Microstructural MRI Research Articles

Ultra-high-resolution mapping of myelin and g-ratio in a panel of Mbp enhancer-edited mouse strains using microstructural MRI

Non-invasive myelin water fraction (MWF) and g-ratio mapping using microstructural MRI have the potential to offer critical insights into brain microstructure and our understanding of neuroplasticity and neuroinflammation. By leveraging a unique panel of variably hypomyelinating mouse strains, we validated a high-resolution, model-free image reconstruction method for whole-brain MWF mapping. Further, by employing a bipolar gradient echo MRI sequence, we achieved high spatial resolution and robust mapping of MWF and g-ratio across the whole mouse brain. Our regional white matter-tract specific analyses demonstrated a graded decrease in MWF in white matter tracts which correlated strongly with myelin basic protein gene (Mbp) mRNA levels. Using these measures, we derived the first sensitive calibrations between MWF and Mbp mRNA in the mouse. Minimal changes in axonal density supported our hypothesis that observed MWF alterations stem from hypomyelination. Overall, our work strongly emphasizes the potential of non-invasive, MRI-derived MWF and g-ratio modeling for both preclinical model validation and ultimately translation to humans.

Longitudinal Imaging of Injured Spinal Cord Myelin and White Matter with 3D Ultrashort Echo Time Magnetization Transfer (UTE-MT) and Diffusion MRI.

Quantitative MRI techniques could be helpful to noninvasively and longitudinally monitor dynamic changes in spinal cord white matter following injury, but imaging and postprocessing techniques in small animals remain lacking. Unilateral C5 hemisection lesions were created in a rat model, and ultrashort echo time magnetization transfer (UTE-MT) and diffusion-weighted sequences were used for imaging following injury. Magnetization transfer ratio (MTR) measurements and preferential diffusion along the longitudinal axis of the spinal cord were calculated as fractional anisotropy or an apparent diffusion coefficient ratio over transverse directions. The area of myelinated white matter was obtained by thresholding the spinal cord using mean MTR or diffusion ratio values from the contralesional side of the spinal cord. A decrease in white matter areas was observed on the ipsilesional side caudal to the lesions, which is consistent with known myelin and axonal changes following spinal cord injury. The myelinated white matter area obtained through the UTE-MT technique and the white matter area obtained through diffusion imaging techniques showed better performance to distinguish evolution after injury (AUCs > 0.94, p < 0.001) than the mean MTR (AUC = 0.74, p = 0.01) or ADC ratio (AUC = 0.68, p = 0.05) values themselves. Immunostaining for myelin basic protein (MBP) and neurofilament protein NF200 (NF200) showed atrophy and axonal degeneration, confirming the MRI results. These compositional and microstructural MRI techniques may be used to detect demyelination or remyelination in the spinal cord after spinal cord injury.

Protocol for a randomised controlled unblinded feasibility trial of HD-DRUM: a rhythmic movement training application for cognitive and motor symptoms in people with Huntington’s disease

IntroductionHuntington’s disease (HD) is an inherited neurodegenerative disease causing progressive cognitive and motor decline, largely due to basal ganglia (BG) atrophy. Rhythmic training offers promise as therapy to counteract BG-regulated...

Complemental Value of Microstructural and Macrostructural MRI in the Discrimination of Neurodegenerative Parkinson Syndromes.

