Pathways explaining racial/ethnic and socio-economic disparities in brain white matter integrity outcomes in the UK Biobank study.

Pathways explaining racial/ethnic and socio-economic status (SES) disparities in white matter integrity (WMI) reflecting brain health, remain underexplored, particularly in the UK population. We examined racial/ethnic and SES disparities in diffusion tensor brain magnetic resonance imaging (dMRI) markers, namely global and tract-specific mean fractional anisotropy (FA), and tested total, direct and indirect effects through lifestyle, health-related and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70 y at baseline assessment (47% men). Multiple linear regression models were conducted, testing independent associations of race/ethnicity, socio-economic and other downstream factors in relation to global mean FA, while stratifying by Alzheimer's Disease polygenic Risk Score (AD PRS) tertiles. Race (Non-White vs. White) and lower SES predicted poorer WMI (i.e. lower global mean FA) at follow-up, with racial/ethnic disparities in FAmean involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across tract-specific FA outcomes, with SES-FAmean total effect being partially mediated (41% of total effect = indirect effect). Furthermore, the association of poor cognition with FAmean was markedly stronger in the two uppermost AD PRS tertiles compared to the lower tertile (T2 and T3: ß±SE: -0.0009 ± 0.0001 vs. T1: ß±SE: -0.0005 ± 0.0001, P < 0.001), independently of potentially confounding factors. Race and lower SES were generally important determinants of adverse WMI outcomes, with partial mediation of socio-economic disparities in global mean FA through lifestyle, health-related and cognition factors. The association of poor cognition with lower global mean FA was stronger at higher AD polygenic risk.

Subclinical Metabolic and Cardiovascular Factors and Brain White Matter Microstructural Integrity in Young Women.

Women who have experienced pregnancy complications, specifically preeclampsia and gestational diabetes, have well documented increased risks of cardiovascular, metabolic, and neurological disease later in life. This study examined how specific cardiovascular and metabolic risk factors for preeclampsia assessed in a non-pregnant state were associated with brain white matter microstructural integrity. This study examined sixty-two healthy women (mean age 31 ± 5 years) who received metabolic and cardiovascular assessments as well as multiple modality MRI imaging. Participants were either nulliparous (n = 31) or had a history of preterm preeclampsia (n = 31). Imaging included acquisition Diffusion Tensor Imaging (DTI) to assess white matter integrity within the brain. We hypothesized that healthy, young, non-pregnant women with cardiovascular and metabolic profiles suggesting elevated risk would have decreased white matter integrity, represented by lower Fractional Anisotropy (FA) and increased Mean Diffusivity (MD) estimates in the posterior cortical areas of the brain. We observed increased white matter degradation (lower FA and increased MD) in posterior and occipital tracts, commissural fibers, and subcortical structures in women with increased adiposity, worse measures of cardiovascular and metabolic function, including greater insulin resistance (HOMA-IR), hyperlipidemia, elevated blood pressure, and increased arterial stiffness. The relationships detected between subclinical cardiovascular and metabolic phenotypes and increased white matter disruption at a young age, outside of pregnancy, are indicative that adverse changes are detectable long before cognitive clinical presentation. This may suggest that many of the long-term cardiovascular and metabolic risks of aging are influenced by physiologic aging trajectories rather than damage caused by pregnancy complications.

Structural white matter properties and cognitive resilience to tau pathology.

INTRODUCTION: We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS: We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-ß/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS: Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION: White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS: Aß and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.

Brain and cognitive changes in patients with long COVID compared with infection-recovered control subjects.

