Dataset Information

Evaluating the accuracy of diffusion MRI models in white matter.

ABSTRACT: 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.

SUBMITTER: Rokem A

PROVIDER: S-EPMC4400066 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluating the accuracy of diffusion MRI models in white matter.

Rokem Ariel A Yeatman Jason D JD Pestilli Franco F Kay Kendrick N KN Mezer Aviv A van der Walt Stefan S Wandell Brian A BA

PloS one 20150416 4

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 distributio ...[more]

PMID: 25879933

Similar Datasets

Project description:Mood depressive disorder is one of the most disabling chronic diseases with a high rate of everyday life disability that affects 350 million people around the world. Recent advances in neuroimaging have reported widespread structural abnormalities, suggesting a dysfunctional frontal-limbic circuit involved in the pathophysiological mechanisms of depression. However, a variety of different white matter regions has been implicated and is sought to suffer from lack of reproducibility of such categorical-based biomarkers. These inconsistent results might be attributed to various factors: actual categorical definition of depression as well as clinical phenotype variability. In this study, we 1/ examined WM changes in a large cohort (114 patients) compared to a healthy control group and 2/ sought to identify specific WM alterations in relation to specific depressive phenotypes such as anhedonia (i.e. lack of pleasure), anxiety and psychomotor retardation -three core symptoms involved in depression. Consistent with previous studies, reduced white matter was observed in the genu of the corpus callosum extending to the inferior fasciculus and posterior thalamic radiation, confirming a frontal-limbic circuit abnormality. Our analysis also reported other patterns of increased fractional anisotropy and axial diffusivity as well as decreased apparent diffusion coefficient and radial diffusivity in the splenium of the corpus callosum and posterior limb of the internal capsule. Moreover, a positive correlation between FA and anhedonia was found in the superior longitudinal fasciculus as well as a negative correlation in the cingulum. Then, the analysis of the anxiety and diffusion metric revealed that increased anxiety was associated with greater FA values in genu and splenium of corpus callosum, anterior corona radiata and posterior thalamic radiation. Finally, the motor retardation analysis showed a correlation between increased Widlöcher depressive retardation scale scores and reduced FA in the body and genu of the corpus callosum, fornix, and superior striatum. Through this twofold approach (categorical and phenotypic), this study has underlined the need to move forward to a symptom-based research area of biomarkers, which help to understand the pathophysiology of mood depressive disorders and to stratify precise phenotypes of depression with targeted therapeutic strategies.

Project description:BackgroundPreterm infants are at high risk of diffuse white matter injury and adverse neurodevelopmental outcome. The multiple hit hypothesis suggests that the risk of white matter injury increases with cumulative exposure to multiple perinatal risk factors. Our aim was to test this hypothesis in a large cohort of preterm infants using diffusion weighted magnetic resonance imaging (dMRI).MethodsWe studied 491 infants (52% male) without focal destructive brain lesions born at < 34 weeks, who underwent structural and dMRI at a specialist Neonatal Imaging Centre. The median (range) gestational age (GA) at birth was 30+ 1 (23+ 2-33+ 5) weeks and median postmenstrual age at scan was 42+ 1 (38-45) weeks. dMRI data were analyzed using tract based spatial statistics and the relationship between dMRI measures in white matter and individual perinatal risk factors was assessed. We tested the hypothesis that increased exposure to perinatal risk factors was associated with lower fractional anisotropy (FA), and higher radial, axial and mean diffusivity (RD, AD, MD) in white matter. Neurodevelopmental performance was investigated using the Bayley Scales of Infant and Toddler Development, Third Edition (BSITD-III) in a subset of 381 infants at 20 months corrected age. We tested the hypothesis that lower FA and higher RD, AD and MD in white matter were associated with poorer neurodevelopmental performance.ResultsIdentified risk factors for diffuse white matter injury were lower GA at birth, fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition, necrotizing enterocolitis and male sex. Clinical chorioamnionitis and patent ductus arteriosus were not associated with white matter injury. Multivariate analysis demonstrated that fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition were independently associated with lower FA values. Exposure to cumulative risk factors was associated with reduced white matter FA and FA values at term equivalent age were associated with subsequent neurodevelopmental performance.ConclusionThis study suggests multiple perinatal risk factors have an independent association with diffuse white matter injury at term equivalent age and exposure to multiple perinatal risk factors exacerbates dMRI defined, clinically significant white matter injury. Our findings support the multiple hit hypothesis for preterm white matter injury.

Dataset Information

Evaluating the accuracy of diffusion MRI models in white matter.

Publications

Evaluating the accuracy of diffusion MRI models in white matter.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets