Diffusion MRI Metrics Research Articles

The role of critical immune genes in brain disorders: insights from neuroimaging immunogenetics.

Genetic variants in the human leukocyte antigen and killer cell immunoglobulin-like receptor regions have been associated with many brain-related diseases, but how they shape brain structure and function remains unclear. To identify the genetic variants in HLA and KIR genes associated with human brain phenotypes, we performed a genetic association study of ∼30 000 European unrelated individuals using brain MRI phenotypes generated by the UK Biobank (UKB). We identified 15 HLA alleles in HLA class I and class II genes significantly associated with at least one brain MRI-based phenotypes (P < 5 × 10−8). These associations converged on several main haplotypes within the HLA. In particular, the human leukocyte antigen alleles within an ancestral haplotype 8.1 were associated with multiple MRI measures, including grey matter volume, cortical thickness (TH) and diffusion MRI (dMRI) metrics. These alleles have been strongly associated with schizophrenia. Additionally, associations were identified between HLA-DRB1*04∼DQA1*03:01∼DQB1*03:02 and isotropic volume fraction of diffusion MRI in multiple white matter tracts. This haplotype has been reported to be associated with Parkinson’s disease. These findings suggest shared genetic associations between brain MRI biomarkers and brain-related diseases. Additionally, we identified 169 associations between the complement component 4 (C4) gene and imaging phenotypes. We found that C4 gene copy number was associated with cortical TH and dMRI metrics. No KIR gene copy numbers were associated with image-derived phenotypes at genome-wide threshold. To address the multiple testing burden in the phenome-wide association study, we performed a multi-trait association analysis using trait-based association test that uses extended Simes procedure and identified MRI image-specific associations. This study contributes to insight into how critical immune genes affect brain-related traits as well as the development of neurological and neuropsychiatric disorders.

Spatiotemporal characterisation of ischaemic lesions in transient stroke animal models using diffusion free water elimination and mapping MRI with echo time dependence

Background and purposeThe excess fluid as a result of vasogenic oedema and the subsequent tissue cavitation obscure the microstructural characterisation of ischaemic tissue by conventional diffusion and relaxometry MRI. They lead to a pseudo-normalisation of the water diffusivity and transverse relaxation time maps in the subacute and chronic phases of stroke. Within the context of diffusion MRI, the free water elimination and mapping method (FWE) with echo time dependence has been proposed as a promising approach to measure the amount of free fluid in brain tissue robustly and to eliminate its biasing effect on other biomarkers. In this longitudinal study of transient middle cerebral artery occlusion (MCAo) in the rat brain, we investigated the use of FWE MRI with echo time dependence for the characterisation of the tissue microstructure and explored the potential of the free water fraction as a novel biomarker of ischaemic tissue condition. MethodsAdult rats received a transient MCAo. Diffusion- and transverse relaxation-weighted MRI experiments were performed longitudinally, pre-occlusion and on days 1, 3, 4, 5, 6, 7 and 10 after MCAo on four rats. Histology was performed for non-stroke and 1, 3 and 10 days after MCAo on three different rats at each time point. ResultsThe free water fraction was homogeneously increased in the ischaemic cortex one day after stroke. Between three and ten days after stroke, the core of the ischaemic tissue showed a progressive normalisation in the amount of free water, whereas the inner and outer border zones of the ischaemic cortex depicted a large, monotonous increase with time. The specific lesions in brain sections were verified by H&E and immunostaining. The tissue-specific diffusion and relaxometry MRI metrics in the ischaemic cortex were significantly different compared to their conventional counterpart. ConclusionsOur results demonstrate that the free water fraction in FWE MRI with echo time dependence is a valuable biomarker, sensitive to the progressive degeneration in ischaemic tissue. We showed that part of the heterogeneity previously observed in conventional parameter maps can be accounted for by a heterogeneous distribution of free water in the tissue. Our results suggest that the temporal evolution of the free fluid fraction map at the core and inner border zone can be associated with the pathological changes linked to the evolution of vasogenic oedema. Namely, the homogeneous increase in free water one day after stroke and its tendency to normalise in the core of the ischaemic cortex starting three days after stroke, followed by a progressive increase in free water at the inner border zone from three to ten days after stroke. Finally, the monotonous increase in free fluid in the outer border zone of the cortex reflects the formation of fluid-filled cysts.

