Keywords: Microstructure, Quantitative Imaging
Motivation: Time-dependent diffusion MRI (td-dMRI) offers valuable microstructural insights but faces clinical challenges due to sensitivity to acquisition parameters and system variability.
Goal(s): This study aims to develop an optimization framework for OGSE and PGSE parameters tailored to specific MRI systems and anatomical regions, enhancing the stability and accuracy of quantitative estimations across different SNR levels.
Approach: This framework uses a genetic algorithm to optimize OGSE and PGSE parameters with system performance and tissue-specific SNR constraints, validated on a 5.0T MRI system.
Results: Optimized parameters achieved lower estimation errors and higher stability compared to values typically derived from conventional literature.
Impact: This framework supports broader clinical adoption of td-dMRI by enhancing diagnostic reliability, enabling multi-center standardization, and extending the approach’s applicability to other diffusion imaging models.
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