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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2015-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4400066?pdf=render |
| _version_ | 1818942577479516160 |
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| author | Ariel Rokem Jason D Yeatman Franco Pestilli Kendrick N Kay Aviv Mezer Stefan van der Walt Brian A Wandell |
| author_facet | Ariel Rokem Jason D Yeatman Franco Pestilli Kendrick N Kay Aviv Mezer Stefan van der Walt Brian A Wandell |
| author_sort | Ariel Rokem |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T07:13:39Z |
| format | Article |
| id | doaj.art-5f81d1b32f0d44ecb44257b5b2fb6a10 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T07:13:39Z |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-5f81d1b32f0d44ecb44257b5b2fb6a102022-12-21T19:48:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012327210.1371/journal.pone.0123272Evaluating the accuracy of diffusion MRI models in white matter.Ariel RokemJason D YeatmanFranco PestilliKendrick N KayAviv MezerStefan van der WaltBrian A WandellModels 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.http://europepmc.org/articles/PMC4400066?pdf=render |
| spellingShingle | Ariel Rokem Jason D Yeatman Franco Pestilli Kendrick N Kay Aviv Mezer Stefan van der Walt Brian A Wandell Evaluating the accuracy of diffusion MRI models in white matter. PLoS ONE |
| title | 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_short | Evaluating the accuracy of diffusion MRI models in white matter. |
| title_sort | evaluating the accuracy of diffusion mri models in white matter |
| url | http://europepmc.org/articles/PMC4400066?pdf=render |
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