The BS variant of C4 protects against age-related loss of white matter microstructural integrity.

Age-related loss of white matter microstructural integrity is a major determinant of cognitive decline, dementia and gait disorders. However, the mechanisms and molecular pathways that contribute to this loss of integrity remain elusive. We performed a genome-wide association study of white matter microstructural integrity as quantified by diffusion MRI metrics (mean diffusivity and fractional anisotropy) in up to 31 128 individuals from UK Biobank (age 45-81 years) based on a two degrees of freedom (2df) test of single nucleotide polymorphism (SNP) and SNP × Age effects. We identified 18 loci that were associated at genome-wide significance with either mean diffusivity (n = 16) or fractional anisotropy (n = 6). Among the top loci was a region on chromosome 6 encoding the human major histocompatibility complex (MHC). Variants in the MHC region were strongly associated with both mean diffusivity [best SNP: 6:28866209_TTTTG_T, beta (standard error, SE) = -0.069 (0.009); 2df P = 6.5 × 10-15] and fractional anisotropy [best SNP: rs3129787, beta (SE) = -0.056 (0.008); 2df P = 3.5 × 10-12]. Of the imputed human leukocyte antigen (HLA) alleles and complement component 4 (C4) structural haplotype variants in the human MHC, the strongest association was with the C4-BS variant [for mean diffusivity: beta (SE) = -0.070 (0.010); P = 2.7 × 10-11; for fractional anisotropy: beta (SE) = -0.054 (0.011); P = 1.6 × 10-7]. After conditioning on C4-BS no associations with HLA alleles remained significant. The protective influence of C4-BS was stronger in older participants [age ≥ 65; interaction P = 0.0019 (mean diffusivity), P = 0.015 (fractional anisotropy)] and in participants without a history of smoking [interaction P = 0.00093 (mean diffusivity), P = 0.021 (fractional anisotropy)]. Taken together, our findings demonstrate a role of the complement system and of gene-environment interactions in age-related loss of white matter microstructural integrity.

Exposure to Repetitive Head Impacts Is Associated With Corpus Callosum Microstructure and Plasma Total Tau in Former Professional American Football Players.

Exposure to repetitive head impacts (RHI) is associated with an increased risk of later-life neurobehavioral dysregulation and neurodegenerative disease. The underlying pathomechanisms are largely unknown. To investigate whether RHI exposure is associated with later-life corpus callosum (CC) microstructure and whether CC microstructure is associated with plasma total tau and neuropsychological/neuropsychiatric functioning. Retrospective cohort study. Seventy-five former professional American football players (age 55.2 ± 8.0 years) with cognitive, behavioral, and mood symptoms. Diffusion-weighted echo-planar MRI at 3 T. Subjects underwent diffusion MRI, venous puncture, neuropsychological testing, and completed self-report measures of neurobehavioral dysregulation. RHI exposure was assessed using the Cumulative Head Impact Index (CHII). Diffusion MRI measures of CC microstructure (i.e., free-water corrected fractional anisotropy (FA), trace, radial diffusivity (RD), and axial diffusivity (AD)) were extracted from seven segments of the CC (CC1-7), using a tractography clustering algorithm. Neuropsychological tests were selected: Trail Making Test Part A (TMT-A) and Part B (TMT-B), Controlled Oral Word Association Test (COWAT), Stroop Interference Test, and the Behavioral Regulation Index (BRI) from the Behavior Rating Inventory of Executive Function, Adult version (BRIEF-A). Diffusion MRI metrics were tested for associations with RHI exposure, plasma total tau, neuropsychological performance, and neurobehavioral dysregulation using generalized linear models for repeated measures. RHI exposure was associated with increased AD of CC1 (correlation coefficient (r)=0.32, P< 0.05) and with increased plasma total tau (r= 0.34, P< 0.05). AD of the anterior CC1 was associated with increased plasma total tau (CC1: r= 0.30, P< 0.05; CC2: r= 0.29, P< 0.05). Higher trace, AD, and RD of CC1 were associated with better performance (P< 0.05) in TMT-A (trace, r= 0.33; AD, r= 0.31; and RD, r= 0.28) and TMT-B (trace, r= 0.31; RD, r= 0.34). Higher FA and AD of CC2 were associated with better performance (P< 0.05) in TMT-A (FA, r= 0.36; AD, r= 0.28), TMT-B (FA, r= 0.36; AD, r= 0.27), COWAT (FA, r= 0.36; AD, r= 0.32), and BRI (AD, r= 0.29). These results suggest an association among RHI exposure, CC microstructure, plasma total tau, and clinical functioning in former professional American football players. 3 Technical Efficacy Stage: 1.

