Jeffrey T. Duda

In Vivo Fiber Tractography Using DT-MRI Data

Fiber tract trajectories in coherently organized brain white matter pathways were computed from in vivo diffusion tensor magnetic resonance imaging (DT‐MRI) data. First, a continuous diffusion tensor field is constructed from this discrete, noisy, measured DT‐MRI data. Then a Frenet equation, describing the evolution of a fiber tract, was solved. This approach was validated using synthesized, noisy DT‐MRI data. Corpus callosum and pyramidal tract trajectories were constructed and found to be consistent with known anatomy. The methods reliability, however, degrades where the distribution of fiber tract directions is nonuniform. Moreover, background noise in diffusion‐weighted MRIs can cause a computed trajectory to hop from tract to tract. Still, this method can provide quantitative information with which to visualize and study connectivity and continuity of neural pathways in the central and peripheral nervous systems in vivo, and holds promise for elucidating architectural features in other fibrous tissues and ordered media. Magn Reson Med 44:625–632, 2000. Published 2000 Wiley‐Liss, Inc.

Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements.

Many studies of the human brain have explored the relationship between cortical thickness and cognition, phenotype, or disease. Due to the subjectivity and time requirements in manual measurement of cortical thickness, scientists have relied on robust software tools for automation which facilitate the testing and refinement of neuroscientific hypotheses. The most widely used tool for cortical thickness studies is the publicly available, surface-based FreeSurfer package. Critical to the adoption of such tools is a demonstration of their reproducibility, validity, and the documentation of specific implementations that are robust across large, diverse imaging datasets. To this end, we have developed the automated, volume-based Advanced Normalization Tools (ANTs) cortical thickness pipeline comprising well-vetted components such as SyGN (multivariate template construction), SyN (image registration), N4 (bias correction), Atropos (n-tissue segmentation), and DiReCT (cortical thickness estimation). In this work, we have conducted the largest evaluation of automated cortical thickness measures in publicly available data, comparing FreeSurfer and ANTs measures computed on 1205 images from four open data sets (IXI, MMRR, NKI, and OASIS), with parcellation based on the recently proposed Desikan-Killiany-Tourville (DKT) cortical labeling protocol. We found good scan-rescan repeatability with both FreeSurfer and ANTs measures. Given that such assessments of precision do not necessarily reflect accuracy or an ability to make statistical inferences, we further tested the neurobiological validity of these approaches by evaluating thickness-based prediction of age and gender. ANTs is shown to have a higher predictive performance than FreeSurfer for both of these measures. In promotion of open science, we make all of our scripts, data, and results publicly available which complements the use of open image data sets and the open source availability of the proposed ANTs cortical thickness pipeline.

Brain atrophy in relapsing multiple sclerosis: relationship to relapses, EDSS, and treatment with interferon β-1a

Brain atrophy is a relevant surrogate marker of the disease process in multiple sclerosis (MS) because it represents the net effect of various pathological processes leading to brain tissue loss. There are various approaches to quantifying central nervous system atrophy in MS. We have focused on a normalized measure of whole brain atrophy, the brain parenchymal fraction (BPF). BPF is defined as the brain parenchymal volume, divided by the volume within the surface of the brain. We applied this method to an MRI data set generated during a phase III clinical trial of interferon β-1a (AVONEX). The purpose of the current study is to further explore clinical and MRI correlates of the BPF, particularly as they relate to relapse rate and Kurtzkes Expanded Disability Status Score (EDSS); and to further explore the therapeutic effects observed in interferon β-1a recipients. Of all demographic and disease measures in the clinical trial data base, T2 lesion volume most closely correlated with BPF in cross sectional studies, and was the baseline factor most closely correlated with progressive brain atrophy in the subsequent 2 years. We also observed that change in T2 lesion volume was the disease measure most closely correlated with change in BPF during 2 years of observation. Of interest, relapse number and EDSS change during 2 years were only weakly correlated with BPF change during the same period. Disability progression, defined as sustained worsening of at least 1.0 EDSS points from baseline, persisting at least 6 months, was associated with significantly greater brain atrophy progression. We observed a therapeutic effect of interferon β-1a in the second year of the clinical trial, and this beneficial effect was not accounted for by change in gadolinium enhanced lesion volume, or by corticosteroid medication within 40 days of the final MRI scan. The BPF is an informative surrogate marker for destructive pathological processes in relaping MS patients, and is useful in demonstrating treatment effects in controlled clinical trials. The significance of progressive brain atrophy during relapsing MS will be assessed by measuring clinical and MRI changes in prospective follow up studies.

Associations between children's socioeconomic status and prefrontal cortical thickness

Childhood socioeconomic status (SES) predicts executive function performance and measures of prefrontal cortical function, but little is known about its anatomical correlates. Structural MRI and demographic data from a sample of 283 healthy children from the NIH MRI Study of Normal Brain Development were used to investigate the relationship between SES and prefrontal cortical thickness. Specifically, we assessed the association between two principal measures of childhood SES, family income and parental education, and gray matter thickness in specific subregions of prefrontal cortex and on the asymmetry of these areas. After correcting for multiple comparisons and controlling for potentially confounding variables, parental education significantly predicted cortical thickness in the right anterior cingulate gyrus and left superior frontal gyrus. These results suggest that brain structure in frontal regions may provide a meaningful link between SES and cognitive function among healthy, typically developing children.

Postictal Diffusion-Weighted Imaging for the Localization of Focal Epileptic Areas in Temporal Lobe Epilepsy

Summary:  Purpose: Diffusion‐weighted MR imaging (DWI) is a novel technique to delineate focal areas of cytotoxic edema of various etiologies. We hypothesized that DWI may also detect the epileptogenic region and adjacent areas during the ictal and early postictal periods in patients with temporal lobe epilepsy (TLE).

Multivariate analysis of structural and diffusion imaging in traumatic brain injury.

RATIONALE AND OBJECTIVES Diffusion tensor (DT) and T1 structural magnetic resonance images provide unique and complementary tools for quantifying the living brain. We leverage both modalities in a diffeomorphic normalization method that unifies analysis of clinical datasets in a consistent and inherently multivariate (MV) statistical framework. We use this technique to study MV effects of traumatic brain injury (TBI). MATERIALS AND METHODS We contrast T1 and DT image-based measurements in the thalamus and hippocampus of 12 TBI survivors and nine matched controls normalized to a combined DT and T1 template space. The normalization method uses maps that are topology-preserving and unbiased. Normalization is based on the full tensor of information at each voxel and, simultaneously, the similarity between high-resolution features derived from T1 data. The technique is termed symmetric normalization for MV neuroanatomy (SyNMN). Voxel-wise MV statistics on the local volume and mean diffusion are assessed with Hotellings T(2) test with correction for multiple comparisons. RESULTS TBI significantly (false discovery rate P < .05) reduces volume and increases mean diffusion at coincident locations in the mediodorsal thalamus and anterior hippocampus. CONCLUSIONS SyNMN reveals evidence that TBI compromises the limbic system. This TBI morphometry study and an additional performance evaluation contrasting SyNMN with other methods suggest that the DT component may aid normalization quality.

Periictal diffusion-weighted imaging in a case of lesional epilepsy.

Summary: Purpose: Diffusion‐weighted MR imaging (DWI) has been used for the early diagnosis of acute ischemic lesions in humans and in animal models of focal status epilepticus. We hypothesized that DWI may be a sensitive, noninvasive tool for the localization of the epileptogenic area during the periictal period.

Longitudinal Reproducibility and Accuracy of Pseudo-Continuous Arterial Spin–labeled Perfusion MR Imaging in Typically Developing Children

PURPOSE To evaluate the longitudinal repeatability and accuracy of cerebral blood flow (CBF) measurements by using pseudo-continuous arterial spin-labeled (pCASL) perfusion magnetic resonance (MR) imaging in typically developing children. MATERIALS AND METHODS Institutional review board approval with HIPAA compliance and informed consent were obtained. Twenty-two children aged 7-17 years underwent repeated pCASL examinations 2-4 weeks apart with a 3-T MR imager, along with in vivo blood T1 and arterial transit time measurements. Phase-contrast (PC) MR imaging was performed as the reference standard for global blood flow volume. Intraclass correlation coefficient (ICC) and within-subject coefficient of variation (wsCV) were used to evaluate accuracy and repeatability. RESULTS The accuracy of pCASL against the reference standard of PC MR imaging increased on incorporating subjectwise in vivo blood T1 measurement (ICC: 0.32 vs 0.58). The ICC further increased to 0.65 by using a population-based model of blood T1. Additionally, CBF measurements with use of pCASL demonstrated a moderate to good level of longitudinal repeatability in whole brain (ICC = 0.61, wsCV = 15%), in gray matter (ICC = 0.65, wsCV = 14%), and across 16 brain regions (mean ICC = 0.55, wsCV = 17%). The mean arterial transit time was 1538 msec ± 123 (standard deviation) in the pediatric cohort studied, which showed an increasing trend with age (P = .043). CONCLUSION Incorporating developmental changes in blood T1 is important for improving the accuracy of pCASL CBF measurements in children and adolescents; the noninvasive nature, accuracy, and longitudinal repeatability should facilitate the use of pCASL perfusion MR imaging in neurodevelopmental studies.

A Digital Atlas of the Dog Brain

There is a long history and a growing interest in the canine as a subject of study in neuroscience research and in translational neurology. In the last few years, anatomical and functional magnetic resonance imaging (MRI) studies of awake and anesthetized dogs have been reported. Such efforts can be enhanced by a population atlas of canine brain anatomy to implement group analyses. Here we present a canine brain atlas derived as the diffeomorphic average of a population of fifteen mesaticephalic dogs. The atlas includes: 1) A brain template derived from in-vivo, T1-weighted imaging at 1 mm isotropic resolution at 3 Tesla (with and without the soft tissues of the head); 2) A co-registered, high-resolution (0.33 mm isotropic) template created from imaging of ex-vivo brains at 7 Tesla; 3) A surface representation of the gray matter/white matter boundary of the high-resolution atlas (including labeling of gyral and sulcal features). The properties of the atlas are considered in relation to historical nomenclature and the evolutionary taxonomy of the Canini tribe. The atlas is available for download (https://cfn.upenn.edu/aguirre/wiki/public:data_plosone_2012_datta).

Multivariate normalization with symmetric diffeomorphisms for multivariate studies

Current clinical and research neuroimaging protocols acquire images using multiple modalities, for instance, T1, T2, diffusion tensor and cerebral blood flow magnetic resonance images (MRI). These multivariate datasets provide unique and often complementary anatomical and physiological information about the subject of interest. We present a method that uses fused multiple modality (scalar and tensor) datasets to perform intersubject spatial normalization. Our multivariate approach has the potential to eliminate inconsistencies that occur when normalization is performed on each modality separately. Furthermore, the multivariate approach uses a much richer anatomical and physiological image signature to infer image correspondences and perform multivariate statistical tests. In this initial study, we develop the theory for Multivariate Symmetric Normalization (MVSyN), establish its feasibility and discuss preliminary results on a multivariate statistical study of 22q deletion syndrome.