Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

BACKGROUND AND PURPOSE: Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7 Tesla (T) MRI. METHODS: The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n = 15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12 months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. RESULTS: A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38 vs. 1.53, p < .001) and qMT (2.47 vs. 2.97, p < .001) but not in NODDI measures (p > .27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p = .03). CONCLUSIONS: SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

High-resolution diffusion tensor imaging of the fornix predicts memory function in multiple sclerosis.

Background: Cognitive dysfunction is a known symptom of multiple sclerosis (MS), with memory recognized as a frequently impacted domain. Here, we used high-resolution MRI at 7 tesla to build on cross-sectional work by evaluating the longitudinal relationship of diffusion tensor imaging (DTI) measures of the fornix to episodic memory performance. Methods: A sample of 80 people with multiple sclerosis (mean age 51.9 ± 8.1 years; 24% male) underwent baseline clinical evaluation, neuropsychological assessment, and MRI. Sixty-four participants had follow-up neuropsychological testing after 1-2 years. Linear regression was used to assess the relationship of baseline imaging measures to follow-up episodic memory performance, measured using the Selective Reminding Test and Brief Visuospatial Memory Test. A reduced prediction model included cognitive function at baseline, age, sex, and disease course. Results: Radial (ß = -0.222, p < 0.026; likelihood ratio test (LRT) p < 0.018), axial (ß = -0.270, p < 0.005; LRT p < 0.003), and mean (ß = -0.242, p < 0.0139; LRT p < 0.009) diffusivity of the fornix significantly added to the model, with follow-up analysis indicating that a longer prediction interval may increase accuracy. Conclusion: These results suggest that fornix DTI has predictive value specific to memory function in MS and warrants additional investigation in the drive to develop predictors of disease progression.

Evaluation of a connectivity-based imaging metric that reflects functional decline in Multiple Sclerosis.

Cognitive impairment is a common symptom in individuals with Multiple Sclerosis (MS), but meaningful, reliable biomarkers relating to cognitive decline have been elusive, making evaluation of the impact of therapeutics on cognitive function difficult. Here, we combine pathway-based MRI measures of structural and functional connectivity to construct a metric of functional decline in MS. The Structural and Functional Connectivity Index (SFCI) is proposed as a simple, z-scored metric of structural and functional connectivity, where changes in the metric have a simple statistical interpretation and may be suitable for use in clinical trials. Using data collected at six time points from a 2-year longitudinal study of 20 participants with MS and 9 age- and sex-matched healthy controls, we probe two common symptomatic domains, motor and cognitive function, by measuring structural and functional connectivity in the transcallosal motor pathway and posterior cingulum bundle. The SFCI is significantly lower in participants with MS compared to controls (p = 0.009) and shows a significant decrease over time in MS (p = 0.012). The change in SFCI over two years performed favorably compared to measures of brain parenchymal fraction and lesion volume, relating to follow-up measures of processing speed (r = 0.60, p = 0.005), verbal fluency (r = 0.57, p = 0.009), and score on the Multiple Sclerosis Functional Composite (r = 0.67, p = 0.003). These initial results show that the SFCI is a suitable metric for longitudinal evaluation of functional decline in MS.

Towards safe operation of an active retinal prosthesis during functional MRI and diffusion tensor imaging.

OBJECTIVE: To determine if the Argus II retinal prosthesis can operate during functional MRI (fMRI) and diffusion tensor imaging (DTI) acquisitions and if currents induced in the prosthesis by imaging are at safe levels. MATERIALS AND METHODS: One Argus II retinal prosthesis was modified to enable current measurements during imaging. Active electronics were modified to enable operation during scans. Induced current was measured during diagnostic scans, which were previously shown to be safe for implanted patients, and during fMRI and DTI scans. All measurements were performed using an ASTM phantom to ensure reproducible placement. RESULTS: The prosthesis was able to maintain communication with the external RF coil during the fMRI and DTI scans except briefly during pre-scans. Current levels induced during fMRI and DTI scans were consistently below those measured during diagnostic scans. CONCLUSIONS: fMRI and DTI may be safely performed while the Argus II retinal prosthesis is operating.

