White Matter Brain Regions Research Articles

Neurite Orientation Dispersion and Density Imaging (NODDI) reveals white matter microstructural changes in Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) patients with cognitive impairment

PurposeThis study aimed to assess changes in white matter microstructure among patients undergoing obstructive sleep apnea hypopnea syndrome (OSAHS) complicated by cognitive impairment through neurite orientation dispersion and density imaging (NODDI), and evaluate the relationship to cognitive impairment as well as the diagnostic performance in early intervention. MethodsTotally 23 OSAHS patients, 43 OSAHS patients complicated by cognitive impairment, and 15 healthy controls were enrolled in OSA, OSACI and HC groups of this work. NODDI toolbox and FMRIB's Software Library (FSL) were used to calculate neurite density index (NDI), Fractional anisotropy (FA), volume fraction of isotropic water molecules (Viso), and orientation dispersion index (ODI). Tract-based spatial statistics (TBSS) were carried out to examine the above metrics with one-way ANOVA. This study explored the correlations of the above metrics with mini-mental state examination (MMSE), and montreal cognitive assessment (MoCA) scores. Furthermore, receiver operating characteristic (ROC) curves were plotted. Meanwhile, area under curve (AUC) values were calculated to evaluate the diagnostic performance of the above metrics. ResultsNDI, ODI, Viso, and FA were significantly different among different brain white matter regions, among which, difference in NDI showed the greatest statistical significance. In comparison with HC group, OSA group had reduced NDI and ODI, whereas elevated Viso levels. Conversely, compared to the OSA group, the OSACI group displayed a slight increase in NDI and ODI values, which remained lower than HC group, viso values continued to rise. Post-hoc analysis highlighted significant differences in these metrics, except for FA, which showed no notable changes or correlations with neuropsychological tests. ROC analysis confirmed the diagnostic efficacy of NDI, ODI, and Viso with AUCs of 0.6908, 0.6626, and 0.6363, respectively, whereas FA's AUC of 0.5042, indicating insufficient diagnostic efficacy. ConclusionsThis study confirmed that NODDI effectively reveals microstructural changes in white matter of OSAHS patients with cognitive impairment, providing neuroimaging evidence for early clinical diagnosis and intervention.

A Diffusion Tensor Imaging White Matter Atlas of the Domestic Canine Brain

Abstract There is increasing reliance on magnetic resonance imaging (MRI) techniques in both research and clinical settings. However, few standardized methods exist to permit comparative studies of brain pathology and function. To help facilitate these studies, we have created a detailed, MRI-based white matter atlas of the canine brain using diffusion tensor imaging. This technique, which relies on the movement properties of water, permits the creation of a three-dimensional diffusivity map of white matter brain regions that can be used to predict major axonal tracts. To generate an atlas of white matter tracts, thirty neurologically and clinically normal dogs underwent MRI imaging under anesthesia. High-resolution, three-dimensional T1-weighted sequences were collected and averaged to create a population average template. Diffusion weighted imaging sequences were collected and used to generate diffusivity maps, which were then registered to the T1-weighted template. Using these diffusivity maps, individual white matter tracts—including association, projection, commissural, brainstem, olfactory and cerebellar tracts—were identified with reference to previous canine brain atlas sources. To enable the use of this atlas, we created downloadable overlay files for each white matter tract identified using manual segmentation software. In addition, using diffusion tensor imaging tractography, we created tract files to delineate major projection pathways. This comprehensive white matter atlas serves as a standard reference to aid in the interpretation of quantitative changes in brain structure and function in clinical and research settings.

Effects of Aging, Fitness, and Cerebrovascular Status on White Matter Microstructural Health.

