Neurite Orientation Dispersion And Density Imaging Research Articles

Medial Temporal Lobe White Matter Integrity is Related to Memory and Amyloid‐Beta Pathology in Aging

AbstractBackgroundDamage to white matter (WM) within the medial temporal lobe (MTL) may underlie memory decline in aging and Alzheimer’s disease (AD). We measured MTL WM tract integrity through diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging (NODDI). We tested WM integrity associations with memory performance and amyloid‐ß pathology in cognitively normal older adults.Method105 cognitively normal older adults (70.8 years old, 65% female) with diffusion MRI were processed with MRtrix3. Standard diffusion metrics of fractional anisotropy (FA) and mean diffusivity (MD) were calculated. NODDI MDT was used to generate the neurite density index (NDI), representing number of voxels with unhindered diffusion, and the orientation dispersion index (ODI), representing the variability of neurite orientation. We calculated these measures for MTL tracts from the JHU WM Atlas: cingulum‐hippocampus, fornix column/body, and fornix/stria terminalis. Participants received 18F‐florbetapir (FBP) to measure Aß pathology (n = 94), and global FBP SUVR was calculated. Memory was measured with the Rey Auditory Verbal Learning Test delayed recall score (RAVLT, n = 81). Analyses covaried for age and/or education.ResultBetter memory was associated with lower ODI in the fornix column/body (r = ‐0.27, p = 0.018), with trends for higher FA (r = 0.021, p = 0.06) and lower NDI (r = ‐0.19, p = 0.09). Better memory was also associated with higher MD in the cingulum‐hippocampus (right: r = 0.23, p = 0.04; left: r = 0.25, p = 0.03), with trends for lower ODI (right: r = ‐.20, p = 0.08; left: r = ‐0.20, p = 0.09). Higher FBP SUVR was associated with increased FA in the fornix column/body (r = 0.31, p = 0.003) and a trend in the left cingulum hippocampus (r = 0.20, p = 0.054). Memory or FBP SUVR was not significantly related to integrity of the fornix/stria terminalis.ConclusionIntegrity of fornix column/body and cingulum‐hippocampus were related to both memory performance and Aß pathology. Our results suggest that using a combination of NODDI as well as diffusion tensor metrics provided a more robust understanding of memory impacts in aging.

Examining the interplay between AD pathology and intracellular/extracellular properties of cortical tissue in preclinical AD

AbstractBackgroundAD pathology affects neuronal microstructural decades before clinical manifestation of the disease. Amyloid plaques and tau tangles are key contributors to alterations in brain microstructural properties such as neurite morphology and axonal transport and packing, among others. It takes many years for these microstructural changes to build up and be reliably detected using volumetric MRI measures of neurodegeneration. Here, we examined the utility of neurite imaging – a biologically inspired model for examining cortical microstructure – to examine the impact of amyloid and tau pathology on intra‐ and extra‐cellular properties of cortical tissue and to further improve our mechanistic understanding of AD development.MethodWe utilized multimodal imaging data collected as part of ADNI‐3 including structural, multi‐shell diffusion MRI, and amyloid (18F‐florbetapir) and tau (18F‐flortaucipir) PET. The sample included 90 cognitively normal older adults (CN:23/67 amyloid‐positive/negative, age = 72.0(8.8) years) and 65 older adults with mild cognitive impairment (MCI: 36/29 amyloid‐positive/negative, 73.3(7.2) years). Neurite orientation dispersion and density imaging (NODDI) measures including intracellular volume fraction (ICVF), neurite orientation and dispersion index (ODI) in gray matter, standardized uptake value ratio (SUVR) for amyloid/tau PET and cortical thickness were extracted for 360 regions defined by surface‐based HCP atlas. We performed mediation analyses to examine the interplay between AD pathology and intracellular/extracellular properties of brain tissue and also compared the clinical utility of cortical neurite measures against volumetric MRI in detecting brain changes associated with AD pathology (tau burden) in preclinical AD.ResultMediation analyses showed that tau burden mediates the impact of amyloid on intracellular properties of brain tissue (ICVF) in medial and lateral temporal structures (Fig.1A) whereas ODI is a significant mediator of the effect of extracellular amyloid accumulation on intra‐cellular tau burden in entorhinal cortex (Fig.1B) in amyloid‐positive older adults. Further, among the regions with highest tau burden in amyloid‐positive CN group, ICVF changes in lateral temporal cortex successfully distinguished preclinical AD from amyloid‐negative CN and was associated with tau pathology.ConclusionOverall, these preliminary results suggest that accumulation of amyloid plaques results in reduction of neurite complexity while build‐up of tau reduces the intracellular volume fraction in preclinical stage of AD.