Serum neurofilament light chain concentration in a phase 1/2 trial of autologous mesenchymal stem cell transplantation.

BACKGROUND: Serum neurofilament light chain concentration is a proposed biomarker of axonal injury in multiple sclerosis. Mesenchymal stem cells have anti-inflammatory and repair-promoting activities, making them of interest for potential multiple sclerosis treatment. OBJECTIVES: The purpose of this study was to assess correlation of serum neurofilament light chain concentration and measures of multiple sclerosis disease activity/severity, longitudinal stability of serum neurofilament light chain concentration, and treatment effect of mesenchymal stem cell transplantation on serum neurofilament light chain concentration. METHODS: Twenty-four multiple sclerosis patients underwent intravenous infusion of autologous mesenchymal stem cells. Clinical assessments, serum collection, and brain magnetic resonance imaging were performed at months -1, 0 (transplant), 1, 3, and 6. Matched control serum was collected once (n = 10). Serum neurofilament light chain concentration was measured by single-molecule array. Serum neurofilament light chain concentration correlations with disease measures were analyzed by Spearman correlations and linear mixed effect models. Pre-post transplant serum neurofilament light chain concentration was compared by Wilcoxon signed rank testing. RESULTS: There were significant (p<0.01) correlations between serum neurofilament light chain concentration and gadolinium-enhancing lesion number (rho = 0.55) and volume (rho = 0.65), and new/enlarging T2 lesions (rho = 0.65). Patients without disease activity had lower fluctuation in serum neurofilament light chain concentration (p = 0.01). Mean pre- versus post-treatment serum neurofilament light chain concentration values were not significantly different. CONCLUSIONS: Serum neurofilament light chain concentration correlated with magnetic resonance imaging measures of disease activity cross sectionally and longitudinally, and was stable in patients without disease activity. There was no clear treatment effect of mesenchymal stem cell transplantation on serum neurofilament light chain concentration.

The role of the thalamus and hippocampus in episodic memory performance in patients with multiple sclerosis.

BACKGROUND: Episodic memory loss is one of the most common cognitive symptoms in patients with multiple sclerosis (MS), but the pathophysiology of this symptom remains unclear. Both the hippocampus and thalamus have been implicated in episodic memory and show regional atrophy in patients with MS. OBJECTIVE: In this work, we used functional magnetic resonance imaging (fMRI) during a verbal episodic memory task, lesion load, and volumetric measures of the hippocampus and thalamus to assess the relative contributions to verbal and visual-spatial episodic memory. METHODS: Functional activation, lesion load, and volumetric measures from 32 patients with MS and 16 healthy controls were used in a predictive analysis of episodic memory function. RESULTS: After adjusting for disease duration, immediate recall performance on a visual-spatial episodic memory task was significantly predicted by hippocampal volume ( p < 0.003). Delayed recall on the same task was significantly predicted by volume of the left thalamus ( p < 0.003). For both memory measures, functional activation of the thalamus during encoding was more predictive than that of volume measures ( p < 0.002). CONCLUSION: Our results suggest that functional activation may be useful as a predictive measure of episodic memory loss in patients with MS.

Phase 2 Trial of Ibudilast in Progressive Multiple Sclerosis.

BACKGROUND: There are limited treatments for progressive multiple sclerosis. Ibudilast inhibits several cyclic nucleotide phosphodiesterases, macrophage migration inhibitory factor, and toll-like receptor 4 and can cross the blood-brain barrier, with potential salutary effects in progressive multiple sclerosis. METHODS: We enrolled patients with primary or secondary progressive multiple sclerosis in a phase 2 randomized trial of oral ibudilast (≤100 mg daily) or placebo for 96 weeks. The primary efficacy end point was the rate of brain atrophy, as measured by the brain parenchymal fraction (brain size relative to the volume of the outer surface contour of the brain). Major secondary end points included the change in the pyramidal tracts on diffusion tensor imaging, the magnetization transfer ratio in normal-appearing brain tissue, the thickness of the retinal nerve-fiber layer, and cortical atrophy, all measures of tissue damage in multiple sclerosis. RESULTS: Of 255 patients who underwent randomization, 129 were assigned to ibudilast and 126 to placebo. A total of 53% of the patients in the ibudilast group and 52% of those in the placebo group had primary progressive disease; the others had secondary progressive disease. The rate of change in the brain parenchymal fraction was -0.0010 per year with ibudilast and -0.0019 per year with placebo (difference, 0.0009; 95% confidence interval, 0.00004 to 0.0017; P=0.04), which represents approximately 2.5 ml less brain-tissue loss with ibudilast over a period of 96 weeks. Adverse events with ibudilast included gastrointestinal symptoms, headache, and depression. CONCLUSIONS: In a phase 2 trial involving patients with progressive multiple sclerosis, ibudilast was associated with slower progression of brain atrophy than placebo but was associated with higher rates of gastrointestinal side effects, headache, and depression. (Funded by the National Institute of Neurological Disorders and Stroke and others; NN102/SPRINT-MS ClinicalTrials.gov number, NCT01982942 .).