Various MRI-based techniques were tested for the differentiation of neurodegenerative Parkinson syndromes (NPS); the value of these techniques in direct comparison and combination is uncertain. We thus compared the diagnostic performance of macrostructural, single compartmental, and multicompartmental MRI in the differentiation of NPS. We retrospectively included patients with NPS, including 136 Parkinson's disease (PD), 41 multiple system atrophy (MSA) and 32 progressive supranuclear palsy (PSP) and 27healthy controls (HC). Macrostructural tissue probability values (TPV) were obtained by CAT12. The microstructure was assessed using amesoscopic approach by diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and diffusion microstructure imaging (DMI). After an atlas-based read-out, alinear support vector machine (SVM) was trained on atraining set (n = 196) and validated in an independent test cohort (n = 40). The diagnostic performance of the SVM was compared for different inputs individually and in combination. Regarding the inputs separately, we observed the best diagnostic performance for DMI. Overall, the combination of DMI and TPV performed best and correctly classified 88% of the patients. The corresponding area under the receiver operating characteristic curve was 0.87 for HC, 0.97 for PD, 1.0 for MSA, and 0.99 for PSP. We were able to demonstrate that (1) MRI parameters that approximate the microstructure provided substantial added value over conventional macrostructural imaging, (2) multicompartmental biophysically motivated models performed better than the single compartmental DTI and (3) combining macrostructural and microstructural information classified NPS and HC with satisfactory performance, thus suggesting acomplementary value of both approaches.

The association between microstructural MRI biomarkers and sequential amyloid and tau‐related cortical changes in asymptomatic elderly individuals

AbstractBackgroundIn Alzheimer’s disease, early amyloid‐β and tau deposition may have differential downstream effects on synaptic function and neuronal loss in a stage‐dependent manner. Amyloid‐related synaptic changes are thought to precede tau accumulation, which starts in the medial temporal lobe before propagating and leading to neurodegeneration. We explored whether microstructural MRI measures can detect these different sequential cortical changes.MethodSeventy‐nine healthy, asymptomatic individuals, recruited from the Insight 46 study of the British 1946 birth cohort underwent combined PET/MR with [18F]florbetapir Aβ‐PET at ∼73yrs, and [18F]MK‐6240 tau‐PET at ∼76yrs. Standard uptake value ratios were calculated using a whole cerebellar reference for florbetapir and an inferior cerebellar reference for MK‐6240. Multi‐shell diffusion MRI was acquired; neurite orientation dispersion and density imaging was used to quantify neurite density (NDI) and orientation dispersion (ODI, a proxy measure of dendritic morphology/complexity), with DTI measuring mean diffusivity (MD), a less specific measure of degenerative change. PET and microstructural MRI biomarkers were assessed in a neocortical composite ROI and across Braak stages.ResultThirty‐six participants were amyloid positive, 18 of whom were tau positive (eight Braak stage 1‐2, four Braak 3‐4, six Braak 5‐6). Across all participants, in the neocortical composite, significant differences between amyloid positive and amyloid negative individuals were found in both tau PET (p = 0.0092) and ODI (p = 0.030) but not for other measures. Within the amyloid positive group, in the cortical composite, significant differences in MD (p = 0.0093) but not ODI were seen when comparing those who were tau positive and negative. In the amyloid positive group, there was an association between tau PET and MD in the MTL (Braak 1‐2) (r = 0.34, p = 0.040) and Braak 3‐4 (r = 0.37, p = 0.025), with an association between tau and ODI (r = 0.48, p = 0.0031) in Braak 3‐4 only. After adjusting for volume, only the association between tau PET and ODI in Braak 3‐4 remained (p = 0.038).ConclusionOur results are consistent with amyloid deposition causing dendritic/changes (as assessed by ODI) with consequent synaptic dysfunction. Later tau propogation is then associated with frank neuronal breakdown (as measured by MD). dMRI cortical imaging biomarkers have the potential to provide proxy measures of underlying AD stage/pathology prior to symptom onset.

