Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.

Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.

Genetic risk for schizophrenia is associated with altered visually-induced gamma band activity: evidence from a population sample stratified polygenic risk.

Gamma oscillations (30-90 Hz) have been proposed as a signature of cortical visual information processing, particularly the balance between excitation and inhibition, and as a biomarker of neuropsychiatric diseases. Magnetoencephalography (MEG) provides highly reliable visual-induced gamma oscillation estimates, both at sensor and source level. Recent studies have reported a deficit of visual gamma activity in schizophrenia patients, in medication naive subjects, and high-risk clinical participants, but the genetic contribution to such a deficit has remained unresolved. Here, for the first time, we use a genetic risk score approach to assess the relationship between genetic risk for schizophrenia and visual gamma activity in a population-based sample drawn from a birth cohort. We compared visual gamma activity in a group (N = 104) with a high genetic risk profile score for schizophrenia (SCZ-PRS) to a group with low SCZ-PRS (N = 99). Source-reconstructed V1 activity was extracted using beamformer analysis applied to MEG recordings using individual MRI scans. No group differences were found in the induced gamma peak amplitude or peak frequency. However, a non-parametric statistical contrast of the response spectrum revealed more robust group differences in the amplitude of high-beta/gamma power across the frequency range, suggesting that overall spectral shape carries important biological information beyond the individual frequency peak. Our findings show that changes in gamma band activity correlate with liability to schizophrenia and suggest that the index changes to synaptic function and neuronal firing patterns that are of pathophysiological relevance rather than consequences of the disorder.

Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory.

The dorsal hippocampal commissure (DHC) is a white matter tract that provides interhemispheric connections between temporal lobe brain regions. Despite the importance of these regions for learning and memory, there is scant evidence of a role for the DHC in successful memory performance. We used diffusion-weighted magnetic resonance imaging (DW-MRI) and white matter tractography to reconstruct the DHC in both humans (in vivo) and nonhuman primates (ex vivo). Across species, our findings demonstrate a close consistency between the known anatomy and tract reconstructions of the DHC. Anterograde tract-tracer techniques also highlighted the parahippocampal origins of DHC fibers in nonhuman primates. Finally, we derived diffusion tensor MRI metrics from the DHC in a large sample of human subjects to investigate whether interindividual variation in DHC microstructure is predictive of memory performance. The mean diffusivity of the DHC correlated with performance in a standardized recognition memory task, an effect that was not reproduced in a comparison commissure tract-the anterior commissure. These findings highlight a potential role for the DHC in recognition memory, and our tract reconstruction approach has the potential to generate further novel insights into the role of this previously understudied white matter tract in both health and disease.

The presence of antibiotic resistance genes in coastal soil and sediment samples from the eastern seaboard of the USA.

Infections from antibiotic resistant microorganisms are considered to be one of the greatest global public health challenges that result in huge annual economic losses. While genes that impart resistance to antibiotics (AbR) existed long before the discovery and use of antibiotics, anthropogenic uses of antibiotics in agriculture, domesticated animals, and humans are known to influence the prevalence of these genes in pathogenic microorganisms. It is critical to understand the role that natural and anthropogenic processes have on the occurrence and distribution of antibiotic resistance in microbial populations to minimize health risks associated with exposures. As part of this research, 15 antibiotic resistance genes were analyzed in coastal sediments and soils along the eastern seaboard of the USA using presence/absence quantitative and digital polymerase chain reaction assays. Samples (53 soil and 192 sediment samples including 54 replicates) were collected from a variety of coastal settings where human and wildlife exposure is likely. At least one of the antibiotic resistance genes was detected in 76.4% of the samples. Samples that contained at least five or more antibiotic resistance genes (5.7%) where typically hydrologically down gradient of watersheds influenced by combined sewer outfalls (CSO). The most frequently detected antibiotic resistance target genes were found in 33.2%, 34.4%, and 42.2% of samples (target genes blaSHV, tetO, and aadA2, respectively). These data provide unique insight into potential exposure of AbR genes over a large geographical region of the eastern seaboard of the USA.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Effects of a common insecticide on wetland communities with varying quality of leaf litter inputs.

