Intracellular Volume Fraction Research Articles

Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. Retrospective. Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). The Bayesian method's performance in fitting cell diameter ( ), intracellular volume fraction ( ), and extracellular diffusion coefficient ( ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for , , and compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for compared to r = 0.698 using NLLS, P = 0.5764). The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. 3 TECHNICAL EFFICACY: Stage 1.

Association of Gene Expression and Tremor Network Structure.

Transcriptomic changes in the essential tremor (ET)-associated cerebello-thalamo-cortical "tremor network" and their association to brain structure have not been investigated. The aim was to characterize molecular changes associated with network-level imaging-derived phenotypes (IDP) found in ET. We performed an imaging-transcriptomic study in British adults using imaging-genome-wide association study summary statistics (UK Biobank "BIG40" cohort; n = 33,224, aged 40-69 years). We imputed imaging-transcriptomic associations for 184 IDPs and analyzed functional enrichment of gene modules and aggregate network-level phenotypes. Validation was performed in cerebellar-tissue RNA-sequencing data from ET patients and controls (n = 55). Among 237,896 individual predicted gene expression levels for 6063 unique genes/transcripts, we detected 2269 genome-wide significant associations (Bonferroni P < 2.102e-7, 0.95%). These were concentrated in intracellular volume fraction measures of white matter pathways and in genes with putative links to tremor (MAPT, ARL17A, KANSL1, SPPL2C, LRRC37A4P, PLEKHM1, and FMNL1). Whole-tremor-network cortical thickness was associated with a gene module linked to mitochondrial organization and protein quality control (r = 0.91, P = 2e-70), whereas white-gray T1-weighted magnetic resonance imaging (MRI) contrast in the tremor network was associated with a gene module linked to sphingolipid synthesis and ethanolamine metabolism (r = -0.90, P = 2e-68). Imputed association effect sizes and RNA-sequencing log-fold change in the validation dataset were significantly correlated for cerebellar peduncular diffusion MRI phenotypes, and there was a close overlap of significant associations between both datasets for gray matter phenotypes (χ2 = 6.40, P = 0.006). The identified genes and processes are potential treatment targets for ET, and our results help characterize molecular changes that could in future be used for patient treatment selection or prognosis prediction. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

White Matter Hyperintensities and Microstructural Alterations in Contact Sport Athletes from Adolescence to Early Midlife.

Studies have demonstrated associations between cumulative concussion and repetitive head impact exposure (RHI) via contact sports with white matter (WM) alterations later in life. The course of WM changes associated with exposure earlier in the lifespan are unclear. This study investigated alterations in white matter (WM hyperintensity [WMH] volume and microstructural changes) associated with concussion and RHI exposure from adolescence to early midlife, as well as the interaction between exposure and age-cohort (i.e., adolescent/young adult compared to early midlife athlete cohorts) on WM outcomes. Participating football players included an adolescent/young adulthood cohort (n=82; Mage=18.41.7) and an early midlife cohort (37 former collegiate players approximately 15-years removed from sport; Mage=37.71.4). Years of football participation and number of prior concussions were exposures of interest. White matter outcomes included log-transformed manually segmented total WMH volume and neurite orientation dispersion and density imaging metrics of microstructure/organization (isotropic volume fraction[Viso], intra-cellular volume fraction[Vic], and orientation dispersion[OD]). Regression models were fit to test effects of concussion history, years of football participation, and age-cohort by years of football participation with WM outcomes. Spearman's correlations assessed associations between significant WM metrics and measures of cognitive and psychological function. A significant age-cohort by years of participation effect was observed for whole brain white matter OD, B=-0.002, SE=0.001, p=0.001. The interaction was driven by a negative association between years of participation and OD within the younger cohort, B=-0.001, SE=0.0004, p=0.008, whereas a positive association between participation and OD in the early midlife cohort, B=0.001, SE=0.0003, p=0.039, was observed. Follow-up ROI analyses showed significant interaction effects for OD in the body of the corpus callosum, genu of the corpus callosum, cingulum, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, posterior thalamic radiation (ps<0.05). Greater concussion history was significantly associated with greater Viso in the early midlife cohort, B=0.001, SE= 0.0002, p=0.010. Years of participation and concussion history were not associated with WMH volume, ps>0.05. Performance on a measure of executive function was significantly associated with years of participation, =.34, p=.04, and a trend was observed for OD, =.28, p=.09 in the early midlife cohort only. The global characterization of white matter changes associated with years of football participation were broadly similar and stable from adolescence through early midlife (i.e., microstructural alterations, but not macroscopic lesions). An inverse association between years of participation and orientation dispersion across age-cohorts may represent a process of initial recovery/reorganization proximal to sport, followed by later reduction of white matter coherence.

