Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease.

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aß-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aß-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

Leriglitazone halts disease progression in adult patients with early cerebral adrenoleukodystrophy.

Cerebral adrenoleukodystrophy (CALD) is an X-linked rapidly progressive demyelinating disease leading to death usually within a few years. The standard of care is haematopoietic stem cell transplantation (HSCT), but many men are not eligible due to age, absence of a matched donor or lesions of the corticospinal tracts (CST). Based on the ADVANCE study showing that leriglitazone decreases the occurrence of CALD, we treated 13 adult CALD patients (19-67 years of age) either not eligible for HSCT (n = 8) or awaiting HSCT (n = 5). Patients were monitored every 3 months with standardized neurological scores, plasma biomarkers and brain MRI comprising lesion volumetrics and diffusion tensor imaging. The disease stabilized clinically and radiologically in 10 patients with up to 2 years of follow-up. Five patients presented with gadolinium enhancing CST lesions that all turned gadolinium negative and, remarkably, regressed in four patients. Plasma neurofilament light chain levels stabilized in all 10 patients and correlated with lesion load. The two patients who continued to deteriorate were over 60 years of age with prominent cognitive impairment. One patient died rapidly from coronavirus disease 2019. These results suggest that leriglitazone can arrest disease progression in adults with early-stage CALD and may be an alternative treatment to HSCT.

White matter tracts and executive functions: a review of causal and correlation evidence.

Executive functions are high-level cognitive processes involving abilities such as working memory/updating, set-shifting and inhibition. These complex cognitive functions are enabled by interactions among widely distributed cognitive networks, supported by white matter tracts. Executive impairment is frequent in neurological conditions affecting white matter; however, whether specific tracts are crucial for normal executive functions is unclear. We review causal and correlation evidence from studies that used direct electrical stimulation during awake surgery for gliomas, voxel-based and tract-based lesion-symptom mapping, and diffusion tensor imaging to explore associations between the integrity of white matter tracts and executive functions in healthy and impaired adults. The corpus callosum was consistently associated with all executive processes, notably its anterior segments. Both causal and correlation evidence showed prominent support of the superior longitudinal fasciculus to executive functions, notably to working memory. More specifically, strong evidence suggested that the second branch of the superior longitudinal fasciculus is crucial for all executive functions, especially for flexibility. Global results showed left lateralization for verbal tasks and right lateralization for executive tasks with visual demands. The frontal aslant tract potentially supports executive functions, however, additional evidence is needed to clarify whether its involvement in executive tasks goes beyond the control of language. Converging evidence indicates that a right-lateralized network of tracts connecting cortical and subcortical grey matter regions supports the performance of tasks assessing response inhibition, some suggesting a role for the right anterior thalamic radiation. Finally, correlation evidence suggests a role for the cingulum bundle in executive functions, especially in tasks assessing inhibition. We discuss these findings in light of current knowledge about the functional role of these tracts, descriptions of the brain networks supporting executive functions and clinical implications for individuals with brain tumours.

Thalamic connectivity topography in newborns with spina bifida: association with neurological functional level but not developmental outcome at 2 years.

Spina bifida affects spinal cord and cerebral development, leading to motor and cognitive delay. We investigated whether there are associations between thalamocortical connectivity topography, neurological function, and developmental outcomes in open spina bifida. Diffusion tensor MRI was used to assess thalamocortical connectivity in 44 newborns with open spina bifida who underwent prenatal surgical repair. We quantified the volume of clusters formed based on the strongest probabilistic connectivity to the frontal, parietal, and temporal cortex. Developmental outcomes were assessed using the Bayley III Scales, while the functional level of the lesion was assessed by neurological examination at 2 years of age. Higher functional level was associated with smaller thalamo-parietal, while lower functional level was associated with smaller thalamo-temporal connectivity clusters (Bonferroni-corrected P < 0.05). Lower functional levels were associated with weaker thalamic temporal connectivity, particularly in the ventrolateral and ventral anterior nuclei. No associations were found between thalamocortical connectivity and developmental outcomes. Our findings suggest that altered thalamocortical circuitry development in open spina bifida may contribute to impaired lower extremity function, impacting motor function and independent ambulation. We hypothesize that the neurologic function might not merely be caused by the spinal cord lesion, but further impacted by the disruption of cerebral neuronal circuitry.

