Abstract #4824

Multi-Center and Multi-Vendor Platform DCE-MRI Prediction of Breast Cancer Therapy Response: A Preliminary Comparison of Imaging Biomarkers

Brendan Moloney¹, Xin Li¹, Michael Hirano², Assim Saad Eddin³, Jeong Youn Lim¹, Debosmita Biswas², Anum S. Kazerouni², Alina Tudorica¹, Isabella Li², Mary Lynn Bryant², Courtney Wille³, Chelsea Pyle¹, Habib Rahbar², Su Kim Hsieh³, Travis Rice-Stitt¹, Suzanne Dintzis², Amani Bashir³, Evthokia Hobbs¹, Alexandra Zimmer¹, Jennifer Specht², Sneha Phadke³, Nicole Fleege³, James Holmes³, Savannah C. Partridge², and Wei Huang¹

¹Oregon Health & Science University, Portland, OR, United States, ²University of Washington, Seattle, WA, United States, ³University of Iowa, Iowa City, IA, United States

Synopsis

Keywords: Treatment Response, Cancer, Multi-Center and Multi-Vendor platform, DCE-MRI, Therapy Response, Ktrans

Motivation: Validate Shutter-Speed model (SSM) DCE-MRI as a robust predictor of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) in a multi-center and multi-vendor platform setting.

Goal(s): Compare tumor size, semi-quantitative, and quantitative DCE-MRI for early prediction of NAC response.

Approach: BC patients treated with NAC underwent longitudinal high spatiotemporal resolution DCE-MRI at three sites using a 3T Siemens, GE, or Philips system. Semi-quantitative signal-enhancement-ratio (SER) and quantitative Tofts model (TM) and SSM pharmacokinetic (PK) parameters were derived from DCE time-course data.

Results: PK parameters outperformed size and SER while SSM was superior to TM in early prediction of pathologic response.

Impact: It is feasible to implement quantitative high spatiotemporal resolution SSM DCE-MRI in trials with multi-center and multi-vendor platform settings for robust assessment of BC response to NAC.

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