ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2025
Optimization of the Data Pattern and Analysis Algorithm for the T2-based Water Suppression Diffusion MRImaging (T2wsup-dMRI) Technique.
Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
We have proposed a T2-based free water suppression diffusion MRI (T2wsup-dMRI) technique to address parameter quantification issues due to cerebrospinal fluid (CSF) partial volume effects (PVEs), using a closed form (CF) algorithm. This study optimizes data patterns in (TE, b-value) space and analyzes algorithms for enhanced accuracy and precision. We simulated noise-added numerical, phantom, and brain MRI data to evaluate relative error and coefficient of variation in quantitative parameters using various data patterns and analysis algorithms (CF and least squares [LSQ] fitting). With 4 minimum data points applied to healthy brain tissue with T2 < 100 ms, the CF algorithm with water volume separation was optimal. For more than 4 points, a smaller b-value with shorter TE combined with 2d single- and bi-exponential LSQ fitting provided the best results. The T2wsup-dMRI technique reduces CSF-PVE artifacts in tissue-specific parameter quantification, enhancing approaches for patient needs, data acquisition, and computing costs.
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