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma

PurposeAdvanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma. MethodsIn this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations. ResultsOnly intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736). ConclusionsThis study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

101 Glymphatic System Impairment Associated With Neurocognitive Dysfunction and Alzheimers Biomarkers in Moyamoya Disease

INTRODUCTION: Glymphatic system alterations have been proved to be associated with cognitive dysfunction in Alzheimer’s Disease (AD). The glymphatic pathway has not been elucidated in moyamoya disease (MMD), which was recognized as a chronic hypoperfusion model for AD. METHODS: We prospectively recruited 30 MMD patients and 30 matched healthy controls (HC) from October 2022 to March 2023. Participants underwent neurocognition evaluation, and multimodal magnetic resonance imaging (MRI). AD-related serum biomarkers, as well as correlations among these variables were examined. The glymphatic function was assessed by diffusion tensor image analysis along perivascular space (DTI-ALPS). Whole-brain (white matter and grey matter) volumes were calculated by using 3D T1-weighted MRI. Microstructural changes of white matter (intracellular volume fraction, Vic; orientation dispersion index, OD) were evaluated by neurite orientation dispersion and density imaging (NODDI). RESULTS: Serum Alzheimer’s biomarkers (ApoE, Aβ40, Aβ42, and tau) were significantly elevated and associated with neurocognitive dysfunction in MMD. Lower periventricular ALPS-index was identified in patients with MMD (P &lt; 0.001). The decreased ALPS-index correlated with declined neurocognitive performance of intelligence quotient, attention, and memory, increased levels of serum ApoE, Aβ40, Aβ42, as well as higher periventricular white matter volume and lower periventricular grey matter volume (P &lt; 0.001). Moreover, MMD patients had significantly lower Vic in the white matter and a lower OD in the cortex than HC. CONCLUSIONS: We firstly demonstrated the impaired glymphatic system as assessed by lower ALPS-index in patients with MMD. Glymphatic impairment was associated with AD-related biomarkers and cognitive dysfunction in MMD. These findings suggested that glymphatic disorder may interact with MMD-related pathophysiological processes.

White Matter Alterations in Military Service Members With Remote Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the signature injury experienced by military service members and is associated with poor neuropsychiatric outcomes. Yet, there is a lack of reliable clinical tools for mTBI diagnosis and prognosis. To examine the white matter microstructure and neuropsychiatric outcomes of service members with a remote history of mTBI (ie, mTBI that occurred over 2 years ago) using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). This case-control study examined 98 male service members enrolled in a study at the National Intrepid Center of Excellence. Eligible participants were active duty status or able to enroll in the Defense Enrollment Eligibility Reporting system, ages 18 to 60 years, and had a remote history of mTBI; controls were matched by age. Remote history of mTBI. White matter microstructure was assessed using a region-of-interest approach of skeletonized diffusion images, including DTI (fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity) and NODDI (orientation dispersion index [ODI], isotropic volume fraction, intra-cellular volume fraction). Neuropsychiatric outcomes associated with posttraumatic stress disorder (PTSD) and postconcussion syndrome were assessed. A total of 65 male patients with a remote history of mTBI (mean [SD] age, 40.5 [5.0] years) and 33 age-matched male controls (mean [SD] age, 38.9 [5.6] years) were included in analysis. Compared with the control cohort, the 65 service members with mTBI presented with significantly more severe PTSD-like symptoms (mean [SD] PTSD CheckList-Civilian [PCL-C] version scores: control, 19.0 [3.8] vs mTBI, 41.2 [11.6]; P < .001). DTI and NODDI metrics were altered in the mTBI group compared with the control, including intra-cellular volume fraction of the right cortico-spinal tract (β = -0.029, Cohen d = 0.66; P < .001), ODI of the left posterior thalamic radiation (β = -0.006, Cohen d = 0.55; P < .001), and ODI of the left uncinate fasciculus (β = 0.013, Cohen d = 0.61; P < .001). In service members with mTBI, fractional anisotropy of the left uncinate fasciculus was associated with postconcussion syndrome (β = 5.4 × 10-3; P = .003), isotropic volume fraction of the genu of the corpus callosum with PCL-C (β = 4.3 × 10-4; P = .01), and ODI of the left fornix and stria terminalis with PCL-C avoidance scores (β = 1.2 × 10-3; P = .02). In this case-control study of military-related mTBI, the results suggest that advanced magnetic resonance imaging techniques using NODDI can reveal white matter microstructural alterations associated with neuropsychiatric symptoms in the chronic phase of mTBI. Diffusion trends observed throughout widespread white matter regions-of-interest may reflect mechanisms of neurodegeneration as well as postinjury tissue scarring and reorganization.

Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.

Multi-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics. Data from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases. Fractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%. In conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

Quantifying blood-brain barrier permeability in patients with ischemic stroke using non-contrast MRI

Increased blood-brain barrier permeability (BBBP) after ischemic stroke predisposes patients to hemorrhagic conversion. While altered BBBP can impact patient recovery, it is not routinely assessed during the workup of acute ischemic stroke (AIS). We study the effectiveness of the non-contrast MRI sequences diffusion-prepared pseudocontinuous arterial spin labeling (DP-pCASL) and Neurite Orientation Dispersion and Density Imaging (NODDI) in assessing BBBP and correlating to tissue microstructure after ischemic insult. Twelve patients with AIS were prospectively enrolled to undergo our multimodal MR imaging, which generated the DP-pCASL-derived cerebral blood flow (CBF), arterial transit time (ATT), and water exchange rate (kw) and the NODDI-derived b0, mean diffusivity (MD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic volume fraction (ISO) parametric maps. The mean age of the patients was 70.2 ± 14.8 with an average NIHSS of 13.0 (7.3–19.8). MR imaging was performed on average at 53.7 (27.8–93.3) hours from stroke symptom onset. The water exchange rate (kw) of the infarcted area and its contralateral territory were 89.7 min−1 (66.7–121.9) and 89.9 min−1 (65.9–106.0) respectively (p = 0.887). Multivariable linear regression analysis showed that b0, ODI, ISO and mechanical thrombectomy were significant predictors of kw. DP-pCASL and NODDI are promising non-contrast sequences for the routine assessment of BBBP.

A comprehensive analysis of APOE genotype effects on human brain structure in the UK Biobank

Alzheimer’s disease (AD) risk is increased in carriers of the apolipoprotein E (APOE) ε4 allele and decreased in ε2 allele carriers compared with the ε3ε3 genotype. The aim of this study was to determine whether: the APOE genotype affects brain grey (GM) or white matter (WM) structure; and if differences exist, the age when they become apparent and whether there are differential effects by sex. We used cross-sectional magnetic resonance imaging data from ~43,000 (28,494 after pre-processing) white British cognitively healthy participants (7,446 APOE ε4 carriers) aged 45–80 years from the UK Biobank cohort and investigated image-derived phenotypes (IDPs). We observed no statistically significant effects of APOE genotype on GM structure volumes or median T2* in subcortical structures, a measure related to iron content. The volume of white matter hyperintensities differed significantly between APOE genotype groups with higher volumes in APOE ε4ε4 (effect size 0.14 standard deviations [SD]) and ε3ε4 carriers (effect size 0.04 SD) but no differences in ε2 carriers compared with ε3ε3 carriers. WM integrity measures in the dorsal (mean diffusivity [MD]) and ventral cingulum (MD and intracellular volume fraction), posterior thalamic radiation (MD and isotropic volume fraction) and sagittal stratum (MD) indicated lower integrity in APOE ε4ε4 carriers (effect sizes around 0.2–0.3 SD) and ε3ε4 (effect sizes around 0.05 SD) carriers but no differences in ε2 carriers compared with the APOE ε3ε3 genotype. Effects did not differ between men and women. APOE ε4 homozygotes had lower WM integrity specifically at older ages with a steeper decline of WM integrity from the age of 60 that corresponds to around 5 years greater “brain age”. APOE genotype affects various white matters measures, which might be indicative of preclinical AD processes. This hypothesis can be assessed in future when clinical outcomes become available.

Imaging Biomarker for Early-Stage Alzheimer Disease: Utility of Hippocampal Histogram Analysis of Diffusion Metrics.

Biomarkers have been required for diagnosing early Alzheimer disease. We assessed the utility of hippocampal diffusion parameters for diagnosing Alzheimer disease pathology in mild cognitive impairment. Sixty-nine patients with mild cognitive impairment underwent both CSF measurement and multi-shell diffusion imaging at 3T. Based on the CSF biomarker level, patients were classified according to the presence (Alzheimer disease group, n = 35) or absence (non-Alzheimer disease group, n = 34) of Alzheimer disease pathology. Neurite orientation dispersion and density imaging and diffusion tensor imaging parametric maps were generated. Two observers independently created the hippocampal region of interest for calculating histogram features. Interobserver correlations were calculated. The statistical significance of intergroup differences was tested by using the Mann-Whitney U test. Logistic regression analyses, using both the clinical scale and the image data, were used to predict intergroup differences, after which group discriminations were performed. Most intraclass correlation coefficient values were between 0.59 and 0.91. In the regions of interest of both observers, there were statistically significant intergroup differences for the left-side neurite orientation dispersion and density imaging-derived intracellular volume fraction, right-side diffusion tensor imaging-derived mean diffusivity, left-side diffusion tensor imaging-derived mean diffusivity, axial diffusivity, and radial diffusivity (P < .05). Logistic regression models revealed that diffusion parameters contributed the most to discriminating between the groups. The areas under the receiver operating characteristic curve for the regions of interest of observers A/B were 0.69/0.68, 0.69/0.68, 0.73/0.68, 0.71/0.68, and 0.68/0.68 for the left-side intracellular volume fraction (mean), right-side mean diffusivity (mean), left-side mean diffusivity (10th percentile), axial diffusivity (10th percentile), and radial diffusivity (mean). Hippocampal diffusion parameters might be useful for the early diagnosis of Alzheimer disease.

Neonatal Nucleus Accumbens Microstructure Modulates Individual Susceptibility to Preconception Maternal Stress in Relation to Externalizing Behaviors

Maternal stress influences in utero brain development and is a modifiable risk factor for offspring psychopathologies. Reward circuitry dysfunction underlies various internalizing and externalizing psychopathologies. This study examined (1) the association between maternal stress and microstructural characteristics of the neonatal nucleus accumbens (NAcc), a major node of the reward circuitry, and (2) whether neonatal NAcc microstructure modulates individual susceptibility to maternal stress in relation to childhood behavioral problems. K-means longitudinal cluster analysis was performed to determine trajectories of maternal stress measures (Perceived Stress Scale [PSS], hair cortisol) from preconception to the third trimester. Neonatal NAcc microstructural measures (orientation density index [ODI] and intracellular volume fraction [ICVF]) were compared across trajectories. We then examined the interaction between maternal stress and neonatal NAcc microstructure on child internalizing and externalizing behaviors, assessed between ages 3 and 4 years. Two trajectories of maternal stress magnitude ("low"/"high") were identified for both PSS (n= 287) and hair cortisol (n= 336). Right neonatal NAcc ODI (rNAcc-ODI) was significantly lower in "low" relative to "high" PSS trajectories (n= 77, p= .04). PSS at preconception had the strongest association with rNAcc-ODI (r= 0.293, p= .029). No differences in NAcc microstructure were found between hair cortisol trajectories. A significant interaction between preconception PSS and rNAcc-ODI on externalizing behavior was observed (n= 47, p= .047). Our study showed that the preconception period contributes to in utero NAcc development, and that NAcc microstructure modulates individual susceptibility to preconception maternal stress in relation to externalizing problems.