Characterizing microstructural development in the fetal brain using diffusion MRI from 23 to 36 weeks of gestation.

We utilized motion-corrected diffusion tensor imaging (DTI) to evaluate microstructural changes in healthy fetal brains during the late second and third trimesters. Data were derived from fetal magnetic resonance imaging scans conducted as part of a prospective study spanning from 2013 March to 2019 May. The study included 44 fetuses between the gestational ages (GAs) of 23 and 36 weeks. We reconstructed fetal brain DTI using a motion-tracked slice-to-volume registration framework. Images were segmented into 14 regions of interest (ROIs) through label propagation using a fetal DTI atlas, with expert refinement. Statistical analysis involved assessing changes in fractional anisotropy (FA) and mean diffusivity (MD) throughout gestation using mixed-effects models, and identifying points of change in trajectory for ROIs with nonlinear trends. Results showed significant GA-related changes in FA and MD in all ROIs except in the thalamus' FA and corpus callosum's MD. Hemispheric asymmetries were found in the FA of the periventricular white matter (pvWM), intermediate zone, and subplate and in the MD of the ganglionic eminence and pvWM. This study provides valuable insight into the normal patterns of development of MD and FA in the fetal brain. These changes are closely linked with cytoarchitectonic changes and display indications of early functional specialization.

Effects of multiple anesthetic exposures on rhesus macaque brain development: a longitudinal structural MRI analysis.

Concerns about the potential neurotoxic effects of anesthetics on developing brain exist. When making clinical decisions, the timing and dosage of anesthetic exposure are critical factors to consider due to their associated risks. In our study, we investigated the impact of repeated anesthetic exposures on the brain development trajectory of a cohort of rhesus monkeys (n = 26) over their first 2 yr of life, utilizing longitudinal magnetic resonance imaging data. We hypothesized that early or high-dose anesthesia exposure could negatively influence structural brain development. By employing the generalized additive mixed model, we traced the longitudinal trajectories of brain volume, cortical thickness, and white matter integrity. The interaction analysis revealed that age and cumulative anesthetic dose were variably linked to white matter integrity but not to morphometric measures. Early high-dose exposure was associated with increased mean, axial, and radial diffusivities across all white matter regions, compared to late-low-dose exposure. Our findings indicate that early or high-dose anesthesia exposure during infancy disrupts structural brain development in rhesus monkeys. Consequently, the timing of elective surgeries and procedures that require anesthesia for children and pregnant women should be strategically planned to account for the cumulative dose of volatile anesthetics, aiming to minimize the potential risks to brain development.

Glymphatic dysfunction mediates the influence of choroid plexus enlargement on information processing speed in patients with white matter hyperintensities.

Glymphatic dysfunction has been correlated with cognitive decline, with a higher choroid plexus volume (CPV) being linked to a slower glymphatic clearance rate. Nevertheless, the interplay between CPV, glymphatic function, and cognitive impairment in white matter hyperintensities (WMHs) has not yet been investigated. In this study, we performed neuropsychological assessment, T1-weighted three-dimensional (3D-T1) images, and diffusion tensor imaging (DTI) in a cohort of 206 WMHs subjects and 43 healthy controls (HCs) to further explore the relationship. The DTI analysis along the perivascular space (DTI-ALPS) index, as a measure of glymphatic function, was calculated based on DTI. Severe WMHs performed significantly worse in information processing speed (IPS) than other three groups, as well as in executive function than HCs and mild WMHs. Additionally, severe WMHs demonstrated lower DTI-ALPS index and higher CPV than HCs and mild WMHs. Moderate WMHs displayed higher CPV than HCs and mild WMHs. Mini-Mental State Examination, IPS, and executive function correlated negatively with CPV but positively with DTI-ALPS index in WMHs patients. Glymphatic function partially mediated the association between CPV and IPS, indicating a potential mechanism for WMHs-related cognitive impairment. CPV may act as a valuable prognostic marker and glymphatic system as a promising therapeutic target for WMHs-related cognitive impairment.

White matter microstructure and functional connectivity in the brains of infants with Turner syndrome.

Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.

Alterations in white matter fiber tracts and their correlation with flying cadet behavior.

An increasing number of studies have shown that flight training alters the human brain structure; however, most studies have focused on gray matter, and the exploration of white matter structure has been largely neglected. This study aimed to investigate the changes in white matter structure induced by flight training and estimate the correlation between such changes and psychomotor and flight performance. Diffusion tensor imaging data were obtained from 25 flying cadets and 24 general college students. Data were collected in 2019 and 2022 and analyzed using automated fiber quantification. This study found no significant changes in the flight group in 2019. However, in 2022, the flight group exhibited significant alterations in the diffusion tensor imaging of the right anterior thalamic radiation, left cingulum cingulate, bilateral superior longitudinal fasciculus, and left arcuate fasciculus. These changes occurred within local nodes of the fiber tracts. In addition, we found that changes in fiber tracts in the 2022 flight group were correlated with the reaction time of the psychomotor test task and flight duration. These findings may help improve flight training programs and provide new ideas for the selection of excellent pilots.

White matter fiber integrity and structural brain network topology: implications for balance function in postischemic stroke patients.

Previous studies have suggested that ischemic stroke can result in white matter fiber injury and modifications in the structural brain network. However, the relationship with balance function scores remains insufficiently explored. Therefore, this study aims to explore the alterations in the microstructural properties of brain white matter and the topological characteristics of the structural brain network in postischemic stroke patients and their potential correlations with balance function. We enrolled 21 postischemic stroke patients and 21 age, sex, and education-matched healthy controls (HC). All participants underwent balance function assessment and brain diffusion tensor imaging. Tract-based spatial statistics (TBSS) were used to compare the fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of white matter fibers between the two groups. The white matter structural brain network was constructed based on the automated anatomical labeling atlas, and we conducted a graph theory-based analysis of its topological properties, including global network properties and local node properties. Additionally, the correlation between the significant structural differences and balance function score was analyzed. The TBSS results showed that in comparison to the HC, postischemic stroke patients exhibited extensive damage to their whole-brain white matter fiber tracts (P < 0.05). Graph theory analysis showed that in comparison to the HC, postischemic stroke patients exhibited statistically significant reductions in the values of global efficiency, local efficiency, and clustering coefficient, as well as an increase in characteristic path length (P < 0.05). In addition, the degree centrality and nodal efficiency of some nodes in postischemic stroke patients were significantly reduced (P < 0.05). The white matter fibers of the entire brain in postischemic stroke patients are extensively damaged, and the topological properties of the structural brain network are altered, which are closely related to balance function. This study is helpful in further understanding the neural mechanism of balance function after ischemic stroke from the white matter fiber and structural brain network topological properties.

Association between metabolic syndrome and white matter integrity in young and mid-age post-9/11 adult Veterans.

Metabolic syndrome has been associated with reduced brain white matter integrity in older individuals. However, less is known about how metabolic syndrome might impact white matter integrity in younger populations. This study examined metabolic syndrome-related global and regional white matter integrity differences in a sample of 537 post-9/11 Veterans. Metabolic syndrome was defined as ≥3 factors of: increased waist circumference, hypertriglyceridemia, low high-density lipoprotein cholesterol, hypertension, and high fasting glucose. T1 and diffusion weighted 3 T MRI scans were processed using the FreeSurfer image analysis suite and FSL Diffusion Toolbox. Atlas-based regions of interest were determined from a combination of the Johns Hopkins University atlas and a Tract-Based Spatial Statistics-based FreeSurfer WMPARC white matter skeleton atlas. Analyses revealed individuals with metabolic syndrome (n = 132) had significantly lower global fractional anisotropy than those without metabolic syndrome (n = 405), and lower high-density lipoprotein cholesterol levels was the only metabolic syndrome factor significantly related to lower global fractional anisotropy levels. Lobe-specific analyses revealed individuals with metabolic syndrome had decreased fractional anisotropy in frontal white matter regions compared with those without metabolic syndrome. These findings indicate metabolic syndrome is prevalent in this sample of younger Veterans and is related to reduced frontal white matter integrity. Early intervention for metabolic syndrome may help alleviate adverse metabolic syndrome-related brain and cognitive effects with age.

Functional and structural abnormalities of the speech disorders: a multimodal activation likelihood estimation meta-analysis.

Speech disorders are associated with different degrees of functional and structural abnormalities. However, the abnormalities associated with specific disorders, and the common abnormalities shown by all disorders, remain unclear. Herein, a meta-analysis was conducted to integrate the results of 70 studies that compared 1843 speech disorder patients (dysarthria, dysphonia, stuttering, and aphasia) to 1950 healthy controls in terms of brain activity, functional connectivity, gray matter, and white matter fractional anisotropy. The analysis revealed that compared to controls, the dysarthria group showed higher activity in the left superior temporal gyrus and lower activity in the left postcentral gyrus. The dysphonia group had higher activity in the right precentral and postcentral gyrus. The stuttering group had higher activity in the right inferior frontal gyrus and lower activity in the left inferior frontal gyrus. The aphasia group showed lower activity in the bilateral anterior cingulate gyrus and left superior frontal gyrus. Across the four disorders, there were concurrent lower activity, gray matter, and fractional anisotropy in motor and auditory cortices, and stronger connectivity between the default mode network and frontoparietal network. These findings enhance our understanding of the neural basis of speech disorders, potentially aiding clinical diagnosis and intervention.

Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms.

White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.

A Cellular Ground Truth to Develop MRI Signatures in Glioma Models by Correlative Light Sheet Microscopy and Atlas-Based Coregistration.

Glioblastoma is the most common malignant primary brain tumor with poor overall survival. Magnetic resonance imaging (MRI) is the main imaging modality for glioblastoma but has inherent shortcomings. The molecular and cellular basis of MR signals is incompletely understood. We established a ground truth-based image analysis platform to coregister MRI and light sheet microscopy (LSM) data to each other and to an anatomic reference atlas for quantification of 20 predefined anatomic subregions. Our pipeline also includes a segmentation and quantification approach for single myeloid cells in entire LSM datasets. This method was applied to three preclinical glioma models in male and female mice (GL261, U87MG, and S24), which exhibit different key features of the human glioma. Multiparametric MR data including T2-weighted sequences, diffusion tensor imaging, T2 and T2* relaxometry were acquired. Following tissue clearing, LSM focused on the analysis of tumor cell density, microvasculature, and innate immune cell infiltration. Correlated analysis revealed differences in quantitative MRI metrics between the tumor-bearing and the contralateral hemisphere. LSM identified tumor subregions that differed in their MRI characteristics, indicating tumor heterogeneity. Interestingly, MRI signatures, defined as unique combinations of different MRI parameters, differed greatly between the models. The direct correlation of MRI and LSM allows an in-depth characterization of preclinical glioma and can be used to decipher the structural, cellular, and, likely, molecular basis of tumoral MRI biomarkers. Our approach may be applied in other preclinical brain tumor or neurologic disease models, and the derived MRI signatures could ultimately inform image interpretation in a clinical setting.SIGNIFICANCE STATEMENT We established a histologic ground truth-based approach for MR image analyses and tested this method in three preclinical glioma models exhibiting different features of glioblastoma. Coregistration of light sheet microscopy to MRI allowed for an evaluation of quantitative MRI data in histologically distinct tumor subregions. Coregistration to a mouse brain atlas enabled a regional comparison of MRI parameters with a histologically informed interpretation of the results. Our approach is transferable to other preclinical models of brain tumors and further neurologic disorders. The method can be used to decipher the structural, cellular, and molecular basis of MRI signal characteristics. Ultimately, information derived from such analyses could strengthen the neuroradiological evaluation of glioblastoma as they enhance the interpretation of MRI data.

A diminished sciatic nerve structural integrity is associated with distinct peripheral sensory phenotypes in individuals with type 2 diabetes.

AIMS/HYPOTHESIS: Quantitative sensory testing (QST) allows the identification of individuals with rapid progression of diabetic sensorimotor polyneuropathy (DSPN) based on certain sensory phenotypes. Hence, the aim of this study was to investigate the relationship of these phenotypes with the structural integrity of the sciatic nerve among individuals with type 2 diabetes. METHODS: Seventy-six individuals with type 2 diabetes took part in this cross-sectional study and underwent QST of the right foot and high-resolution magnetic resonance neurography including diffusion tensor imaging of the right distal sciatic nerve to determine the sciatic nerve fractional anisotropy (FA) and cross-sectional area (CSA), both of which serve as markers of structural integrity of peripheral nerves. Participants were then assigned to four sensory phenotypes (participants with type 2 diabetes and healthy sensory profile [HSP], thermal hyperalgesia [TH], mechanical hyperalgesia [MH], sensory loss [SL]) by a standardised sorting algorithm based on QST. RESULTS: Objective neurological deficits showed a gradual increase across HSP, TH, MH and SL groups, being higher in MH compared with HSP and in SL compared with HSP and TH. The number of participants categorised as HSP, TH, MH and SL was 16, 24, 17 and 19, respectively. There was a gradual decrease of the sciatic nerve's FA (HSP 0.444, TH 0.437, MH 0.395, SL 0.382; p=0.005) and increase of CSA (HSP 21.7, TH 21.5, MH 25.9, SL 25.8 mm2; p=0.011) across the four phenotypes. Further, MH and SL were associated with a lower sciatic FA (MH unstandardised regression coefficient [B]=-0.048 [95% CI -0.091, -0.006], p=0.027; SL B=-0.062 [95% CI -0.103, -0.020], p=0.004) and CSA (MH ß=4.3 [95% CI 0.5, 8.0], p=0.028; SL B=4.0 [95% CI 0.4, 7.7], p=0.032) in a multivariable regression analysis. The sciatic FA correlated negatively with the sciatic CSA (r=-0.35, p=0.002) and markers of microvascular damage (high-sensitivity troponin T, urine albumin/creatinine ratio). CONCLUSIONS/INTERPRETATION: The most severe sensory phenotypes of DSPN (MH and SL) showed diminishing sciatic nerve structural integrity indexed by lower FA, likely representing progressive axonal loss, as well as increasing CSA of the sciatic nerve, which cannot be detected in individuals with TH. Individuals with type 2 diabetes may experience a predefined cascade of nerve fibre damage in the course of the disease, from healthy to TH, to MH and finally SL, while structural changes in the proximal nerve seem to precede the sensory loss of peripheral nerves and indicate potential targets for the prevention of end-stage DSPN. TRIAL REGISTRATION: ClinicalTrials.gov NCT03022721.

Microstructural and Microvascular Phenotype of Sarcomere Mutation Carriers and Overt Hypertrophic Cardiomyopathy.