Cortical microstructural MRI for detection of early target engagement in AD drug trials: post‐hoc analysis of exploratory outcomes from a Phase 1b safety study for XPro1595 in AD

AbstractBackgroundEvidence in support of the amyloid cascade hypothesis for Alzheimer’s disease (AD) suggests that pathological amyloid‐beta (Aβ) is initially associated with synaptic hyperactivity and accumulates in an activity dependent fashion. These findings are corroborated by longitudinal data from cohort studies with Aβ‐PET imaging, wherein Aβ accumulates first in gray matter (GM) cortices associated with the default‐mode network (DMN) before spreading in a semi‐hierarchical pattern to different neocortical regions as the disease progresses (Mattsson et al. 2019). Mapping brain regions most frequently affected by Aβ pathology at different stages of disease may provide a framework for investigation of new drug entities targeting other components of Aβ toxicity using less invasive imaging modalities. The hypothesis here is that indicators of disease specific, tissue‐level treatment effects should be first detectable in brain regions most frequently affected by active pathology.MethodXPro1595 is a selective, brain penetrant neutralizer of soluble TNF with potent anti‐neuroinflammatory effects recently assessed for safety and pharmacological activity in a small, open‐label phase‐1b dose finding study (NCT03943264) in patients with AD. Clinical trial results for patients (n = 9) with analyzable dMRIs who completed 12‐weeks of treatment with XPro1595 [0.3 mg/kg; n = 3) or (1.0 mg/kg; n = 6)] met criteria for post‐hoc analysis. Exploratory outcomes included the novel cortical diffusivity measurement PerpPD+. PerpPD+ represents the diffusion components perpendicular to cortical GM minicolumns, indicates microscopic disruption when increased, and has proven more sensitive than standard volumetrics to changes in indicators of synaptic function, neuroinflammation and neurodegeneration across the AD continuum.ResultMean MMSE scores at baseline were 23.7 (SD = 2.5) and 15.8 (SD = 7.0) in the low‐dose and high‐dose groups, respectively, indicating varying degrees of severity. Week‐12 results showed decreases in bilateral PerPD+ at the whole brain level and in multiple GM cortices documented in the literature with the highest frequency of early (precuneus, isthmus cingulate, posterior cingulate, insula, and lateral and medial orbitofrontal) and late (lingual, pericalcarine, paracentral, precentral, and postcentral) Aβ accumulation (Figures1‐2).ConclusionCortical diffusivity measurements related to minicolumnar microstructure may provide an opportunity for noninvasive detection of early, disease specific, tissue‐level target engagement in clinical trials for investigational new drugs in AD.

Two human brain systems micro-structurally associated with obesity.

The relationship between obesity and human brain structure is incompletely understood. Using diffusion-weighted MRI from ∼30,000 UK Biobank participants, we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal/temporal/striatal system associated with ISOVF and a medial temporal/occipital/striatal system associated with ICVF. The ISOVF~WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF~WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg = 0.026, P = 0.36) and ICVF (rg = 0.112, P < 9×10-4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (P<0.05). These correlational results are consistent with a two-way mechanistic model whereby genetically determined differences in neurite density in the medial temporal system may contribute to obesity, whereas water content in the prefrontal system could reflect a consequence of obesity mediated by innate immune system activation.

