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Effects of fitting methods, high b-values and image quality on diffusion and perfusion quantification and reproducibility in the calf

journal contribution
posted on 2023-04-21, 02:26 authored by Ying-Hwey Nai, Xiaomeng Wang, Julian Gan, Cheryl Pei Ling LianCheryl Pei Ling Lian, Ryan Fraser Kirwan, Forest Su Lim Tan, Derek J. Hausenloy

The study aimed to optimize diffusion-weighted imaging (DWI) image acquisition and analysis protocols in calf muscles by investigating the effects of different model-fitting methods, image quality, and use of high b-value and constraints on parameters of interest (POIs). The optimized modeling methods were used to select the optimal combinations of b-values, which will allow shorter acquisition time while achieving the same reliability as that obtained using 16 b-values.

Methods

Test-retest baseline and high-quality DWI images of ten healthy volunteers were acquired on a 3T MR scanner, using 16 b-values, including a high b-value of 1200 s/mm2, and structural T1-weighted images for calf muscle delineation. Three and six different fitting methods were used to derive ADC from monoexponential (ME) model and Dd, fp, and Dp from intravoxel incoherent motion (IVIM) model, with or without the high b-value. The optimized ME and IVIM models were then used to determine the optimal combinations of b-values, obtainable with the least number of b-values, using the selection criteria of coefficient of variance (CV) ≤10% for all POIs.

Results

The find minimum multivariate algorithm was more flexible and yielded smaller fitting errors. The 2-steps fitting method, with fixed Dd, performed the best for IVIM model. The inclusion of high b-value reduced outliers, while constraints improved 2-steps fitting only.

Conclusions

The optimal numbers of b-values for ME and IVIM models were nine and six b-values respectively. Test-retest reliability analyses showed that only ADC and Ddwere reliable for calf diffusion evaluation, with CVs of 7.22% and 4.09%.

Funding

AcRF T1 1/2022-28

History

Journal/Conference/Book title

Computers in Biology and Medicine

Publication date

2023-03-01

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