Prevalence and 3-month follow-up of cerebrovascular MRI markers in hospitalized COVID-19 patients: the CORONIS study.

PURPOSE: To investigate the prevalence of cerebrovascular MRI markers in unselected patients hospitalized for COVID-19 (Coronavirus disease 2019), we compared these with healthy controls without previous SARS-CoV-2 infection or hospitalization and subsequently, investigated longitudinal (incidental) lesions in patients after three months. METHODS: CORONIS (CORONavirus and Ischemic Stroke) was an observational cohort study in adult hospitalized patients for COVID-19 and controls without COVID-19, conducted between April 2021 and September 2022. Brain MRI was performed shortly after discharge and after 3 months. Outcomes included recent ischemic (DWI-positive) lesions, previous infarction, microbleeds, white matter hyperintensities (WMH) and intracerebral hemorrhage and were analysed with logistic regression to adjust for confounders. RESULTS: 125 patients with COVID-19 and 47 controls underwent brain MRI a median of 41.5 days after symptom onset. DWI-positive lesions were found in one patient (1%) and in one (2%) control, both clinically silent. WMH were more prevalent in patients (78%) than in controls (62%) (adjusted OR: 2.95 [95% CI: 1.07-8.57]), other cerebrovascular MRI markers did not differ. Prevalence of markers in ICU vs. non-ICU patients was similar. After three months, five patients (5%) had new cerebrovascular lesions, including DWI-positive lesions (1 patient, 1.0%), cerebral infarction (2 patients, 2.0%) and microbleeds (3 patients, 3.1%). CONCLUSION: Overall, we found no higher prevalence of cerebrovascular markers in unselected hospitalized COVID-19 patients compared to controls. The few incident DWI-lesions were most likely to be explained by risk-factors of small vessel disease. In the general hospitalized COVID-19 population, COVID-19 shows limited impact on cerebrovascular MRI markers shortly after hospitalization.

Orthostatic hypotension, cognition and structural brain imaging in hemodynamically impaired patients.

BACKGROUND: Orthostatic hypotension (OH) is associated with an increased risk of dementia, potentially attributable to cerebral hypoperfusion. We investigated which patterns and characteristics of OH are related to cognition or to potentially underlying structural brain injury in hemodynamically impaired patients and healthy reference participants. METHODS: Participants with carotid occlusive disease or heart failure, and reference participants from the Heart-Brain Connection Study underwent OH measurements, neuropsychological assessment and brain MRI. We analyzed the association between OH, global cognitive functioning, white matter hyperintensity (WMH) volume and brain parenchymal fraction with linear regression. We stratified by participant group, severity and duration of OH, chronotropic incompetence and presence of orthostatic symptoms. RESULTS: Of 337 participants (mean age 67.3 ± 8.8 years, 118 (35.0%) women), 113 (33.5%) had OH. Overall, presence of OH was not associated with cognitive functioning (ß: -0.12 [-0.24-0.00]), but we did observe worse cognitive functioning in those with severe OH (≥ 30/15 mmHg; ß: -0.18 [-0.34 to -0.02]) and clinically manifest OH (ß: -0.30 [-0.52 to -0.08]). These associations did not differ significantly by OH duration or chronotropic incompetence, and were similar between patient groups and reference participants. Similarly, both severe OH and clinically manifest OH were associated with a lower brain parenchymal fraction, and severe OH also with a somewhat higher WMH volume. CONCLUSIONS: Severe OH and clinically manifest OH are associated with worse cognitive functioning. This supports the notion that specific patterns and characteristics of OH determine its impact on brain health.

Influence of arterial transit time delays on the differentiation between tumor progression and pseudoprogression in glioblastoma by arterial spin labeling magnetic resonance imaging.

Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL-MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL-MRI and DSC-MRI scans were acquired at 3 months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL-MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow-up until 9 months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL-MRI and DSC-MRI was observed only for ASL images with moderate ATT severity (30%-65%). The perfusion assessment showed ASL-MRI tending more towards hyperperfusion than DSC-MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL-MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p = 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL-MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.