In vivo cortical diffusion imaging relates to Alzheimer’s disease neuropathology

BackgroundThere has been increasing interest in cortical microstructure as a complementary and earlier measure of neurodegeneration than macrostructural atrophy, but few papers have related cortical diffusion imaging to post-mortem neuropathology.This study aimed to characterise the associations between the main Alzheimer’s disease (AD) neuropathological hallmarks and multiple cortical microstructural measures from in vivo diffusion MRI. Comorbidities and co-pathologies were also investigated.MethodsForty-three autopsy cases (8 cognitively normal, 9 mild cognitive impairment, 26 AD) from the National Alzheimer’s Coordinating Center and Alzheimer’s Disease Neuroimaging Initiative databases were included. Structural and diffusion MRI scans were analysed to calculate cortical minicolumn-related measures (AngleR, PerpPD+, and ParlPD) and mean diffusivity (MD). Neuropathological hallmarks comprised Thal phase, Braak stage, neuritic plaques, and combined AD neuropathological changes (ADNC—the “ABC score” from NIA-AA recommendations).Regarding comorbidities, relationships between cortical microstructure and severity of white matter rarefaction (WMr), cerebral amyloid angiopathy (CAA), atherosclerosis of the circle of Willis (ACW), and locus coeruleus hypopigmentation (LCh) were investigated.Finally, the effect of coexistent pathologies—Lewy body disease and TAR DNA-binding protein 43 (TDP-43)—on cortical microstructure was assessed.ResultsCortical diffusivity measures were significantly associated with Thal phase, Braak stage, ADNC, and LCh. Thal phase was associated with AngleR in temporal areas, while Braak stage was associated with PerpPD+ in a wide cortical pattern, involving mainly temporal and limbic areas. A similar association was found between ADNC (ABC score) and PerpPD+.LCh was associated with PerpPD+, ParlPD, and MD.Co-existent neuropathologies of Lewy body disease and TDP-43 exhibited significantly reduced AngleR and MD compared to ADNC cases without co-pathology.ConclusionsCortical microstructural diffusion MRI is sensitive to AD neuropathology. The associations with the LCh suggest that cortical diffusion measures may indirectly reflect the severity of locus coeruleus neuron loss, perhaps mediated by the severity of microglial activation and tau spreading across the brain.Recognizing the impact of co-pathologies is important for diagnostic and therapeutic decision-making.Microstructural markers of neurodegeneration, sensitive to the range of histopathological features of amyloid, tau, and monoamine pathology, offer a more complete picture of cortical changes across AD than conventional structural atrophy.

Measures of MRI Brain Biomarkers in Middle Age According to Average Modified Mediterranean Diet Scores Throughout Young and Middle Adulthood.

The Mediterranean diet (MedDiet) has been linked with better cognitive function and brain integrity. To examine the association of modified Mediterranean diet (mMedDiet) scores from early through middle adulthood in relation to volumetric and microstructural midlife MRI brain measures. Assess the association of mMedDiet and brain measures with four cognitive domains. If variables are correlated, determine if brain measures mediate the relationship between mMedDiet and cognition. 618 participants (mean age 25.4±3.5 at year 0) of the Coronary Artery Risk Development in Young Adults (CARDIA) study were included. Cumulative average mMedDiet scores were calculated by averaging scores from years 0, 7, and 20. MRI scans were obtained at years 25 and 30. General linear models were used to examine the association between mMedDiet and brain measures. Higher cumulative average mMedDiet scores were associated with better microstructural white matter (WM) integrity measured by fractional anisotropy (FA) at years 25 and 30 (all ptrend <0.05). Higher mMedDiet scores at year 7 were associated with higher WM FA at year 25 (β= 0.003, ptrend = 0.03). Higher mMedDiet scores at year 20 associated with higher WM FA at years 25 (β= 0.0005, ptrend = 0.002) and 30 (β= 0.0003, ptrend = 0.02). mMedDiet scores were not associated with brain volumes. Higher mMedDiet scores and WM FA were both correlated with better executive function, processing speed, and global cognition (all ptrend <0.05). WM FA did not mediate the association between mMedDiet scores and cognition. mMedDiet scores may be associated with microstructural WM integrity at midlife.

A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla

Multimodal microstructural MRI has shown increased sensitivity and specificity to changes in various brain disease and injury models in the preclinical setting. Here, we present an in vivo longitudinal dataset, including a subset of ex vivo data, acquired as control data and to investigate microstructural changes in the healthy mouse brain. The dataset consists of structural T2-weighted imaging, magnetization transfer ratio and saturation imaging, and advanced quantitative diffusion MRI (dMRI) methods. The dMRI methods include oscillating gradient spin echo (OGSE) dMRI and microscopic anisotropy (μA) dMRI, which provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The technical skills required to analyze microstructural MRI data are complex and include MRI sequence development, acquisition, and computational neuroimaging expertise. Here, we share unprocessed and preprocessed data, and scalar maps of quantitative MRI metrics. We envision utility of this dataset in the microstructural MRI field to develop and test biophysical models, methods that model temporal brain dynamics, and registration and preprocessing pipelines.

