Importance of exactb-tensor calculation for quantitative diffusion tensor imaging and tracking of neuronal fiber bundles

Quantitative diffusion tensor imaging (DTI) is a novel method of magnetic resonance (MR) imaging providing information on the brain’s microstructure in vivo. DTI can be effectively measured with modern clinical MR scanners. However, imaging sequence details required for accurateb matrix calculation...

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Veröffentlicht in:Applied magnetic resonance 2005-03, Vol.29 (1), p.107-122
Hauptverfasser: Il’yasov, K. A., Barta, G., Kreher, B. W., Bellemann, M. E., Hennig, J.
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container_end_page 122
container_issue 1
container_start_page 107
container_title Applied magnetic resonance
container_volume 29
creator Il’yasov, K. A.
Barta, G.
Kreher, B. W.
Bellemann, M. E.
Hennig, J.
description Quantitative diffusion tensor imaging (DTI) is a novel method of magnetic resonance (MR) imaging providing information on the brain’s microstructure in vivo. DTI can be effectively measured with modern clinical MR scanners. However, imaging sequence details required for accurateb matrix calculation and for following DTI quantification are normally unknown to the user. In this work, we investigated the accuracy ofb value approximation if theb matrix is calculated without taking into account the effect of imaging gradients. It was found that an error of more than 4% in DTI estimation arises for a quite typical brain imaging protocol. The errors in mean diffusivity and fractional anisotropy index depend on diffusion tensor shape and eigenvectors orientation and exceed noise level in DTI quantification. These errors however have a strong impact on fiber tracking — up to 30% difference was found between the fiber tracks corresponding to exact and approximate calculated DTI data. Since these errors are dependent on imaging parameters and sequence implementation, accurateb matrix calculations are important for adequate comparison between data acquired on different MR scanners and also for data measured with the different imaging protocols.
doi_str_mv 10.1007/BF03166958
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subjects Anisotropy
Brain
Data acquisition
Eigenvectors
Errors
Magnetic resonance imaging
Mathematical analysis
Noise levels
Scanners
Tensors
Tracking
title Importance of exactb-tensor calculation for quantitative diffusion tensor imaging and tracking of neuronal fiber bundles
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