Scan-rescan repeatability and cross-scanner comparability of DTI metrics in healthy subjects in the SPRINT-MS multicenter trial.

PURPOSE: To assess intrascanner repeatability and cross-scanner comparability for diffusion tensor imaging (DTI) metrics in a multicenter clinical trial. METHODS: DTI metrics (including longitudinal diffusivity [LD], fractional anisotropy [FA], mean diffusivity [MD], and transverse diffusivity [TD]) from pyramidal tracts for healthy controls were calculated from images acquired on twenty-seven 3T MR scanners (Siemens and GE) with 6 different scanner models and 7 different software versions as part of the NN102/SPRINT-MS clinical trial. Each volunteer underwent two scanning sessions on the same scanner. Signal-to-noise ratio (SNR) and signal-to-noise floor ratio (SNFR) were also assessed. RESULTS: DTI metrics showed good scan-rescan repeatability. There were no significant differences between scans and rescans in LD, FA, MD, or TD values. Although the cross-scanner coefficient of variation (CV) values for all DTI metrics were <5.7%, significant differences were observed for LD (p < 3.3e-5) and FA (p < 0.0024) when GE scanners were compared with Siemens scanners. Significant differences were also observed for SNR when comparing GE scanners and Siemens Skyra scanners (p < 1.4e-7) and when comparing Siemens Skyra scanners and TIM Trio scanners (p < 1.0e-10). Analysis of background signal also demonstrated differences between GE and Siemens scanners in terms of signal statistics. The measured signal intensity from a background noise region of interest was significantly higher for GE scanners than for Siemens scanners (p < 1.2e-12). Significant differences were also observed for SNFR when comparing GE scanners and Siemens Skyra scanners (p < 2.5e-11), GE scanners and Siemens Trio scanners (p < 7.5e-11), and Siemens Skyra scanners and TIM Trio scanners (p < 2.5e-9). CONCLUSIONS: The good repeatability of the DTI metrics among the 27 scanners used in this study confirms the feasibility of combining DTI data from multiple centers using high angular resolution sequences. Our observations support the feasibility of longitudinal multicenter clinical trials using DTI outcome measures. The noise floor level and SNFR are important parameters that must be assessed when comparing studies that used different scanner models.

Quantitative quality assurance in a multicenter HARDI clinical trial at 3T.

A phantom-based quality assurance (QA) protocol was developed for a multicenter clinical trial including high angular resolution diffusion imaging (HARDI). A total of 27 3T MR scanners from 2 major manufacturers, GE (Discovery and Signa scanners) and Siemens (Trio and Skyra scanners), were included in this trial. With this protocol, agar phantoms doped to mimic relaxation properties of brain tissue are scanned on a monthly basis, and quantitative procedures are used to detect spiking and to evaluate eddy current and Nyquist ghosting artifacts. In this study, simulations were used to determine alarm thresholds for minimal acceptable signal-to-noise ratio (SNR). Our results showed that spiking artifact was the most frequently observed type of artifact. Overall, Trio scanners exhibited less eddy current distortion than GE scanners, which in turn showed less distortion than Skyra scanners. This difference was mainly caused by the different sequences used on these scanners. The SNR for phantom scans was closely correlated with the SNR from volunteers. Nearly all of the phantom measurements with artifact-free images were above the alarm threshold, suggesting that the scanners are stable longitudinally. Software upgrades and hardware replacement sometimes affected SNR substantially but sometimes did not. In light of these results, it is important to monitor longitudinal SNR with phantom QA to help interpret potential effects on in vivo measurements. Our phantom QA procedure for HARDI scans was successful in tracking scanner performance and detecting unwanted artifacts.

