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.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