Combined assessment of progressive apraxia of speech brain microstructure by diffusion tensor imaging tractography and multishell neurite orientation dispersion and density imaging.

Progressive apraxia of speech (PAOS) is characterized by difficulties with motor speech programming and planning. PAOS targets gray matter (GM) and white matter (WM) microstructure that can be assessed using diffusion tensor imaging (DTI) and multishell applications, such as neurite orientation dispersion and density imaging (NODDI). In this study, we aimed to apply DTI and NODDI to add further insight into PAOS tissue microstructure. Twenty-two PAOS patients and 26 age- and sex-matched controls, recruited by the Neurodegenerative Research Group (NRG) at Mayo Clinic, underwent diffusion MRI on 3T MRI. Brain maps of fractional anisotropy (FA) and mean diffusivity (MD) from DTI and intracellular volume fraction (ICVF) and isotropic volume fraction (IsoVF) from NODDI were generated. Global WM and GM, and specific WM tracts were identified using tractography and lobar GM regions. Global WM differences between PAOS and controls were greatest for ICVF, and global GM differences were greatest for MD and IsoVF. Abnormalities in key WM tracts involved in PAOS, including the body of the corpus callosum and frontal aslant tract, were identified with FA, MD, and ICVF, with excellent differentiation of PAOS from controls (area under the receiver operating characteristic curves >.90). MD and ICVF identified abnormalities in arcuate fasciculus, thalamic radiations, and corticostriatal tracts. Significant correlations were identified between an index of articulatory errors and DTI and NODDI metrics from the arcuate fasciculus, frontal aslant tract, and inferior longitudinal fasciculus. DTI and NODDI represent different aspects of brain tissue microstructure, increasing the number of potential biomarkers for PAOS.

White and Gray Matter Abnormality in Burning Mouth Syndrome Evaluated with Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging.

Burning mouth syndrome (BMS) is defined by a burning sensation or pain in the tongue or other oral sites despite the presence of normal mucosa on inspection. Both psychiatric and neuroimaging investigations have examined BMS; however, there have been no analyses using the neurite orientation dispersion and density imaging (NODDI) model, which provides detailed information of intra- and extracellular microstructures. Therefore, we performed voxel-wise analyses using both NODDI and diffusion tensor imaging (DTI) models and compared the results to better comprehend the pathology of BMS. Fourteen patients with BMS and 11 age- and sex-matched healthy control subjects were prospectively scanned using a 3T-MRI machine using 2-shell diffusion imaging. Diffusion tensor metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], and radial diffusivity [RD]) and neurite orientation and dispersion index metrics (intracellular volume fraction [ICVF], isotropic volume fraction [ISO], and orientation dispersion index [ODI]) were retrieved from diffusion MRI data. These data were analyzed using tract-based spatial statistics (TBSS) and gray matter-based spatial statistics (GBSS). TBSS analysis showed that patients with BMS had significantly higher FA and ICVF and lower MD and RD than the healthy control subjects (family-wise error [FWE] corrected P < 0.05). Changes in ICVF, MD, and RD were observed in widespread white matter areas. Fairly small areas with different FA were included. GBSS analysis showed that patients with BMS had significantly higher ISO and lower MD and RD than the healthy control subjects (FWE-corrected P < 0.05), mainly limited to the amygdala. The increased ICVF in the BMS group may represent myelination and/or astrocytic hypertrophy, and microstructural changes in the amygdala in GBSS analysis indicate the emotional-affective profile of BMS.

