Automated Apparent Diffusion Coefficient Calculation Using Multimodal Image Registration for Prediction of Breast Cancer Treatment Response
Nu Le, Wen Li, Lisa J. Wilmes, Natsuko Onishi, Jessica Gibbs, Bonnie N. Joe, John Kornak, Dariya I. Malyarenko, Thomas L. Chenevert, Patrick J. Bolan, Savannah C. Partridge, Nola Hylton · 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 · 2024
Motivation: Tumor delineation is a challenging but critical step for ADC calculation in Diffusion-weighted (DW) MRI. Automated delineation methods are still underdeveloped for DW-MRI. Goal(s): To compare the predictive performance of manual vs. automated ADC values at multiple timepoints during neoadjuvant treatment. Approach: We used MRI data from the ACRIN 6698 trial for this analysis. Automated ADC values were computed using transformed ROIs from image registration between pre-contrast DCE and DWI (b=0). Results: Predictive performance improved with automated ADC values at 3-week timepoint and remained similar at 12-week and pre-surgery timepoints. Impact: This work offers a practical approach for automated ADC calculation, allowing radiologists to expedite clinical decisions for breast cancer patients at early treatment timepoints; therefore, improving patient care.