Chemical contamination of aquatic systems often co-occurs with dramatic changes in surrounding terrestrial vegetation. Plant leaf litter serves as a crucial resource input to many freshwater systems, and changes in litter species composition can alter the attributes of freshwater communities. However, little is known how variation in litter inputs interacts with chemical contaminants. We investigated the ecological effects resulting from changes in tree leaf litter inputs to freshwater communities, and how those changes might interact with the timing of insecticide contamination. Using the common insecticide malathion, we hypothesized that inputs of nutrient-rich and labile leaf litter (e.g., elm [Ulmus spp.] or maple [Acer spp.]) would reduce the negative effects of insecticides on wetland communities relative to inputs of recalcitrant litter (e.g., oak [Quercus spp.]). We exposed artificial wetland communities to a factorial combination of three litter species treatments (elm, maple, and oak) and four insecticide treatments (no insecticide, small weekly doses of 10 µg L-1, and either early or late large doses of 50 µg L-1). Communities consisted of microbes, algae, snails, amphipods, zooplankton, and two species of tadpoles. After two months, we found that maple and elm litter generally induced greater primary and secondary production. Insecticides induced a reduction in the abundance of amphipods and some zooplankton species, and increased phytoplankton. In addition, we found interactive effects of litter species and insecticide treatments on amphibian responses, although specific effects depended on application regime. Specifically, with the addition of insecticide, elm and maple litter induced a reduction in gray tree frog survival, oak and elm litter delayed tree frog metamorphosis, and oak and maple litter reduced green frog tadpole mass. Our results suggest that attention to local forest composition, as well as the timing of pesticide application might help ameliorate the harmful effects of pesticides observed in freshwater systems.

Relationship Between Cortical Gyrification, White Matter Connectivity, and Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition, which is accompanied by differences in gray matter neuroanatomy and white matter connectivity. However, it is unknown whether these differences are linked or reflect independent aetiologies. Using a multimodal neuroimaging approach, we therefore examined 51 male adults with ASD and 48 neurotypical controls to investigate the relationship between gray matter local gyrification (lGI) and white matter diffusivity in associated fiber tracts. First, ASD individuals had a significant increase in gyrification around the left pre- and post-central gyrus. Second, white matter fiber tracts originating and/or terminating in the cluster of increased lGI had a significant increase in axial diffusivity. This increase in diffusivity was predominantly observed in tracts in close proximity to the cortical sheet. Last, we demonstrate that the increase in lGI was significantly correlated with increased diffusivity of short tracts. This relationship was not significantly modulated by a main effect of group (i.e., ASD), which was more closely associated with gray matter gyrification than white matter diffusivity. Our findings suggest that differences in gray matter neuroanatomy and white matter connectivity are closely linked, and may reflect common rather than distinct aetiological pathways.

Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.

Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced by thresholding, making statistical comparisons of network metrics difficult. However, by testing for effects across multiple thresholds using MTPC, true group differences can be robustly identified.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.

OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. METHODS: Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. RESULTS: Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. CONCLUSIONS: Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

Hedonic tone is associated with left supero-lateral medial forebrain bundle microstructure.

BACKGROUND: The medial forebrain bundle (MFB) is an important pathway of the reward system. Two branches have been described using diffusion magnetic resonance imaging (MRI)-based tractography: the infero-medial MFB (imMFB) and the supero-lateral MFB (slMFB). Previous studies point to white-matter microstructural alterations of the slMFB in major depressive disorder (MDD) during acute episodes. To extend this finding, this study investigates whether white-matter microstructure is also altered in MDD patients that are in remission. Further, we explore associations between diffusion MRI-based metrics of white-matter microstructure of imMFB, slMFB and hedonic tone, the ability to derive pleasure. METHOD: Eighteen remitted depressed (RD) and 22 never depressed (ND) participants underwent high angular resolution diffusion-weighted imaging (HARDI) scans. To reconstruct the two pathways of the MFB (imMFB and slMFB) we used the damped Richardson-Lucy (dRL) algorithm. Mean fractional anisotropy (FA) was sampled along the tracts. RESULTS: Mean FA of imMFB, slMFB and a comparison tract (the middle cerebellar peduncle) did not differ between ND and RD participants. Hedonic capacity correlated negatively with mean FA of the left slMFB, explaining 21% of the variance. CONCLUSIONS: Diffusion MRI-based metrics of white-matter microstructure of the MFB in RD do not differ from ND. Hedonic capacity is associated with altered white-matter microstructure of the slMFB.