Identification of Distinct Brain MRI Phenotypes and Their Association With Long-Term Dementia Risk in Community-Dwelling Older Adults.

BACKGROUND AND OBJECTIVES: Individual brain MRI markers only show at best a modest association with long-term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We aimed to identify different brain MRI phenotypes by hierarchical clustering analysis based on combined neurovascular and neurodegenerative brain MRI markers and to determine the long-term dementia risk within the brain MRI phenotype subgroups. METHODS: Hierarchical clustering analysis based on 32 combined neurovascular and neurodegenerative brain MRI markers in community-dwelling individuals of the Age-Gene/Environment Susceptibility Reykjavik Study was applied to identify brain MRI phenotypes. A Cox proportional hazards regression model was used to determine the long-term risk for dementia per subgroup. RESULTS: We included 3,056 participants and identified 15 subgroups with distinct brain MRI phenotypes. The phenotypes ranged from limited burden, mostly irregular white matter hyperintensity (WMH) shape and cerebral atrophy, mostly irregularly WMHs and microbleeds, mostly cortical infarcts and atrophy, mostly irregularly shaped WMH and cerebral atrophy to multiburden subgroups. Each subgroup showed different long-term risks for dementia (min-max range hazard ratios [HRs] 1.01-6.18; mean time to follow-up 9.9 ± 2.6 years); especially the brain MRI phenotype with mainly WMHs and atrophy showed a large increased risk (HR 6.18, 95% CI 3.37-11.32). DISCUSSION: Distinct brain MRI phenotypes can be identified in community-dwelling older adults. Our results indicate that distinct brain MRI phenotypes are related to varying long-term risks of developing dementia. Brain MRI phenotypes may in the future assist in an improved understanding of the structural correlates of dementia predisposition.

Sporadic cerebral small vessel disease and cognitive decline in healthy older adults: A systematic review and meta-analysis.

We performed a systematic review and meta-analysis on prospective studies that provided risk estimates for the impact of 3 different MRI markers of small vessel disease (SVD), namely white matter hyperintensities (WMH), cerebral microbleeds (CMB) and lacunes, on cognitive decline in relatively healthy older adults without cognitive deficits at baseline. A total of 23 prospective studies comprising 11,486 participants were included for analysis. Extracted data was pooled, reviewed and meta-analysed separately for global cognition, executive function, memory and attention. The pooled effect size for the association between cerebral SVD and cognitive decline was for global cognition -0.10 [-0.14; -0.05], for executive functioning -0.18 [-0.24; - 0.11], for memory -0.12 [-0.17; -0.07], and for attention -0.17 [-0.23; -0.11]. Results for the association of individual MRI markers of cerebral SVD were statistically significant for WMH and global cognition -0.15 [-0.24; -0.06], WMH and executive function -0.23 [-0.33; -0.13], WMH and memory -0.19 [-0.29; -0.09], WMH and attention -0.24 [-0.39; -0.08], CMB and executive function -0.07 [-0.13; -0.02], CMB and memory -0.11 [-0.21; -0.02] and CMB and attention -0.13 [-0.25; -0.02]. In conclusion, presence of MRI markers of cerebral SVD were found to predict an increased risk of cognitive decline in relatively healthy older adults. While WMH were found to significantly affect all cognitive domains, CMB influenced decline in executive functioning over time as well as (in some studies) decline in memory and attention.

MRI phenotypes of glioblastomas early after treatment are suggestive of overall patient survival.

Background: Distinguishing true tumor progression (TP) from treatment-induced abnormalities (eg, pseudo-progression (PP) after radiotherapy) on conventional MRI scans remains challenging in patients with a glioblastoma. We aimed to establish brain MRI phenotypes of glioblastomas early after treatment by combined analysis of structural and perfusion tumor characteristics and assessed the relation with recurrence rate and overall survival time. Methods: Structural and perfusion MR images of 67 patients at 3 months post-radiotherapy were visually scored by a neuroradiologist. In total 23 parameters were predefined and used for hierarchical clustering analysis. Progression status was assessed based on the clinical course of each patient 9 months after radiotherapy (or latest available). Multivariable Cox regression models were used to determine the association between the phenotypes, recurrence rate, and overall survival. Results: We established 4 subgroups with significantly different tumor MRI characteristics, representing distinct MRI phenotypes of glioblastomas: TP and PP rates did not differ significantly between subgroups. Regression analysis showed that patients in subgroup 1 (characterized by having mostly small and ellipsoid nodular enhancing lesions with some hyper-perfusion) had a significant association with increased mortality at 9 months (HR: 2.6 (CI: 1.1-6.3); P = .03) with a median survival time of 13 months (compared to 22 months of subgroup 2). Conclusions: Our study suggests that distinct MRI phenotypes of glioblastomas at 3 months post-radiotherapy can be indicative of overall survival, but does not aid in differentiating TP from PP. The early prognostic information our method provides might in the future be informative for prognostication of glioblastoma patients.

White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis.

T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

White matter hyperintensity shape is associated with long-term dementia risk.

INTRODUCTION: We aimed to investigate the association between white matter hyperintensity (WMH) shape and volume and the long-term dementia risk in community-dwelling older adults. METHODS: Three thousand seventy-seven participants (mean age: 75.6 ± 5.2 years) of the Age Gene/Environment Susceptibility (AGES)-Reykjavik study underwent baseline 1.5T brain magnetic resonance imaging and were followed up for dementia (mean follow-up: 9.9 ± 2.6 years). RESULTS: More irregular shape of periventricular/confluent WMH (lower solidity (hazard ratio (95% confidence interval) 1.34 (1.17 to 1.52), p < .001) and convexity 1.38 (1.28 to 1.49), p < .001); higher concavity index 1.43 (1.32 to 1.54), p < .001) and fractal dimension 1.45 (1.32 to 1.58), p < .001)), higher total WMH volume (1.68 (1.54 to 1.87), p < .001), higher periventricular/confluent WMH volume (1.71 (1.55 to 1.89), p < .001), and higher deep WMH volume (1.17 (1.08 to 1.27), p < .001) were associated with an increased long-term dementia risk. DISCUSSION: WMH shape markers may in the future be useful in determining patient prognosis and may aid in patient selection for future preventive treatments in community-dwelling older adults.

Study protocol of IMAGINE-HD: Imaging iron accumulation and neuroinflammation with 7T-MRI + CSF in Huntington's disease.

INTRODUCTION: Strong evidence suggests a significant role for iron accumulation in the brain in addition to the well-documented neurodegenerative aspects of Huntington's disease (HD). The putative mechanisms by which iron is linked to the HD pathogenesis are multiple, including oxidative stress, ferroptosis and neuroinflammation. However, no previous study in a neurodegenerative disease has linked the observed increase of brain iron accumulation as measured by MRI with well-established cerebrospinal fluid (CSF) and blood biomarkers for iron accumulation, or with associated processes such as neuroinflammation. This study is designed to link quantitative data from iron levels and neuroinflammation metabolites obtained from 7T MRI of HD patients, with specific and well-known clinical biofluid markers for iron accumulation, neurodegeneration and neuroinflammation. Biofluid markers will provide quantitative measures of overall iron accumulation, neurodegeneration and neuroinflammation, while MRI measurements on the other hand will provide quantitative spatial information on brain pathology, neuroinflammation and brain iron accumulation, which will be linked to clinical outcome measures. METHODS: This is an observational cross-sectional study, IMAGINE-HD, in HD gene expansion carriers and healthy controls. We include premanifest HD gene expansion carriers and patients with manifest HD in an early or moderate stage. The study includes a 7T MRI scan of the brain, clinical evaluation, motor, functional, and neuropsychological assessments, and sampling of CSF and blood for the detection of iron, neurodegenerative and inflammatory markers. Quantitative Susceptibility Maps will be reconstructed using T2* weighted images to quantify brain iron levels and Magnetic Resonance Spectroscopy will be used to obtain information about neuroinflammation by measuring cell-specific intracellular metabolites' level and diffusion. Age and sex matched healthy subjects are included as a control group. DISCUSSION: Results from this study will provide an important basis for the evaluation of brain iron levels and neuroinflammation metabolites as an imaging biomarker for disease stage in HD and their relationship with the salient pathomechanisms of the disease on the one hand, and with clinical outcome on the other.

The prevalence and severity of fatigue in meningioma patients and its association with patient-, tumor- and treatment-related factors.

Background: Fatigue is a commonly reported and severe symptom in primary brain tumor patients, but the exact occurrence in meningioma patients is unknown. This study aimed to determine the frequency and severity of fatigue in meningioma patients as well as associations between the level of fatigue and patient-, tumor-, and treatment-related factors. Methods: In this multicenter cross-sectional study, meningioma patients completed questionnaires on fatigue (MFI-20), sleep (PSQI), anxiety and depression (HADS), tumor-related symptoms (MDASI-BT), and cognitive functioning (MOS-CFS). Multivariable regression models were used to evaluate the independent association between fatigue and each patient-, tumor-, and treatment-related factor separately, corrected for relevant confounders. Results: Based on predetermined in- and exclusion criteria, 275 patients, on average 5.3 (SD = 2.0) year since diagnosis, were recruited. Most patients had undergone resection (92%). Meningioma patients reported higher scores on all fatigue subscales compared to normative data and 26% were classified as fatigued. Having experienced a complication due to resection (OR 3.6, 95% CI: 1.8-7.0), having received radiotherapy (OR 2.4, 95% CI: 1.2-4.8), a higher number of comorbidities (OR 1.6, 95% CI: 1.3-1.9) and lower educational level (low level as reference; high level OR 0.3, 95% CI: 0.2-0.7) were independently associated with more fatigue. Conclusions: Fatigue is a frequent problem in meningioma patients even many years after treatment. Both patient- and treatment-related factors were determinants of fatigue, with the treatment-related factors being the most likely target for intervention in this patient population.

Clinical outcome in patients with suspected inflammatory neuropsychiatric lupus treated with immunosuppression: an observational cohort study.

BACKGROUND: The short-term and long-term outcome of inflammatory neuropsychiatric SLE (NPSLE) with immunosuppressive treatment is largely unknown. We used clinical data from our tertiary referral centre for NPSLE to investigate the type of inflammatory NPSLE manifestations, type of immunosuppressive treatment prescribed for these manifestations and clinical outcomes. METHODS: All patients with SLE visiting the Leiden University Medical Centre NPSLE clinic between 2007 and 2021 receiving immunosuppressive therapy for neuropsychiatric symptoms were included. Clinical, immunological and radiological information was collected in as standardised way during a 1-day multidisciplinary assessment. In a multidisciplinary consensus meeting, the presence of NPSLE and the type of NPSLE manifestations and treatment were determined. For this study, short-term (0-6 months) and long-term outcomes (7-24 months) of the NP symptoms were assessed by two independent readers and scored on a 7-point Likert scale, ranging from death to resolved. RESULTS: In total, 95 out of 398 (24%) patients visiting the NPSLE clinic between 2007 and 2021 received any form of immunosuppressive treatment for 101 separate NPSLE events. The most common NP manifestation was cognitive dysfunction (50%) as identified by formal cognitive assessment, often present in combination with other NPSLE manifestations. Treatment modalities were induction (24%), induction and maintenance (73%) and other therapy (3%). The treatments mostly consisted of (combinations of) prednisone (97%), methylprednisolone (53%), azathioprine (generally 2 mg/kg daily) (49%) and cyclophosphamide (generally induction 750 mg/m2 every 4 weeks for 24 weeks or 500mg biweekly for 12 weeks) (42%). Short-term outcome showed improvement on the Likert scale in 73% (improved: 22%, much improved: 29%, resolved: 22%), no change in 21% and worsening in 6% of patients. Long-term outcome was available for 78 out of 101 events and showed improvement in 70% (improved: 14%, much improved: 28%, resolved: 28%), no change in 17%, worsening in 10% and death in 3% of patients (none directly NPSLE-related). CONCLUSION: The outcome of inflammatory NPSLE after immunosuppressive treatment is generally good, with improvement of neuropsychiatric symptoms occuring in approximately 70% of events.

Postoperative delirium is associated with grey matter brain volume loss.

Delirium is associated with long-term cognitive dysfunction and with increased brain atrophy. However, it is unclear whether these problems result from or predisposes to delirium. We aimed to investigate preoperative to postoperative brain changes, as well as the role of delirium in these changes over time. We investigated the effects of surgery and postoperative delirium with brain MRIs made before and 3 months after major elective surgery in 299 elderly patients, and an MRI with a 3 months follow-up MRI in 48 non-surgical control participants. To study the effects of surgery and delirium, we compared brain volumes, white matter hyperintensities and brain infarcts between baseline and follow-up MRIs, using multiple regression analyses adjusting for possible confounders. Within the patients group, 37 persons (12%) developed postoperative delirium. Surgical patients showed a greater decrease in grey matter volume than non-surgical control participants [linear regression: B (95% confidence interval) = -0.65% of intracranial volume (-1.01 to -0.29, P < 0.005)]. Within the surgery group, delirium was associated with a greater decrease in grey matter volume [B (95% confidence interval): -0.44% of intracranial volume (-0.82 to -0.06, P = 0.02)]. Furthermore, within the patients, delirium was associated with a non-significantly increased risk of a new postoperative brain infarct [logistic regression: odds ratio (95% confidence interval): 2.8 (0.7-11.1), P = 0.14]. Our study was the first to investigate the association between delirium and preoperative to postoperative brain volume changes, suggesting that delirium is associated with increased progression of grey matter volume loss.

Carotid Artery Stenosis and Progression of Hemispheric Brain Atrophy: The SMART-MR Study.

INTRODUCTION: It has been hypothesized that carotid artery stenosis (CAS) may lead to greater atrophy of subserved brain regions; however, prospective studies on the impact of CAS on progression of hemispheric brain atrophy are lacking. We examined the association between CAS and progression of hemispheric brain atrophy. METHODS: We included 654 patients (57 ± 9 years) of the SMART-MR study, a prospective cohort study of patients with manifest arterial disease. Patients had baseline CAS duplex measurements and a 1.5T brain MRI at baseline and after 4 years of follow-up. Mean change in hemispheric brain volumes (% of intracranial volume [ICV]) was estimated between baseline and follow-up for left-sided and right-sided CAS across three degrees of stenosis (mild [≤29%], moderate [30-69%], and severe [≥70%]), adjusting for demographics, cerebrovascular risk factors, and brain infarcts. RESULTS: Mean decrease in left and right hemispheric brain volumes was 1.15% ICV and 0.82% ICV, respectively, over 4 years of follow-up. Severe right-sided CAS, compared to mild CAS, was associated with a greater decrease in volume of the left hemisphere (B = -0.49% ICV, 95% CI: -0.86 to -0.13) and more profoundly of the right hemisphere (B = -0.90% ICV, 95% CI: -1.27 to -0.54). This pattern was independent of cerebrovascular risk factors, brain infarcts, and white matter hyperintensities on MRI, and was also observed when accounting for the presence of severe bilateral CAS. Increasing degrees of left-sided CAS, however, was not associated with greater volume loss of the left or right hemisphere. CONCLUSIONS: Our data indicate that severe (≥70%) CAS could represent a risk factor for greater ipsilateral brain volume loss, independent of cerebrovascular risk factors, brain infarcts, or white matter hyperintensities on MRI. Further longitudinal studies in other cohorts are warranted to confirm this novel finding.

Tract-based white matter hyperintensity patterns in patients with systemic lupus erythematosus using an unsupervised machine learning approach.

Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

White matter hyperintensity shape is associated with cognitive functioning - the SMART-MR study.

White matter hyperintensity (WMH) shape has been associated with the severity of the underlying brain pathology, suggesting it is a potential neuroimaging marker of WMH impact on brain function. In 563 patients with vascular disease (58 ± 10 years), we examined the relationship between WMH volume, shape, and cognitive functioning. WMH volume and shape were automatically determined on 1.5T brain MRI data. Standardized linear regression analyses estimated the association between WMH volume and shape (concavity index, solidity, convexity, fractal dimension, and eccentricity) and memory and executive functioning, adjusted for age, sex, educational level, and reading ability. Larger WMH volumes were associated with lower executive functioning Z-scores (b (95%-CI): -0.09 (-0.17;-0.01)). Increased shape complexity of periventricular/confluent WMH associated with lower executive functioning (concavity index +1SD: -0.13 (-0.20;-0.06); solidity -1SD: -0.09 (-0.17;-0.02)) and lower memory function (fractal dimension +1SD: -0.10 (-0.18;-0.02)). Of note, the association between concavity index and executive functioning was independent of WMH volume (-0.12 (-0.19;-0.04)). Our results suggest that WMH shape contains additional information about WMH burden, not otherwise captured by WMH volume.

Different cardiovascular risk factors are related to distinct white matter hyperintensity MRI phenotypes in older adults.

The underlying mechanisms of the association between cardiovascular risk factors and a higher white matter hyperintensity (WMH) burden are unknown. We investigated the association between cardiovascular risk factors and advanced WMH markers in 155 non-demented older adults (mean age: 71 ± 5 years). The association between cardiovascular risk factors and quantitative MRI-based WMH shape and volume markers were examined using linear regression analysis. Presence of hypertension was associated with a more irregular shape of periventricular/confluent WMH (convexity (B (95 % CI)): -0.12 (-0.22--0.03); concavity index: 0.06 (0.02-0.11)), but not with total WMH volume (0.22 (-0.15-0.59)). Presence of diabetes was associated with deep WMH volume (0.89 (0.15-1.63)). Body mass index or hyperlipidemia showed no association with WMH markers. In conclusion, different cardiovascular risk factors seem to be related to a distinct pattern of WMH shape markers in non-demented older adults. These findings may suggest that different underlying cardiovascular pathological mechanisms lead to different WMH MRI phenotypes, which may be valuable for early detection of individuals at risk for stroke and dementia.

Prevalence, risk factors, and long-term outcomes of cerebral ischemia in hospitalized COVID-19 patients - study rationale and protocol of the CORONIS study: A multicentre prospective cohort study.

Background: COVID-19 is often complicated by thrombo-embolic events including ischemic stroke. The underlying mechanisms of COVID-19-associated ischemic stroke, the incidence and risk factors of silent cerebral ischemia, and the long-term functional outcome in these patients are currently unknown. Patients and methods: CORONavirus and Ischemic Stroke (CORONIS) is a multicentre prospective cohort study investigating the prevalence, risk factors and long-term incidence of (silent) cerebral ischemia, and the long-term functional outcome among patients with COVID-19. We aim to include 200 adult patients hospitalized with COVID-19 without symptomatic ischemic stroke to investigate the prevalence of silent cerebral ischemia compared with 60 (matched) controls with MRI. In addition, we will identify potential risk factors and/or causes of cerebral ischemia in COVID-19 patients with (n = 70) or without symptomatic stroke (n = 200) by means of blood sampling, cardiac workup and brain MRI. We will measure functional outcome and cognitive function after 3 and 12 months with standardized questionnaires in all patients with COVID-19. Finally, the long-term incidence of (new) silent cerebral ischemia in patients with COVID-19 will be assessed with follow up MRI (n = 120). Summary: The CORONIS study is designed to add further insight into the prevalence, long-term incidence and risk factors of cerebral ischemia, and the long-term functional outcome in hospitalized adult patients with COVID-19.

