Babak A. Ardekani

Attention-deficit/hyperactivity disorder: A preliminary diffusion tensor imaging study

BACKGROUND The purpose of this study was to explore whether there are white matter (WM) abnormalities in children with attention-deficit/hyperactivity disorder (ADHD) using diffusion tensor imaging. Based upon the literature, we predicted decreased fractional anisotropy (FA) findings in the frontal and cerebellar regions. METHODS Eighteen patients with ADHD and 15 age- and gender-matched healthy volunteers received DTI assessments. Fractional anisotropy maps of WM were compared between groups with a voxelwise analysis after intersubject registration to Talairach space. RESULTS Children with ADHD had decreased FA in areas that have been implicated in the pathophysiology of ADHD: right premotor, right striatal, right cerebral peduncle, left middle cerebellar peduncle, left cerebellum, and left parieto-occipital areas. CONCLUSIONS These preliminary data support the hypothesis that alterations in brain WM integrity in frontal and cerebellar regions occur in ADHD. The pattern of decreased FA might implicate the corticopontocerebellar circuit in the pathophysiology of ADHD.

MRI study of white matter diffusion anisotropy in schizophrenia

Diffusion tensor imaging (DTI) can provide information about brain white matter integrity. The results of DTI studies in schizophrenia are somewhat variable and could benefit from standardized image processing methods. Fourteen patients with schizophrenia or schizoaffective disorder and 14 healthy volunteers underwent DTI. Scans were analyzed using a rigorous voxelwise approach. The key dependent variable, fractional anisotropy, was lower for patients in the corpus callosum, left superior temporal gyrus, parahippocampal gyri, middle temporal gyri, inferior parietal gyri, medial occipital lobe, and the deep frontal perigenual region. Regions showing reduced white matter fractional anisotropy are known to be abnormal in schizophrenia. The voxelwise method used in the current study can provide the basis for hypothesis-driven research.

Diffusion-Tensor Imaging Implicates Prefrontal Axonal Injury in Executive Function Impairment Following Very Mild Traumatic Brain Injury

PURPOSE To determine whether frontal white matter diffusion abnormalities can help predict acute executive function impairment after mild traumatic brain injury (mTBI). MATERIALS AND METHODS This study had institutional review board approval, included written informed consent, and complied with HIPAA. Diffusion-tensor imaging and standardized neuropsychologic assessments were performed in 20 patients with mTBI within 2 weeks of injury and 20 matched control subjects. Fractional anisotropy (FA) and mean diffusivity (MD) images (imaging parameters: 3.0 T, 25 directions, b = 1000 sec/mm(2)) were compared by using whole-brain voxelwise analysis. Spearman correlation analyses were performed to evaluate associations between diffusion measures and executive function. RESULTS Multiple clusters of lower frontal white matter FA, including the dorsolateral prefrontal cortex (DLPFC), were present in patients (P < .005), with several clusters also demonstrating higher MD (P < .005). Patients performed worse on tests of executive function. Lower DLPFC FA was significantly correlated with worse executive function performance in patients (P < .05). CONCLUSION Impaired executive function following mTBI is associated with axonal injury involving the DLPFC.

White matter development during late adolescence in healthy males: a cross-sectional diffusion tensor imaging study.

BACKGROUND Previous MRI studies of healthy children have reported age-related white matter (WM) changes in language and motor areas of the brain. The authors investigated WM development in healthy adolescent males through age-associated changes in fractional anisotropy (FA), radial (lambda( perpendicular)) and axial (lambda(||)) diffusivity. METHODS Twenty-four healthy adolescent males (mean age=16.6, SD=2.5 years) were divided into two groups with an age split of 16.9 years and underwent a whole-brain voxelwise analysis. RESULTS At a threshold of p<0.001 and extent threshold of 100 contiguous voxels, several clusters with increased FA and axial diffusivity and no differences in radial diffusivity were observed in older adolescents compared to the younger adolescents in the left arcuate fasciculus, bilateral posterior internal capsule/thalamic radiation, bilateral prefrontal gyrus, right superior temporal gyrus, and posterior corpus callosum. Increased FA and lambda(||) of several clusters along the arcuate fasciculus significantly correlated with a test of language and semantic memory. CONCLUSIONS These results suggest ongoing maturational changes especially in the arcuate fasiculus during late adolescence. Increased FA and lambda(||) with no changes in radial diffusivity may reflect a developmental pattern of reduced tortuousity toward more straightened fibers and/or increased axonal fiber organization during late adolescence.

Clinical and Neuropsychological Correlates of White Matter Abnormalities in Recent Onset Schizophrenia

The objective of this study was to investigate the clinical and neuropsychological correlates of white matter abnormalities in patients with schizophrenia studied early in the course of illness. A total of 33 (21 male/12 female) patients with recent onset schizophrenia and 30 (18 male/12 female) healthy volunteers completed structural and diffusion tensor imaging exams. Patients also received clinical and neuropsychological assessments. Fractional anisotropy (FA) maps were compared between groups in the white matter using a voxelwise analysis following intersubject registration to Talairach space and correlated with functional indices. Compared to healthy volunteers, patients demonstrated significantly (p<0.001, cluster size ⩾100) lower FA within temporal lobe white matter regions corresponding approximately to the right and left uncinate fasciculus, left inferior fronto-occipital fasciculus, and left superior longitudinal fasciculus. There were no areas of significantly higher FA in patients compared to healthy volunteers. Lower FA in the bilateral uncinate fasciculus correlated significantly with greater severity of negative symptoms (alogia and affective flattening), and worse verbal learning/memory functioning. In addition, higher FA in the inferior fronto-occipital fasciculus correlated significantly with greater severity of delusions and hallucinations. White matter abnormalities are evident in patients with schizophrenia early in the course of illness, appearing most robust in left temporal regions. These abnormalities have clinical and neuropsychological correlates, which may be useful in further characterizing structure–function relations in schizophrenia and constraining neurobiological models of the disorder.

Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging.

This article presents two related advancements to the diffusional kurtosis imaging estimation framework to increase its robustness to noise, motion, and imaging artifacts. The first advancement substantially improves the estimation of diffusion and kurtosis tensors parameterizing the diffusional kurtosis imaging model. Rather than utilizing conventional unconstrained least squares methods, the tensor estimation problem is formulated as linearly constrained linear least squares, where the constraints ensure physically and/or biologically plausible tensor estimates. The exact solution to the constrained problem is found via convex quadratic programming methods or, alternatively, an approximate solution is determined through a fast heuristic algorithm. The computationally more demanding quadratic programming‐based method is more flexible, allowing for an arbitrary number of diffusion weightings and different gradient sets for each diffusion weighting. The heuristic algorithm is suitable for real‐time settings such as on clinical scanners, where run time is crucial. The advantage offered by the proposed constrained algorithms is demonstrated using in vivo human brain images. The proposed constrained methods allow for shorter scan times and/or higher spatial resolution for a given fidelity of the diffusional kurtosis imaging parametric maps. The second advancement increases the efficiency and accuracy of the estimation of mean and radial kurtoses by applying exact closed‐form formulae. Magn Reson Med, 2011.

Multifocal White Matter Ultrastructural Abnormalities in Mild Traumatic Brain Injury with Cognitive Disability: A Voxel-Wise Analysis of Diffusion Tensor Imaging

The purpose of the present study is to identify otherwise occult white matter abnormalities in patients suffering persistent cognitive impairment due to mild traumatic brain injury (TBI). The study had Institutional Review Board (IRB) approval, included informed consent and complied with the U.S. Health Insurance Portability and Accountability Act (HIPAA) of 1996. We retrospectively analyzed diffusion tensor MRI (DTI) of 17 patients (nine women, eight men; age range 26-70 years) who had cognitive impairment due to mild TBI that occurred 8 months to 3 years prior to imaging. Comparison was made to 10 healthy controls. Fractional anisotropy (FA) and mean diffusivity (MD) images derived from DTI (1.5 T; 25 directions; b = 1000) were compared using whole brain histogram and voxel-wise analyses. Histograms of white matter FA show an overall shift toward lower FA in patients. Areas of significantly decreased FA (p < 0.005) were found in the subject group in corpus callosum, subcortical white matter, and internal capsules bilaterally. Co-located elevation of mean diffusivity (MD) was found in the patients within each region. Similar, though less extensive, findings were demonstrated in each individual patient. Multiple foci of low white matter FA and high MD are present in cognitively impaired mild TBI patients, with a distribution that conforms to that of diffuse axonal injury. Evaluation of single subjects also reveals foci of low FA, suggesting that DTI may ultimately be useful for clinical evaluation of individual patients.

Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans.

The objective of inter-subject registration of three-dimensional volumetric brain scans is to reduce the anatomical variability between the images scanned from different individuals. This is a necessary step in many different applications such as voxelwise group analysis of imaging data obtained from different individuals. In this paper, the ability of three different image registration algorithms in reducing inter-subject anatomical variability is quantitatively compared using a set of common high-resolution volumetric magnetic resonance imaging scans from 17 subjects. The algorithms are from the automatic image registration (AIR; version 5), the statistical parametric mapping (SPM99), and the automatic registration toolbox (ART) packages. The latter includes the implementation of a non-linear image registration algorithm, details of which are presented in this paper. The accuracy of registration is quantified in terms of two independent measures: (1) post-registration spatial dispersion of sets of homologous landmarks manually identified on images before or after registration; and (2) voxelwise image standard deviation maps computed within the set of images registered by each algorithm. Both measures showed that the ART algorithm is clearly superior to both AIR and SPM99 in reducing inter-subject anatomical variability. The spatial dispersion measure was found to be more sensitive when the landmarks were placed after image registration. The standard deviation measure was found sensitive to intensity normalization or the method of image interpolation.

Evaluation of volume-based and surface-based brain image registration methods

Establishing correspondences across brains for the purposes of comparison and group analysis is almost universally done by registering images to one another either directly or via a template. However, there are many registration algorithms to choose from. A recent evaluation of fully automated nonlinear deformation methods applied to brain image registration was restricted to volume-based methods. The present study is the first that directly compares some of the most accurate of these volume registration methods with surface registration methods, as well as the first study to compare registrations of whole-head and brain-only (de-skulled) images. We used permutation tests to compare the overlap or Hausdorff distance performance for more than 16,000 registrations between 80 manually labeled brain images. We compared every combination of volume-based and surface-based labels, registration, and evaluation. Our primary findings are the following: 1. de-skulling aids volume registration methods; 2. custom-made optimal average templates improve registration over direct pairwise registration; and 3. resampling volume labels on surfaces or converting surface labels to volumes introduces distortions that preclude a fair comparison between the highest ranking volume and surface registration methods using present resampling methods. From the results of this study, we recommend constructing a custom template from a limited sample drawn from the same or a similar representative population, using the same algorithm used for registering brains to the template.

Functional magnetic resonance imaging of brain activity in the visual oddball task.

Abnormalities in the P300 ERP, elicited by the oddball task and measured using EEG, have been found in a number of central nervous system disorders including schizophrenia, Alzheimers disease, and alcohol dependence. While electrophysiological studies provide high temporal resolution, localizing the P300 deficit has been particularly difficult because the measurements are collected from the scalp. Knowing which brain regions are involved in this process would elucidate the behavioral correlates of P300. The aim of this study was to determine the brain regions involved in a visual oddball task using fMRI. In this study, functional and high-resolution anatomical MR images were collected from seven normal volunteers. The data were analyzed using a randomization-based statistical method that accounts for multiple comparisons, requires no assumptions about the noise structure of the data, and does not require spatial or temporal smoothing. Activations were detected (P<0.01) bilaterally in the supramarginal gyrus (SMG; BA 40), superior parietal lobule (BA 7), the posterior cingulate gyrus, thalamus, inferior occipitotemporal cortex (BA 19/37), insula, dorsolateral prefrontal cortex (BA 9), anterior cingulate cortex (ACC), medial frontal gyrus (BA 6), premotor area, and cuneus (BA 17). Our results are consistent with previous studies that have observed activation in ACC and SMG. Activation of thalamus, insula, and the occipitotemporal cortex has been reported less consistently. The present study lends further support to the involvement of these structures in visual target detection.