Modern Methods for Interrogating the Human Connectome.

OBJECTIVES: Connectionist theories of brain function took hold with the seminal contributions of Norman Geschwind a half century ago. Modern neuroimaging techniques have expanded the scientific interest in the study of brain connectivity to include the intact as well as disordered brain. METHODS: In this review, we describe the most common techniques used to measure functional and structural connectivity, including resting state functional MRI, diffusion MRI, and electroencephalography and magnetoencephalography coherence. We also review the most common analytical approaches used for examining brain interconnectivity associated with these various imaging methods. RESULTS: This review presents a critical analysis of the assumptions, as well as methodological limitations, of each imaging and analysis approach. CONCLUSIONS: The overall goal of this review is to provide the reader with an introduction to evaluating the scientific methods underlying investigations that probe the human connectome.

The relationship between cognitive function and high-resolution diffusion tensor MRI of the cingulum bundle in multiple sclerosis.

BACKGROUND: Imaging can provide noninvasive neural markers of disease progression in multiple sclerosis (MS) that are related to behavioral and cognitive symptoms. Past work suggests that diffusion tensor imaging (DTI) provides a measure of white matter pathology, including demyelination and axonal counts. OBJECTIVES: In the current study, the authors investigate the relationship of DTI measures in the cingulum bundle to common deficits in MS, including episodic memory, working memory, and information processing speed. METHODS: Fifty-seven patients with MS and 17 age- and education-matched controls underwent high-spatial resolution diffusion scans and cognitive testing. Probabilistic tracking was used to generate tracks from the posterior cingulate cortex to the entorhinal cortex. RESULTS: Radial and axial diffusivity values were significantly different between patients and controls (p < 0.031), and in patients bilateral diffusion measures were significantly related to measures of episodic memory and speed of processing (p < 0.033). CONCLUSIONS: The tractography-based measures of posterior cingulum integrity reported here support further development of DTI as a viable measure of axonal integrity and cognitive function in patients with MS.

Hippocampal volume is related to cognitive decline and fornicial diffusion measures in multiple sclerosis.

PURPOSE: To assess for associations between hippocampal atrophy and measures of cognitive function, hippocampal magnetization transfer ratio (MTR), and diffusion measures of the fornix, the largest efferent white matter tract from the hippocampus, in patients with multiple sclerosis (MS) and controls. MATERIALS AND METHODS: A total of 53 patients with MS and 20 age- and sex-matched healthy controls participated in cognitive testing and scanning including high spatial-resolution diffusion imaging and a T1-MPRAGE scan. Hippocampal volume and fornicial thickness measures were calculated and compared to mean values of fornicial transverse diffusivity, mean diffusivity, longitudinal diffusivity, fractional anisotropy, mean hippocampal MTR, and scores on measures of episodic memory, processing speed, and working memory tasks. RESULTS: In patients with MS, hippocampal volume was significantly related to fornicial diffusion measures (P<7×10(-4)) and to measures of verbal (P=0.030) and visual spatial (P=0.004) episodic memory and a measure of information processing speed (P<0.037). DISCUSSION: These results highlight the role of the hippocampus in cognitive dysfunction in patients with MS and suggest that measures of hippocampal atrophy could be used to capture aspects of disease progression.

Diffusion weighted imaging of prefrontal cortex in prodromal Huntington's disease.