Between 2.5 and 28% of people infected with SARS-CoV-2 suffer Long COVID or persistence of symptoms for months after acute illness. Many symptoms are neurological, but the brain changes underlying the neuropsychological impairments remain unclear. This study aimed to provide a detailed description of the cognitive profile, the pattern of brain alterations in Long COVID and the potential association between them. To address these objectives, 83 patients with persistent neurological symptoms after COVID-19 were recruited, and 22 now healthy controls chosen because they had suffered COVID-19 but did not experience persistent neurological symptoms. Patients and controls were matched for age, sex and educational level. All participants were assessed by clinical interview, comprehensive standardized neuropsychological tests and structural MRI. The mean global cognitive function of patients with Long COVID assessed by ACE III screening test (Overall Cognitive level - OCLz= -0.39± 0.12) was significantly below the infection recovered-controls (OCLz= +0.32± 0.16, p< 0.01). We observed that 48% of patients with Long COVID had episodic memory deficit, with 27% also impaired overall cognitive function, especially attention, working memory, processing speed and verbal fluency. The MRI examination included grey matter morphometry and whole brain structural connectivity analysis. Compared to infection recovered controls, patients had thinner cortex in a specific cluster centred on the left posterior superior temporal gyrus. In addition, lower fractional anisotropy (FA) and higher radial diffusivity (RD) were observed in widespread areas of the patients' cerebral white matter relative to these controls. Correlations between cognitive status and brain abnormalities revealed a relationship between altered connectivity of white matter regions and impairments of episodic memory, overall cognitive function, attention and verbal fluency. This study shows that patients with neurological Long COVID suffer brain changes, especially in several white matter areas, and these are associated with impairments of specific cognitive functions.

Activation of NLRP3 inflammasome in a rat model of cerebral small vessel disease.

Cerebral small vessel disease (CSVD) is increasingly being recognized as a leading contributor to cognitive impairment in the elderly. However, there is a lack of effective preventative or therapeutic options for CSVD. In this exploratory study, we investigated the interplay between neuroinflammation and CSVD pathogenesis as well as the cognitive performance, focusing on NLRP3 signaling as a new therapeutic target. Spontaneously hypertensive stroke-prone (SHRSP) rats served as a CSVD model. We found that SHRSP rats showed decline in learning and memory abilities using morris water maze test. Activated NLRP3 signaling and an increased expression of the downstream pro-inflammatory factors, including IL (interleukin)-6 and tumor necrosis factor α were determined. We also observed a remarkable increase in the production of pyroptosis executive protein gasdermin D, and elevated astrocytic and microglial activation. In addition, we identify several neuropathological hallmarks of CSVD, including blood-brain barrier breakdown, white matter damage, and endothelial dysfunction. These results were in correlation with the activation of NLRP3 inflammasome. Thus, our findings reveal that the NLRP3-mediated inflammatory pathway could play a central role in the pathogenesis of CSVD, presenting a novel target for potential CSVD treatment.

Differential associations between abnormal cardiac left ventricular geometry types and cerebral white matter disease.

OBJECTIVES: Reduced cardiac outflow due to left ventricular hypertrophy has been suggested as a potential risk factor for development of cerebral white matter disease. Our study aimed to examine the correlation between left ventricular geometry and white matter disease volume to establish a clearer understanding of their relationship, as it is currently not well-established. METHODS: Consecutive patients from 2016 to 2021 who were ≥18 years and underwent echocardiography, cardiac MRI, and brain MRI within one year were included. Four categories of left ventricular geometry were defined based on left ventricular mass index and relative wall thickness on echocardiography. White matter disease volume was quantified using an automated algorithm applied to axial T2 FLAIR images and compared across left ventricular geometry categories. RESULTS: We identified 112 patients of which 34.8 % had normal left ventricular geometry, 20.5 % had eccentric hypertrophy, 21.4 % had concentric remodeling, and 23.2 % had concentric hypertrophy. White matter disease volume was highest in patients with concentric hypertrophy and concentric remodeling, compared to eccentric hypertrophy and normal morphology with a trend-P value of 0.028. Patients with higher relative wall thickness had higher white matter disease volume (10.73 ± 10.29 cc vs 5.89 ± 6.46 cc, P = 0.003), compared to those with normal relative wall thickness. CONCLUSION: Our results showed that abnormal left ventricular geometry is associated with higher white matter disease burden, particularly among those with abnormal relative wall thickness. Future studies are needed to explore causative relationships and potential therapeutic options that may mediate the adverse left ventricular remodeling and its effect in slowing white matter disease progression.

Distinct spatial contributions of amyloid pathology and cerebral small vessel disease to hippocampal morphology.

INTRODUCTION: Cerebral small vessel disease (SVD) and amyloid beta (Aß) pathology frequently co-exist. The impact of concurrent pathology on the pattern of hippocampal atrophy, a key substrate of memory impacted early and extensively in dementia, remains poorly understood. METHODS: In a unique cohort of mixed Alzheimer's disease and moderate-severe SVD, we examined whether total and regional neuroimaging measures of SVD, white matter hyperintensities (WMH), and Aß, as assessed by 18F-AV45 positron emission tomography, exert additive or synergistic effects on hippocampal volume and shape. RESULTS: Frontal WMH, occipital WMH, and Aß were independently associated with smaller hippocampal volume. Frontal WMH had a spatially distinct impact on hippocampal shape relative to Aß. In contrast, hippocampal shape alterations associated with occipital WMH spatially overlapped with Aß-vulnerable subregions. DISCUSSION: Hippocampal degeneration is differentially sensitive to SVD and Aß pathology. The pattern of hippocampal atrophy could serve as a disease-specific biomarker, and thus guide clinical diagnosis and individualized treatment strategies for mixed dementia.

A new family of instance-level loss functions for improving instance-level segmentation and detection of white matter hyperintensities in routine clinical brain MRI.

In this study, we introduce "instance loss functions", a new family of loss functions designed to enhance the training of neural networks in the instance-level segmentation and detection of objects in biomedical image data, particularly those of varied numbers and sizes. Intended to be utilized conjointly with traditional loss functions, these proposed functions, prioritize object instances over pixel-by-pixel comparisons. The specific functions, the instance segmentation loss (Linstance), the instance center loss (Lcenter), the false instance rate loss (Lfalse), and the instance proximity loss (Lproximity), serve distinct purposes. Specifically, Linstance improves instance-wise segmentation quality, Lcenter enhances segmentation quality of small instances, Lfalse minimizes the rate of false and missed detections across varied instance sizes, and Lproximity improves detection quality by pulling predicted instances towards the ground truth instances. Through the task of segmenting white matter hyperintensities (WMH) in brain MRI, we benchmarked our proposed instance loss functions, both individually and in combination via an ensemble inference models approach, against traditional pixel-level loss functions. Data were sourced from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the WMH Segmentation Challenge datasets, which exhibit significant variation in WMH instance sizes. Empirical evaluations demonstrate that combining two instance-level loss functions through ensemble inference models outperforms models using other loss function on both the ADNI and WMH Segmentation Challenge datasets for the segmentation and detection of WMH instances. Further, applying these functions to the segmentation of nuclei in histopathology images demonstrated their effectiveness and generalizability beyond WMH, improving performance even in contexts with less severe instance imbalance.

Association between dietary magnesium intake, inflammation, and neurodegeneration.

BACKGROUND: Consistent evidence shows that magnesium (Mg) intake is associated with lower blood pressure (BP), and that lower BP is associated with improved cerebral health. However, recent findings indicate that the positive effect of dietary Mg intake on cerebral health is not mediated by a decrease in BP. As Mg's anti-inflammatory action is a plausible alternative mechanism, the objective of this study was to investigate the associations between Mg intake and inflammation to determine whether it mediates any neuroprotective effect. METHODS: Participants from the UK Biobank (n = 5775, aged 40-73 years, 54.7% female) were assessed for dietary magnesium using an online food questionnaire, brain and white matter lesion (WML) volumes were segmented with FreeSurfer software, and inflammation markers including high-sensitivity C-reactive protein (hs-CRP), leukocyte, erythrocyte count, and Glycoprotein acetylation (GlycA) were measured using specific laboratory techniques such as immunoturbidimetry, automated cell counting, and nuclear magnetic resonance. Hierarchical linear regression models were performed to investigate the association between dietary Mg, and inflammatory markers and between dietary Mg, brain and WMLs volumes. Mediation analysis was performed to test a possible mediation role of inflammation on the association between dietary Mg and brain and WMLs volumes. RESULTS: Higher dietary Mg intake was associated with lower inflammation: hs-CRP level (- 0.0497%; 95% confidence interval [CI] - 0.0497%,  - 0.0199%) leukocytes count (- 0.0015%; 95%CI - 0.00151%,  - 0.0011%), and GlycA (- 0.0519%; 95%CI - 0.1298%,  - 0.0129%). Moreover, higher dietary Mg intake was associated with larger grey matter volume (0.010%; 95%CI 0.004%, 0.017%), white matter volume (0.012%; 95%CI 0.003,  0.022) and right hippocampal volume (0.002%; 95%CI 0.0007, -0.0025%). Lower hs-CRP levels mediated the positive association between higher dietary Mg intake and larger grey matter volume. CONCLUSIONS: The anti-inflammatory effects of dietary Mg intake in the general population, appears to mediate its neuroprotective effect.

Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis.

BACKGROUND: Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice. OBJECTIVE: We performed a systematic review and meta-analysis on the use of QSM in MS. METHODS: Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively. RESULTS: After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions. CONCLUSIONS: We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.

Lateralization of dorsal fiber tract targeting Broca's area concurs with language skills during development.

Language is bounded to the left hemisphere in the adult brain and the functional lateralization can already be observed early during development. Here we investigate whether this is paralleled by a lateralization of the white matter structural language network. We analyze the strength and microstructural properties of language-related fiber tracts connecting temporal and frontal cortices with a separation of two dorsal tracts, one targeting the posterior Broca's area (BA44) and one targeting the precentral gyrus (BA6). In a large sample of young children (3-6 years), we demonstrate that, in contrast to the BA6-targeting tract, the microstructural asymmetry of the BA44-targeting fiber tract significantly correlates locally with different aspects of development. While the asymmetry in its anterior segment reflects age, the asymmetry in its posterior segment is associated with the children's language skills. These findings demonstrate a fine-grained structure-to-function mapping in the lateralized network and go beyond our current view of language-related human brain maturation.

White matter hyperintensities and the surrounding normal appearing white matter are associated with water channel disruption in the oldest old.

INTRODUCTION: Age-related magnetic resonance imaging (MRI) T2 white matter hyperintensities (WMHs) are common and associated with neurological decline. We investigated the histopathological underpinnings of MRI WMH and surrounding normal appearing white matter (NAWM), with a focus on astroglial phenotypes. METHODS: Brain samples from 51 oldest old Oregon Alzheimer's Disease Research Center participants who came to autopsy underwent post mortem (PM) 7 tesla MRI with targeted histopathological sampling of WMHs and NAWM. Stained slides were digitized and quantified. Mixed-effects models determined differences in molecular characteristics between WMHs and the NAWM and across NAWM. RESULTS: PM MRI-targeted WMHs are characterized by demyelination, microglial activation, and prominent astrocytic alterations, including disrupted aquaporin (AQP) expression. Similar changes occur within the surrounding NAWM in a pattern of decreasing severity with increased distance from WMHs. DISCUSSION: Decreased AQP expression within WMH and proximal NAWM suggest an overwhelmed system wherein water homeostasis is no longer maintained, contributing to WM damage in older individuals. HIGHLIGHTS: Post mortem magnetic resonance imaging (MRI) was used to characterize the pathology of white matter hyperintensities (WMHs) and surrounding normal appearing white matter (NAWM). Stained immunohistochemical (IHC) slides from targeted WMH and NAWM samples were digitized and quantified. WMHs and NAWM were associated with inflammation, demyelination, and gliosis. WMHs and NAWM astrocytic changes included decreased AQP1 and AQP4 expression. Abnormal NAWM pathology diminished in severity with increasing distance from WMH.

MR Imaging-based Biomarker Development in Hemorrhagic Stroke Patients Including Brain Iron Quantification, Diffusion Tensor Imaging, and Phenomenon of Ultra-early Erythrolysis.

This review article discusses the role of MR imaging-based biomarkers in understanding and managing hemorrhagic strokes, focusing on intracerebral hemorrhage (ICH) and aneurysmal subarachnoid hemorrhage. ICH is a severe type of stroke with high mortality and morbidity rates, primarily caused by the rupture of small blood vessels in the brain, resulting in hematoma formation. MR imaging-based biomarkers, including brain iron quantification, ultra-early erythrolysis detection, and diffusion tensor imaging, offer valuable insights for hemorrhagic stroke management. These biomarkers could improve early diagnosis, risk stratification, treatment monitoring, and patient outcomes in the future, revolutionizing our approach to hemorrhagic strokes.

Ldl-stimulated microglial activation exacerbates ischemic white matter damage.

The role of microglia in triggering the blood-brain barrier (BBB) impairment and white matter damage after chronic cerebral hypoperfusion is unclear. Here we demonstrated that the vessel-adjacent microglia were specifically activated by the leakage of plasma low-density lipoprotein (LDL), which led to BBB breakdown and ischemic demyelination. Interestingly, we found that LDL stimulation enhanced microglial phagocytosis, causing excessive engulfment of myelin debris and resulting in an overwhelming lipid burden in microglia. Surprisingly, these lipid-laden microglia exhibited a suppressed profile of inflammatory response and compromised pro-regenerative properties. Microglia-specific knockdown of LDLR or systematic medication lowering circulating LDL-C showed protective effects against ischemic demyelination. Overall, our findings demonstrated that LDL-stimulated vessel-adjacent microglia possess a disease-specific molecular signature, characterized by suppressed regenerative properties, which is associated with the propagation of demyelination during ischemic white matter damage.

A systematic review of automated methods to perform white matter tract segmentation.

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

Older adults with reduced cerebrovascular reactivity exhibit high white matter hyperintensity burden.

Cerebrovascular reactivity (CVR) deficits may contribute to small vessel disease, such as white matter hyperintensities (WMH). Moreover, apolipoprotein-e4 (APOE4) carriers at genetic risk for Alzheimer's disease exhibit cerebrovascular dysfunction relative to non-carriers. We examined whether older adults, and APOE4 carriers specifically, with diminished CVR would exhibit higher WMH burden. Independently living older adults (N = 125, mean age = 69.2 years; SD = 7.6; 31.2% male) free of dementia or clinical stroke underwent brain MRI to quantify cerebral perfusion during CVR to hypercapnia and hypocapnia and determine WMH volume. Adjusting for age, sex and intracranial volume, hierarchical regression analysis revealed a significant association between whole brain CVR to hypercapnia and WMH overall [B = -.02, 95% CI (-.04, -.008), p =.003] and in APOE4 carriers [B = -.03, 95% CI (-.06, -.009), p =.009]. Findings suggest deficits in cerebral vasodilatory capacity are associated with WMH burden in older adults and future studies are warranted to further delineate the effect of APOE4 on precipitating WMH.

Single-cell approaches define two groups of mammalian oligodendrocyte precursor cells and their evolution over developmental time.

Here, we used single-cell RNA sequencing (scRNA-seq), single-cell ATAC sequencing (scATAC-seq), and single-cell spatial transcriptomics to characterize murine cortical OPCs throughout postnatal life. During development, we identified two groups of differentially localized PDGFRα+ OPCs that are transcriptionally and epigenetically distinct. One group (active, or actOPCs) is metabolically active and enriched in white matter. The second (homeostatic, or hOPCs) is less active, enriched in gray matter, and predicted to derive from actOPCs. In adulthood, these two groups are transcriptionally but not epigenetically distinct, and relative to developing OPCs are less active metabolically and have less open chromatin. When adult oligodendrogenesis is enhanced during experimentally induced remyelination, adult OPCs do not reacquire a developmental open chromatin state, and the oligodendrogenesis trajectory is distinct from that seen neonatally. These data suggest that there are two OPC groups subserving distinct postnatal functions and that neonatal and adult OPC-mediated oligodendrogenesis are fundamentally different.

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Background: White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods: We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results: Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion: Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Relationship of neutrophil/lymphocyte ratio with cerebral small vessel disease and its common imaging markers.

BACKGROUND: High neutrophil/lymphocyte ratio (NLR) is associated with poor prognosis in ischemic stroke. However, the role of NLR in cerebral small vessel disease (CSVD) is controversial. Herein, we evaluated the value of NLR in identifying CSVD and its relationship with the common imaging markers of CSVD. METHODS: A total of 667 patients were enrolled in this study, including 368 in the CSVD group and 299 in the non-CSVD group. Clinical, laboratory, and imaging data were collected. The relationship of NLR with CSVD and common imaging markers of CSVD were analyzed with univariate and multivariate logistic regression analysis. The predictive value of NLR was assessed with the receiver operating characteristic curve. RESULTS: NLR (odds ratio [OR] = 1.929, 95% confidence interval [CI] = 1.599-2.327, p < .001) was an independent risk factor for CSVD. NLR was also independently associated with moderate to severe white matter hyperintensity (WMH) (OR = 2.136, 95% CI = 1.768-2.580, p < .001), moderate to severe periventricular WMH (OR = 2.138, 95% CI = 1.771-2.579, p < .001), and moderate to severe deep WMH (OR = 1.654, 95% CI = 1.438-1.902, p < .001), moderately to severely enlarged perivascular spaces (EPVS) (OR = 1.248, 95% CI = 1.110-1.402, p < .001), moderately to severely EPVS in the basal ganglia (OR = 1.136, 95% CI = 1.012-1.275, p = .030), and moderately to severely EPVS in the centrum semiovale (OR = 1.140, 95% CI = 1.027-1.266, p = .014). However, NLR was not statistically significantly associated with lacune. The optimal cutoff point of NLR in predicting CSVD was 2.47, with sensitivity and specificity of 84.2% and 66.9%, respectively (p < .01). The diagnostic effect was maximized when NLR was combined with other risk factors. CONCLUSIONS: NLR is an independent risk factor for CSVD and is independently associated with common imaging markers of CSVD. NLR may serve as a valid and convenient biomarker for assessing CSVD.

White matter biomarker for predicting de novo Parkinson's disease using tract-based spatial statistics: a machine learning-based model.

Background: Parkinson's disease (PD) is an irreversible, chronic degenerative disease of the central nervous system, potentially associated with cerebral white matter (WM) lesions. Investigating the microstructural alterations within the WM in the early stages of PD can help to identify the disease early and enable intervention to reduce the associated serious threats to health. Methods: This study selected 227 cases from the Parkinson's Progression Markers Initiative (PPMI) database, including 152 de novo PD patients and 75 normal controls (NC). Whole-brain voxel analysis of the WM was performed using the tract-based spatial statistics (TBSS) method. The WM regions with statistically significant differences (P<0.05) between the PD and NC groups were identified and used as masks. The mask was applied to each case's fractional anisotropy (FA) image to extract voxel values as feature vectors. Geometric dimensionality reduction was then applied to eliminate redundant values in the feature vectors. Subsequently, the cases were randomly divided into a training group (158 cases, including 103 PD patients and 55 NC) and a test group (69 cases, including 49 PD patients and 20 NC). The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to extract the minimal set of relevant features, then the random forest (RF) algorithm was utilized for classification using 5-fold cross validation. The resulting model was further integrated with clinical factors to create a comprehensive prediction model. Results: In comparison to the NC group, the FA values in PD patients exhibited a statistically significant decrease (P<0.05), indicating the presence of widespread WM lesions across multiple brain regions. Moreover, the PD prediction model, constructed based on these WM lesion regions, yielded prediction accuracy (ACC) and area under the receiver operating characteristic (ROC) curve (AUC) values of 0.778 and 0.865 in the validation set, and 0.783 and 0.831 in the test set, respectively. Furthermore, the performance of the integrated model showed some improvement, with ACC and AUC values in the test set reaching 0.804 and 0.844, respectively. Conclusions: The quantitative calculation of WM lesion area on FA images using the TBSS method can serve as a neuroimaging biomarker for diagnosing and predicting early PD at the individual level. When integrated with clinical variables, the predictive performance improves.