Abstract #3457

Comparison of diffusion-weighted imaging ADC metrics for early prediction of neoadjuvant treatment response in HER2-negative breast cancer

Judith Zimmermann¹, Julia Carmona-Bozo¹, Nu N Le¹, Natsuko Onishi¹, Lisa J Wilmes¹, Jessica Gibbs¹, Jiachao Liang¹, David C Newitt¹, Savannah C Partridge², Patrick J Bolan³, John Kornak⁴, Elissa Price¹, Bonnie N Joe¹, Barbara LeStage⁵, I-SPY 2 Investigator Network⁶, I-SPY 2 Imaging Working Group¹, Wen Li¹, and Nola Hylton¹

¹Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Radiology, University of Washington, Seattle, WA, United States, ³Radiology, University of Minnesota, Minneapolis, MN, United States, ⁴Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States, ⁵I-SPY 2 Advocacy Group, San Francisco, CA, United States, ⁶Quantum Leap Healthcare, San Francisco, CA, United States

Synopsis

Keywords: Breast, Diffusion/other diffusion imaging techniques, treatment response prediction, biomarkers, neoadjuvant chemotherapy

In breast imaging, diffusion-based (DW) MRI delivers complementary quantitative value to conventional dynamic contrast enhanced MRI. ADC maps of tumor tissue calculated from DW-MRI, specifically mean ADC of the tumor region of interest, have shown promise for measuring early response to neoadjuvant chemotherapy (NAC). However, depending on intra-tumoral heterogeneity, other histogram-based ADC metrics may provide even better predictive performance than mean ADC, but are yet to be studied thoroughly. Here, we investigated nine ADC-based metrics regarding their predictive performance for NAC treatment response.

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