White matter (WM) microstructural health declines with increasing age, with evidence suggesting that improved cardiorespiratory fitness (CRF) may mitigate this decline. Specifically, higher fit older adults tend to show preserved WM microstructural integrity compared to their lower fit counterparts. However, the extent to which fitness and aging independently impact WM integrity across the adult lifespan is still an open question, as is the extent to which cerebrovascular health mediates these relationships. In a large sample (N = 125, aged 25-72), we assessed the impact of age and fitness on fractional anisotropy (FA, derived using diffusion weighted imaging, DWI) and probed the mediating role of cerebrovascular health (derived using diffuse optical tomography of the cerebral arterial pulse, pulse-DOT) in these relationships. After orthogonalizing age and fitness and computing a PCA on whole brain WM regions, we found several WM regions impacted by age that were independent from the regions impacted by fitness (hindbrain areas, including brainstem and cerebellar tracts), whereas other areas showed interactive effects of age and fitness (midline areas, including fornix and corpus callosum). Critically, cerebrovascular health mediated both relationships suggesting that vascular health plays a linking role between age, fitness, and brain health. Secondarily, we assessed potential sex differences in these relationships and found that, although females and males generally showed the same age-related FA declines, males exhibited somewhat steeper declines than females. Together, these results suggest that age and fitness impact specific WM regions and highlight the mediating role of cerebrovascular health in maintaining WM health across adulthood.

Microstructural brain abnormalities and associated neurocognitive dysfunction in obstructive sleep apnea: a pilot study with diffusion kurtosis imaging.

To assess the possible brain abnormalities in adult patients with moderate and severe obstructive sleep apnea (OSA) using the mean kurtosis (MK) from diffusion kurtosis imaging (DKI) and analyze the correlation between MK and cognitive function. A total of 30 patients with moderate and severe OSA and 30 healthy controls (HCs) evaluated by the Montreal Cognitive Assessment (MoCA) scale were enrolled. All subjects underwent DKI and 3D T1-weighted imaging (T1WI) on a 3.0T MR scanner. The MK values of gray and white matter brain regions were compared. Partial correlation analysis was used to analyze the correlation between respiratory sleep parameters/cognitive score and MK values in different brain regions. Compared with the HCs, the MK of 20 brain regions (13 after false discovery rate (FDR) correction) and cognitive scores in the OSA group were significantly lower. In the OSA group, the apnea-hypopnea index (AHI) was negatively correlated with the MK in the white matter of the right occipital lobe; the LSpO2 was positively correlated with the MK in the bilateral parietal, precentral, and right postcentral cortex; the total score of MoCA scale was positively correlated with MK in the left hippocampus; the language function was positively correlated with MK in the white matter of left parietal lobe, and the delayed recall was positively correlated with the MK in right insula cortex and bilateral cingulate. After FDR correction, only the correlations of LSpO2 with right precentral gyrus cortex, and bilateral parietal cortex were significant. MK values of DKI imaging may provide valuable information in assessing the neurological impacts of obstructive sleep apnea.

Potential of focal cortical dysplasia in migraine pathogenesis.

Focal cortical dysplasias are abnormalities of the cerebral cortex associated with an elevated risk of neurological disturbances. Cortical spreading depolarization/depression is a correlate of migraine aura/headache and a trigger of migraine pain mechanisms. However, cortical spreading depolarization/depression is associated with cortical structural changes, which can be classified as transient focal cortical dysplasias. Migraine is reported to be associated with changes in various brain structures, including malformations and lesions in the cortex. Such malformations may be related to focal cortical dysplasias, which may play a role in migraine pathogenesis. Results obtained so far suggest that focal cortical dysplasias may belong to the causes and consequences of migraine. Certain focal cortical dysplasias may lower the threshold of cortical excitability and facilitate the action of migraine triggers. Migraine prevalence in epileptic patients is higher than in the general population, and focal cortical dysplasias are an established element of epilepsy pathogenesis. In this narrative/hypothesis review, we present mainly information on cortical structural changes in migraine, but studies on structural alterations in deep white matter and other brain regions are also presented. We develop the hypothesis that focal cortical dysplasias may be causally associated with migraine and link pathogeneses of migraine and epilepsy.

Sex-specific interactions between stress axis and redox balance are associated with internalizing symptoms and brain white matter microstructure in adolescents