Ultra‐high‐resolution quantitative MRI at the grey/white interface in Alzheimer’s disease and posterior cortical atrophy

AbstractBackgroundCortical grey matter (CGM) and superficial white matter (SWM) undergo pathological changes, but standard MRI spatial resolutions make interpreting disease‐related effects at their interface challenging. We present findings from a study investigating the grey/white interface in typical amnestic Alzheimer’s disease (tAD), posterior cortical atrophy (PCA) and healthy controls using ultra‐high‐resolution quantitative MRI measures sensitive to microstructural properties.MethodEleven participants (Table 1) were scanned at 7T using multi‐echo FLASH (0.5mm isotropic resolution with prospective motion correction) and diffusion MRI (dMRI) (1.25mm isotropic resolution). The hMRI toolbox produced multi‐parametric mapping (MPM) measures: R1, R2* and Proton Density (PD) (Vaculciakova et al., 2021https://doi.org/10.1002/mrm.29253). dMRI processing included denoising and correcting for Gibbs ringing, eddy currents, susceptibility artifacts and motion. Metrics from dMRI were fractional anisotropy (FA), and mean diffusivity (MD), as well as tissue fraction (TF), neurite density index (NDI) and orientation dispersion index (ODI) from Neurite Orientation Dispersion and Density Imaging (NODDI). A deep learning segmentation approach estimated the grey/white boundary (Billot et al., 2021, arXiv:2107.09559). MPM and dMRI measures were sampled from the CGM into the SWM at 0.5mm increments in regions of interest (Harvard‐Oxford cortical atlas). Tissue‐weighted (tw) averages were calculated for NDI and ODI. Metrics were visualized across the grey/white interface using boxplots.ResultFigures 1‐2 show MPM and dMRI measures in the precuneus (dashed lines indicate group medians). Qualitatively, most tAD and PCA participants had lower R1 and R2* than controls, most prominently 0.5mm into the SWM (Figure 1). PD appeared higher in tAD and PCA patients across the grey/white interface. Qualitatively, most tAD and PCA participants had lower TF and higher MD in the CGM, where twNDI and FA appeared lower than controls across grey/white interface (Figure 2). Most tAD and PCA had qualitatively lower twODI in CGM and a flatter slope across the grey/white interface compared to controls.ConclusionMacromolecular (R1, R2* and twNDI) and iron content (R2*) MR measures at 7T appear reduced in tAD and PCA across the grey/white interface, whereas neurite organisational complexity (twODI) may become more homogeneous. Ongoing study will assess if these findings are consistent with further participants.

Neurite‐based white matter alterations in MAPT mutation carriers: A multi‐shell diffusion MRI study in the ALLFTD consortium

AbstractBackgroundWe aimed to assess axonal integrity in MAPT mutation carriers and early white matter (WM) neurodegeneration in asymptomatic carriers using traditional diffusion tensor imaging (DTI) measurements, i.e., fractional anisotropy (FA) and mean diffusivity (MD), and neurite orientation dispersion and density imaging (NODDI).MethodWe included available multi‐shell diffusion MRI data from 21 MAPT mutation carriers (16 asymptomatic; 5 symptomatic) and 31 non‐carrier family members as controls from the ALLFTD consortium. We used linear mixed‐effect models to assess WM abnormalities measured with FA and MD, neurite density index (NDI) and orientation dispersion index (ODI), combined across hemispheres. Separate models were conducted in all MAPT mutation carriers relative to controls while accounting for relatedness and age, then in symptomatic and asymptomatic carriers relative to controls. ComBat was used to harmonize data across sites.ResultIn models contrasting all MAPT carriers versus controls, WM alterations involved the cingulum bundle (FA, ODI), fronto‐temporal, entorhinal (FA, MD, NDI), and the inferior temporal WM (FA) after correcting for multiple comparisons (Fig. 1). In models contrasting symptomatic and asymptomatic MAPT carriers versus controls, symptomatic carriers had widespread involvement of the fronto‐temporal WM including the cingulum (FA, ODI), entorhinal (MD, FA, NDI), amygdala (MD, NDI) and inferior temporal (FA) areas after correcting for multiple comparisons. Asymptomatic carriers showed higher entorhinal MD and lower inferior temporal and cingulum FA relative to controls, and a more widespread pattern of higher ODI involved the medial temporal, superior temporal and occipital WM as well as long association and projection fibers including the internal capsule, cingulate bundle and fronto‐occipital fasciculi, although they were not statistically significant after correction for multiple comparisons.ConclusionTraditional DTI and novel NODDI measurements revealed some extent of overlap as well as divergences in patterns of WM abnormalities, indicating axonal loss is a feature of neurodegeneration in MAPT mutation carriers. Our results suggest that traditional DTI and novel NODDI measurements may have different sensitivities to WM alterations in MAPT mutation carriers, and that axon‐based metrics, particularly ODI measurements, may be more sensitive to the early WM involvement during the asymptomatic stage of the disease.

Locus coeruleus microstructural integrity is linked to plasma GFAP concentration and Aβ42/40 ratio in cognitively unimpaired individuals: a 7T MRI study

AbstractBackgroundRecent autopsy and in vivo MRI studies supported structural integrity of the brainstem locus coeruleus (LC) as a potential indicator of initial AD‐related pathological processes. Importantly, in the earliest stages of the disease, these changes to the neuronal density of the LC are associated with changes to the somatic morphology and dendritic atrophy. Here, we aimed to examine whether LC microstructural integrity, assessed in vivo with advanced diffusion‐weighted magnetic resonance imaging (dMRI), is related to plasma AD biomarkers in a sample of cognitively unimpaired individuals.MethodFifty‐seven cognitively unimpaired participants (mean age = 59.3±14.7y; 28 females) (Table 1) underwent a dMRI scanning session using a multi‐shell, high angular resolution acquisition protocol in a 7T scanner. LC microstructure was evaluated by applying the Neurite Orientation Dispersion and Density Imaging (NODDI) biophysical model on the dMRI data, yielding two metrics of microstructural integrity: Neurite Density Index (NDI) and Orientation Dispersion Index (ODI). Additionally, blood samples were analyzed to assess AD plasma biomarkers, including Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and tau phosphorylated at threonine 181 (pTau181) or threonine 231 (pTau231).ResultHigher age was associated with lower LC ODI (t = ‐2.77, p = 0.008) but not LC NDI values (t = 0.44, p = 0.658). Multiple linear regressions adjusted for age, sex, and estimated Total Intracranial Volume (eTIV) showed that lower NDI in the LC was associated with higher plasma GFAP levels (t = ‐2.08, p = .04, Figure 1). In addition, we found a negative association between ODI within the LC and Aβ42/40 (t = ‐2.79, p = .007, Figure 2). No significant relationships were found between LC NDI/ODI values and plasma NfL or pTau biomarkers.ConclusionConsistent with animal studies, these findings suggest that microstructural changes in the LC are associated with astroglial activation in the earliest stages of the disease. Associations with Aβ42/40 were unexpected but might reflect loss of white matter compartments or changes in lipid density. In future analyses, we will further examine the biological interpretation of the NODDI metrics in subcortical regions, in particular in the context of AD‐related processes.

Comparison of diffusion metrics in dementia

AbstractBackgroundThe recent FDA approval of a disease‐modifying drug for Alzheimer’s disease has stressed the need for a test which can be used at scale to detect neurodegeneration. MRI diffusion shows great promise (Douaud et al., 2013), and recently a multiplicity of analysis methods have been developed. We look at which diffusion analysis method might be most sensitive.MethodWe worked with data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) (Weber et al., 2021). Participants with Alzheimer’s disease (AD) and a group of age‐matched healthy controls (HC) were identified. T1 images were processed with FreeSurfer v7 (Fischl, 2012), providing tissue segmentations and cortical parcellations, as well as regional volumes. Diffusion images were preprocessed using the PreQual pipeline in native space (including FSL’s Topup and Eddy) (Cai et al, 2021), and analysed with Diffusion Tensor Imaging (DTI), Neurite Orientation Dispersion and Density Imaging (NODDI) (Zhang, Schneider, et al, 2012), Apparent Measures Using Reduced Acquisitions (AMURA) (Aja‐Fernández et al, 2022), Diffusion Orientation Complexity (DOC) (Haroon et al, 2009) and Probabilistic Index of Connectivity (PICo) (Parker et al, 2003). Regional values were extracted in FreeSurfer regions (grey and white matter).Pairwise Mann‐Whitney U‐tests were carried out between AD and HC regional measures. Regions with the most statistically significant volume differences were selected; diffusion‐based metrics for these regions were calculated using weighted values and compared. The 10 metrics with the smallest p‐values were used to find the most significant regions, and these were compared with volumes.ResultParticipants: 100 AD (38 female, age 74.5±7.9 years) and 207 HC (132 female, age 72.0±7.4 years).We selected the 25 most significant regions from the volumetric analyses. From these regions, the most effective diffusion metrics were DTI‐derived mean, axial and radial diffusivities, and 5 of the AMURA metrics.Given the 10 most significant metrics, of the 15 most significant volumes, 8 were also in the top diffusion regions.ConclusionThis study demonstrates that DTI metrics are most sensitive at differentiating HC from AD. If confirmed this has clinical significance, as these scans are widely available.

Advanced measures of cortical microstructural change and associations with cognitive and blood‐based biomarkers in autosomal dominant Alzheimer’s disease

AbstractBackgroundIn Alzheimer’s disease (AD), dysfunction and loss of cortical neurons occurs prior to symptom onset. Diffusion tensor imaging, measuring mean diffusivity (MD), provides a metric of microscopic change but lacks specificity for different underlying microstructural processes. We used Neurite Orientation Dispersion and Density Imaging (NODDI) to investigate specific cortical microstructural features across the disease course in autosomal dominant AD (ADAD).MethodSixty‐three ADAD family members (36 mutation carriers) (Table 1) underwent T1w and multi‐shell diffusion MRI (dMRI). Cortical thickness and cortical MD were estimated, with NODDI providing measures of tissue fraction (TF), neurite density index (NDI) and orientation dispersion index (ODI) (a proxy measure of dendritic complexity). Imaging metrics were sampled across six cortical regions of interest (ROIs) known to be particularly vulnerable to early neurodegeneration. Associations between dMRI measures and 1) disease stage as measured by estimated years to onset (EYO), 2) AD blood biomarkers, and 3) cognitive measures were assessed.ResultAcross mutation carriers, ODI (Figure 1) and TF (Figure 2) demonstrated negative associations (p<0.05) with EYO in most ROIs, while MD demonstrated positive correlations. Most associations remained after adjusting for cortical thickness. The association between ODI and EYO in the supramarginal gyrus also remained after adjustment for MD (p = 0.002). In presymptomatic carriers, EYO appeared most prominently associated with ODI (p<0.05 in 3/6 regions). ODI, TF and MD showed widespread associations with MMSE and CDR sum of boxes. TF was negatively, and MD positively, associated with serum NfL across ROIs, but for ODI this was only the case in the supramarginal gyrus. ptau181 demonstrated significant associations with ODI in the supramarginal (p = 0.0089) and inferior parietal (p = 0.033) cortices, and with MD in the entorhinal cortex (p = 0.015).ConclusionCortical dendritic complexity (modelled by ODI) and cortical tissue fraction decrease, while overall diffusivity increases as individuals approach symptom onset. ODI appears to be the metric most closely associated with presymptomatic disease stage, possibly reflecting early dendritic pruning, and is associated with ptau – a measure of early pathology – while MD and TF may be more sensitive to later larger scale changes, given their associations with serum NfL and cognitive measures.

Advanced measures of cortical microstructural change and associations with cognitive and blood‐based biomarkers in autosomal dominant Alzheimer’s disease

AbstractBackgroundIn Alzheimer’s disease (AD), dysfunction and loss of cortical neurons occurs prior to symptom onset. Diffusion tensor imaging, measuring mean diffusivity (MD), provides a metric of microscopic change but lacks specificity for different underlying microstructural processes. We used Neurite Orientation Dispersion and Density Imaging (NODDI) to investigate specific cortical microstructural features across the disease course in autosomal dominant AD (ADAD).MethodSixty‐three ADAD family members (36 mutation carriers) (Table 1) underwent T1w and multi‐shell diffusion MRI (dMRI). Cortical thickness and cortical MD were estimated, with NODDI providing measures of tissue fraction (TF), neurite density index (NDI) and orientation dispersion index (ODI) (a proxy measure of dendritic complexity). Imaging metrics were sampled across six cortical regions of interest (ROIs) known to be particularly vulnerable to early neurodegeneration. Associations between dMRI measures and 1) disease stage as measured by estimated years to onset (EYO), 2) AD blood biomarkers, and 3) cognitive measures were assessed.ResultAcross mutation carriers, ODI (Figure 1) and TF (Figure 2) demonstrated negative associations (p<0.05) with EYO in most ROIs, while MD demonstrated positive correlations. Most associations remained after adjusting for cortical thickness. The association between ODI and EYO in the supramarginal gyrus also remained after adjustment for MD (p = 0.002). In presymptomatic carriers, EYO appeared most prominently associated with ODI (p<0.05 in 3/6 regions). ODI, TF and MD showed widespread associations with MMSE and CDR sum of boxes. TF was negatively, and MD positively, associated with serum NfL across ROIs, but for ODI this was only the case in the supramarginal gyrus. ptau181 demonstrated significant associations with ODI in the supramarginal (p = 0.0089) and inferior parietal (p = 0.033) cortices, and with MD in the entorhinal cortex (p = 0.015).ConclusionCortical dendritic complexity (modelled by ODI) and cortical tissue fraction decrease, while overall diffusivity increases as individuals approach symptom onset. ODI appears to be the metric most closely associated with presymptomatic disease stage, possibly reflecting early dendritic pruning, and is associated with ptau – a measure of early pathology – while MD and TF may be more sensitive to later larger scale changes, given their associations with serum NfL and cognitive measures.

Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study

Memory consolidation can benefit from post-learning sleep, eventually leading to long-term microstructural brain modifications to accommodate new memory representations. Non-invasive diffusion-weighted magnetic resonance imaging (DWI) allows the observation of (micro)structural brain remodeling after time-limited motor learning. Here, we combine conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) that allows modeling dendritic and axonal complexity in gray matter to investigate with improved specificity the microstructural brain mechanisms underlying time- and sleep-dependent motor memory consolidation dynamics. Sixty-one young healthy adults underwent four DWI sessions, two sequential motor trainings, and a night of total sleep deprivation or regular sleep distributed over five days. We observed rapid-motor-learning-related remodeling in occipitoparietal, temporal, and motor-related subcortical regions, reflecting temporary dynamics in learning-related neuronal brain plasticity processes. Sleep-related consolidation seems not to exert a detectable impact on diffusion parameters, at least on the timescale of a few days.

Quantitative diffusion imaging and genotype-by-sex interactions in a rat model of Alexander disease.

The clinical diagnosis and classification of Alexander disease (AxD) relies in part on qualitative neuroimaging biomarkers; however, these biomarkers fail to distinguish and discriminate different subtypes of AxD, especially in the presence of overlap in clinical symptoms. To address this gap in knowledge, we applied neurite orientation dispersion and density imaging (NODDI) to an innovative CRISPR-Cas9 rat genetic model of AxD to gain quantitative insights into the neural substrates and brain microstructural changes seen in AxD and to potentially identify novel quantitative NODDI biomarkers of AxD. Multi-shell DWI of age- and sex-matched AxD and wild-type Sprague Dawley rats (n = 6 per sex per genotype) was performed and DTI and NODDI measures calculated. A 3 × 2 × 2 analysis of variance model was used to determine the effect of genotype, biological sex, and laterality on quantitative measures of DTI and NODDI across regions of interest implicated in AxD. There is a significant effect of genotype in the amygdala, hippocampus, neocortex, and thalamus in measures of both DTI and NODDI brain microstructure. A genotype by biological sex interaction was identified in DTI and NODDI measures in the corpus callosum, hippocampus, and neocortex. We present the first application of NODDI to the study of AxD using a rat genetic model of AxD. Our analysis identifies alterations in NODDI and DTI measures to large white matter tracts and subcortical gray nuclei. We further identified genotype by sex interactions, suggesting a possible role for biological sex in the neuropathogenesis of AxD.

Free-Water Imaging in Friedreich Ataxia Using Multi-Compartment Models.

The neurological phenotype of Friedreich ataxia (FRDA) is characterized by neurodegeneration and neuroinflammation in the cerebellum and brainstem. Novel neuroimaging approaches quantifying brain free-water using diffusion magnetic resonance imaging (dMRI) are potentially more sensitive to these processes than standard imaging markers. To quantify the extent of free-water and microstructural change in FRDA-relevant brain regions using neurite orientation dispersion and density imaging (NODDI), and bitensor diffusion tensor imaging (btDTI). Multi-shell dMRI was acquired from 14 individuals with FRDA and 14 controls. Free-water measures from NODDI (FISO) and btDTI (FW) were compared between groups in the cerebellar cortex, dentate nuclei, cerebellar peduncles, and brainstem. The relative sensitivity of the free-water measures to group differences was compared to microstructural measures of NODDI intracellular volume, free-water corrected fractional anisotropy, and conventional uncorrected fractional anisotropy. In individuals with FRDA, FW was elevated in the cerebellar cortex, peduncles (excluding middle), dentate, and brainstem (P < 0.005). FISO was elevated primarily in the cerebellar lobules (P < 0.001). On average, FW effect sizes were larger than all other markers (mean ηρ 2 = 0.43), although microstructural measures also had very large effects in the superior and inferior cerebellar peduncles and brainstem (ηρ 2 > 0.37). Across all regions and metrics, effect sizes were largest in the superior cerebellar peduncles (ηρ 2 > 0.46). Multi-compartment diffusion measures of free-water and neurite integrity distinguish FRDA from controls with large effects. Free-water magnitude in the brainstem and cerebellum provided the greatest distinction between groups. This study supports further applications of multi-compartment diffusion modeling, and investigations of free-water as a measure of disease expression and progression in FRDA. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Applicability of multiple quantitative magnetic resonance methods in genetic brain white matter disorders.

Magnetic resonance imaging (MRI) measures of tissue microstructure are important for monitoring brain white matter (WM) disorders like leukodystrophies and multiple sclerosis. They should be sensitive to underlying pathological changes. Three whole-brain isotropic quantitative methods were applied and compared within a cohort of controls and leukodystrophy patients: two novel myelin water imaging (MWI) techniques (multi-compartment relaxometry diffusion-informed MWI: MCR-DIMWI, and multi-echo T2 relaxation imaging with compressed sensing: METRICS) and neurite orientation dispersion and density imaging (NODDI). For 9 patients with different leukodystrophies (age range 0.4-62.4 years) and 15 control subjects (2.3-61.3 years), T1-weighted MRI, fluid-attenuated inversion recovery, multi-echo gradient echo with variable flip angles, METRICS, and multi-shell diffusion-weighted imaging were acquired on 3 Tesla. MCR-DIMWI, METRICS, NODDI, and quality control measures were extracted to evaluate differences between patients and controls in WM and deep gray matter (GM) regions of interest (ROIs). Pearson correlations, effect size calculations, and multi-level analyses were performed. MCR-DIMWI and METRICS-derived myelin water fractions (MWFs) were lower and relaxation times were higher in patients than in controls. Effect sizes of MWF values and relaxation times were large for both techniques. Differences between patients and controls were more pronounced in WM ROIs than in deep GM. MCR-DIMWI-MWFs were more homogeneous within ROIs and more bilaterally symmetrical than METRICS-MWFs. The neurite density index was more sensitive in detecting differences between patients and controls than fractional anisotropy. Most measures obtained from MCR-DIMWI, METRICS, NODDI, and diffusion tensor imaging correlated strongly with each other. This proof-of-concept study shows that MCR-DIMWI, METRICS, and NODDI are sensitive techniques to detect changes in tissue microstructure in WM disorders.

Altered amygdala volumes and microstructure in focal epilepsy patients with tonic-clonic seizures, ictal, and post-convulsive central apnea.

Sudden unexpected death in epilepsy (SUDEP) is a leading cause of death for patients with epilepsy; however, the pathophysiology remains unclear. Focal-to-bilateral tonic-clonic seizures (FBTCS) are a major risk factor, and centrally-mediated respiratory depression may increase the risk further. Here, we determined the volume and microstructure of the amygdala, a key structure that can trigger apnea in people with focal epilepsy, stratified by the presence or absence of FBTCS, ictal central apnea (ICA), and post-convulsive central apnea (PCCA). Seventy-three patients with focal impaired awareness seizures without FBTC seizures (FBTCneg group) and 30 with FBTCS (FBTCpos group) recorded during video electroencephalography (VEEG) with respiratory monitoring were recruited prospectively during presurgical investigations. We acquired high-resolution T1-weighted anatomic and multi-shell diffusion images, and computed neurite orientation dispersion and density imaging (NODDI) metrics in all patients with epilepsy and 69 healthy controls. Amygdala volumetric and microstructure alterations were compared between three groups: healthy subjects, FBTCneg and FBTCpos groups. The FBTCpos group was further subdivided by the presence of ICA and PCCA, verified by VEEG. Bilateral amygdala volumes were significantly increased in the FBTCpos cohort compared to healthy controls and the FBTCneg group. Patients with recorded PCCA had the highest increase in bilateral amygdala volume of the FBTCpos cohort. Amygdala neurite density index (NDI) values were decreased significantly in both the FBTCneg and FBTCpos groups relative to healthy controls, with values in the FBTCpos group being the lowest of the two. The presence of PCCA was associated with significantly lower NDI values vs the non-apnea FBTCpos group (p = 0.004). Individuals with FBTCpos and PCCA show significantly increased amygdala volumes and disrupted architecture bilaterally, with greater changes on the left side. The structural alterations reflected by NODDI and volume differences may be associated with inappropriate cardiorespiratory patterns mediated by the amygdala, particularly after FBTCS. Determination of amygdala volumetric and architectural changes may assist identification of individuals at risk.

Evidence of Ongoing Cerebral Microstructural Reorganization in Children With Persisting Symptoms Following Mild Traumatic Brain Injury: A NODDI DTI Analysis.

Approximately 300-550 children per 100,000 sustain a mild traumatic brain injury (mTBI) each year, of whom ∼25-30% have long-term cognitive problems. Following mTBI, free water (FW) accumulation occurs in white matter (WM) tracts. Diffusion tensor imaging (DTI) can be used to investigate structural integrity following mTBI. Compared with conventional DTI, neurite orientation dispersion and density imaging (NODDI) orientation dispersion index (ODI) and fraction of isolated free water (FISO) metrics may allow a more advanced insight into microstructural damage following pediatric mTBI. In this longitudinal study, we used NODDI to explore whole-brain and tract-specific differences in ODI and FISO in children with persistent symptoms after mTBI (n = 80) and in children displaying clinical recovery (n = 32) at 1 and 2-3 months post-mTBI compared with healthy controls (HCs) (n = 21). Two-way repeated measures analysis of variance (ANOVA) and voxelwise two-sample t tests were conducted to compare whole-brain and tract-specific diffusion across groups. All results were corrected at positive false discovery rate (pFDR) <0.05. We also examined the association between NODDI metrics and clinical outcomes, using logistical regression to investigate the value of NODDI metrics in predicting future recovery from mTBI. Whole-brain ODI was significantly increased in symptomatic participants compared with HCs at both 1 and 2 months post-injury, where the uncinate fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF) were particularly implicated. Using region of interest (ROI) analysis in significant WM, bilateral IFOF and UF voxels, symptomatic participants had the highest ODI in all ROIs. ODI was lower in asymptomatic participants, and HCs had the lowest ODI in all ROIs. No changes in FISO were found across groups or over time. WM ODI was moderately correlated with a higher youth-reported post-concussion symptom inventory (PCSI) score. With 87% predictive power, ODI (1 month post-injury) and clinical predictors (age, sex, PCSI score, attention scores) were a more sensitive predictor of recovery at 2-3 months post-injury than fractional anisotropy (FA) and clinical predictors, or clinical predictors alone. FISO could not predict recovery at 2-3 months post-injury. Therefore, we found that ODI was significantly increased in symptomatic children following mTBI compared with HCs at 1 month post-injury, and progressively decreased over time alongside clinical recovery. We found no significant differences in FISO between groups or over time. WM ODI at 1 month was a more sensitive predictor of clinical recovery at 2-3 months post-injury than FA, FISO, or clinical measures alone. Our results show evidence of ongoing microstructural reorganization or neuroinflammation between 1 and 2-3 months post-injury, further supporting delayed return to play in children who remain symptomatic. We recommend future research examining the clinical utility of NODDI following mTBI to predict recovery or persistence of post-concussion symptoms and thereby inform management of mTBI.

Changes in Cortical Microstructure of the Human Brain Resulting from Long-Term Motor Learning.

The mechanisms subserving motor skill acquisition and learning in the intact human brain are not fully understood. Previous studies in animals have demonstrated a causal relationship between motor learning and structural rearrangements of synaptic connections, raising the question of whether neurite-specific changes are also observable in humans. Here, we use advanced diffusion magnetic resonance imaging (MRI), sensitive to dendritic and axonal processes, to investigate neuroplasticity in response to long-term motor learning. We recruited healthy male and female human participants (age range 19-29) who learned a challenging dynamic balancing task (DBT) over four consecutive weeks. Diffusion MRI signals were fitted using Neurite Orientation Dispersion and Density Imaging (NODDI), a theory-driven biophysical model of diffusion, yielding measures of tissue volume, neurite density and the organizational complexity of neurites. While NODDI indices were unchanged and reliable during the control period, neurite orientation dispersion increased significantly during the learning period mainly in primary sensorimotor, prefrontal, premotor, supplementary, and cingulate motor areas. Importantly, reorganization of cortical microstructure during the learning phase predicted concurrent behavioral changes, whereas there was no relationship between microstructural changes during the control phase and learning. Changes in neurite complexity were independent of alterations in tissue density, cortical thickness, and intracortical myelin. Our results are in line with the notion that structural modulation of neurites is a key mechanism supporting complex motor learning in humans.SIGNIFICANCE STATEMENT The structural correlates of motor learning in the human brain are not fully understood. Results from animal studies suggest that synaptic remodeling (e.g., reorganization of dendritic spines) in sensorimotor-related brain areas is a crucial mechanism for the formation of motor memory. Using state-of-the-art diffusion magnetic resonance imaging (MRI), we found a behaviorally relevant increase in the organizational complexity of neocortical microstructure, mainly in primary sensorimotor, prefrontal, premotor, supplementary, and cingulate motor regions, following training of a challenging dynamic balancing task (DBT). Follow-up analyses suggested structural modulation of synapses as a plausible mechanism driving this increase, while colocalized changes in cortical thickness, tissue density, and intracortical myelin could not be detected. These results advance our knowledge about the neurobiological basis of motor learning in humans.

