Arvind Caprihan

Reproducibility of Quantitative Tractography Methods Applied to Cerebral White Matter

Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols were refined by several iterations of intra- and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T2 of individual white matter tracts. Distinctive features in FA and T2 were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.

A Baseline for the Multivariate Comparison of Resting-State Networks

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

Use of tissue water as a concentration reference for proton spectroscopic imaging

A strategy for using tissue water as a concentration standard in 1H magnetic resonance spectroscopic imaging studies on the brain is presented, and the potential errors that may arise when the method is used are examined. The sensitivity of the method to errors in estimates of the different water compartment relaxation times is shown to be small at short echo times (TEs). Using data from healthy human subjects, it is shown that different image segmentation approaches that are commonly used to account for partial volume effects (SPM2, FSLs FAST, and K‐means) lead to different estimates of metabolite levels, particularly in gray matter (GM), owing primarily to variability in the estimates of the cerebrospinal fluid (CSF) fraction. While consistency does not necessarily validate a method, a multispectral segmentation approach using FAST yielded the lowest intersubject variability in the estimates of GM metabolites. The mean GM and white matter (WM) levels of N‐acetyl groups (NAc, primarily N‐acetylaspartate), choline (Ch), and creatine (Cr) obtained in these subjects using the described method with FAST multispectral segmentation are reported: GM [NAc] = 17.16 ± 1.19 mM; WM [NAc] = 14.26 ± 1.38 mM; GM [Ch] = 3.27 ± 0.47 mM; WM [Ch] = 2.65 ± 0.25 mM; GM [Cr] = 13.98 ± 1.20 mM; and WM [Cr] = 7.10 ± 0.67 mM. Magn Reson Med, 2006.

Proton Echo-Planar Spectroscopic Imaging of J-Coupled Resonances in Human Brain at 3 and 4 Tesla

In this multicenter study, 2D spatial mapping of J‐coupled resonances at 3T and 4T was performed using short‐TE (15 ms) proton echo‐planar spectroscopic imaging (PEPSI). Water‐suppressed (WS) data were acquired in 8.5 min with 1‐cm3 spatial resolution from a supraventricular axial slice. Optimized outer volume suppression (OVS) enabled mapping in close proximity to peripheral scalp regions. Constrained spectral fitting in reference to a non‐WS (NWS) scan was performed with LCModel using correction for relaxation attenuation and partial‐volume effects. The concentrations of total choline (tCho), creatine + phosphocreatine (Cr+PCr), glutamate (Glu), glutamate + glutamine (Glu+Gln), myo‐inositol (Ins), NAA, NAA+NAAG, and two macromolecular resonances at 0.9 and 2.0 ppm were mapped with mean Cramer‐Rao lower bounds (CRLBs) between 6% and 18% and ∼150‐cm3 sensitive volumes. Aspartate, GABA, glutamine (Gln), glutathione (GSH), phosphoethanolamine (PE), and macromolecules (MMs) at 1.2 ppm were also mapped, although with larger mean CRLBs between 30% and 44%. The CRLBs at 4T were 19% lower on average as compared to 3T, consistent with a higher signal‐to‐noise ratio (SNR) and increased spectral resolution. Metabolite concentrations were in the ranges reported in previous studies. Glu concentration was significantly higher in gray matter (GM) compared to white matter (WM), as anticipated. The short acquisition time makes this methodology suitable for clinical studies. Magn Reson Med, 2007.

White Matter Integrity, Creativity, and Psychopathology: Disentangling Constructs with Diffusion Tensor Imaging

That creativity and psychopathology are somehow linked remains a popular but controversial idea in neuroscience research. Brain regions implicated in both psychosis-proneness and creative cognition include frontal projection zones and association fibers. In normal subjects, we have previously demonstrated that a composite measure of divergent thinking (DT) ability exhibited significant inverse relationships in frontal lobe areas with both cortical thickness and metabolite concentration of N-acetyl-aspartate (NAA). These findings support the idea that creativity may reside upon a continuum with psychopathology. Here we examine whether white matter integrity, assessed by Fractional Anisotropy (FA), is related to two measures of creativity (Divergent Thinking and Openness to Experience). Based on previous findings, we hypothesize inverse correlations within fronto-striatal circuits. Seventy-two healthy, young adult (18–29 years) subjects were scanned on a 3 Tesla scanner with Diffusion Tensor Imaging. DT measures were scored by four raters (α = .81) using the Consensual Assessment Technique, from which a composite creativity index (CCI) was derived. We found that the CCI was significantly inversely related to FA within the left inferior frontal white matter (t = 5.36, p = .01), and Openness was inversely related to FA within the right inferior frontal white matter (t = 4.61, p = .04). These findings demonstrate an apparent overlap in specific white matter architecture underlying the normal variance of divergent thinking, openness, and psychotic-spectrum traits, consistent with the idea of a continuum.

Long-term effects of marijuana use on the brain

Significance The existing literature on the long-term effects of marijuana on the brain provides an inconsistent picture (i.e., presence or absence of structural changes) due to methodological differences across studies. We overcame these methodological issues by collecting multimodal measures in a large group of chronic marijuana using adults with a wide age range that allows for characterization of changes across lifespan without developmental or maturational biases as in other studies. Our findings suggest that chronic marijuana use is associated with complex neuroadaptive processes and that onset and duration of use have unique effects on these processes. Questions surrounding the effects of chronic marijuana use on brain structure continue to increase. To date, however, findings remain inconclusive. In this comprehensive study that aimed to characterize brain alterations associated with chronic marijuana use, we measured gray matter (GM) volume via structural MRI across the whole brain by using voxel-based morphology, synchrony among abnormal GM regions during resting state via functional connectivity MRI, and white matter integrity (i.e., structural connectivity) between the abnormal GM regions via diffusion tensor imaging in 48 marijuana users and 62 age- and sex-matched nonusing controls. The results showed that compared with controls, marijuana users had significantly less bilateral orbitofrontal gyri volume, higher functional connectivity in the orbitofrontal cortex (OFC) network, and higher structural connectivity in tracts that innervate the OFC (forceps minor) as measured by fractional anisotropy (FA). Increased OFC functional connectivity in marijuana users was associated with earlier age of onset. Lastly, a quadratic trend was observed suggesting that the FA of the forceps minor tract initially increased following regular marijuana use but decreased with protracted regular use. This pattern may indicate differential effects of initial and chronic marijuana use that may reflect complex neuroadaptive processes in response to marijuana use. Despite the observed age of onset effects, longitudinal studies are needed to determine causality of these effects.

Comparative reliability of proton spectroscopy techniques designed to improve detection of J-coupled metabolites.

Improved detection of J‐coupled neurometabolites through the use of modified proton magnetic resonance spectroscopy (1H‐MRS) techniques has recently been reported. TE‐averaged point‐resolved spectroscopy (PRESS) uses the J modulation effects by averaging FIDs with differing echo times to improve detection of glutamate, while standard PRESS detection of glutamate can be improved by using an appropriate single echo determined from J‐modulation simulations. In the present study, the reliabilities of TE‐averaged PRESS, standard PRESS with TE = 40 ms, and standard PRESS with TE = 30 ms in detecting metabolite levels in the cingulate gyrus of the human brain at 3T were compared in six subjects. TE‐averaged PRESS measures showed a mean variability of 9% for N‐acetyl aspartate, choline, and creatine, compared with < 4% for the 30‐ and 40‐ms PRESS techniques. The coefficients of variation for glutamate were 10%, 7%, and 5% for TE‐averaged, 30‐ms, and 40‐ms PRESS, respectively. PRESS with a TE of 40 ms also demonstrated improved reliability for GABA and glutamine concentrations. These results show that with the appropriate selection of echo time standard PRESS can be a reliable 1H‐MRS technique for the measurement of J‐coupled neurometabolites in the human brain and, moreover, compares favorably with at least one J‐edited technique. Magn Reson Med 60:964–969, 2008.