Adolescence is marked by the maturation of systems involved in emotional regulation and by an increased risk for internalizing disorders (anxiety/depression), especially in females. Hypothalamic-pituitary-adrenal (HPA)-axis function and redox homeostasis (balance between reactive oxygen species and antioxidants) have both been associated with internalizing disorders and may represent critical factors for the development of brain networks of emotional regulation. However, sex-specific interactions between these factors and internalizing symptoms and their link with brain maturation remain unexplored. We investigated in a cohort of adolescents aged 13–15 from the general population (n = 69) whether sex-differences in internalizing symptoms were associated with the glutathione (GSH)-redox cycle homeostasis and HPA-axis function and if these parameters were associated with brain white matter microstructure development. Female adolescents displayed higher levels of internalizing symptoms, GSH-peroxidase (GPx) activity and cortisol/11-deoxycortisol ratio than males. There was a strong correlation between GPx and GSH-reductase (Gred) activities in females only. The cortisol/11-deoxycortisol ratio, related to the HPA-axis activity, was associated with internalizing symptoms in both sexes, whereas GPx activity was associated with internalizing symptoms in females specifically. The cortisol/11-deoxycortisol ratio mediated sex-differences in internalizing symptoms and the association between anxiety and GPx activity in females specifically. In females, GPx activity was positively associated with generalized fractional anisotropy in widespread white matter brain regions. We found that higher levels of internalizing symptoms in female adolescents than in males relate to sex-differences in HPA-axis function. In females, our results suggest an important interplay between HPA-axis function and GSH-homeostasis, a parameter strongly associated with brain white matter microstructure.

Neuroprotective effects of maternal melatonin administration in early-onset placental insufficiency and fetal growth restriction.

Early-onset fetal growth restriction (FGR) is associated with adverse outcomes. We hypothesised that maternal melatonin administration will improve fetal brain structure in FGR. Surgery was performed on twin-bearing ewes at 88 days (0.6 gestation), and FGR induced in one twin via single umbilical artery ligation. Melatonin was administered intravenously (6 mg/day) to a group of ewes commencing on day of surgery until 127 days (0.85 gestation), when the ewe/fetuses were euthanized, and fetal brains collected. Study groups were control (n = 5), FGR (n = 5), control+melatonin (control+MLT; n = 6) and FGR+melatonin (FGR + MLT; n = 6). Melatonin administration did not significantly alter fetal body or brain weights. Myelin (CNPase+) fibre density was reduced in FGR vs. control animals in most brain regions examined (p < 0.05) and melatonin treatment restored CNPase fibre density. Similar but less pronounced effect was seen with mature myelin (MBP+) staining. Significant differences in activated microglia (Iba-1) activity were seen between lamb groups (MLT mitigated FGR effect) in periventricular white matter, subventricular zone and external capsule (p < 0.05). Similar effects were seen in astrogliosis (GFAP) in intragyral white matter and cortex. Maternal melatonin administration in early onset FGR led to improved myelination of white matter brain regions, possibly mediated by decreased inflammation. Maternal melatonin administration might lead to neuroprotection in the growth-restricted fetus, possibly via dampening neuroinflammation and enhancing myelination. This preclinical study adds to the body of work on this topic, and informs clinical translation. Neuroprotection likely to improve long-term outcomes of this vulnerable infant group.

Genetic basis of anatomical asymmetry and aberrant dynamic functional networks in Alzheimer's disease.

Genetic associations with macroscopic brain networks can provide insights into healthy and aberrant cortical connectivity in disease. However, associations specific to dynamic functional connectivity in Alzheimer's disease are still largely unexplored. Understanding the association between gene expression in the brain and functional networks may provide useful information about the molecular processes underlying variations in impaired brain function. Given the potential of dynamic functional connectivity to uncover brain states associated with Alzheimer's disease, it is interesting to ask: How does gene expression associated with Alzheimer's disease map onto the dynamic functional brain connectivity? If genetic variants associated with neurodegenerative processes involved in Alzheimer's disease are to be correlated with brain function, it is essential to generate such a map. Here, we investigate how the relation between gene expression in the brain and dynamic functional connectivity arises from nodal interactions, quantified by their role in network centrality (i.e. the drivers of the metastability), and the principal component of genetic co-expression across the brain. Our analyses include genetic variations associated with Alzheimer's disease and also genetic variants expressed within the cholinergic brain pathways. Our findings show that contrasts in metastability of functional networks between Alzheimer's and healthy individuals can in part be explained by the two combinations of genetic co-variations in the brain with the confidence interval between 72% and 92%. The highly central nodes, driving the brain aberrant metastable dynamics in Alzheimer's disease, highly correlate with the magnitude of variations from two combinations of genes expressed in the brain. These nodes include mainly the white matter, parietal and occipital brain regions, each of which (or their combinations) are involved in impaired cognitive function in Alzheimer's disease. In addition, our results provide evidence of the role of genetic associations across brain regions in asymmetric changes in ageing. We validated our findings on the same cohort using alternative brain parcellation methods. This work demonstrates how genetic variations underpin aberrant dynamic functional connectivity in Alzheimer's disease.

