TY - JOUR
T1 - An optimized b-value sampling for the quantification of interstitial fluid using diffusion-weighted MRI, a genetic algorithm approach
AU - Drenthen, G.S.
AU - Jansen, J.F.A.
AU - van der, M.M.
AU - Voorter, P.H.M.
AU - Backes, W.H.
N1 - Funding Information:
The authors thank Siemens Healthcare for providing a prototype diffusion sequence for the acquisition of the in vivo 7T multi-b-value images. They also thank Dr. Thorsten Feiweier for the development of this sequence.
Publisher Copyright:
© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
PY - 2023/7
Y1 - 2023/7
N2 - PurposeMulti-b-value diffusion-weighted MRI techniques can simultaneously measure the parenchymal diffusivity, microvascular perfusion, and a third, intermediate diffusion component. This component is related to the interstitial fluid in the brain parenchyma. However, simultaneously estimating three diffusion components from multi-b-value data is difficult and has strong dependence on SNR and chosen b-values. As the number of acquired b-values is limited due to scanning time, it is important to know which b-values are most effective to be included. Therefore, this study evaluates an optimized b-value sampling for interstitial fluid estimation. MethodThe optimized b-value sampling scheme is determined using a genetic algorithm. Subsequently, the performance of this optimized sampling is assessed by comparing it with a linear, logarithmic, and previously proposed sampling scheme, in terms of the RMS error (RMSE) for the intermediate component estimation. The in vivo performance of the optimized sampling is assessed using 7T data with 101 equally spaced b-values ranging from 0 to 1000 s/mm(2). In this case, the RMSE was determined by comparing the fit that includes all b-values. ResultsThe optimized b-value sampling for estimating the intermediate component was reported to be [0, 30, 90, 210, 280, 350, 580, 620, 660, 680, 720, 760, 980, 990, 1000] s/mm(2). For computer simulations, the optimized sampling had a lower RMSE, compared with the other samplings for varying levels of SNR. For the in vivo data, the voxel-wise RMSE of the optimized sampling was lower compared with other sampling schemes. ConclusionThe genetic algorithm-optimized b-value scheme improves the quantification of the diffusion component related to interstitial fluid in terms of a lower RMSE.
AB - PurposeMulti-b-value diffusion-weighted MRI techniques can simultaneously measure the parenchymal diffusivity, microvascular perfusion, and a third, intermediate diffusion component. This component is related to the interstitial fluid in the brain parenchyma. However, simultaneously estimating three diffusion components from multi-b-value data is difficult and has strong dependence on SNR and chosen b-values. As the number of acquired b-values is limited due to scanning time, it is important to know which b-values are most effective to be included. Therefore, this study evaluates an optimized b-value sampling for interstitial fluid estimation. MethodThe optimized b-value sampling scheme is determined using a genetic algorithm. Subsequently, the performance of this optimized sampling is assessed by comparing it with a linear, logarithmic, and previously proposed sampling scheme, in terms of the RMS error (RMSE) for the intermediate component estimation. The in vivo performance of the optimized sampling is assessed using 7T data with 101 equally spaced b-values ranging from 0 to 1000 s/mm(2). In this case, the RMSE was determined by comparing the fit that includes all b-values. ResultsThe optimized b-value sampling for estimating the intermediate component was reported to be [0, 30, 90, 210, 280, 350, 580, 620, 660, 680, 720, 760, 980, 990, 1000] s/mm(2). For computer simulations, the optimized sampling had a lower RMSE, compared with the other samplings for varying levels of SNR. For the in vivo data, the voxel-wise RMSE of the optimized sampling was lower compared with other sampling schemes. ConclusionThe genetic algorithm-optimized b-value scheme improves the quantification of the diffusion component related to interstitial fluid in terms of a lower RMSE.
KW - cerebral clearance
KW - diffusion weighted imaging
KW - glymphatics
KW - interstitial fluid
KW - IVIM
KW - magnetic resonance imaging
KW - MAGNETIC-FIELD
U2 - 10.1002/mrm.29612
DO - 10.1002/mrm.29612
M3 - Article
C2 - 36744716
SN - 0740-3194
VL - 90
SP - 194
EP - 201
JO - Magnetic Resonance in Medicine
JF - Magnetic Resonance in Medicine
IS - 1
ER -