefore discard all spatial information related to tissue heterogeneity. In this study, a novel voxel-by-voxel analysis based on a logistic ridge regression model was employed to optimize the ability of DCE- and DW-MRI to predict the response of breast tumors to NAC. The results indicate that incorporating changes in the spatial heterogeneity in DCE- and DW-MRI data improves the ability to predict treatment response for breast cancer patients receiving NAC.

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