White matter microstructural alterations in patients with neuropathic pain after spinal cord injury: a diffusion tensor imaging study.

Through contrastive analysis, we aimed to identify the white matter brain regions that show microstructural changes in patients with neuropathic pain (NP) after spinal cord injury (SCI). We categorized patients with SCI into NP (n = 30) and non-NP (n = 15) groups. We extracted diffusion tensor maps of fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. A randomization-based method in tract-based spatial statistics was used to perform voxel-wise group comparisons among the FA, MD, AD, and RD for nonparametric permutation tests. Atlas-based analysis located significantly different regions (p < 0.05) in the appointed brain atlas. Compared to the non-NP group, the NP group showed higher FA in the posterior body and splenium of the corpus callosum and higher AD in the corpus callosum, internal capsule, corona radiata, posterior thalamic radiation, sagittal stratum, external capsule, cingulum, fornix/stria terminalis, superior longitudinal fasciculus, and uncinate fasciculus. The results demonstrated that compared with the non-NP group, NP pathogenesis after SCI was potentially related to higher values in FA that are associated with microstructural changes in the posterior body and splenium of the corpus callosum, which could be regarded as central sensitization or network hyperexcitability.

A review of brain regions and associated post-concussion symptoms.

The human brain is an exceptionally complex organ that is comprised of billions of neurons. Therefore, when a traumatic event such as a concussion occurs, somatic, cognitive, behavioral, and sleep impairments are the common outcome. Each concussion is unique in the sense that the magnitude of biomechanical forces and the direction, rotation, and source of those forces are different for each concussive event. This helps to explain the unpredictable nature of post-concussion symptoms that can arise and resolve. The purpose of this narrative review is to connect the anatomical location, healthy function, and associated post-concussion symptoms of some major cerebral gray and white matter brain regions and the cerebellum. As a non-exhaustive description of post-concussion symptoms nor comprehensive inclusion of all brain regions, we have aimed to amalgamate the research performed for specific brain regions into a single article to clarify and enhance clinical and research concussion assessment. The current status of concussion diagnosis is highly subjective and primarily based on self-report of symptoms, so this review may be able to provide a connection between brain anatomy and the clinical presentation of concussions to enhance medical imaging assessments. By explaining anatomical relevance in terms of clinical concussion symptom presentation, an increased understanding of concussions may also be achieved to improve concussion recognition and diagnosis.

Hypertensive Adults Exhibit Lower Myelin Content: A Multicomponent Relaxometry and Diffusion Magnetic Resonance Imaging Study.

It is unknown whether hypertension plays any role in cerebral myelination. To fill this knowledge gap, we studied 90 cognitively unimpaired adults, age range 40 to 94 years, who are participants in the Baltimore Longitudinal Study of Aging and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing to look for potential associations between hypertension and cerebral myelin content across 14 white matter brain regions. Myelin content was probed using our advanced multicomponent magnetic resonance relaxometry method of myelin water fraction, a direct and specific magnetic resonance imaging measure of myelin content, and longitudinal and transverse relaxation rates (R1 and R2), 2 highly sensitive magnetic resonance imaging metrics of myelin content. We also applied diffusion tensor imaging magnetic resonance imaging to measure fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values, which are metrics of cerebral microstructural tissue integrity, to provide context with previous magnetic resonance imaging findings. After adjustment of age, sex, systolic blood pressure, smoking status, diabetes status, and cholesterol level, our results indicated that participants with hypertension exhibited lower myelin water fraction, fractional anisotropy, R1 and R2 values and higher mean diffusivity, radial diffusivity, and axial diffusivity values, indicating lower myelin content and higher impairment to the brain microstructure. These associations were significant across several white matter regions, particularly in the corpus callosum, fronto-occipital fasciculus, temporal lobes, internal capsules, and corona radiata. These original findings suggest a direct association between myelin content and hypertension and form the basis for further investigations including longitudinal assessments of this relationship.

Motion Robust MR Fingerprinting Scan to Image Neonates With Prenatal Opioid Exposure.

To explore whether MR fingerprinting (MRF) scans provide motion-robust and quantitative brain tissue measurements for non-sedated infants with prenatal opioid exposure (POE). Prospective. 13 infants with POE (3 male; 12 newborns (age 7-65 days) and 1 infant aged 9-months). 3T, 3D T1-weighted MPRAGE, 3D T2-weighted TSE and MRF sequences. The image quality of MRF and MRI was assessed in a fully crossed, multiple-reader, multiple-case study. Sixteen image quality features in three types-image artifacts, structure and myelination visualization-were ranked by four neuroradiologists (8, 7, 5, and 8 years of experience respectively), using a 3-point scale. MRF T1 and T2 values in 8 white matter brain regions were compared between babies younger than 1 month and babies between 1 and 2 months. Generalized estimating equations model to test the significance of differences of regional T1 and T2 values of babies under 1 month and those older. MRI and MRF image quality was assessed using Gwet's second order auto-correlation coefficient (AC2) with confidence levels. The Cochran-Mantel-Haenszel test was used to assess the difference in proportions between MRF and MRI for all features and stratified by the type of features. A P value <0.05 was considered statistically significant. The MRF of two infants were excluded in T1 and T2 value analysis due to severe motion artifact but were included in the image quality assessment. In infants under 1 month of age (N = 6), the T1 and T2 values were significantly higher compared to those between 1 and 2 months of age (N = 4). MRF images showed significantly higher image quality ratings in all three feature types compared to MRI images. MR Fingerprinting scans have potential to be a motion-robust and efficient method for nonsedated infants. 2 TECHNICAL EFFICACY STAGE: 1.

Lower Myelin Content Is Associated With Lower Gait Speed in Cognitively Unimpaired Adults.

Mounting evidence indicates that abnormal gait speed predicts the progression of neurodegenerative diseases, including Alzheimer's disease. Understanding the relationship between white matter integrity, especially myelination, and motor function is crucial to the diagnosis and treatment of neurodegenerative diseases. We recruited 118 cognitively unimpaired adults across an extended age range of 22-94 years to examine associations between rapid or usual gait speeds and cerebral myelin content. Using our advanced multicomponent magnetic resonance relaxometry method, we measured myelin water fraction (MWF), a direct measure of myelin content, as well as longitudinal and transverse relaxation rates (R1 and R2), sensitive but nonspecific magnetic resonance imaging measures of myelin content. After adjusting for covariates and excluding 22 data sets due to cognitive impairments or artifacts, our results indicate that participants with higher rapid gait speed exhibited higher MWF, R1, and R2 values, that is, higher myelin content. These associations were statistically significant within several white matter brain regions, particularly the frontal and parietal lobes, splenium, anterior corona radiata, and superior fronto-occipital and longitudinal fasciculus. In contrast, we did not find any significant associations between usual gait speed and MWF, R1, or R2, which suggests that rapid gait speed may be a more sensitive marker of demyelination than usual gait speed. These findings advance our understanding on the implication of myelination in gait impairment among cognitively unimpaired adults, providing further evidence of the interconnection between white matter integrity and motor function.