Improved reproducibility of diffusion MRI of the human brain with a four-way blip-up and down phase-encoding acquisition approach.

PurposeTo assess the effects of blip‐up and ‐down echo planar imaging (EPI) acquisition designs, with different choices of phase‐encoding directions (PEDs) on the reproducibility of diffusion MRI (dMRI)‐derived metrics in the human brain.MethodsDiffusion MRI data in seven subjects were acquired five times, each with five different protocols. The base design included 64 diffusion directions acquired with anterior‐posterior (AP) PED, the first and second protocols added reverse phase‐encoded b=0s/mm2 posterior‐anterior (PA) PED images. The third one included 32 directions all with PED acquisitions with opposite polarity (AP and PA). The fourth protocol, also with 32 unique directions used four PEDs (AP, PA, right‐left (RL), and left‐right (LR)). The scan time was virtually identical for all protocols. The variability of diffusion MRI metrics for each subject and each protocol was computed across the different sessions.ResultsThe highest reproducibility for all dMRI metrics was obtained with protocol four (AP/PA‐RL/LR, ie, four‐way PED). Protocols that used only b=0s/mm2 for distortion correction, which are the most widely used designs, had the lowest reproducibility.ConclusionsAn acquisition design with four PEDs, including all DWIs in addition to b=0s/mm2 images should be used to achieve high reproducibility in diffusion MRI studies.

Diffusion MRI metrics of brain microstructure in Alzheimer’s disease: Boosting disease sensitivity with multi‐shell imaging and advanced pre‐processing

AbstractBackgroundDiffusion MRI (dMRI) provides novel measures of white matter (WM) microstructure, offering biomarkers that provide insight into brain aging and Alzheimer’s disease. As advanced acquisitions are implemented (multi‐shell/multi‐band; MB), novel models are developed to more accurately represent tissue microstructure. In its third phase, the Alzheimer’s Disease Neuroimaging Initiative (ADNI‐3) updated their acquisition protocols to include MB dMRI. As acquisition protocols are being updated, it is important to understand which processing steps consistently improve dMRI model fit and derived measure sensitivity to biological effects. Here, we compared state‐of‐the‐art processing methods for ADNI‐3 MB scans to (1) establish an updated dMRI ADNI processing pipeline, and (2) fit more sophisticated tissue parameters sensitive to clinical measures of burden.MethodBaseline MB ADNI‐3 scans (N=137; Table 1) were downloaded and processed with both the dMRI pipeline we established during ADNI‐2 (Pipeline‐A) and the one we have updated during ADNI‐3 (Pipeline‐B; Fig. 1). We obtained scalar diffusion tensor imaging (DTI) maps from the down‐sampled preprocessed dMRI, and higher model metrics using all diffusion volumes using NODDI. Covarying for age, sex, age*sex, and modeling acquisition site as a random effect, we tested associations between regions of interest (ROI; Table 2) diffusion scalar measures and a set of standardized clinical measures (Fig. 2). We modeled effects of age in controls, covarying for sex, age*sex and modeling site as a random effect. All results were corrected for multiple comparisons (FDR). Within WM, voxel‐wise DTI model error (RMSE) was compared across pipelines with paired t‐tests in controls (Fig. 3).ResultFractional anisotropy measures were most affected by the different preprocessing methods, while diffusivity metrics were most strongly correlated with standard clinical measures of cognitive disease burden, such as CDR‐sob. Metrics from NODDI, such as ODI, behaved similarly to FA, showing greatest differences in effect sizes across pipelines.ConclusionWe are currently applying Pipeline‐B to all available ADNI‐3 dMRI scans, to make the data available to the imaging community. As new preprocessing and denoising tools are available and acquisition protocols become more complex, our analyses indicate that preprocessing steps can sensitize diffusion metrics to differences in clinical disease burden.

Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease.

To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change, and reproducibility of diffusion metrics. We included 50 patients with sporadic and 59 patients with genetically defined SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 patients with sporadic SVD with longitudinal high-frequency imaging (in total 459 MRIs). Intersite reproducibility was determined in 10 patients with CADASIL scanned back-to-back on 2 different 3T MRI scanners. Metrics from DKI showed the strongest associations with processing speed performance (R 2 up to 21%) and the largest added benefit on top of conventional SVD imaging markers in patients with sporadic SVD and patients with CADASIL with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible. Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available intersite dataset facilitates future studies. This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

Simple SummaryAn accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

The impact of realistic axonal shape on axon diameter estimation using diffusion MRI

To study axonal microstructure with diffusion MRI, axons are typically modeled as straight impermeable cylinders, whereby the transverse diffusion MRI signal can be made sensitive to the cylinder’s inner diameter. However, the shape of a real axon varies along the axon direction, which couples the longitudinal and transverse diffusion of the overall axon direction. Here we develop a theory of the intra-axonal diffusion MRI signal based on coarse-graining of the axonal shape by 3-dimensional diffusion. We demonstrate how the estimate of the inner diameter is confounded by the diameter variations (beading), and by the local variations in direction (undulations) along the axon. We analytically relate diffusion MRI metrics, such as time-dependent radial diffusivity D⊥(t)and kurtosis K⊥(t),to the axonal shape, and validate our theory using Monte Carlo simulations in synthetic undulating axons with randomly positioned beads, and in realistic axons reconstructed from electron microscopy images of mouse brain white matter. We show that (i) In the narrow pulse limit, the inner diameter from D⊥(t)is overestimated by about twofold due to a combination of axon caliber variations and undulations (each contributing a comparable effect size); (ii) The narrow-pulse kurtosis K⊥|t→∞deviates from that in an ideal cylinder due to caliber variations; we also numerically calculate the fourth-order cumulant for an ideal cylinder in the wide pulse limit, which is relevant for inner diameter overestimation; (iii) In the wide pulse limit, the axon diameter overestimation is mainly due to undulations at low diffusion weightings b; and (iv) The effect of undulations can be considerably reduced by directional averaging of high-b signals, with the apparent inner diameter given by a combination of the axon caliber (dominated by the thickest axons), caliber variations, and the residual contribution of undulations.

Tract-specific analysis improves sensitivity of spinal cord diffusion MRI to cross-sectional and longitudinal changes in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a late-onset fatal neurodegenerative disease that causes progressive degeneration of motor neurons in the brain and the spinal cord. Corticospinal tract degeneration is a defining feature of ALS. However, there have been very few longitudinal, controlled studies assessing diffusion MRI (dMRI) metrics in different fiber tracts along the spinal cord in general or the corticospinal tract in particular. Here we demonstrate that a tract-specific analysis, with segmentation of ascending and descending tracts in the spinal cord white matter, substantially increases the sensitivity of dMRI to disease-related changes in ALS. Our work also identifies the tracts and spinal levels affected in ALS, supporting electrophysiologic and pathologic evidence of involvement of sensory pathways in ALS. We note changes in diffusion metrics and cord cross-sectional area, with enhanced sensitivity to disease effects through a multimodal analysis, and with strong correlations between these metrics and spinal components of ALSFRS-R.

Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain.

Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10−4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.

Diffusion MRI biomarkers of white matter microstructure vary nonmonotonically with increasing cerebral amyloid deposition

Beta amyloid (Aβ) accumulation is the earliest pathological marker of Alzheimer's disease (AD), but early AD pathology also affects white matter (WM) integrity. We performed a cross-sectional study including 44 subjects (23 healthy controls and 21 mild cognitive impairment or early AD patients) who underwent simultaneous PET-MR using 18F-Florbetapir, and were categorized into 3 groups based on Aβ burden: Aβ− [mean mSUVr ≤1.00], Aβi [1.00 < mSUVr <1.17], Aβ+ [mSUVr ≥1.17]. Intergroup comparisons of diffusion MRI metrics revealed significant differences across multiple WM tracts. Aβi group displayed more restricted diffusion (higher fractional anisotropy, radial kurtosis, axonal water fraction, and lower radial diffusivity) than both Aβ− and Aβ+ groups. This nonmonotonic trend was confirmed by significant continuous correlations between mSUVr and diffusion metrics going in opposite direction for 2 cohorts: pooled Aβ−/Aβi and pooled Aβi/Aβ+. The transient period of increased diffusion restriction may be due to inflammation that accompanies rising Aβ burden. In the later stages of Aβ accumulation, neurodegeneration is the predominant factor affecting diffusion.

Exploratory relationships between cognitive improvements and training induced plasticity in hippocampus and cingulum in a rat model of mild traumatic brain injury: a diffusion MRI study.

Traumatic brain injury (TBI) is a major cause of long-term cognitive deficits, even in mild TBI patients. Computerized cognitive training can help alleviate complaints and improve daily life functioning of TBI patients. However, the underlying biological mechanisms of cognitive training in TBI are not fully understood. In the present study, we utilised for the first time a touchscreen cognitive training system in a rat model of mild TBI. Moreover, we wanted to examine whether the beneficial effects of a cognitive training are task-dependent and selective in their target. Specifically, we examined the effect of two training tasks, i.e. the Paired Associate Learning (PAL) task targeting spatial memory functioning and 5-Choice Continuous Performance (5-CCP) task loading on attention and inhibition control, on the microstructural organization of the hippocampus and cingulum, respectively, using diffusion tensor imaging (DTI). Our findings revealed that the two training protocols induced similar effects on the diffusion MRI metrics. Further, in the TBI groups who received training microstructural organization in the hippocampus and cingulum improved (as denoted by increases in fractional anisotropy), while a worsening (i.e., increases in mean diffusivity and radial diffusivity) was found in the TBI control group. In addition, these alterations in diffusion MRI metrics coincided with improved performance on the training tasks in the TBI groups who received training. Our findings show the potential of DTI metrics as reliable measure to evaluate cognitive training in TBI patients and to facilitate future research investigating further improvement of cognitive training targeting deficits in spatial memory and attention.

Blood Perfusion and Cellular Microstructural Changes Associated With Iron Deposition in Multiple Sclerosis Lesions

