Evaluating the Accuracy of Diffusion MRI Models in White Matter
Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However, evaluations of model-accuracy of commonly used models have no...
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| Format: | Online |
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Public Library of Science
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4400066/ |
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pubmed-44000662015-04-21 Evaluating the Accuracy of Diffusion MRI Models in White Matter Rokem, Ariel Yeatman, Jason D. Pestilli, Franco Kay, Kendrick N. Mezer, Aviv van der Walt, Stefan Wandell, Brian A. Research Article Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However, evaluations of model-accuracy of commonly used models have not been published before. Here, we evaluate model-accuracy of the two main classes of diffusion MRI models. The diffusion tensor model (DTM) summarizes diffusion as a 3-dimensional Gaussian distribution. Sparse fascicle models (SFM) summarize the signal as a sum of signals originating from a collection of fascicles oriented in different directions. We use cross-validation to assess model-accuracy at different gradient amplitudes (b-values) throughout the white matter. Specifically, we fit each model to all the white matter voxels in one data set and then use the model to predict a second, independent data set. This is the first evaluation of model-accuracy of these models. In most of the white matter the DTM predicts the data more accurately than test-retest reliability; SFM model-accuracy is higher than test-retest reliability and also higher than the DTM model-accuracy, particularly for measurements with (a) a b-value above 1000 in locations containing fiber crossings, and (b) in the regions of the brain surrounding the optic radiations. The SFM also has better parameter-validity: it more accurately estimates the fiber orientation distribution function (fODF) in each voxel, which is useful for fiber tracking. Public Library of Science 2015-04-16 /pmc/articles/PMC4400066/ /pubmed/25879933 http://dx.doi.org/10.1371/journal.pone.0123272 Text en © 2015 Rokem et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Rokem, Ariel Yeatman, Jason D. Pestilli, Franco Kay, Kendrick N. Mezer, Aviv van der Walt, Stefan Wandell, Brian A. |
| spellingShingle |
Rokem, Ariel Yeatman, Jason D. Pestilli, Franco Kay, Kendrick N. Mezer, Aviv van der Walt, Stefan Wandell, Brian A. Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| author_facet |
Rokem, Ariel Yeatman, Jason D. Pestilli, Franco Kay, Kendrick N. Mezer, Aviv van der Walt, Stefan Wandell, Brian A. |
| author_sort |
Rokem, Ariel |
| title |
Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| title_short |
Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| title_full |
Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| title_fullStr |
Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| title_full_unstemmed |
Evaluating the Accuracy of Diffusion MRI Models in White Matter |
| title_sort |
evaluating the accuracy of diffusion mri models in white matter |
| description |
Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However, evaluations of model-accuracy of commonly used models have not been published before. Here, we evaluate model-accuracy of the two main classes of diffusion MRI models. The diffusion tensor model (DTM) summarizes diffusion as a 3-dimensional Gaussian distribution. Sparse fascicle models (SFM) summarize the signal as a sum of signals originating from a collection of fascicles oriented in different directions. We use cross-validation to assess model-accuracy at different gradient amplitudes (b-values) throughout the white matter. Specifically, we fit each model to all the white matter voxels in one data set and then use the model to predict a second, independent data set. This is the first evaluation of model-accuracy of these models. In most of the white matter the DTM predicts the data more accurately than test-retest reliability; SFM model-accuracy is higher than test-retest reliability and also higher than the DTM model-accuracy, particularly for measurements with (a) a b-value above 1000 in locations containing fiber crossings, and (b) in the regions of the brain surrounding the optic radiations. The SFM also has better parameter-validity: it more accurately estimates the fiber orientation distribution function (fODF) in each voxel, which is useful for fiber tracking. |
| publisher |
Public Library of Science |
| publishDate |
2015 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4400066/ |
| _version_ |
1613212535079567360 |