BACKGROUND: In hypertrophic cardiomyopathy (HCM), myocyte disarray and microvascular disease (MVD) have been implicated in adverse events, and recent evidence suggests that these may occur early. As novel therapy provides promise for disease modification, detection of phenotype development is an emerging priority. To evaluate their utility as early and disease-specific biomarkers, we measured myocardial microstructure and MVD in 3 HCM groups-overt, either genotype-positive (G+LVH+) or genotype-negative (G-LVH+), and subclinical (G+LVH-) HCM-exploring relationships with electrical changes and genetic substrate. METHODS: This was a multicenter collaboration to study 206 subjects: 101 patients with overt HCM (51 G+LVH+ and 50 G-LVH+), 77 patients with G+LVH-, and 28 matched healthy volunteers. All underwent 12-lead ECG, quantitative perfusion cardiac magnetic resonance imaging (measuring myocardial blood flow, myocardial perfusion reserve, and perfusion defects), and cardiac diffusion tensor imaging measuring fractional anisotropy (lower values expected with more disarray), mean diffusivity (reflecting myocyte packing/interstitial expansion), and second eigenvector angle (measuring sheetlet orientation). RESULTS: Compared with healthy volunteers, patients with overt HCM had evidence of altered microstructure (lower fractional anisotropy, higher mean diffusivity, and higher second eigenvector angle; all P<0.001) and MVD (lower stress myocardial blood flow and myocardial perfusion reserve; both P<0.001). Patients with G-LVH+ were similar to those with G+LVH+ but had elevated second eigenvector angle (P<0.001 after adjustment for left ventricular hypertrophy and fibrosis). In overt disease, perfusion defects were found in all G+ but not all G- patients (100% [51/51] versus 82% [41/50]; P=0.001). Patients with G+LVH- compared with healthy volunteers similarly had altered microstructure, although to a lesser extent (all diffusion tensor imaging parameters; P<0.001), and MVD (reduced stress myocardial blood flow [P=0.015] with perfusion defects in 28% versus 0 healthy volunteers [P=0.002]). Disarray and MVD were independently associated with pathological electrocardiographic abnormalities in both overt and subclinical disease after adjustment for fibrosis and left ventricular hypertrophy (overt: fractional anisotropy: odds ratio for an abnormal ECG, 3.3, P=0.01; stress myocardial blood flow: odds ratio, 2.8, P=0.015; subclinical: fractional anisotropy odds ratio, 4.0, P=0.001; myocardial perfusion reserve odds ratio, 2.2, P=0.049). CONCLUSIONS: Microstructural alteration and MVD occur in overt HCM and are different in G+ and G- patients. Both also occur in the absence of hypertrophy in sarcomeric mutation carriers, in whom changes are associated with electrocardiographic abnormalities. Measurable changes in myocardial microstructure and microvascular function are early-phenotype biomarkers in the emerging era of disease-modifying therapy.

Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning-Derived Diffusion Scalar Maps From T1.

BACKGROUND: Cerebral small vessel disease is the most common pathology underlying vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to white matter damage and better predicts dementia risk than conventional magnetic resonance imaging sequences, such as T1 and fluid attenuation inversion recovery, but diffusion tensor imaging takes longer to acquire and is not routinely available in clinical practice. As diffusion tensor imaging-derived scalar maps-fractional anisotropy (FA) and mean diffusivity (MD)-are frequently used in clinical settings, one solution is to synthesize FA/MD from T1 images. METHODS: We developed a deep learning model to synthesize FA/MD from T1. The training data set consisted of 4998 participants with the highest white matter hyperintensity volumes in the UK Biobank. Four external validations data sets with small vessel disease were included: SCANS (St George's Cognition and Neuroimaging in Stroke; n=120), RUN DMC (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort; n=502), PRESERVE (Blood Pressure in Established Cerebral Small Vessel Disease; n=105), and NETWORKS (n=26), along with 1000 normal controls from the UK Biobank. RESULTS: The synthetic maps resembled ground-truth maps (structural similarity index >0.89 for MD maps and >0.80 for FA maps across all external validation data sets except for SCANS). The prediction accuracy of dementia using whole-brain median MD from the synthetic maps is comparable to the ground truth (SCANS ground-truth c-index, 0.822 and synthetic, 0.821; RUN DMC ground truth, 0.816 and synthetic, 0.812) and better than white matter hyperintensity volume (SCANS, 0.534; RUN DMC, 0.710). CONCLUSIONS: We have developed a fast and generalizable method to synthesize FA/MD maps from T1 to improve the prediction accuracy of dementia in small vessel disease when diffusion tensor imaging data have not been acquired.