Impaired mobility and MRI markers of vascular brain injury: Atherosclerosis Risk in Communities and UK Biobank studies

BackgroundVascular brain injury (VBI) may be an under-recognised contributor to mobility impairment. We examined associations between MRI VBI biomarkers and impaired mobility.MethodsWe separately analysed Atherosclerosis Risk in Communities (ARIC) and...

Tensor-valued diffusion MRI of human acute stroke.

Tensor-valued diffusion encoding can disentangle orientation dispersion and subvoxel anisotropy, potentially offering insight into microstructural changes after cerebral ischemia. The purpose was to evaluate tensor-valued diffusion MRI in human acute ischemic stroke, assess potential confounders from diffusion time dependencies, and compare to Monte Carlo diffusion simulations of axon beading. Linear (LTE) and spherical (STE) b-tensor encoding with inherently different effective diffusion times were acquired in 21 acute ischemic stroke patients between 3 and 57 h post-onset at 3 T in 2.5 min. In an additional 10 patients, STE with 2 LTE yielding different effective diffusion times were acquired for comparison. Diffusional variance decomposition (DIVIDE) was used to estimate microscopic anisotropy (μFA), as well as anisotropic, isotropic, and total diffusional variance (MKA , MKI , MKT ). DIVIDE parameters, and diffusion tensor imaging (DTI)-derived mean diffusivity and fractional anisotropy (FA) were compared in lesion versus contralateral white matter. Monte Carlo diffusion simulations of various cylindrical geometries for all b-tensor protocols were used to interpret parameter measurements. MD was ˜40% lower in lesions for all LTE/STE protocols. The DIVIDE parameters varied with effective diffusion time: higher μFA and MKA in lesion versus contralateral white matter for STE with longer effective diffusion time LTE, whereas the shorter effective diffusion time LTE protocol yielded lower μFA and MKA in lesions. Both protocols, regardless of diffusion time, were consistent with simulations of greater beading amplitude and intracellular volume fraction. DIVIDE parameters depend on diffusion time in acute stroke but consistently indicate neurite beading and larger intracellular volume fraction.

Distance from main arteries influences microstructural and functional brain tissue characteristics

Given the substantial dependence of neurons on continuous supply of energy, the distribution of major cerebral arteries opens a question whether the distance from the main supply arteries constitutes a modulating factor for the microstructural and functional properties of brain tissue. To tackle this question, multimodal MRI acquisitions of 102 healthy volunteers over the full adult age span were utilised. Relaxation along a fictitious field in the rotating frame of rank n = 4 (RAFF4), adiabatic T1ρ, T2ρ, and intracellular volume fraction (fICVF) derived from diffusion-weighted imaging were implemented to quantify microstructural (cellularity, myelin density, iron concentration) tissue characteristics and degree centrality and fractional amplitude of low-frequency fluctuations to probe for functional metrics. Inverse correlation of arterial distance with robust homogeneity was detected for T1ρ, T2ρ and RAFF4 for cortical grey matter and white matter, showing substantial complex microstructural differences between brain tissue close and farther from main arterial trunks. Albeit with wider variability, functional metrics pointed to increased connectivity and neuronal activity in areas farther from main arteries. Surprisingly, multiple of these microstructural and functional distance-based gradients diminished with higher age, pointing to uniformization of brain tissue with ageing. All in all, this pilot study provides a novel insight on brain regionalisation based on artery distance, which merits further investigation to validate its biological underpinnings.

Radiomic texture analysis based on neurite orientation dispersion and density imaging to differentiate glioblastoma from solitary brain metastasis

BackgroundWe created discriminative models of different regions of interest (ROIs) using radiomic texture features of neurite orientation dispersion and density imaging (NODDI) and evaluated the feasibility of each model in differentiating glioblastoma multiforme (GBM) from solitary brain metastasis (SBM).MethodsWe conducted a retrospective study of 204 patients with GBM (n = 146) or SBM (n = 58). Radiomic texture features were extracted from five ROIs based on three metric maps (intracellular volume fraction, orientation dispersion index, and isotropic volume fraction of NODDI), including necrosis, solid tumors, peritumoral edema, tumor bulk volume (TBV), and abnormal bulk volume. Four feature selection methods and eight classifiers were used for the radiomic texture feature selection and model construction. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the models. Routine magnetic resonance imaging (MRI) radiomic texture feature models generated in the same manner were used for the horizontal comparison.ResultsNODDI-radiomic texture analysis based on TBV subregions exhibited the highest accuracy (although nonsignificant) in differentiating GBM from SBM, with area under the ROC curve (AUC) values of 0.918 and 0.882 in the training and test datasets, respectively, compared to necrosis (AUCtraining:0.845, AUCtest:0.714), solid tumor (AUCtraining:0.852, AUCtest:0.821), peritumoral edema (AUCtraining:0.817, AUCtest:0.762), and ABV (AUCtraining:0.834, AUCtest:0.779). The performance of the five ROI radiomic texture models in routine MRI was inferior to that of the NODDI-radiomic texture model.ConclusionPreoperative NODDI-radiomic texture analysis based on TBV subregions shows great potential for distinguishing GBM from SBM.

NODDI Identifies Cognitive Associations with In Vivo Microstructural Changes in Remote Cortical Regions and Thalamocortical Pathways in Thalamic Stroke.

The roles of cerebral structures distal to isolated thalamic infarcts in cognitive deficits remain unclear. We aimed to identify the in vivo microstructural characteristics of remote gray matter (GM) and thalamic pathways and elucidate their roles across cognitive domains. Patients with isolated ischemic thalamic stroke and healthy controls underwent neuropsychological assessment and magnetic resonance imaging. Neurite orientation dispersion and density imaging (NODDI) was modeled to derive the intracellular volume fraction (VFic) and orientation dispersion index. Fiber density (FD) was determined by constrained spherical deconvolution, and tensor-derived fractional anisotropy (FA) was calculated. Voxel-wise GM analysis and thalamic pathway tractography were performed. Twenty-six patients and 26 healthy controls were included. Patients exhibited reduced VFic in remote GM regions, including ipsilesional insular and temporal subregions. The microstructural metrics VFic, FD, and FA within ipsilesional thalamic pathways decreased (false discovery rate [FDR]-p < 0.05). Noteworthy associations emerged as VFic within insular cortices (ρ = -0.791 to -0.630; FDR-p < 0.05) and FD in tracts connecting the thalamus and insula (ρ = 0.830 to 0.971; FDR-p < 0.001) were closely associated with executive function. The VFic in Brodmann area 52 (ρ = -0.839; FDR-p = 0.005) and FA within its thalamic pathway (ρ = -0.799; FDR-p = 0.003) correlated with total auditory memory scores. In conclusion, NODDI revealed neurite loss in remote normal-appearing GM regions and ipsilesional thalamic pathways in thalamic stroke. Reduced cortical dendritic density and axonal density of thalamocortical tracts in specific subregions were associated with improved cognitive functions. Subacute microstructural alterations beyond focal thalamic infarcts might reflect beneficial remodeling indicating post-stroke plasticity.

Distinct Neural Correlates of Anxiety and Depression in Subjective Cognitive Decline versus Healthy Aging, a Microstructural Diffusion MRI Study

AbstractBackgroundA common criticism of considering Subjective Cognitive Decline (SCD) as a preclinical stage of Alzheimer’s Disease is that it may be explained by depression or anxiety1. We used NODDI, a diffusion microstructural model2, to explore the pathophysiology of depression and anxiety in SCD versus controls.Method325 participants in the Cam‐CAN study 3 (127 SCD) older than 55 were included in the analysis. Diffusion imaging data was collected on a 3T Siemens TIM Trio scanner with a 32‐channel head coil for 0, 1000 and 2000 s/mm2 b‐values and 30 gradient directions. Preprocessing and calculation of the NODDI metric Intracellular Volume Fraction (ICVF) were completed using MRTrix3, AMICO and MATLAB. The hippocampal cingulum bundle and fornix regions of interest (ROIs)4 were extracted from the ICBM‐DTI‐81 atlas. Depression and anxiety were assessed using the Hamilton Anxiety and Depression Scale (HADS). Linear regression models were completed in R. Gender and age were included as nuisance variables.ResultThere were no differences in gender or age distribution between cohorts, however participants with SCD were more depressed and anxious on average (Table 1). There was a significant interaction effect between depression and cohort in the fornix (Figure 1), as well as between anxiety and cohort in the hippocampal cingulum (Figure 2). In post‐hoc analyses, only the SCD group showed a correlation between depression and ICVF in the fornix (Figure 1) while only controls showed a correlation between anxiety and ICVF in the hippocampal cingulum (Figure 2), indicating different pathophysiology underlying psychiatric symptoms in the two groups.ConclusionAnxiety and depression appear to be associated with different microstructural features in SCD versus controls, suggesting anxiety and depression in SCD is a phenomenon distinct from anxiety and depression in healthy aging. Future work will explore the relationship between anxiety and depression and risk of conversion to mild cognitive impairment.1. Mitchell AJ, Beaumont H, Ferguson D, et al. Acta Psychiatrica Scandinavica. 2014;130(6):439‐51.2. Daducci A, Canales‐Rodriguez EJ, Zhang H, et al. Neuroimage. 2015;105:32‐44.3. Shafto MA, Tyler LK, Dixon M, et al. BMC neurology. 2014;14(1):1‐25.4. Kantarci K. Frontiers in Aging Neuroscience. 2014;6.

Distinct Neural Correlates of Anxiety and Depression in Subjective Cognitive Decline versus Healthy Aging, a Microstructural Diffusion MRI Study

AbstractBackgroundA common criticism of considering Subjective Cognitive Decline (SCD) as a preclinical stage of Alzheimer’s Disease is that it may be explained by depression or anxiety1. We used NODDI, a diffusion microstructural model2, to explore the pathophysiology of depression and anxiety in SCD versus controls.Method325 participants in the Cam‐CAN study 3 (127 SCD) older than 55 were included in the analysis. Diffusion imaging data was collected on a 3T Siemens TIM Trio scanner with a 32‐channel head coil for 0, 1000 and 2000 s/mm2 b‐values and 30 gradient directions. Preprocessing and calculation of the NODDI metric Intracellular Volume Fraction (ICVF) were completed using MRTrix3, AMICO and MATLAB. The hippocampal cingulum bundle and fornix regions of interest (ROIs)4 were extracted from the ICBM‐DTI‐81 atlas. Depression and anxiety were assessed using the Hamilton Anxiety and Depression Scale (HADS). Linear regression models were completed in R. Gender and age were included as nuisance variables.ResultThere were no differences in gender or age distribution between cohorts, however participants with SCD were more depressed and anxious on average (Table 1). There was a significant interaction effect between depression and cohort in the fornix (Figure 1), as well as between anxiety and cohort in the hippocampal cingulum (Figure 2). In post‐hoc analyses, only the SCD group showed a correlation between depression and ICVF in the fornix (Figure 1) while only controls showed a correlation between anxiety and ICVF in the hippocampal cingulum (Figure 2), indicating different pathophysiology underlying psychiatric symptoms in the two groups.ConclusionAnxiety and depression appear to be associated with different microstructural features in SCD versus controls, suggesting anxiety and depression in SCD is a phenomenon distinct from anxiety and depression in healthy aging. Future work will explore the relationship between anxiety and depression and risk of conversion to mild cognitive impairment. • Mitchell AJ, Beaumont H, Ferguson D, et al. Acta Psychiatrica Scandinavica. 2014;130(6):439‐51. • Daducci A, Canales‐Rodriguez EJ, Zhang H, et al. Neuroimage. 2015;105:32‐44. • Shafto MA, Tyler LK, Dixon M, et al. BMC neurology. 2014;14(1):1‐25. • Kantarci K. Frontiers in Aging Neuroscience. 2014;6.