Huntington's disease (HD) is a devastating neurodegenerative disease with no effective disease-modifying treatments. There is considerable interest in finding reliable indicators of disease progression to judge the efficacy of novel treatments that slow or stop disease onset before debilitating signs appear. Diffusion-weighted imaging (DWI) may provide a reliable marker of disease progression by characterizing diffusivity changes in white matter (WM) in individuals with prodromal HD. The prefrontal cortex (PFC) may play a role in HD progression due to its prominent striatal connections and documented role in executive function. This study uses DWI to characterize diffusivity in specific regions of PFC WM defined by FreeSurfer in 53 prodromal HD participants and 34 controls. Prodromal HD individuals were separated into three CAG-Age Product (CAP) groups (16 low, 22 medium, 15 high) that indexed baseline progression. Statistically significant increases in mean diffusivity (MD) and radial diffusivity (RD) among CAP groups relative to controls were seen in inferior and lateral PFC regions. For MD and RD, differences among controls and HD participants tracked with baseline disease progression. The smallest difference was for the low group and the largest for the high group. Significant correlations between Trail Making Test B (TMTB) and mean fractional anisotropy (FA) and/or RD paralleled group differences in mean MD and/or RD in several right hemisphere regions. The gradient of effects that tracked with CAP group suggests DWI may provide markers of disease progression in future longitudinal studies as increasing diffusivity abnormalities in the lateral PFC of prodromal HD individuals.

Low consistency of four brain connectivity measures derived from intracranial electrode measurements.

Measures of brain connectivity are currently subject to intense scientific and clinical interest. Multiple measures are available, each with advantages and disadvantages. Here, we study epilepsy patients with intracranial electrodes, and compare four different measures of connectivity. Perhaps the most direct measure derives from intracranial electrodes; however, this is invasive and spatial coverage is incomplete. These electrodes can be actively stimulated to trigger electrophysical responses to provide the first measure of connectivity. A second measure is the recent development of simultaneous BOLD fMRI and intracranial electrode stimulation. The resulting BOLD maps form a measure of effective connectivity. A third measure uses low frequency BOLD fluctuations measured by MRI, with functional connectivity defined as the temporal correlation coefficient between their BOLD waveforms. A fourth measure is structural, derived from diffusion MRI, with connectivity defined as an integrated diffusivity measure along a connecting pathway. This method addresses the difficult requirement to measure connectivity between any two points in the brain, reflecting the relatively arbitrary location of the surgical placement of intracranial electrodes. Using a group of eight epilepsy patients with intracranial electrodes, the connectivity from one method is compared to another method using all paired data points that are in common, yielding an overall correlation coefficient. This method is performed for all six paired-comparisons between the four methods. While these show statistically significant correlations, the magnitudes of the correlation are relatively modest (r (2) between 0.20 and 0.001). In summary, there are many pairs of points in the brain that correlate well using one measure yet correlate poorly using another measure. These experimental findings present a complicated picture regarding the measure or meaning of brain connectivity.

Logical foundations and fast implementation of probabilistic tractography.

Although tractography can noninvasively map axonal pathways, current approaches are typically incomplete or computationally intensive. Fast, complete maps may serve as a useful clinical tool for assessing neurological disorders stemming from pathological anatomical connections such as epilepsy. We re-frame tractography in terms of logic and conditional probabilities. The formalism inherently includes global constraints and can compute connections between any two arbitrary regions of the brain. The formalism also lends itself to a fast implementation using standard partial differential equation solvers, which makes whole-brain probabilistic maps of anatomical connectivity feasible. We demonstrate results of our implementation on in vivo data and show that it outperforms Monte Carlo approaches in both computation time and identification of pathways.

High spatial and angular resolution diffusion-weighted imaging reveals forniceal damage related to memory impairment.

INTRODUCTION: Diffusion tensor imaging (DTI) measures in patients with multiple sclerosis (MS), particularly those measures associated with a specific white matter pathway, have consistently shown correlations with function. This study sought to investigate correlations between DTI measures in the fornix and common cognitive deficits in MS patients, including episodic memory, working memory and attention. MATERIALS AND METHODS: Patients with MS and group age- and sex-matched controls underwent high-resolution diffusion scanning (1-mm isotropic voxels) and cognitive testing. Manually drawn forniceal regions of interest were applied to individual maps of tensor-derived measures, and mean values of transverse diffusivity (TD), mean diffusivity (MD), longitudinal diffusivity (LD) and fractional anisotropy (FA) were calculated. RESULTS: In 40 patients with MS [mean age ± S.D.=42.55 ± 9.1 years; Expanded Disability Status Scale (EDSS)=2.0 ± 1.2; Multiple Sclerosis Functional Composite (MSFC) score=0.38 ± 0.46] and 20 healthy controls (mean age ± S.D.=41.35 ± 9.7 years; EDSS=0.0 ± 0; MSFC score=0.74 ± 0.24), we found that FA, MD and TD values in the fornix were significantly different between groups (P<.03), and patient performance on the Brief Visuospatial Memory Test-Revised (BVMT-R) was correlated with DTI measures (P<.03). DISCUSSION: These results are consistent with findings of axonal degeneration in MS and support the use of DTI as an indicator of disease progression.