Differences in brain structure and cognitive performance between patients with long-COVID and those with normal recovery.

BACKGROUND: The pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing. METHODS: Individuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons. RESULTS: There were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all ß<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05). CONCLUSIONS: Differences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found.

Diffusion tensor imaging metrics as natural markers of multiple sclerosis-induced brain disorders with a low Expanded Disability Status Scale score.

Non-invasive and effective differentiation along with determining the degree of deviations compared to the healthy cohort is important in the case of various brain disorders, including multiple sclerosis (MS). Evaluation of the effectiveness of diffusion tensor metrics (DTM) in 3T DTI for recording MS-related deviations was performed using a time-acceptable MRI protocol with unique comprehensive detection of systematic errors related to spatial heterogeneity of magnetic field gradients. In a clinical study, DTMs were acquired in segmented regions of interest (ROIs) for 50 randomly selected healthy controls (HC) and 50 multiple sclerosis patients. Identical phantom imaging was performed for each clinical measurement to estimate and remove the influence of systematic errors using the b-matrix spatial distribution in the DTI (BSD-DTI) technique. In the absence of statistically significant differences due to age in healthy volunteers and patients with multiple sclerosis, the existence of significant differences between groups was proven using DTM. Moreover, a statistically significant impact of spatial systematic errors occurs for all ROIs and DTMs in the phantom and for approximately 90 % in the HC and MS groups. In the case of a single patient measurement, this appears for all the examined ROIs and DTMs. The obtained DTMs effectively discriminate healthy volunteers from multiple sclerosis patients with a low mean score on the Expanded Disability Status Scale. The magnitude of the group differences is typically significant, with an effect size of approximately 0.5, and similar in both the standard approach and after elimination of systematic errors. Differences were also observed between metrics obtained using these two approaches. Despite a small alterations in mean DTMs values for groups and ROIs (1-3 %), these differences were characterized by a huge effect (effect size ∼0.8 or more). These findings indicate the importance of determining the spatial distribution of systematic errors specific to each MR scanner and DTI acquisition protocol in order to assess their impact on DTM in the ROIs examined. This is crucial to establish accurate DTM values for both individual patients and mean values for a healthy population as a reference. This approach allows for an initial reliable diagnosis based on DTI metrics.

Connectome alterations following perinatal deafness in the cat.

Following sensory deprivation, areas and networks in the brain may adapt and reorganize to compensate for the loss of input. These adaptations are manifestations of compensatory crossmodal plasticity, which has been documented in both human and animal models of deafness-including the domestic cat. Although there are abundant examples of structural plasticity in deaf felines from retrograde tracer-based studies, there is a lack of diffusion-based knowledge involving this model compared to the current breadth of human research. The purpose of this study was to explore white matter structural adaptations in the perinatally-deafened cat via tractography, increasing the methodological overlap between species. Plasticity was examined by identifying unique group connections and assessing altered connectional strength throughout the entirety of the brain. Results revealed a largely preserved connectome containing a limited number of group-specific or altered connections focused within and between sensory networks, which is generally corroborated by deaf feline anatomical tracer literature. Furthermore, five hubs of cortical plasticity and altered communication following perinatal deafness were observed. The limited differences found in the present study suggest that deafness-induced crossmodal plasticity is largely built upon intrinsic structural connections, with limited remodeling of underlying white matter.