MRI-Based Classification of Neuropsychiatric Systemic Lupus Erythematosus Patients With Self-Supervised Contrastive Learning.

INTRODUCTION/PURPOSE: Systemic lupus erythematosus (SLE) is a chronic auto-immune disease with a broad spectrum of clinical presentations, including heterogeneous neuropsychiatric (NP) syndromes. Structural brain abnormalities are commonly found in SLE and NPSLE, but their role in diagnosis is limited, and their usefulness in distinguishing between NPSLE patients and patients in which the NP symptoms are not primarily attributed to SLE (non-NPSLE) is non-existent. Self-supervised contrastive learning algorithms proved to be useful in classification tasks in rare diseases with limited number of datasets. Our aim was to apply self-supervised contrastive learning on T1-weighted images acquired from a well-defined cohort of SLE patients, aiming to distinguish between NPSLE and non-NPSLE patients. SUBJECTS AND METHODS: We used 3T MRI T1-weighted images of 163 patients. The training set comprised 68 non-NPSLE and 34 NPSLE patients. We applied random geometric transformations between iterations to augment our data sets. The ML pipeline consisted of convolutional base encoder and linear projector. To test the classification task, the projector was removed and one linear layer was measured. Validation of the method consisted of 6 repeated random sub-samplings, each using a random selection of a small group of patients of both subtypes. RESULTS: In the 6 trials, between 79% and 83% of the patients were correctly classified as NPSLE or non-NPSLE. For a qualitative evaluation of spatial distribution of the common features found in both groups, Gradient-weighted Class Activation Maps (Grad-CAM) were examined. Thresholded Grad-CAM maps show areas of common features identified for the NPSLE cohort, while no such communality was found for the non-NPSLE group. DISCUSSION/CONCLUSION: The self-supervised contrastive learning model was effective in capturing common brain MRI features from a limited but well-defined cohort of SLE patients with NP symptoms. The interpretation of the Grad-CAM results is not straightforward, but indicates involvement of the lateral and third ventricles, periventricular white matter and basal cisterns. We believe that the common features found in the NPSLE population in this study indicate a combination of tissue loss, local atrophy and to some extent that of periventricular white matter lesions, which are commonly found in NPSLE patients and appear hypointense on T1-weighted images.

A cluster of blood-based protein biomarkers reflecting coagulation relates to the burden of cerebral small vessel disease.

Biological processes underlying cerebral small vessel disease (cSVD) are largely unknown. We hypothesized that identification of clusters of inter-related bood-based biomarkers that are associated with the burden of cSVD provides leads on underlying biological processes. In 494 participants (mean age 67.6 ± 8.7 years; 36% female; 75% cardiovascular diseases; 25% reference participants) we assessed the relation between 92 blood-based biomarkers from the OLINK cardiovascular III panel and cSVD, using cluster-based analyses. We focused particularly on white matter hyperintensities (WMH). Nineteen biomarkers individually correlated with WMH ratio (r range: 0.16-0.27, Bonferroni corrected p-values <0.05), of which sixteen biomarkers formed one biomarker cluster. Pathway analysis showed that this biomarker cluster predominantly reflected coagulation processes. This cluster related also significantly to other cSVD manifestations (lacunar infarcts, microbleeds, and enlarged perivascular spaces), which supports generalizability beyond WMHs. To study possible causal effects of biological processes reflected by the cluster we performed a mediation analysis that showed a mediation effect of the cluster on the relation between age and WMH ratio (proportion mediated 17%), and hypertension and WMH-volume (proportion mediated 21%). In conclusion, we identified a cluster of blood-based biomarkers reflecting coagulation, that is related to manifestations of cSVD, corroborating involvement of coagulation abnormalities in the etiology of cSVD.