Improved precision in CHARMED assessment of white matter through sampling scheme optimization and model parsimony testing.

PURPOSE: The composite hindered and restricted model of diffusion provides microstructural indices that are potentially more specific than those from diffusion tensor imaging. However, in comparison to diffusion tensor imaging, the acquisition time is longer, limiting clinical applications. Moreover, the model requires several parameters to be estimated whose confidence intervals can be large. Here, the composite hindered and restricted model of diffusion acquisition and data processing pipelines are optimized to extend the utility of this approach. METHODS: A multishell sampling scheme was optimized using the electrostatic repulsion algorithm, combined with optimal ordering. The optimal protocol, using as few measurements as possible, was determined through leave-n-out analyses. Parsimonious model selection criteria were used to select between nested models, comprising up to three restricted compartments. The schemes were evaluated using both through Monte-Carlo simulations and in vivo data. RESULTS: The optimization/model selection procedure resulted in increased accuracy and precision on the estimated parameters, allowing for a reduction in acquisition time and marked improvements in data quality. The final protocol provided whole brain coverage data in only 12 min. CONCLUSION: Through careful optimization of the acquisition and analysis pipeline for the composite hindered and restricted model of diffusion, it is possible to reduce acquisition time for whole brain datasets to a time that is clinically applicable.

Extracellular protons inhibit charge immobilization in the cardiac voltage-gated sodium channel.

Low pH depolarizes the voltage-dependence of cardiac voltage-gated sodium (NaV1.5) channel activation and fast inactivation and destabilizes the fast-inactivated state. The molecular basis for these changes in protein behavior has not been reported. We hypothesized that changes in the kinetics of voltage sensor movement may destabilize the fast-inactivated state in NaV1.5. To test this idea, we recorded NaV1.5 gating currents in Xenopus oocytes using a cut-open voltage-clamp with extracellular solution titrated to either pH 7.4 or pH 6.0. Reducing extracellular pH significantly depolarized the voltage-dependence of both the QON/V and QOFF/V curves, and reduced the total charge immobilized during depolarization. We conclude that destabilized fast-inactivation and reduced charge immobilization in NaV1.5 at low pH are functionally related effects.

RAPID: a routine assurance pipeline for imaging of diffusion.

Despite the widespread adoption of diffusion MRI techniques, there is still no consensus on a comprehensive quality assurance routine specific for diffusion acquisitions. We propose here a routine assurance pipeline for imaging of diffusion. The routine simply comprises diffusion-weighted acquisitions on a phantom; each repetition lasts less than 5 min and can be performed using a variety of isotropic test liquids. The proposed QA script checks for the linearity of G, the uniformity of Gmax across the field-of-view, the mutual agreement of gradient power across the three logical axes and the temporal stability. Optionally, the routine can correct for the mutual agreement of gradient power along the three axes, returning a set of gradient orientations to be used in data analysis. The effectiveness of the scheme in the presence of mismatched gradient amplitudes is reported using both simulations and in vivo data. The script is freely available online.

A pitfall in the reconstruction of fibre ODFs using spherical deconvolution of diffusion MRI data.

Diffusion weighted (DW) MRI facilitates non-invasive quantification of tissue microstructure and, in combination with appropriate signal processing, three-dimensional estimates of fibrous orientation. In recent years, attention has shifted from the diffusion tensor model, which assumes a unimodal Gaussian diffusion displacement profile to recover fibre orientation (with various well-documented limitations), towards more complex high angular resolution diffusion imaging (HARDI) analysis techniques. Spherical deconvolution (SD) approaches assume that the fibre orientation density function (fODF) within a voxel can be obtained by deconvolving a 'common' single fibre response function from the observed set of DW signals. In practice, this common response function is not known a priori and thus an estimated fibre response must be used. Here the establishment of this single-fibre response function is referred to as 'calibration'. This work examines the vulnerability of two different SD approaches to inappropriate response function calibration: (1) constrained spherical harmonic deconvolution (CSHD)--a technique that exploits spherical harmonic basis sets and (2) damped Richardson-Lucy (dRL) deconvolution--a technique based on the standard Richardson-Lucy deconvolution. Through simulations, the impact of a discrepancy between the calibrated diffusion profiles and the observed ('Target') DW-signals in both single and crossing-fibre configurations was investigated. The results show that CSHD produces spurious fODF peaks (consistent with well known ringing artefacts) as the discrepancy between calibration and target response increases, while dRL demonstrates a lower over-all sensitivity to miscalibration (with a calibration response function for a highly anisotropic fibre being optimal). However, dRL demonstrates a reduced ability to resolve low anisotropy crossing-fibres compared to CSHD. It is concluded that the range and spatial-distribution of expected single-fibre anisotropies within an image must be carefully considered to ensure selection of the appropriate algorithm, parameters and calibration. Failure to choose the calibration response function carefully may severely impact the quality of any resultant tractography.