Tensor image registration library: Deformable registration of stand‐alone histology images to whole‐brain post‐mortem MRI data

BackgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data. MethodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. ResultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2–0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. ConclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.

The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines.

The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.

139. Quantitative microstructural MRI accurately predicts the likelihood of patients with degenerative cervical myelopathy requiring surgical intervention

<h3>BACKGROUND CONTEXT</h3> The definitive management of degenerative cervical myelopathy (DCM) is surgical decompression in moderate to severe cases. The evidence for early surgical intervention in mild DCM patients is less definitive and therefore, current guidelines are less clear on the relative merits of operative vs nonoperative intervention in this group of patients. According to the best available evidence, anywhere from 20%-62% of patients with mild DCM will deteriorate within 6 years; however, there is no reliable way to predict such a deterioration. However, advances in microstructural MRI may afford a novel approach to address this knowledge gap since these imaging techniques allow one to assess pathological changes such as demyelination, scarring and axonal/neuronal loss. <h3>PURPOSE</h3> Using prospectively collected data, we investigate whether quantitative MRI (qMRI) metrics can predict which patients with DCM are likely to deteriorate clinically and require surgery within one year of presentation. <h3>STUDY DESIGN/SETTING</h3> Prospective cohort study. <h3>PATIENT SAMPLE</h3> This study included 58 DCM patients (33 mild, 15 moderate and 10 severe). <h3>OUTCOME MEASURES</h3> Quantitative MRI metrics and mJOA. <h3>METHODS</h3> Data were stratified into patients who required surgery within one year of follow-up and those who remained stable and continued in the nonoperative group. MRI Acquisition and Image Processing: All patients underwent a multiparametric qMRI scan protocol including diffusion tensor (DTI), magnetization transfer (MT) and T2* weighted imaging at the initial visit. Quantitative metrics including cross sectional area (CSA), fractional anisotropy (FA), magnetization transfer ratio (MTR), and T2* white matter to gray matter ratio (T2*WI WM/GM) were measured in the cervical spine at the rostral, caudal and most compressed levels (MCL). Statistical analysis multivariable logistic regression was performed using baseline FA, MTR and T2*WI WM/GM in the rostral spine and CSA at the MCL as predictor variables. Surgical decompression at one year was used as the dependent variable. Model discrimination and reliability were measured using c-index and Brier's score respectively. Validation and calibration were performed using bootstrap method with 100 repetitions. <h3>RESULTS</h3> A total of 33 mild (mJOA 15-17), 15 moderate (mJOA 12-14) and 10 severe (mJOA 0-11) DCM patients were included in the study. Twenty-eight patients had undergone surgical decompresion at One-year follow-up, whereas the other 28 remained in nonoperative managment. Baseline qMRI was able to identify patients requiring surgery, with an accuracy of 81.6% (AUC or c-index). The model showed good reliability with a Brier score of 0.18 and Somers' Dxy rank correlation of 0.63. Calibration using bootstrap method showed overall good predictive ability with slight over prediction at higher observed probability of surgery. <h3>CONCLUSIONS</h3> Baseline quantitative MRI is able to accurately predict the likelihood of deterioration and surgical intervention in DCM patients. It can potentially play an important role in screening patient populations for surgical candidates or those who are at high risk of deterioration. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio

IntroductionQuantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. MethodsSeventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained.3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated.Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. ResultsIn NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and −0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DiscussionG-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. ConclusionMTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.

Diffusion Tensor Orientation as a Microstructural MRI Marker of Mossy Fiber Sprouting After TBI in Rats.

