Abstract #2340

Integration of DCE-MRI Texture Features with Clinical Data for Improved Early Prediction of Breast Cancer Therapy Response

Archana Machireddy¹, Guillaume Thibault¹, Alina Tudorica¹, Aneela Afzal¹, May Mishal¹, Kathleen Kemmer¹, Arpana Naik¹, Megan Troxell¹, Eric Goranson¹, Karen Oh¹, Nicole Roy¹, Neda Jafarian¹, Megan Holtorf¹, Wei Huang¹, and Xubo Song¹

¹Oregon Health and Science University, Portland, OR, United States

This study investigated the effect of integrating clinical data with DCE-MRI texture features in early prediction of breast cancer therapy response. DCE-MRI data collected from 55 breast cancer patients before and after the first cycle of neoadjuvant chemotherapy were subjected to pharmacokinetic analysis. Texture features were extracted from voxel-based DCE-MRI parametric maps. Predictive performances with imaging features alone and in combination with clinical features were assessed and compared. Addition of clinical features to image texture features increased predictive capability in discriminating pathologic complete response (pCR) vs. non-pCR compared to using imaging features alone.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.