Background and Purpose: Susceptibility-weighted imaging (SWI) has emerged as a useful clinical tool in many neurological diseases including multiple sclerosis (MS). This study aims to investigate the relationship between SWI signal changes due to iron deposition in MS lesions and tissue blood perfusion and microstructural abnormalities to better understand their underlying histopathologies.Methods: Forty-six patients with relapsing remitting MS were recruited for this study. Conventional FLAIR, pre- and post-contrast T1-weighted imaging, SWI, diffusion tensor imaging (DTI), and dynamic susceptibility contrast (DSC) perfusion MRI were performed in these patients at 3T. The SWI was processed using both magnitude and phase information with one slice minimal intensity projection (mIP) and phase multiplication factor of 4. MS lesions were classified into 3 types based on their lesional signal appearance on SWI mIP relative to perilesional normal appearing white matter (peri-NAWM): Type-1: hypointense, Type-2: isointense, and Type-3: hyperintense lesions. The DTI and DSC MRI data were processed offline to generate DTI-derived mean diffusivity (MD) and fractional anisotropy (FA) maps, as well as DSC-derived cerebral blood flow (CBF) and cerebral blood volume (CBV) maps. Comparisons of diffusion and perfusion measurements between lesions and peri-NAWM, as well between different types of lesions, were performed.Results: A total of 137 lesions were identified on FLAIR in these patients that include 40 Type-1, 46 Type-2, and 51 Type-3 lesions according to their SWI intensity relative to peri-NAWM. All lesion types showed significant higher MD and lower FA compared to their peri-NAWM (P < 0.0001). Compared to Type-1 lesions (likely represent iron deposition), Type-2 lesions had significantly higher MD and lower FA (P < 0.001) as well as lower perfusion measurements (P < 0.05), while Type 3 lesions had significantly higher perfusion (P < 0.001) and lower FA (P < 0.05). Compared to Type-2, Type-3 lesions had higher perfusion (P < 0.0001) and marginally higher MD and lower FA (P < 0.05).Conclusion: The significant differences in diffusion and perfusion MRI metrics associated with MS lesions, that appear with different signal appearance on SWI, may help to identify the underlying destructive pathways of myelin and axons and their evolution related to inflammatory activities.

Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis.

ObjectiveTo evaluate alterations in apparent axon diameter and axon density obtained by high‐gradient diffusion MRI in the corpus callosum of MS patients and the relationship of these advanced diffusion MRI metrics to neurologic disability and cognitive impairment in MS.MethodsThirty people with MS (23 relapsing‐remitting MS [RRMS], 7 progressive MS [PMS]) and 23 healthy controls were scanned on a human 3‐tesla (3T) MRI scanner equipped with 300 mT/m maximum gradient strength using a comprehensive multishell diffusion MRI protocol. Data were fitted to a three‐compartment geometric model of white matter to estimate apparent axon diameter and axon density in the midline corpus callosum. Neurologic disability and cognitive function were measured using the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Minimal Assessment of Cognitive Function in MS battery.ResultsApparent axon diameter was significantly larger and axon density reduced in the normal‐appearing corpus callosum (NACC) of MS patients compared to healthy controls, with similar trends seen in PMS compared to RRMS. Larger apparent axon diameter in the NACC of MS patients correlated with greater disability as measured by the EDSS (r = 0.555, P = 0.007) and poorer performance on the Symbol Digits Modalities Test (r = ‐0.593, P = 0.008) and Brief Visuospatial Memory Test–Revised (r = −0.632, P < 0.01), tests of interhemispheric processing speed and new learning and memory, respectively.InterpretationApparent axon diameter in the corpus callosum obtained from high‐gradient diffusion MRI is a potential imaging biomarker that may be used to understand the development and progression of cognitive impairment in MS.

A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain.