Quantitative assessment of motion correction for high angular resolution diffusion imaging.

Several methods have been proposed for motion correction of high angular resolution diffusion imaging (HARDI) data. There have been few comparisons of these methods, partly due to a lack of quantitative metrics of performance. We compare two motion correction strategies using two figures of merit: displacement introduced by the motion correction and the 95% confidence interval of the cone of uncertainty of voxels with prolate tensors. What follows is a general approach for assessing motion correction of HARDI data that may have broad application for quality assurance and optimization of postprocessing protocols. Our analysis demonstrates two important issues related to motion correction of HARDI data: (1) although neither method we tested was dramatically superior in performance, both were dramatically better than performing no motion correction, and (2) iteration of motion correction can improve the final results. Based on the results demonstrated here, iterative motion correction is strongly recommended for HARDI acquisitions.

Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation.

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity.

Recent studies indicate that functional connectivity using low-frequency BOLD fluctuations (LFBFs) is reduced between the bilateral primary sensorimotor regions in multiple sclerosis. In addition, it has been shown that pathway-dependent measures of the transverse diffusivity of water in white matter correlate with related clinical measures of functional deficit in multiple sclerosis. Taken together, these methods suggest that MRI methods can be used to probe both functional connectivity and anatomic connectivity in subjects with known white matter impairment. We report the results of a study comparing anatomic connectivity of the transcallosal motor pathway, as measured with diffusion tensor imaging (DTI) and functional connectivity of the bilateral primary sensorimotor cortices (SMC), as measured with LFBFs in the resting state. High angular resolution diffusion imaging was combined with functional MRI to define the transcallosal white matter pathway connecting the bilateral primary SMC. Maps were generated from the probabilistic tracking employed and these maps were used to calculate the mean pathway diffusion measures fractional anisotropy FA, mean diffusivity MD, longitudinal diffusivity lambda(1), and transverse diffusivity lambda(2). These were compared with LFBF-based functional connectivity measures (F(c)) obtained at rest in a cohort of 11 multiple sclerosis patients and approximately 10 age- and gender-matched control subjects. The correlation between FA and F(c) for MS patients was r = -0.63, P < 0.04. The correlation between all subjects lambda(2) and F(c) was r = 0.42, P < 0.05. The correlation between all subjects lambda(2) and F(c) was r = -0.50, P < 0.02. None of the control subject correlations were significant, nor were FA, lambda(1), or MD significantly correlated with F(c) for MS patients. This constitutes the first in vivo observation of a correlation between measures of anatomic connectivity and functional connectivity using spontaneous LFBFs.

An objective method for regularization of fiber orientation distributions derived from diffusion-weighted MRI.

Spherical deconvolution is an elegant method by which the orientation of crossing fibers in the brain can be estimated from a diffusion-weighted MRI measurement. However, higher resolution of fiber directions comes at the cost of higher susceptibility to noise. In this study, we describe the use of linear regularization of the fiber orientation distribution function by Damped Singular Value Decomposition. Furthermore, the degree of regularization is optimized on a voxel-by-voxel basis with no user interaction using Generalized Cross Validation. We find, by simulations, that regularization can improve the reliability of fiber orientation determination when the signal-to-noise ratio is low. Simulations and in vivo measurements indicate that spurious peaks of the fiber orientation distribution function in regions with low anisotropy largely disappear when regularization is introduced. The methods examined are fast enough to be used on a routine basis with diffusion MRI data sets and may improve estimation of water diffusion properties in heterogeneous white matter and boost reliability of fiber tracking through regions of brain with complex fiber geometry.