Distinct subdivisions of the cingulum bundle revealed by diffusion MRI fibre tracking: implications for neuropsychological investigations.

The cingulum is a prominent white matter tract that supports prefrontal, parietal, and temporal lobe interactions. Despite being composed of both short and long association fibres, many MRI-based reconstructions (tractography) of the cingulum depict an essentially uniform tract that almost encircles the corpus callosum. The present study tested the validity of dividing this tract into subdivisions corresponding to the 'parahippocampal', 'retrosplenial', and 'subgenual' portions of the cingulum. These three cingulum subdivisions occupied different medial-lateral locations, producing a topographic arrangement of cingulum fibres. Other comparisons based on these different reconstructions indicate that only a small proportion of the total white matter in the cingulum traverses the length of the tract. In addition, both the radial diffusivity and fractional anisotropy of the subgenual subdivision differed from that of the retrosplenial subdivision which, in turn, differed from that of the parahippocampal subdivision. The extent to which the radial diffusivity scores and the fractional anisotropy scores correlated between the various cingulum subdivisions proved variable, illustrating how one subdivision may not act as a proxy for other cingulum subdivisions. Attempts to relate the status of the cingulum, as measured by MRI-based fibre tracking, with cognitive or affective measures will, therefore, depend greatly on how and where the cingulum is reconstructed. The present study provides a new framework for subdividing the cingulum, based both on its known connectivity and MRI-based properties.

Extracellular proton modulation of the cardiac voltage-gated sodium channel, Nav1.5.

Low pH depolarizes the voltage dependence of voltage-gated sodium (Na(V)) channel activation and fast inactivation. A complete description of Na(V) channel proton modulation, however, has not been reported. The majority of Na(V) channel proton modulation studies have been completed in intact tissue. Additionally, several Na(V) channel isoforms are expressed in cardiac tissue. Characterizing the proton modulation of the cardiac Na(V) channel, Na(V)1.5, will thus help define its contribution to ischemic arrhythmogenesis, where extracellular pH drops from pH 7.4 to as low as pH 6.0 within ~10 min of its onset. We expressed the human variant of Na(V)1.5 with and without the modulating ß(1) subunit in Xenopus oocytes. Lowering extracellular pH from 7.4 to 6.0 affected a range of biophysical gating properties heretofore unreported. Specifically, acidic pH destabilized the fast-inactivated and slow-inactivated states, and elevated persistent I(Na). These data were incorporated into a ventricular action potential model that displayed a reduced maximum rate of depolarization as well as disparate increases in epicardial, mid-myocardial, and endocardial action potential durations, indicative of an increased heterogeneity of repolarization. Portions of these data were previously reported in abstract form.

Differential corticospinal tract degeneration in homozygous 'D90A' SOD-1 ALS and sporadic ALS.

