Cancer-Net PCa-MultiSeg: Multimodal Enhancement of Prostate Cancer Lesion Segmentation Using Synthetic Correlated Diffusion Imaging

The recent study on prostate cancer lesion segmentation highlights the potential of synthetic correlated diffusion imaging (CDI$^s$) as a significant enhancement to traditional imaging methods. Current deep learning approaches have struggled with low Dice scores of 0.32 or lower, indicating a pressing need for improvement. By evaluating CDI$^s$ alongside diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) sequences in a cohort of 200 patients, researchers found that CDI$^s$ integration reliably enhances or preserves segmentation performance in 94% of configurations tested. Notably, the combination of CDI$^s$ and DWI emerged as the safest enhancement pathway, yielding significant improvements in half of the evaluated architectures without any degradation. This method's advantage lies in its ability to utilize existing DWI acquisitions without requiring additional scan time or modifications, facilitating immediate clinical deployment. The study's findings not only a…