Keywords: DWI/DTI/DKI, Whole Body, Multiple Myeloma, Whole-body DWI, Deep Learning Reconstruction
Motivation: Whole-body diffusion-weighted imaging (WB-DWI) is increasingly used for assessing multiple myeloma (MM). However, current WB-DWI techniques face challenges, including slow scanning speeds and suboptimal image quality. Deep-learning reconstruction (DLR) has recently been proposed to address these issues.
Goal(s): Investigate the impact of DLR on Whole-body DWI's image quality in routine MM scanning.
Approach: Thirty MM patients with original WB-DWI images and DLR WB-DWI images are to be included. Image quality is compared using objective and subjective metrics.
Impact: DLR holds the potential to improve WB-DWI routine scanning by accelerating scan times while enhancing image quality, thereby supporting more effective detection and assessment of MM.
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