Head Injury or Head Motion? Assessment and Quantification of Motion Artifacts in Diffusion Tensor Imaging Studies

The relationship between head motion and diffusion values such as fractional anisotropy (FA) and mean diffusivity (MD) is currently not well understood. Simulation studies suggest that head motion may introduce either a positive or negative bias, but this has not been quantified in clinical studies. Moreover, alternative measures for removing bias as result of head motion, such as the removal of problematic gradients, has been suggested but not carefully evaluated. The current study examined the impact of head motion on FA and MD across three common pipelines (tract‐based spatial statistics, voxelwise, and region of interest analyses) and determined the impact of removing diffusion weighted images. Our findings from a large cohort of healthy controls indicate that while head motion was associated with a positive bias for both FA and MD, the effect was greater for MD. The positive bias was observed across all three analysis pipelines and was present following established protocols for data processing, suggesting that current techniques (i.e., correction of both image and gradient table) for removing motion bias are likely insufficient. However, the removal of images with gross artifacts did not fundamentally change the relationship between motion and DTI scalar values. In addition, Monte Carlo simulations suggested that the random removal of images increases the bias and reduces the precision of both FA and MD. Finally, we provide an example of how head motion can be quantified across different neuropsychiatric populations, which should be implemented as part of any diffusion tensor imaging quality assurance protocol. Hum Brain Mapp, 2012.

Resting-state functional connectivity differences in premature children

We examine the coherence in the spontaneous brain activity of sleeping children as measured by the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals. The results are described in terms of resting-state networks (RSN) and their properties. More specifically, in this study we examine the effect of severe prematurity on the spatial location of the visual, temporal, motor, basal ganglia, and the default mode networks, the temporal response properties of each of these networks, and the functional connectivity between them. Our results suggest that the anatomical locations of the RSNs are well developed by 18 months of age and their spatial locations are not distinguishable between premature and term born infants at 18 months or at 36 months, with the exception of small spatial differences noted in the basal ganglia area and the visual cortex. The two major differences between term and pre-term children were present at 36 but not 18 months and include: (1) increased spectral energy in the low frequency range (0.01–0.06 Hz) for pre-term children in the basal ganglia component, and (2) stronger connectivity between RSNs in term children. We speculate that children born very prematurely are vulnerable to injury resulting in weaker connectivity between resting-state networks by 36 months of age. Further work is required to determine whether this could be a clinically useful tool to identify children at risk of developmental delay related to premature birth.

Sensitivity-Encoded (SENSE) Proton Echo-Planar Spectroscopic Imaging (PEPSI) in the Human Brain

Magnetic resonance spectroscopic imaging (MRSI) provides spatially resolved metabolite information that is invaluable for both neuroscience studies and clinical applications. However, lengthy data acquisition times, which are a result of time‐consuming phase encoding, represent a major challenge for MRSI. Fast MRSI pulse sequences that use echo‐planar readout gradients, such as proton echo‐planar spectroscopic imaging (PEPSI), are capable of fast spectral‐spatial encoding and thus enable acceleration of image acquisition times. Combining PEPSI with recent advances in parallel MRI utilizing RF coil arrays can further accelerate MRSI data acquisition. Here we investigate the feasibility of ultrafast spectroscopic imaging at high field (3T and 4T) by combining PEPSI with sensitivity‐encoded (SENSE) MRI using eight‐channel head coil arrays. We show that the acquisition of single‐average SENSE‐PEPSI data at a short TE (15 ms) can be accelerated to 32 s or less, depending on the field strength, to obtain metabolic images of choline (Cho), creatine (Cre), N‐acetyl‐aspartate (NAA), and J‐coupled metabolites (e.g., glutamate (Glu) and inositol (Ino)) with acceptable spectral quality and localization. The experimentally measured reductions in signal‐to‐noise ratio (SNR) and Cramer‐Rao lower bounds (CRLBs) of metabolite resonances were well explained by both the g‐factor and reduced measurement times. Thus, this technology is a promising means of reducing the scan times of 3D acquisitions and time‐resolved 2D measurements. Magn Reson Med 57:249–257, 2007.