Diffusion tensor imaging (DTI) metrics are highly sensitive to microstructural brain alterations and are potentially useful imaging biomarkers for underlying neuropathologic changes after experimental and human traumatic brain injury (TBI). As potential imaging biomarkers require direct correlation with neuropathologic alterations for validation and interpretation, this study systematically examined neuropathologic abnormalities underlying alterations in DTI metrics in the hippocampus and cortex following controlled cortical impact (CCI) in rats. Ex vivo DTI metrics were directly compared with a comprehensive histologic battery for neurodegeneration, microgliosis, astrocytosis, and mossy fiber sprouting by Timm histochemistry at carefully matched locations immediately, 48 hours, and 4 weeks after injury. DTI abnormalities corresponded to spatially overlapping but temporally distinct neuropathologic alterations representing an aggregate measure of dynamic tissue damage and reorganization. Prominent DTI alterations of were observed for both the immediate and acute intervals after injury and associated with neurodegeneration and inflammation. In the chronic period, diffusion tensor orientation in the hilus of the dentate gyrus became prominently abnormal and was identified as a reliable structural biomarker for mossy fiber sprouting after CCI in rats, suggesting potential application as a biomarker to follow secondary progression in experimental and human TBI.

Multiparametric Microstructural MRI and Machine Learning Classification Yields High Diagnostic Accuracy in Amyotrophic Lateral Sclerosis: Proof of Concept.

The potential of multiparametric quantitative neuroimaging has been extensively discussed as a diagnostic tool in amyotrophic lateral sclerosis (ALS). In the past, the integration of multimodal, quantitative data into a useful diagnostic classifier was a major challenge. With recent advances in the field, machine learning in a data driven approach is a potential solution: neuroimaging biomarkers in ALS are mainly observed in the cerebral microstructure, with diffusion tensor imaging (DTI) and texture analysis as promising approaches. We set out to combine these neuroimaging markers as age-corrected features in a machine learning model with a cohort of 502 subjects, divided into 404 patients with ALS and 98 healthy controls. We calculated a linear support vector classifier (SVC) which is a very robust model and then verified the results with a multilayer perceptron (MLP)/neural network. Both classifiers were able to separate ALS patients from controls with receiver operating characteristic (ROC) curves showing an area under the curve (AUC) of 0.87–0.88 (“good”) for the SVC and 0.88–0.91 (“good” to “excellent”) for the MLP. Among the coefficients of the SVC, texture data contributed the most to a correct classification. We consider these results as a proof of concept that demonstrated the power of machine learning in the application of multiparametric quantitative neuroimaging data to ALS.

Abstract 14024: High-Field MRI Advanced Neuroimaging Characterization of Cerebrovascular Damage in a Mouse Model of Hypertension-Induced Cognitive Impairment

Introduction: Hypertension in one of the main risk factors for vascular cognitive impairment (VCI) and neurodegenerative pathologies as Alzheimer’s Disease (AD). To identify the underlying mechanisms it is important to use experimental models that present the pathophysiological characteristics of AD and VCI, hence allowing the investigation of molecular processes not explorable in humans. To ease the translational potential of these findings it is fundamental to characterize the brain damage with techniques easily applicable to the cognitive-declining patient, like MRI. Methods: Transverse aortic constriction (TAC) was performed in C57Bl/6J mice to induce severe hypertension to the cerebral vasculature and long term VCI. The cognitive performance at the Morris Water Maze (MWM) and Novel Object Recognition (NOR), the cerebrovascular injury by macro and microstructural MRI and cerebral blood flow (CBF) were analyzed. T2w volumetric images, diffusion tensor imaging, CBF sequences were performed on a small-animal dedicated 7 Tesla MRI. Results: TAC-hypertensive mice displayed significantly reduced learning capabilities, evidenced in the acquisition phase of MWM, and a marked impairment in spatial and short-term memory shown by probe trial in MWM and NOR test. At the structural MRI, TAC mice showed white matter microstructural degradation in the Fimbria, evidenced by a reduction of Fractional Anisotropy (SHAM vs TAC: 0.52±0.01 vs 0.44±0.02, p=0.047), coupled with a hypothalamic swelling (Right: SHAM vs TAC: 7.14±0.09 vs 7.50±0.11mm 3 , p=0.035; Left: SHAM vs TAC: 7.18±0.20 vs 7.91±0.17mm 3 , p=0.019). Hemodynamic alterations resulted in reduced cortical and hypothalamic CBF (Cortex: SHAM vs TAC: 96.6±3.4 vs 77.1±6.8 mL/100mg/min, p=0.046; Hypothalamus: SHAM vs TAC: 140±6 vs 122±4 mL/100mg/min, p=0.025). Furthermore the histological analysis evidenced a capillary rarefaction and reduced capillary-pericyte coverage in the prefrontal cortex, suggestive of a severe impact of the elevated blood pressure on the brain vasculature. Conclusions: In conclusion we have developed a mouse model of hypertension that reproduces typical tracts of the human pathology and a pipeline of analysis that will ease translate findings from bench to bedside.

Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder.

Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.

MRI-derived g-ratio and lesion severity in newly diagnosed multiple sclerosis.

Myelin loss is associated with axonal damage in established multiple sclerosis. This relationship is challenging to study in vivo in early disease. Here, we ask whether myelin loss is associated with axonal damage at diagnosis by combining non-invasive neuroimaging and blood biomarkers. We performed quantitative microstructural MRI and single-molecule ELISA plasma neurofilament measurement in 73 patients with newly diagnosed, immunotherapy naïve relapsing–remitting multiple sclerosis. Myelin integrity was evaluated using aggregate g-ratios, derived from magnetization transfer saturation and neurite orientation dispersion and density imaging diffusion data. We found significantly higher g-ratios within cerebral white matter lesions (suggesting myelin loss) compared with normal-appearing white matter (0.61 versus 0.57, difference 0.036, 95% CI: 0.029–0.043, P < 0.001). Lesion volume (Spearman’s rho rs= 0.38, P < 0.001) and g-ratio (rs= 0.24, P < 0.05) correlated independently with plasma neurofilament. In patients with substantial lesion load (n = 38), those with higher g-ratio (defined as greater than median) were more likely to have abnormally elevated plasma neurofilament than those with normal g-ratio (defined as less than median) [11/23 (48%) versus 2/15 (13%), P < 0.05]. These data suggest that, even at multiple sclerosis diagnosis, reduced myelin integrity is associated with axonal damage. MRI-derived g-ratio may provide useful additional information regarding lesion severity and help to identify individuals with a high degree of axonal damage at disease onset.

Mapping the human lateral geniculate nucleus and its cytoarchitectonic subdivisions using quantitative MRI

The human lateral geniculate nucleus (LGN) of the visual thalamus is a key subcortical processing site for visual information analysis. Due to its small size and deep location within the brain, a non-invasive characterization of the LGN and its microstructurally distinct magnocellular (M) and parvocellular (P) subdivisions in humans is challenging. Here, we investigated whether structural quantitative MRI (qMRI) methods that are sensitive to underlying microstructural tissue features enable MR-based mapping of human LGN M and P subdivisions. We employed high-resolution 7 Tesla in-vivo qMRI in N = 27 participants and ultra-high resolution 7 Tesla qMRI of a post-mortem human LGN specimen. We found that a quantitative assessment of the LGN and its subdivisions is possible based on microstructure-informed qMRI contrast alone. In both the in-vivo and post-mortem qMRI data, we identified two components of shorter and longer longitudinal relaxation time (T1) within the LGN that coincided with the known anatomical locations of a dorsal P and a ventral M subdivision, respectively. Through ground-truth histological validation, we further showed that the microstructural MRI contrast within the LGN pertains to cyto- and myeloarchitectonic tissue differences between its subdivisions. These differences were based on cell and myelin density, but not on iron content. Our qMRI-based mapping strategy paves the way for an in-depth understanding of LGN function and microstructure in humans. It further enables investigations into the selective contributions of LGN subdivisions to human behavior in health and disease.