Validation of an MRI-Based Predictive Model for Treatment Tailoring in the I-SPY 2 Trial

Motivation: Previously, we developed MRI-based models for the prediction of pathologic complete response (pCR) using an initial cohort of 990 patients enrolled in I-SPY. The purpose of this study is to validate the performance of the MRI model using an independent patient cohort from I-SPY 2. Goal(s): The goal is to test the robustness of the MRI-based models. Approach: Area under the receiver operating characteristic curve (AUC), PPV, and sensitivity for pCR prediction was used to evaluate performance in the subsequent cohort. Results: Overall, the sensitivity and PPV were 72% and 57%, slightly higher than the values evaluated in the initial 990 cohort. Impact: This is the first study of MRI-based predictive models that were developed and validated using two separate large cohorts from a multicenter neoadjuvant chemotherapy clinical trial.

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/10.58530/2025/1980
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Validation of an MRI-Based Predictive Model for Treatment Tailoring in the I-SPY 2 Trial

Denise M. Wolf, Jessica Gibbs, Barbara LeStage, 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
Radiomics and Machine Learning in Medical Imaging
article

Validation of an MRI-Based Predictive Model for Treatment Tailoring in the I-SPY 2 Trial

Denise M. Wolf, Jessica Gibbs, Barbara LeStage, Bonnie N. Joe, Natsuko Onishi, John Kornak, Lisa J. Wilmes, Nola M. Hylton, Christina Yau, Sara J. Venters, Teffany Joy Bareng, Mark Jesus M. Magbanua, Nu N. Le, Laura Esserman, Elissa R. Price, Pouya Metanat, Matthew Gibbons, Wen Li, Laura van 't Veer, Angela DeMichele
article en

Abstract

Motivation: Previously, we developed MRI-based models for the prediction of pathologic complete response (pCR) using an initial cohort of 990 patients enrolled in I-SPY. The purpose of this study is to validate the performance of the MRI model using an independent patient cohort from I-SPY 2. Goal(s): The goal is to test the robustness of the MRI-based models. Approach: Area under the receiver operating characteristic curve (AUC), PPV, and sensitivity for pCR prediction was used to evaluate performance in the subsequent cohort. Results: Overall, the sensitivity and PPV were 72% and 57%, slightly higher than the values evaluated in the initial 990 cohort. Impact: This is the first study of MRI-based predictive models that were developed and validated using two separate large cohorts from a multicenter neoadjuvant chemotherapy clinical trial.

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 65%
Radiomics and Machine Learning in Medical Imaging
DOISourceOpenAlex
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