The squirrel monkey (Saimiri sciureus) is a commonly-used surrogate for humans in biomedical research. In the neuroimaging community, MRI and histological atlases serve as valuable resources for anatomical, physiological, and functional studies of the brain; however, no digital MRI/histology atlas is currently available for the squirrel monkey. This paper describes the construction of a web-based multi-modal atlas of the squirrel monkey brain. The MRI-derived information includes anatomical MRI contrast (i.e., T2-weighted and proton-density-weighted) and diffusion MRI metrics (i.e., fractional anisotropy and mean diffusivity) from data acquired both in vivo and ex vivo on a 9.4 Tesla scanner. The histological images include Nissl and myelin stains, co-registered to the corresponding MRI, allowing identification of cyto- and myelo-architecture. In addition, a bidirectional neuronal tracer, biotinylated dextran amine (BDA) was injected into the primary motor cortex, enabling highly specific identification of regions connected to the injection location. The atlas integrates the results of common image analysis methods including diffusion tensor imaging glyphs, labels of 57 white-matter tracts identified using DTI-tractography, and 18 cortical regions of interest identified from Nissl-revealed cyto-architecture. All data are presented in a common space, and all image types are accessible through a web-based atlas viewer, which allows visualization and interaction of user-selectable contrasts and varying resolutions. By providing an easy to use reference system of anatomical information, our web-accessible multi-contrast atlas forms a rich and convenient resource for comparisons of brain findings across subjects or modalities. The atlas is called the Combined Histology-MRI Integrated Atlas of the Squirrel Monkey (CHIASM). All images are accessible through our web-based viewer ( https://chiasm.vuse.vanderbilt.edu /), and data are available for download at ( https://www.nitrc.org/projects/smatlas/ ).

Longitudinal DTI changes following cognitive training therapy in a mild traumatic brain injury rat model

Longitudinal DTI changes following cognitive training therapy in a mild traumatic brain injury rat model

Recovery from chemotherapy-induced white matter changes in young breast cancer survivors?

In a previous longitudinal diffusion tensor imaging (DTI) study, we observed cerebral white matter (WM) alterations (reduced fractional anisotropy (FA)) related to decreased cognitive performance 3-5months after chemotherapy-treatment (t2) when compared to baseline (t1) (Deprez et al. in Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 30(3), 274-281. doi:10.1200/JCO.2011.36.8571, 2012). The current study investigates the evolution and the nature of these previously observed microstructural changes. Twenty-five young women with early-stage breast cancer who received chemotherapy treatment (C+), 14 who did not receive chemotherapy (C-) and 15 healthy controls (HC) previously studied, underwent reassessment 3-4years after treatment (t3). We assessed (1) longitudinal changes of cognitive performance and FA and (2) cross-sectional group differences in myelin-water-imaging and multishell diffusion MRI metrics at t3. MRI metrics were assessed on a voxel-by-voxel basis and in regions-of-interest (ROI) in which previous WM injury was detected. Longitudinal results: Mixed-effects modeling revealed significant group-time interactions for verbal memory and processing speed (p<0.05) reflecting regained performance in the C+ group at t3. Furthermore, in chemotherapy-treated patients, FA returned to baseline levels at t3 in all ROIs (p<0.002), whereas no FA changes were seen in controls. Additionally, FA increase from t2 to t3 correlated with time since treatment in two of the four regions (r=0.40, p<0.05). Cross-sectional results: Advanced diffusion MRI and myelin-water imaging metrics in the ROIs did not differ between groups. Similarly, no whole-brain voxelwise differences were detected. Initial WM alterations and reduced cognitive performance following chemotherapy-treatment were found to recover in a group of young breast cancer survivors three to four years after treatment.

Cerebrovascular reactivity and white matter integrity.

To compare the diffusion and perfusion MRI metrics of normal-appearing white matter (NAWM) with and without impaired cerebrovascular reactivity (CVR). Seventy-five participants with moderate to severe leukoaraiosis underwent blood oxygen level-dependent CVR mapping using a 3T MRI system with precise carbon dioxide stimulus manipulation. Several MRI metrics were statistically compared between areas of NAWM with positive and negative CVR using one-way analysis of variance with Bonferroni correction for multiple comparisons. Areas of NAWM with negative CVR showed a significant reduction in fractional anisotropy by a mean (SD) of 3.7% (2.4), cerebral blood flow by 22.1% (8.2), regional cerebral blood volume by 22.2% (7.0), and a significant increase in mean diffusivity by 3.9% (3.1) and time to maximum by 10.9% (13.2) (p < 0.01), compared to areas with positive CVR. Impaired CVR is associated with subtle changes in the tissue integrity of NAWM, as evaluated using several quantitative diffusion and perfusion MRI metrics. These findings suggest that impaired CVR may contribute to the progression of white matter disease.