A case of Pathological Laughter in a patient with recurrent stroke

Introduction Stroke survivors frequently deal with neuropsychiatric sequelae - depression, anxiety and apathy being the most common ones. Pathological laughing and crying (PLC) is a post stroke condition characterized by brief, intense uncontrollable crying and/or laughing due to a neurological disorder. Prevalence of PLC post stroke has been reported to be 15-20%. Pathological laughter (PL) is commonly associated with bilateral or diffuse cerebral lesions. Ischemic injury involving the internal capsule and basal ganglia seems to be associated with emotional disorders. Objectives To discuss an uncommon case of pathological laughter developing after recurrent infarct. Methods A 32-year-old male patient presented to the medical emergency for complaints of slurring of speech since 7 hours. On examination, patient was alert, oriented, with blood pressure 150/90 mmHg. He had a history of similar stroke 2 years prior to current complaints and was on treatment for hypertension since then. Baseline investigations were done. MRI brain revealed acute lacunar infarcts in bilateral ganglio-capsular region, chronic small vessel ischaemic changes in B/L periventricular white matter (Fazeka grade 2) and micro-haemorrhages in various brain regions. Patient was managed conservatively (antiplatelets, statins, antihypertensives). Patient was then referred to Psychiatry department for uncontrollable laughing spells, which started few hours after onset of above complaints. These occurred without any provocation, every 1-2 hours, lasting for several seconds to a minute, and relieved spontaneously. Patient was aware of episodes and found them embarrassing socially. Mental status examination revealed no mood features or other abnormalities. Patient was prescribed Escitalopram, but shifted to homeopathic medicine and was lost to follow up. Telephonic interview one year later revealed that while other complaints have remitted, patient still has laughing spells of similar quality and frequency. Results Discussion: In post stroke PLC, pathological crying represents about 80% cases, while Pure Pathological Laughing, as in the present case, is uncommon. It is generally seen in diffuse CNS pathologies (eg. multiple sclerosis) or bilateral – ischaemic or degenerative. In case of strokes, PL may herald symptom onset, or may immediately follow focal deficits. The aetiology of PLC is unknown; monoaminergic neurotransmission may be altered in post stroke PLC. SSRIs are regarded as first choice treatment agents, given their greater tolerability overall. Conclusions Pathological laughter is a comparatively uncommon but recognisable and treatable post stroke sequela, more commonly seen in bilateral lesions. Patients often describe PL as distressing and socially disabling, but awareness about this condition and available treatments is lacking. Disclosure of Interest None Declared

Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry

Schizophrenia (SCZ) is a devastating mental condition with significant negative consequences for patients, making correct and prompt diagnosis crucial. The purpose of this study is to use structural magnetic resonance image (MRI) to better classify individuals with SCZ from control normals (CN) and to locate a region of the brain that represents abnormalities associated with SCZ. Deep learning (DL), which is based on the nervous system, could be a very useful tool for doctors to accurately predict, diagnose, and treat SCZ. Gray Matter (GM), Cerebrospinal Fluid (CSF), and White Matter (WM) brain regions are extracted from 99 MRI images obtained from the open-source OpenNeuro database to demonstrate SCZ's regional relationship. In this paper, we use a pretrained ResNet-50 deep network to extract features from MRI images and an ensemble deep random vector functional link (edRVFL) network to classify those features. By examining the results obtained, the edRVFL deep model provides the highest classification accuracy of 96.5% with WM and is identified as the best-performing algorithm compared to the traditional algorithms. Furthermore, we examined the GM, WM, and CSF tissue volumes in CN subjects and SCZ patients using voxel-based morphometry (VBM), and the results show 1363 significant voxels, 6.90 T-value, and 6.21 Z-value in the WM region of SCZ patients. In SCZ patients, WM is most closely linked to structural alterations, as evidenced by VBM analysis and the DL model.

Subiculum fiber degeneration within the fornix white matter tract in 5xFAD mice

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disease that affects all components of the neurovascular unit. The hallmark pathology of AD, amyloid plaques and tau neurofibrillary tangles, aggregate within gray matter areas and spread across neural networks. Although AD pathology is scarce within white matter brain regions, white matter abnormalities have been observed in AD patients using diffusion tensor imaging (DTI; Sachdev et al 2013) and white matter tracts are putative therapeutic targets for deep brain stimulation (Lam et al 2020). Particularly, the fornix is a white matter tract which connects the hippocampus to brain regions of the classic Papez circuit and Default Mode Network (DMN). A recent whole brain analysis using transgenic 5xFAD/Thy1‐GFP mouse (Zhang et al 2020) found evidence of fornix degeneration and dystrophic axon terminals within the mammillary body (a major SUB target) occurring as early as 2 months of age. However, due to the broad expression of GFP under the Thy1 promotor, it is difficult to determine the origin of axon fibers and further characterize if other SUB pathways are also affected.MethodTo investigate white matter changes in AD and further characterize SUB axon degeneration, we performed triple anterograde tract‐tracing of SUB axon fibers and post‐mortem DTI tractography imaging within the same 8‐9 mo. old 5xFAD mice.ResultDTI imaging revealed a significant decrease in fiber density of the fornix white matter tract in 5xFAD mice. Quantification of tracer‐labeled fluorescent fiber density in the 5xFAD mice vs control mice also revealed significant degeneration of SUB fibers within the fornix white matter as well as downstream SUB targets including mammillary body, retrosplenial cortex, and anterior thalamus. Furthermore, SUB axon terminals in 5xFAD mice appeared dystrophic and terminal field topography was disrupted.ConclusionDTI imaging and anatomical tract tracing approaches reveal white matter degeneration in 5xFAD mice and the fornix/SUB fibers are particularly vulnerable in AD. Diminished SUB input to brain regions of the Papez circuit/DMN likely leads to neural network dysfunction. Whether amyloid pathology, neurovascular dysfunction, or inflammatory response in the 5xFAD mouse contributes to white matter degeneration remains to be determined by future studies.