The relationship between cognition and white matter tract damage after mild traumatic brain injury in a premorbidly healthy, hospitalised adult cohort during the post-acute period

IntroductionRecent developments in neuroimaging techniques enable increasingly sensitive consideration of the cognitive impact of damage to white matter tract (WMT) microstructural organisation after mild traumatic brain injury (mTBI).ObjectiveThis study investigated the relationship between WMT microstructural properties and cognitive performance.Participants, setting and designUsing an observational design, a group of 26 premorbidly healthy adults with mTBI and a group of 20 premorbidly healthy trauma control (TC) participants who were well-matched on age, sex, premorbid functioning and a range of physical, psychological and trauma-related variables, were recruited following hospital admission for traumatic injury.Main measuresAll participants underwent comprehensive unblinded neuropsychological examination and structural neuroimaging as outpatients 6–10 weeks after injury. Neuropsychological examination included measures of speed of processing, attention, memory, executive function, affective state, pain, fatigue and self-reported outcome. The WMT microstructural properties were estimated using both diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) modelling techniques. Tract properties were compared between the corpus callosum, inferior longitudinal fasciculus, uncinate fasciculus, anterior corona radiata and three segmented sections of the superior longitudinal fasciculus.ResultsFor the TC group, in all investigated tracts, with the exception of the uncinate fasciculus, two DTI metrics (fractional anisotropy and apparent diffusion coefficient) and one NODDI metric (intra-cellular volume fraction) revealed expected predictive linear relationships between extent of WMT microstructural organisation and processing speed, memory and executive function. The mTBI group showed a strikingly different pattern relative to the TC group, with no relationships evident between WMT microstructural organisation and cognition on most tracts.ConclusionThese findings indicate that the predictive relationship that normally exists in adults between WMT microstructural organisation and cognition, is significantly disrupted 6–10 weeks after mTBI and suggests that WMT microstructural organisation and cognitive function have disparate recovery trajectories.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

BackgroundAlzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical.MethodsParticipants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination).ResultsUsing internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone.ConclusionUsing a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

Infection burden and its association with neurite orientation dispersion and density imaging markers in the UK Biobank

BackgroundInfection burden (IB), although linked to neurodegeneration, including Alzheimer’s Disease (AD), has not been examined against neurite orientation, dispersion, and density imaging (NODDI) measures. MethodsAmong 38,803 UK Biobank adults (Age:40–70 years), we tested associations of total IB (IBtotal, 47.5 %) and hospital-treated IB (IBhosp, 9.7 %) with NODDI measures (5–15 years later), including volume fraction of Gaussian isotropic diffusion (ISOVF), intra-cellular volume fraction (ICVF) and orientation dispersion (OD) indices, using multiple linear regression models. ResultsTotal and hospital-treated infection burdens (IBtotal and IBhosp) were associated with increased ISOVF, indicating increased free-water component. IBtotal was positively associated with OD, indicating that at higher IBtotal there was greater fanning of neurites. This was more evident in the lower cardiovascular health group. IBhosp was associated with higher OD, and lower ICVF at higher AD polygenic risk. Together, these findings indicate that both total and hospital-treated infections have effects on NODDI outcomes in the direction of poor brain health. These effects were largely homogeneous across cardiovascular health and AD polygenic risk groups, with some effects shown to be stronger at poor cardiovascular health and/or higher AD risk. ConclusionsTotal and hospital-treated infections were associated with poorer white matter microstructure (higher ISOVF or OD or lower ICVF), with some heterogeneity across cardiovascular health and AD risk. Longitudinal studies with multiple repeats on neuroimaging markers in comparable samples are needed.

Automated motion artifact detection in early pediatric diffusion MRI using a convolutional neural network.

Diffusion MRI (dMRI) is a widely used method to investigate the microstructure of the brain. Quality control (QC) of dMRI data is an important processing step that is performed prior to analysis using models such as diffusion tensor imaging (DTI) or neurite orientation dispersion and density imaging (NODDI). When processing dMRI data from infants and young children, where intra-scan motion is common, the identification and removal of motion artifacts is of the utmost importance. Manual QC of dMRI data is (1) time-consuming due to the large number of diffusion directions, (2) expensive, and (3) prone to subjective errors and observer variability. Prior techniques for automated dMRI QC have mostly been limited to adults or school-age children. Here, we propose a deep learning-based motion artifact detection tool for dMRI data acquired from infants and toddlers. The proposed framework uses a simple three-dimensional convolutional neural network (3DCNN) trained and tested on an early pediatric dataset of 2,276 dMRI volumes from 121 exams acquired at 1 month and 24 months of age. An average classification accuracy of 95% was achieved following four-fold cross-validation. A second dataset with different acquisition parameters and ages ranging from 2-36 months (consisting of 2,349 dMRI volumes from 26 exams) was used to test network generalizability, achieving 98% classification accuracy. Finally, to demonstrate the importance of motion artifact volume removal in a dMRI processing pipeline, the dMRI data were fit to the DTI and NODDI models and the parameter maps were compared with and without motion artifact removal.

Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis.

The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampalcingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.