BACKGROUND: The homogeneous genotype and stereotyped phenotype of a unique familial form of amyotrophic lateral sclerosis (ALS) (patients homozygous for aspartate-to-alanine mutations in codon 90 (homD90A) superoxide dismutase 1) provides an ideal model for studying genotype/phenotype interactions and pathological features compared with heterogeneous apparently sporadic ALS. The authors aimed to use diffusion tensor tractography to quantify and compare changes in the intracerebral corticospinal tracts of patients with both forms of ALS, building on previous work using whole-brain voxelwise group analysis. METHOD: 21 sporadic ALS patients, seven homD90A patients and 20 healthy controls underwent 1.5 T diffusion tensor MRI. Patients were assessed using 'upper motor neuron burden,' El Escorial and ALSFR-R scales. The intracranial corticospinal tract was assessed using diffusion tensor tractography measures of fractional anisotropy (FA), mean diffusivity, and radial and axial diffusivity obtained from its entire length. RESULTS: Corticospinal tract FA was reduced in sporadic ALS patients compared with both homD90A ALS patients and controls. The diffusion measures in sporadic ALS patients were consistent with anterograde (Wallerian) degeneration of the corticospinal tracts. In sporadic ALS, corticospinal tract FA was related to clinical measures. Despite a similar degree of clinical upper motor neuron dysfunction and disability in homD90A ALS patients compared with sporadic ALS, there were no abnormalities in corticospinal tract diffusion measures compared with controls. CONCLUSIONS: Diffusion tensor tractography has shown axonal degeneration within the intracerebral portion of the corticospinal tract in sporadic ALS patients, but not those with a homogeneous form of familial ALS. This suggests significant genotypic influences on the phenotype of ALS and may provide clues to slower progression of disease in homD90A patients.

Measuring brain stem and cerebellar damage in parkinsonian syndromes using diffusion tensor MRI.

OBJECTIVE: To use diffusion tensor MRI to quantify and compare degeneration of the pons and cerebellar peduncles in multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and Parkinson disease (PD) and to relate changes in diffusion measures to clinical features and localized atrophy. METHODS: We used a region-of-interest approach to measure changes in fractional anisotropy and mean diffusivity in the middle cerebellar peduncles, decussation of the superior cerebellar peduncles, and pons in 17 patients with MSA, 17 with PSP, 12 with PD, and 12 healthy volunteers. We also evaluated atrophy of the cerebellar peduncles and pons on T2-weighted magnetic resonance images in patients with MSA and PSP. RESULTS: In MSA, fractional anisotropy was markedly reduced in the middle cerebellar peduncles, and mean diffusivity increased both here and in the pons compared with other groups, whereas in PSP, mean diffusivity was strikingly increased in the decussation of superior cerebellar peduncles. Cerebellar ataxia was related to mean diffusivity in the middle cerebellar peduncles (r = 0.71, p = 0.001) and pons (r = 0.60, p = 0.01) in MSA. Diffusion measures were related to localized atrophy in both MSA and PSP. CONCLUSIONS: Diffusion tensor MRI can be used to quantify neurodegenerative processes in different brain stem and cerebellar structures in multiple system atrophy and progressive supranuclear palsy during life, and may have diagnostic value. Larger studies of early, undifferentiated parkinsonian syndromes are indicated to provide estimates of the relative diagnostic value of diffusion measures, atrophy measures, and visual assessment of scans.

Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis.

BACKGROUND: Cerebral small vessel disease is a common cause of vascular dementia. Both discrete lacunar infarcts and more diffuse ischaemic changes, seen as confluent high signal (leukoaraiosis) on T2 weighted magnetic resonance imaging (MRI), occur. However, there is a weak correlation between T2 lesion load and cognitive impairment. Diffusion tensor MRI (DTI) is a new technique that may provide a better index of white matter damage. OBJECTIVES: To determine whether DTI measures are correlated more strongly with cognitive performance than lesion load on T2 weighted images, and whether these correlations are independent of conventional MRI parameters. METHODS: 36 patients with ischaemic leukoaraiosis (leukoaraiosis plus a previous lacunar stroke) and 19 healthy volunteers underwent DTI, conventional MRI, and neuropsychological assessment. RESULTS: On DTI, diffusivity was increased both within lesions and in normal appearing white matter. Mean diffusivity of normal appearing white matter correlated with full scale IQ (r = -0.46, p = 0.009) and tests of executive function. These correlations remained significant after controlling for age, sex, brain volume, and T1/T2 lesion volumes. No significant correlation was identified between T2 lesion load and IQ or neuropsychological scores. Of conventional measures, brain volume correlated best with cognitive function. CONCLUSIONS: Diffusion tensor measurements correlate better with cognition than conventional MRI measures. They may be useful in monitoring disease progression and as a surrogate marker for treatment trials. The findings support the role of white matter damage and disruption of white matter connections in the pathogenesis of cognitive impairment in cerebral small vessel disease.