Abstract #2001

Advanced DWI Models for Early Prediction of Pathologic Complete Response in Breast Cancer Treatment: Preliminary Results in a Multicenter Trial

Debosmita Biswas¹, Patrick J Bolan², Dariya Malyarenko³, June A Ricks¹, Mary Lynn Bryant¹, Isabella Li¹, Anum Kazerouni¹, Brendan Moloney⁴, Xin Li⁴, Dallas Turley⁵, Jennifer M. Specht¹, Suzanne Dintzis¹, Habib Rahbar¹, Thomas L Chenevert³, James H Holmes⁶, Wei Huang^4,7, and Savannah C Partridge¹

¹University of Washington, Seattle, WA, United States, ²University of Minnesota, Minneapolis, MN, United States, ³University of Michigan, Ann Arbor, MI, United States, ⁴Oregon Health & Science University, Portland, OR, United States, ⁵Philips Healthcare, Seattle, WA, United States, ⁶University of Iowa, Iowa City, IA, United States, ⁷Corewell Health William Beaumont University Hospital, Royal Oak, MI, United States

Synopsis

Keywords: Breast, Diffusion Modeling, ADC, IVIM, DKI, RSI

Motivation: DWI shows promise for early prediction of pathologic complete response (pCR), an important prognostic marker in neoadjuvant chemotherapy (NAC) treatment.

Goal(s): To compare the performance of conventional ADC and advanced DWI models in predicting pCR in an ongoing multicenter prospective trial.

Approach: In 25 women undergoing NAC, MRI scans were performed at pre- and early-treatment (post 1-cycle) timepoints. Tumors were evaluated using IVIM, DKI, and RSI models, and compared with ADC.

Results: Changes in ADC, IVIM, DKI, and RSI metrics predicted pCR at early-treatment with moderately-high AUCs (0.77-0.92), suggesting future potential utility in guiding breast cancer treatment.

Impact: ADC and advanced DWI models demonstrate accurate early prediction of pathologic response in breast tumors undergoing neoadjuvant chemotherapy. Results support their potential as imaging biomarkers to help optimize breast cancer treatments in the future.

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