Abstract #0055

Breast MRI functional tumor volume segmentation quality may impact the prediction of pathological complete response

Natsuko Onishi¹, Jessica Gibbs¹, Teffany Joy Bareng¹, Wen Li¹, Elissa R. Price¹, Bonnie N. Joe¹, Laura J. Esserman², The I-SPY 2 Consortium³, David C. Newitt¹, and Nola M. Hylton¹

¹Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Department of Surgery, University of California, San Francisco, San Francisco, CA, United States, ³Quantum Leap Healthcare Collaborative, San Francisco, CA, United States

In the I-SPY2 neoadjuvant breast cancer trial, functional tumor volume (FTV) derived from dynamic contrast-enhanced MRI serves as a key marker. Participants in I-SPY2 have the option to “de-escalate” therapy if achievement of pathological complete response (pCR) is highly likely at inter-regimen time point. A model combining FTV-based predictive probabilities with inter-regimen core-biopsy pathology is central to select candidates for this option. This retrospective study compared the performance of longitudinal FTVs in predicting pCR between optimal and non-optimal FTV segmentation groups. The results suggest that improvements to FTV segmentation can improve FTV’s ability to provide predictive guidance for treatment de-escalation.

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