Functional Tumor Volume by Subtype Improves Prediction of Pathological Complete Response in Breast Cancer

Motivation: In the breast cancer I-SPY2 clinical trial, improvement of predictive capability for pathological complete response (pCR) would lead to improved drug candidate identification and treatment length assignment. Goal(s): Improve functional tumor volume (FTV) predictive performance by optimizing parameter thresholds by receptor subtype. Approach: This retrospective study used DCE-MRI to calculate FTV at different enhancement curve parameter thresholds. Resulting FTV metrics were used in prediction models for pCR. Optimal thresholds were selected to maximize receiver operating characteristic area under the curve. Results: Each factor category (subtype, enhancement curve thresholds, and measurement timepoint) were important for improving pCR predictive performance. The maximum AUC was 0.77. Impact: In the breast cancer I-SPY2 clinical trial, better pathological complete response (pCR) prediction would lead to improved treatment redirection and treatment sparing, improving patient outcomes. In this study, we optimized parameters for MRI functional tumor volume calculation to improve predictions.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/1982
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
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article

Functional Tumor Volume by Subtype Improves Prediction of Pathological Complete Response in Breast Cancer

W. Fraser Symmans, Hope Rugo, Jessica Gibbs, Bonnie N. Joe et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Gene expression and cancer classification
article

Functional Tumor Volume by Subtype Improves Prediction of Pathological Complete Response in Breast Cancer

W. Fraser Symmans, Hope Rugo, Jessica Gibbs, Bonnie N. Joe, Claudine Issacs, Natsuko Onishi, Nola Hylton, John Kornak, Lisa J. Wilmes, Douglas Yee, Rebecca Shatsky, Nu Le, Christina Yau, Barbara LeStage, Teffany Joy Bareng, Mark Jesus M. Magbanua, Laura Esserman, Elissa R. Price, Matthew Gibbons, Wen Li, Laura van 't Veer, Denise Wolf, Jane Perlmutter, Angela DeMichele
article en

Abstract

Motivation: In the breast cancer I-SPY2 clinical trial, improvement of predictive capability for pathological complete response (pCR) would lead to improved drug candidate identification and treatment length assignment. Goal(s): Improve functional tumor volume (FTV) predictive performance by optimizing parameter thresholds by receptor subtype. Approach: This retrospective study used DCE-MRI to calculate FTV at different enhancement curve parameter thresholds. Resulting FTV metrics were used in prediction models for pCR. Optimal thresholds were selected to maximize receiver operating characteristic area under the curve. Results: Each factor category (subtype, enhancement curve thresholds, and measurement timepoint) were important for improving pCR predictive performance. The maximum AUC was 0.77. Impact: In the breast cancer I-SPY2 clinical trial, better pathological complete response (pCR) prediction would lead to improved treatment redirection and treatment sparing, improving patient outcomes. In this study, we optimized parameters for MRI functional tumor volume calculation to improve predictions.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 78%
Gene expression and cancer classification
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