Effects of Physical Exertion on Early Changes in Blood-Based Brain Biomarkers: Implications for the Acute Point of Care Diagnosis of Concussion.

Blood-based brain biomarkers (BBM) such as glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) have potential to aid in the diagnosis of concussion. Recently developed point-of-care test devices would enable BBMs to be measured in field settings such military and sport environments within minutes of a suspicious head hit. However, head hits in these environments typically occur in the setting of vigorous physical exertion, which can itself increase BBMs levels. Thus, efforts to develop BBMs as acute concussion aids in field settings need to account for the effects of physical exertion. To determine the acute effects of physical exertion on the BBMs, we measured GFAP, UCH-L1, tau, and neurofilament light chain (NF-L) immediately before, immediately after, and 45 min after a single workout session consisting of aerobic and resistance exercises in 30 collegiate football players. Subjects wore body sensors measuring several aspects of exertion and underwent diffusion tensor imaging 24 h before and 48 h after exertion. All subjects were male with a mean age of 19.5 ± 1.2 years. The mean duration of activity during the workout session was 94 ± 31 min. There was a significant decrease in serum GFAP immediately after (median decrease of 27.76%, p < 0.0001) and a significant increase in serum UCH-L1 45 min after (median increase of 37.11%, p = 0.016) exertion, compared with pre-exertion baseline. No significant changes in tau or NF-L were identified. The duration of exertion had a significant independent linear correlation to the increase in serum UCHL1 from pre-exertion to 45 min after exertion (r = 0.68, p = 0.004). There were no significant pre- to post-exertional changes in any of the 39 examined brain white matter regions, and biomarker changes did not correlate to variation in white matter integrity in any of these regions. Thus, exertion appeared to be associated with immediate decreases in serum GFAP and very acute (45 min) increases in UCH-L1. These changes were related to the duration of exertion, but not to changes in brain white matter integrity. Our results have important implications for how these BBMs might be used to aid in the on-scene diagnosis of concussion occurring in the setting of physical exertion.

Decoding Brain Fog in Head and Neck Cancer Survivors Using Artificial Intelligence

<h3>Purpose/Objective(s)</h3> Brain fogging, which is characterized by memory decline, word-finding difficulty, and decreased multi-tasking ability, is common in head and neck cancer survivors. The precise causes of brain fog are poorly understood, as MRIs are essentially normal in these patients. The purpose of this study was to use artificial intelligence (AI) to detect micro-architectural and biological changes in the brain that are invisible to human eyes. <h3>Materials/Methods</h3> DVH of temporal lobes and whole brain were obtained in 566 and 60 patients, respectively, who underwent IMRT or proton radiation with concurrent chemotherapy for nasopharyngeal carcinoma. EORTC QLQ-C30 was obtained from 92 patients who enrolled in two prospective clinical studies. Automated cortical region segmentation using an open-source software for processing and analyzing brain MRI images was performed in 33 patients with a minimum follow-up of 4 years. Architectural and biological MRI changes in gray matter, white matter, and subcortical brain regions were determined in 34 brain regions. Graph theory-based brain connectome was evaluated to assess the connectivity between different regions of the brain. Radiomics which employs high-throughput quantitative analysis of image features were performed on the T1- and diffusion-weighted sequences. <h3>Results</h3> Patients experienced a continuous decline of cognitive function after radiation, with a 6.6% in decrease in their first year. The brain received a large low-dose bath with a median V10-20(whole brain) (volume of whole brain that received 10-20 Gy) 170cc, V20-30(whole brain) 50.8cc, V10-20(temporal lobe)11.4cc, and V20-30(temporal lobe) 6.18cc. There were global changes in gray matter thickness, with most pronounced changes occurred in parietal lobe (-4.79%, p=0.007) and occipital lobe (-5.68%, p=0.03). Similarly, there were diffuse changes in white matter and subcortical volume. After radiation, the frontal lobe increased by 17.5% (p=0.04), lateral ventricle 41% (p=0.03), and choroid plexus 34.3% (p=0.03). After radiation, the brain exhibited diffuse disrupted connectivity as characterized by increased clustering coefficient (p=0.002) and decreased modularity (p=0.003). Corpus collusum, choroid plexus, cerebellum, hippocampus, brainstem, medialorbito- and superior-frontal, temporal pole, and inferior temporal were analyzed using radiomics. First order interquartile-range, entropy, uniformity, and GLCM features were found to be statistically significant (p< 0.01). After adjusted for age, gender, and time interval between MRI, IMRT patients developed significant more changes in white matter of the temporal lobe (p=0.03) and corpus callosum (p=0.03) when compared to proton patients. <h3>Conclusion</h3> By employing artificial intelligence and computational methods, we are able to detect global disruption in architecture, connectivity, and function in the brain of head and neck cancer survivors. IMRT affects the brain differently than proton.

Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients.

Glioblastoma is characterized by diffuse infiltration into the surrounding tissue along white matter tracts. Identifying the invisible tumour invasion beyond focal lesion promises more effective treatment, which remains a significant challenge. It is increasingly accepted that glioblastoma could widely affect brain structure and function, and further lead to reorganization of neural connectivity. Quantifying neural connectivity in glioblastoma may provide a valuable tool for identifying tumour invasion. Here we propose an approach to systematically identify tumour invasion by quantifying the structural connectome in glioblastoma patients. We first recruit two independent prospective glioblastoma cohorts: the discovery cohort with 117 patients and validation cohort with 42 patients. Next, we use diffusion MRI of healthy subjects to construct tractography templates indicating white matter connection pathways between brain regions. Next, we construct fractional anisotropy skeletons from diffusion MRI using an improved voxel projection approach based on the tract-based spatial statistics, where the strengths of white matter connection and brain regions are estimated. To quantify the disrupted connectome, we calculate the deviation of the connectome strengths of patients from that of the age-matched healthy controls. We then categorize the disruption into regional disruptions on the basis of the relative location of connectome to focal lesions. We also characterize the topological properties of the patient connectome based on the graph theory. Finally, we investigate the clinical, cognitive and prognostic significance of connectome metrics using Pearson correlation test, mediation test and survival models. Our results show that the connectome disruptions in glioblastoma patients are widespread in the normal-appearing brain beyond focal lesions, associated with lower preoperative performance (P < 0.001), impaired cognitive function (P < 0.001) and worse survival (overall survival: hazard ratio = 1.46, P = 0.049; progression-free survival: hazard ratio = 1.49, P = 0.019). Additionally, these distant disruptions mediate the effect on topological alterations of the connectome (mediation effect: clustering coefficient -0.017, P < 0.001, characteristic path length 0.17, P = 0.008). Further, the preserved connectome in the normal-appearing brain demonstrates evidence of connectivity reorganization, where the increased neural connectivity is associated with better overall survival (log-rank P = 0.005). In conclusion, our connectome approach could reveal and quantify the glioblastoma invasion distant from the focal lesion and invisible on the conventional MRI. The structural disruptions in the normal-appearing brain were associated with the topological alteration of the brain and could indicate treatment target. Our approach promises to aid more accurate patient stratification and more precise treatment planning.

Using transfer learning for automated microbleed segmentation.

Cerebral microbleeds are small perivascular hemorrhages that can occur in both gray and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to interrater and intrarater variability. Automated techniques so far have shown high accuracy at a neighborhood ("patch") level at the expense of a high number of false positive voxel-wise lesions. We aimed to develop an automated, more precise microbleed segmentation tool that can use standardizable MRI contrasts. We first trained a ResNet50 network on another MRI segmentation task (cerebrospinal fluid vs. background segmentation) using T1-weighted, T2-weighted, and T2* MRIs. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentation of microbleeds from 78 participants was used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, and data augmentation on the performance of the Microbleed ResNet50 network. The proposed method achieved high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57, 99.16, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1, 20.1, and 0.28% for cortical GM; 100, 100, and 1.0% for deep GM; and 91.1, 44.3, and 0.58% for WM, respectively. The proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity.