Deep White Matter Lesions Research Articles

Impact of atrial fibrillation on the cognitive decline in Alzheimer’s disease

BackgroundAtrial fibrillation (AF) is a strong risk factor for Alzheimer’s disease (AD) independent of ischemic stroke. However, the clinicopathological impact of AF on the severity of AD has not been well elucidated. We aimed to investigate the clinical differences between dementia patients with AF and those without AF by means of imaging data.MethodsFollowing approval from the institutional ethics committee, patients with newly diagnosed AD or amnestic mild cognitive impairment (aMCI) were retrospectively screened (n = 170, 79.5 ± 7.4 years old). Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on the MRI data, the cerebral volume, cerebral microbleeds (CMBs), periventricular white matter lesions (WMLs), and deep WMLs were evaluated. The regional cerebral blood flow (rCBF) was measured using 123I-IMP SPECT.ResultsOf the patients, 14 (8.2%) and 156 (91.8%) had AF (AF group) and sinus rhythm (SR group), respectively. The AF group had significantly lower MMSE scores than the SR group (average [standard deviation (SD)]: 19.4 [4.4] and 22.0 [4.4], respectively; p = 0.0347). Cerebral volume and CMBs did not differ between the two groups. The periventricular WMLs, but not the deep WMLs, were significantly larger in the AF group than in the SR group (mean [SD] mL: 6.85 [3.78] and 4.37 [3.21], respectively; p = 0.0070). However, there was no significant difference in rCBF in the areas related to AD pathology between the two groups.ConclusionAD and aMCI patients with AF showed worse cognitive decline along with larger periventricular WMLs compared to those with SR, although the reduction of rCBF was not different between patients with AF and SR. The white matter lesions may be a more important pathology than the impairment of cerebral blood flow in dementia patients with AF. A larger study is needed to confirm our findings in the future.

White Matter Lesions Predominantly Located in Deep White Matter Represent Embolic Etiology Rather Than Small Vessel Disease

We investigated the correlation between the deep distribution of white matter hyperintensity (WMH) (dWMH: WMH in deep and corticomedullary areas, with minimal periventricular WMH) and a positive agitated saline contrast echocardiography result. We retrospectively recruited participants with comprehensive dementia evaluations, an agitated saline study, and brain imaging. The participants were classified into two groups according to WMH-distributions: dWMH and dpWMH (mainly periventricular WMH with or without deep WMH.) We hypothesized that dWMH is more likely associated with embolism, whereas dpWMH is associated with small-vessel diseases. We compared the clinical characteristics, WMH-distributions, and positive rate of agitated saline studies between the two groups. Among 90 participants, 27 and 12 met the dWMH and dpWMH criteria, respectively. The dWMH-group was younger (62.2±7.5 vs. 78.9±7.3, p<0.001) and had a lower prevalence of hypertension (29.6% vs. 75%, p=0.008), diabetes mellitus (3.7% vs. 25%, p=0.043), and hyperlipidemia (33.3% vs. 83.3%, p=0.043) than the dpWMH-group. Regarding deep white matter lesions, the number of small lesions (<3 mm) was higher in the dWMH-group(10.9±9.7) than in the dpWMH-group (3.1±6.4) (p=0.008), and WMH was predominantly distributed in the border-zones and corticomedullary areas. Most importantly, the positive agitated saline study rate was higher in the dWMH-group than in the dpWMH-group (81.5% vs. 33.3%, p=0.003). The dWMH-group with younger participants had fewer cardiovascular risk factors, showed more border-zone-distributions, and had a higher agitated saline test positivity rate than the dpWMH-group, indicating that corticomedullary or deep WMH-distribution with minimal periventricular WMH suggests embolic etiologies.

Clinical Implications of Internal Carotid Arterial Tortuosity in Patients with White Matter Hyperintensities

AbstractBackgroundWhite matter hyperintensities (WMHs) are observed frequently on MRI in elderly and associated with cognitive dysfunction. Many studies focused on intracranial small vessel disease (SVD), however, few studies linked WMHs with changes of extracranial large feeding arteries. We aimed to investigate the effects of internal carotid artery (ICA) tortuosity changes through quantitative MR Angiography.MethodFifty‐seven patients (age: 72.98±5.62; 32 females/25 males) with WMHs were included. WMHs lesions were semi‐automatically segmented on FLAIR images. ICAs were segmented on the TOF images to generate tortuosity quantitative metrics, including tortuosity index (TI), inflection count metric (ICM), and ICA angle (Figure 1). According to the Fazekas scores, patients were categorized into mild, moderate and severe groups as summarized in Table 1. One‐way ANOVA analyses were applied to reveal the difference of averaged bilateral ICAs' tortuosity measurements. Pearson's correlation coefficients were calculated to quantitatively investigate the relationship between tortuosity and volumes of lesions that are apart from the ventricle in subcortical white matter, i.e., deep white matter lesions (DWMLs), as well as the lesions attached with the ventricular system, i.e., periventricular white matter lesions (PVWMLs).ResultPatients with higher Fazekas scores have higher TI and ICM, indicating higher tortuosity (Figure 2). The correlation results showed that TI and ICM were positively correlated with DWMLs volumes (r = 0.33, P&lt; 0.05; r = 0.4, P&lt; 0.01), however, they did not show associations with PVWMLs. While there's no correlation between averaged bilateral ICA angles and DWMLs or PVWMLs, we found significant correlations between left ICA angles and DWML volumes on left brain (r =0.56, P &lt; 0.005) as well as between right ICA angles and DWML volumes on right brain (r = 0.49, P &lt; 0.05) (Figure 3).ConclusionTortuosity measurements derived from TOF images showed that subjects with higher degree of ICA tortuosity had higher lesion volumes of DWMLs not PVWMLs, indicating DWMLs may have different etiologies such as ischemic origin. The findings also highlight the importance of ICA angle as a risk factor for WMHs development which might be associated with the local hemodynamic shear stress at the bulb, where the ICA plaques are often developed.

Percentage brain volume change in multiple sclerosis mainly reflects white matter and cortical volume.

Brain atrophy in multiple sclerosis (MS), as measured by percentage brain volume change (PBVC) from brain magnetic resonance imaging (MRI), has been established as an outcome parameter in clinical trials. It is unknown to what extent volume changes within different brain tissue compartments contribute to PBVC. We analyzed pairs of MRI scans (at least 6 months apart) in 600 patients with relapsing-remitting MS. Multiple regression revealed that PBVC mainly reflects volume loss of white and cortical gray matter, while deep gray matter and white matter lesions were less represented. Our findings aid the interpretation of PBVC changes in MS.

Impact of constipation on progression of Alzheimer's disease: A retrospective study.

In terms of the gut-brain axis, constipation has been considered to be an important factor of neurodegenerative diseases, although the exact mechanism is still controversial. Herein, we aimed to investigate the contribution of constipation to the progression of dementia in a retrospective study. Patients of Alzheimer's disease(AD) and amnestic mild cognitive impairment were consecutively screened between January 2015 and December 2020, and those of whom brain MRI and neuropsychological tests were performed twice were enrolled in this study. Participants were classified into with constipation (Cons[+], n=20) and without constipation (Cons[-], n=64) groups. Laboratory data at the first visit were used. Regression analysis was performed in MMSE, ADAS-Cog, and the volumes of hippocampus on MRI-MPRAGE images and deep white matter lesions (DWMLs) on MRI-FLAIR images obtained at two different time points. The main finding was that the Cons[+] group showed 2.7 times faster decline in cognitive impairment compared with the Cons[-] group, that is, the liner coefficients of ADAS-Cog were 2.3544 points/year in the Cons[+] and 0.8592 points/year in the Cons[-] groups. Ancillary, changes of DWMLs showed significant correlation with the time span (p < 0.01), and the liner coefficients of DWMLs were 24.48 ml/year in the Cons[+] and 14.83 ml/year in the Cons[-] group, although annual rate of hippocampal atrophy was not different between the two groups. Moreover, serum homocysteine level at baseline was significantly higher in the Cons[+] group than Cons[-] group (14.6 ± 6.4 and 11.5 ± 4.2nmol/ml, respectively: p=0.03). There is a significant correlation between constipation and faster progression of AD symptoms along with expansion of DWMLs.

Imaging Characteristics for Predicting Cognitive Impairment in Patients With Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy.

ObjectivesPatients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) show various clinical symptoms, including migraine, recurrent stroke, and cognitive impairment. We investigated the associations between magnetic resonance imaging (MRI) markers of small vessel disease and neuropsychological tests and identified the MRI characteristics for predicting cognitive impairment in patients with CADASIL.MethodsSubjects included 60 CADASIL patients diagnosed with genetic tests and registered in the Japanese CADASIL REDCap database between June 2016 and December 2020. Patient information including clinical data, modified Rankin Scale (mRS); MRI findings of small vessel disease including periventricular and deep white matter lesions (WML), lacunar infarcts, and cerebral microbleeds (CMBs); and neuropsychological tests, including the Japanese version of the Mini-Mental State Examination (MMSE), the Japanese version of the Montreal Cognitive Assessment (MoCA-J), and the Frontal Assessment Battery (FAB), were evaluated.ResultsData from 44 CADASIL patients were eligible for this study, compared between patients with and without dementia. Regarding the neuroimaging findings, the Fazekas score of periventricular and deep WML was higher in patients with dementia (periventricular, p = 0.003; deep, p = 0.009). The number of lacunar infarcts was higher in patients with dementia (p = 0.001). The standardized partial regression coefficient (SPRC) in MoCA-J was 0.826 (95% CI, 0.723–0.942; p = 0.005) for the number of CMBs. The SPRC in MMSE was 0.826 (95% CI, 0.719–0.949; p = 0.007) for the number of CMBs. The SPRC for FAB decreased significantly to 0.728 (95% CI, 0.551–0.960; p = 0.024) for the number of lacunar infarcts. Receiver operating characteristic (ROC) curves for dementia showed that in the number of lacunar infarcts, a cut-off score of 5.5 showed 90.9% sensitivity and 61.1% specificity. For the number of CMBs, a cut-off score of 18.5 showed 45.5% sensitivity and 100% specificity.ConclusionThe characteristic MRI findings were that CADASIL patients with dementia had severe WML, both periventricular and deep, and a larger number of lacunar infarcts than those without dementia. The risk of dementia may be associated with ≥ 6 lacunar infarcts, ≥19 CMBs, or a Fazekas scale score of 3 in periventricular and deep WML.

Vascular Lesions and Brain Atrophy in Alzheimer's, Vascular and Mixed Dementia: An Optimized 3T MRI Protocol Reveals Distinctive Radiological Profiles.

Vascular lesions may be a common finding also in Alzheimer's dementia, but their role on cognitive status is uncertain. The study aims to investigate their distribution in patients with Alzheimer's, vascular or mixed dementia and detect any distinctive neuroradiological profiles. Seventy-six subjects received a diagnosis of Alzheimer's (AD=32), vascular (VD=26) and mixed (MD=18) dementia. Three independent raters assessed the brain images acquired with an optimized 3T MRI protocol (including (3D FLAIR, T1, SWI, and 2D coronal T2 sequences) using semiquantitative scales for vascular lesions (periventricular lesions (PVL), deep white matter lesions (DWML), deep grey matter lesions (DGML), enlarged perivascular spaces (PVS), and microbleeds (MB)) and brain atrophy (medial temporal atrophy (MTA), posterior atrophy (PA), global cortical atrophy- frontal (GCA-F) and Evans' index). Raters reached a good-to-excellent agreement for all scales (ICC ranging from 0.78-0.96). A greater number of PVL (p<0.001), DWML (p<0.001), DGML (p=0.010), and PVS (p=0.001) was observed in VD compared to AD, while MD showed a significant greater number of PVL (p=0.001), DWML (p=0.002), DGML (p=0.018), and deep and juxtacortical MB (p=0.006 and p<0.001, respectively). Comparing VD and MD, VD showed a higher number of PVS in basal ganglia and centrum semiovale (p=0.040), while MD showed more deep and juxtacortical MB (p=0.042 and p=0.022, respectively). No significant difference was observed in scores of cortical atrophy scales and Evans' index among the three groups. The proposed MRI protocol represents a useful advancement in the diagnostic assessment of patients with cognitive impairment by more accurately detecting vascular lesions, mainly microbleeds, without a significant increase in time and resource expenditure. Our findings confirm that white and grey matter lesions predominate in vascular and mixed dementia, whereas deep and juxtacortical microbleeds predominate in mixed dementia, suggesting that cerebral amyloid angiopathy could be the main underlying pathology.

Fundus Changes Evaluated by OCTA in Patients With Cerebral Small Vessel Disease and Their Correlations: A Cross-Sectional Study.

ObjectiveTo detect fundus changes in patients with cerebral small vessel disease (CSVD) using optical coherence tomography angiography (OCTA) and to investigate the correlations between CSVD and fundus changes.MethodsFrom January 2019 to January 2020, patients diagnosed with CSVD by magnetic resonance imaging (MRI) were enrolled in our study and received fundus examinations using OCTA. CSVD was defined as white matter hyperintensities, enlarged perivascular spaces, lacunes, or microbleeds on MRI. OCTA parameters included foveal avascular zone areas, retinal nerve fiber layer thickness, and capillary densities of the superficial retinal capillary plexuses, deep retinal capillary plexuses, and the radial peripapillary capillary network of the disc. Univariate and multivariate logistic regression analyses were performed to explore the correlation between CSVD and fundus changes.ResultsA total of 115 patients (40% male) were enrolled and analyzed, and the mean age was 65.11 ± 11.23 years. After multivariate logistic regression analysis, the radial peripapillary capillary network density was negatively correlated with severity of deep white matter lesions (OR: 0.909; 95% CI: 0.828–0.998; p = 0.046) and perivascular spaces (OR: 0.881; 95% CI: 0.779–0.995; p = 0.041). Parafoveal vessel densities of the superficial retinal capillary plexuses were independently correlated with lacunes (OR: 0.889; 95% CI: 0.817–0.967; p = 0.006).ConclusionOCTA parameters were correlated with CSVD, indicating that OCTA is a potential method for CSVD screening.

Lacunar infarction aggravates the cognitive deficit in the elderly with white matter lesion.

Cerebral white matter lesion (WML) and lacunar infarction (LI) were primary causes of cognitive deficit. Our study aimed to investigate the correlation between LI and cognitive deficit in the elderly with WML. A total of 118 participants (96 WML patients and 22 controls) were consecutively enrolled according to neuroimaging diagnosis of magnetic resonance imaging for this retrospective study. Neuroimaging evaluation and cognitive function assessment were analyzed. Compared with the controls, moderate and severe WML groups had significantly lower scores of Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA). Most cognitive domains of MOCA scores decreased, corresponding to the severity of WMLs. While there was no significant difference in score of MMSE between deep WML (DWML) and periventricular WML (PVL) groups, the scores of visuospatial/executive and naming function domains of MOCA appeared to be low in the DWML group. The scores of MMSE and MOCA were higher in only WMLs (WML−) group than WMLs combined with LIs (WML+) group, except for the naming cognitive domain. Moreover, LIs were independently correlated with the cognitive deficit in the elderly with WMLs. In the elderly with WMLs, the presence of LIs is associated with further aggravation of cognitive deficit.

Cortical and white matter lesion topology influences focal corpus callosum atrophy in multiple sclerosis.

Background and PurposeCorpus callosum (CC) atrophy is a strong predictor of multiple sclerosis (MS) disability but the contributing pathological mechanisms remain uncertain. We aimed to apply advanced MRI to explore what drives the often nonuniform callosal atrophy.MethodsProspective brain 7 Tesla and 3 Tesla Human Connectom Scanner MRI were performed in 92 MS patients. White matter, leukocortical, and intracortical lesions were manually segmented. FreeSurfer was used to segment the CC and topographically classify lesions per lobe or as deep white matter lesions. Regression models were calculated to predict focal CC atrophy.ResultsThe frontal and parietal lobes contained the majority (≥80%) of all lesion classifications in both relapsing‐remitting and secondary progressive MS subtypes. The anterior subsection of the CC had the smallest proportional volume difference between subtypes (11%). Deep, temporal, and occipital white matter lesions, and occipital intracortical lesions were the strongest predictors of middle‐posterior callosal atrophy (adjusted R 2 = .54‐.39, P < .01).ConclusionsBoth white matter and cortical lesions contribute to regional corpus callosal atrophy. The lobe‐specific lesion topology does not fully explain the inhomogeneous CC atrophy.

Neuroinflammation as potential precursor of leukoencephalopathy in early-stage breast cancer patients: A cross-sectional PET-MRI study.

BackgroundAlthough chemotherapy-induced leukoencephalopathy has been described in case and cohort studies, literature remains inconclusive about its prevalence and mechanisms. Therefore, we investigated the presence of leukoencephalopathy after multiagent chemotherapy in women treated for breast cancer and potential underlying neuroinflammatory processes.MethodsIn this exploratory study, 15 chemotherapy-treated and 15 age-matched chemotherapy-naïve patients with early-stage breast cancer, as well as 15 healthy controls underwent simultaneous PET-MR neuroimaging, including T1-weighted MPRAGE, T2-weighted FLAIR and dynamic PET with the 18-kDA translocator protein (TSPO) radioligand [18F]DPA-714. Total and regional (juxtacortical, periventricular, deep white matter and infratentorial) lesion burden were compared between the groups with one-way ANOVA. With paired t-tests, [18F]DPA-714 volume of distribution [VT, including partial volume correction (PVC)] in lesioned and normal appearing white matter (NAWM) were compared within subjects, to investigate inflammation. Finally, two general linear models were used to examine the predictive values of neurofilament light-chain (NfL) serum levels on (1) total lesion burden or (2) PVC [18F]DPA-714 VT of lesions showing elevated inflammation.ResultsNo significant differences were found in total or localized lesion burden. However, significantly higher (20–45%) TSPO uptake was observed in juxtacortical lesions (p ≤ 0.008, t ≥ 3.90) compared to NAWM in both cancer groups, but only persisted for chemotherapy-treated patients after PVC (p = 0.005, t = 4.30). NfL serum levels were not associated with total lesion volume or tracer uptake in juxtacortical lesions.ConclusionThis multimodal neuroimaging study suggests that neuroinflammatory processes could be involved in the development of juxtacortical, but not periventricular or deep white matter, leukoencephalopathy shortly after chemotherapy for early-stage breast cancer.

White Matter Lesions May Aid in Differentiating Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Idiopathic normal pressure hydrocephalus (iNPH) is often misdiagnosed as Alzheimer's disease (AD) due to overlapping pathophysiology and similar imaging characteristics, including ventricular enlargement and increased white matter lesions (WMLs). To compare the extent and distribution of WMLs directly between iNPH and AD and examine the association with underlying pathophysiology. Twelve patients with iNPH (mean age: 78.08 years; 5 females), 20 with AD (mean age: 75.40 years; 13 females), and 10 normal cognition (NC) participants (mean age: 76.60 years; 7 females) were recruited. The extent and distribution of WMLs and the lateral ventricular volume (LV-V) were evaluated on MRI using voxel-based morphometry analysis. Concentrations of cerebrospinal fluid biomarkers, such as amyloid-β protein (Aβ)42, Aβ40, Aβ38, and tau species, were also measured. Risk factors for small vessel disease (SVD) were assessed by blood examination and medical records. The periventricular WML volume (PWML-V) and deep WML volume (DWML-V) were significantly larger in iNPH than in AD and NC. The DWML-V was dominant in iNPH, while the PWML-V was dominant in AD and NC. GM-V was significantly smaller in AD than in iNPH and NC. The LV-V positively correlated with WML-V in all participants. There was a significant negative correlation between LV-V and Aβ38 in iNPH. Furthermore, there was no significant difference in SVD risk factors between the groups. The differences in the extent and distribution of WMLs between iNPH and AD, especially predominance of DWML-V over PWML-V in iNPH, may reflect decreased fluid and Aβ clearance.

Central vein sign: comparison of multiple sclerosis and leukoaraiosis.

Leukoaraiosis produces white matter lesions (WML) similar to multiple sclerosis (MS) on brain magnetic resonance imaging (MRI), and the distinction between these two conditions is difficult radiologically. This study aimed to investigate the role of the central vein sign (CVS) in susceptibility-weighted imaging (SWI) sequence in distinguishing MS lesions from leukoaraiosis lesions in Turkish population. In this prospective study, axial SWI and sagittal three-dimensional fluid-attenuated inversion recovery (3DFLAIR) were obtained in 374 consecutive patients. The study consisted of 169 (89 MS patients, 80 patients with leukoaraiosis) patients according to the inclusion and exclusion criteria. Two observers evaluated MR images by consensus, and observers were unaware of the patient's clinical findings. Locations (periventricular, juxtacortical, and deep white matter) and the presence of CVS were investigated for each of the lesions. Differences between patients in the leukoaraiosis and MS groups were investigated using the Mann-Whitney U test or chi-square analysis. In addition, receiver operating characteristic (ROC) analysis was used to analyze the diagnostic performance of CVS. A total of 1908 WMLs (1265 MS lesions, 643 leukoaraiosis) were detected in 169 patients. The CVS was significantly higher in the MS lesions (p < 0.001). The CVS positivity rate in periventricular WMLs was higher than in juxtacortical WMLs or deep WMLs, both for all patients and for patients with MS (p < 0.001). The area under the curve (AUC) of the ROC analysis was 0.88 (95% confidence interval 0.83-0.93) for CVS in the distinction of MS lesions and leukoaraiosis. The presence of CVS in the SWI sequence can be used as an auxiliary finding for the diagnosis of MS in the differentiation of MS and leukoaraiosis lesions.

Glymphatic system impairment in multiple sclerosis: relation with brain damage and disability.

Recent evidence has shown the existence of a CNS 'waste clearance' system, defined as the glymphatic system. Glymphatic abnormalities have been described in several neurodegenerative conditions, including Alzheimer's and Parkinson's disease. Glymphatic function has not been thoroughly explored in multiple sclerosis, where neurodegenerative processes are intermingled with inflammatory processes. We aimed to investigate glymphatic system function in multiple sclerosis and to evaluate its association with clinical disability, disease course, demyelination and neurodegeneration, quantified using different MRI techniques. In this retrospective study, we enrolled 71 multiple sclerosis patients (49 relapsing-remitting and 22 progressive multiple sclerosis) and 32 age- and sex-matched healthy control subjects. All subjects underwent neurological and MRI assessment including high-resolution T1, T2 and double inversion recovery sequences, diffusion and susceptibility weighted imaging. We calculated the diffusion along perivascular space index, a proxy for glymphatic function, cortical and deep grey matter volume, white and cortical grey matter lesion volume and normal-appearing white matter microstructural damage. Multiple sclerosis patients showed an overall lower diffusion along perivascular space index versus healthy controls (estimated mean difference: -0.09, P = 0.01). Both relapsing-remitting and progressive multiple sclerosis patients had lower diffusion along perivascular space index versus healthy controls (estimated mean difference: -0.06, P = 0.04 for relapsing-remitting and -0.19, P = 0.001 for progressive multiple sclerosis patients). Progressive multiple sclerosis patients showed lower diffusion along perivascular space index versus relapsing-remitting multiple sclerosis patients (estimated mean difference: -0.09, P = 0.03). In multiple sclerosis patients, lower diffusion along perivascular space index was associated with more severe clinical disability (r = -0.45, P = 0.001) and longer disease duration (r = -0.37, P = 0.002). Interestingly, we detected a negative association between diffusion along perivascular space index and disease duration in the first 4.13 years of the disease course (r = -0.38, P = 0.04) without any association thereafter (up to 34 years of disease duration). Lower diffusion along perivascular space index was associated with higher white (r = -0.36, P = 0.003) and cortical (r = -0.41, P = 0.001) lesion volume, more severe cortical (r = 0.30, P = 0.007) and deep (r = 0.42, P = 0.001) grey matter atrophy, reduced fractional anisotropy (r = 0.42, P = 0.001) and increased mean diffusivity (r = -0.45, P = 0.001) in the normal-appearing white matter. Our results suggest that the glymphatic system is impaired in multiple sclerosis, especially in progressive stages. Impaired glymphatic function was associated with measures of both demyelination and neurodegeneration and reflects a more severe clinical disability. These findings suggest that glymphatic impairment may be a pathological mechanism underpinning multiple sclerosis. The dynamic interplay with other pathological substrates of the disease deserves further investigation.

Changes in wall thickness of retinal arterioles as a surrogate marker of intracranial vascular pathology

AbstractBackgroundMicrovascular injury is a significant contributor to cognitive impairment. Conventional neuroimaging is inadequate for assessing microvascular changes in the brain. Intensity‐based Retinal Arteriolar Visualization in OCT (I‐bRAVO) is a novel method that enables rapid, direct and non‐invasive visualization of retinal arterioles using standard optical coherence tomography images. We aimed to assess retinal microvascular changes using I‐bRAVO and compare it to measures of arteriolosclerosis, white and grey matter damage, and cognitive function.MethodWe included 500 eyes from 250 subjects with sporadic (n=91) and genetic (i.e., Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy, n=21) cerebral small vessel diseases (CSVD), non‐vascular neurodegenerative diseases (NVND, n=113), and healthy controls (HC, n=25). Mean Wall Thickness (MWT) and Wall to Lumen Ratio (WLR) were analyzed in association with imaging and cognitive markers of vascular pathology, including novel imaging classifier of brain arteriolosclerosis (ARTS), MRI markers of white matter injury (Fazekas scale), and grey and white matter atrophy, as well as the Uniform Data Set (v3.0) executive function (UDS3‐EF) score. Linear mixed‐effect models with subject‐specific intercepts were fitted using restricted maximum likelihood estimation.ResultARTS score correlated with MWT (ρ =0.44, P&lt;0.001) and WLR (ρ=0.48, P&lt;0.001). MWT and WLR were higher in CSVD (MWT: 28.18µm, WLR: 0.30) compared with NVND (MWT: 26.72µm, WLR: 0.29) and HC (MWT: 25.17µm, WLR: 0.25) (P&lt;0.001). MWT and WLR were positively associated with superficial white matter disease burden (B= 0.07, 95% CI [0.05 – 0.1], and 5.63 [4.03 – 7.22], respectively, P&lt;0.0001). A similar association was observed between MWT, WLR and deep white matter lesion load. WLR correlated inversely with grey (ρ =0.40, P&lt;0.05) and white matter volume (ρ =0.48, P&lt;0.01) in subjects with vascular cognitive impairment. WLR differentiated cognitively healthy individuals with vascular white matter lesions from those without (AUC= 0.81, P&lt;0.001) with 94% specificity (cutoff value: 0.275). In asymptomatic CSVD, higher WLR was associated with a lower age‐, sex‐ and education‐adjusted UDS3‐EF (β=‐3.1 [‐6.3 – ‐0.01], P&lt;0.05).ConclusionWe describe a rapid, inexpensive novel technique for assessing retinal arterioles as a surrogate marker for intracranial vascular pathology and as a tool for early recognition of presymptomatic CSVD.

Risk Factors of Restroke in Patients with Lacunar Cerebral Infarction Using Magnetic Resonance Imaging Image Features under Deep Learning Algorithm.

This study was aimed to explore the magnetic resonance imaging (MRI) image features based on the fuzzy local information C-means clustering (FLICM) image segmentation method to analyze the risk factors of restroke in patients with lacunar infarction. In this study, based on the FLICM algorithm, the Canny edge detection algorithm and the Fourier shape descriptor were introduced to optimize the algorithm. The difference of Jaccard coefficient, Dice coefficient, peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), running time, and segmentation accuracy of the optimized FLICM algorithm and other algorithms when the brain tissue MRI images were segmented was studied. 36 patients with lacunar infarction were selected as the research objects, and they were divided into a control group (no restroke, 20 cases) and a stroke group (restroke, 16 cases) according to whether the patients had restroke. The differences in MRI imaging characteristics of the two groups of patients were compared, and the risk factors for restroke in lacunar infarction were analyzed by logistic multivariate regression. The results showed that the Jaccard coefficient, Dice coefficient, PSNR value, and SSIM value of the optimized FLICM algorithm for segmenting brain tissue were all higher than those of other algorithms. The shortest running time was 26 s, and the highest accuracy rate was 97.86%. The proportion of patients with a history of hypertension, the proportion of patients with paraventricular white matter lesion (WML) score greater than 2 in the stroke group, the proportion of patients with a deep WML score of 2, and the average age of patients in the stroke group were much higher than those in the control group (P < 0.05). Logistic multivariate regression showed that age and history of hypertension were risk factors for restroke after lacunar infarction (P < 0.05). It showed that the optimized FLICM algorithm can effectively segment brain MRI images, and the risk factors for restroke in patients with lacunar infarction were age and hypertension history. This study could provide a reference for the diagnosis and prognosis of lacunar infarction.

Neural networks in the predictive diagnosis of cognitive impairment in type 1 and type 2 diabetes mellitus

Cognitive dysfunction, including mild cognitive impairment and dementia, is increasingly recognized as a serious complication of diabetes mellitus (DM) that affects patient well-being and disease management. Magnetic resonance imaging (MRI)-studies have shown varying degrees of cortical atrophy, cerebral infarcts, and deep white matter lesions. To explain the relationship between DM and cognitive decline, several hypotheses have been proposed, based on the variability of glycemia leading to morphometric changes in the brain. The ability to predict cognitive decline even before its clinical development will allow the early prevention of this pathology, as well as to predict the course of the existing pathology and to adjust medication regimens. To create a computer neural network model for predicting the development of cognitive impairment in DM on the basis of brain neuroimaging techniques. The study was performed in accordance with the standards of good clinical practice; the protocol was approved by the Ethics Committee. The study included 85 patients with type 1 diabetes and 95 patients with type 2 diabetes, who were divided into a group of patients with normal cognitive function and a group with cognitive impairment. The patient groups were comparable in age and duration of disease. Cognitive impairment was screened using the Montreal Cognitive Assessment Scale. Data for glycemic variability were obtained using continuous glucose monitoring (iPro2, Libre). A standard MRI scan of the brain was performed axially, sagittally, and coronally on a Signa Creator E, GE Healthcare, 1.5 Tesla, China. For MRI data processing we used Free Surfer program (USA) for analysis and visualization of structural and functional neuroimaging data from cross-sectional or longitudinal studies, and for segmentation we used Recon-all batch program directly. All statistical analyses and data processing were performed using Statistica Statsofi software (version 10) on Windows 7/XP Pro operating systems. The IBM WATSON cognitive system was used to build a neural network model. As a result of the study, cognitive impairment in DM type 1was predominantly of mild degree 36.9% (n=24) and moderate degree 30.76% (n=20), and in DM type 2 mild degree 37% (n=30), moderate degree 49.4% (n=40) and severe degree 13.6% (n=11). Cognitive functions in DM type 1 were impaired in memory and attention, whereas in DM type 2 they were also impaired in tasks of visual-constructive skills, fluency, and abstraction (p0.001). The analysis revealed differences in glycemic variability indices in patients with type 1 and type 2 DM and cognitive impairment. Standard MRI of the brain recorded the presence of white and gray matter changes (gliosis and leukoareosis). General and regional cerebral atrophy is characteristic of type 1 and type 2 DM, which is associated with dysglycemia. When building neural network models for type 1 diabetes, the parameters of decreased volumes of the brain regions determine the development of cognitive impairment by 93.5%, whereas additionally, the coefficients of glycemic variability by 98.5%. The same peculiarity was revealed in type 2 DM 95.3% and 97.9%, respectively. In DM type 1 and type 2 with cognitive impairment, elevated coefficients of glycemic variability are more frequently recorded. This publication describes laboratory and instrumental parameters as potential diagnostic options for effective management of DM and prevention of cognitive impairment. Neural network models using glycemic variability coefficients and MR morphometry allow for predictive diagnosis of cognitive disorders in both types of diabetes.

Automated quantification of deep grey matter structures and white matter lesions using magnetic resonance imaging in relapsing remission multiple sclerosis

BackgroundBrain volume loss (BVL) is widespread in MS and occurs throughout the disease course at a rate considerably greater than in the general population. In MS, brain volume correlates with and predicts future disability, making BVL a relevant measure of diffuse CNS damage leading to clinical disease progression, as well as serving as a useful outcome in evaluating MS therapies. The aim of our study was to evaluate the role of automated segmentation and quantification of deep grey matter structures and white matter lesions in Relapsing Remitting Multiple Sclerosis patients using MR images and to correlate the volumetric results with different degrees of disability based on expanded disability status scale (EDSS) scores.ResultsAll the patients in our study showed relative atrophy of the thalamus and the putamen bilaterally when compared with the normal control group. Statistical analysis was significant for the thalamus and the putamen atrophy (P value < 0.05). On the other hand, statistical analysis was not significant for the caudate and the hippocampus (P value > 0.05); there was a significant positive correlation between the white matter lesions volume and EDSS scores (correlation coefficient of 0.7505). On the other hand, there was a significant negative correlation between the thalamus and putamen volumes, and EDSS scores (correlation coefficients < − 0.9), while the volumes of the caudate and the hippocampus had a very weak and non-significant correlation with the EDSS scores (correlation coefficients > − 0.35).ConclusionsThe automated segmentation and quantification tools have a great role in the assessment of brain structural changes in RRMS patients, and that it became essential to integrate these tools in the daily medical practice for the great value they add to the current evaluation measures.

7T MRI Differentiates Remyelinated from Demyelinated Multiple Sclerosis Lesions.

ObjectiveTo noninvasively assess myelin status in chronic white matter lesions of multiple sclerosis (MS), we developed and evaluated a simple classification scheme based on T1 relaxation time maps derived from 7‐tesla postmortem and in vivo MRI.MethodsUsing the MP2RAGE MRI sequence, we classified 36 lesions from 4 postmortem MS brains as “long‐T1,” “short‐T1,” and “mixed‐T1” by visual comparison to neocortex. Within these groups, we compared T1 times to histologically derived measures of myelin and axons. We performed similar analysis of 235 chronic lesions with known date of onset in 25 MS cases in vivo and in a validation cohort of 222 lesions from 66 MS cases, investigating associations with clinical and radiological outcomes.ResultsPostmortem, lesions classified qualitatively as long‐T1, short‐T1, and mixed‐T1 corresponded to fully demyelinated, fully remyelinated, and mixed demyelinated/remyelinated lesions, respectively (p ≤ 0.001). Demyelination (rather than axon loss) dominantly contributed to initial T1 prolongation. We observed lesions with similar characteristics in vivo, allowing manual classification with substantial interrater and excellent intrarater reliability. Short‐T1 lesions were most common in the deep white matter, whereas long‐T1 and mixed‐T1 lesions were prevalent in the juxtacortical and periventricular white matter (p = 0.02) and were much more likely to have paramagnetic rims suggesting chronic inflammation (p < 0.001). Older age at the time of lesion formation portended less remyelination (p = 0.007).Interpretation7‐tesla T1 mapping with MP2RAGE, a clinically available MRI method, allows qualitative and quantitative classification of chronic MS lesions according to myelin content, rendering straightforward the tracking of lesional myelination changes over time. ANN NEUROL 2021;90:612–626

Abstract MP13: Evaluation Of The Effect Of Low Grade Inflammation And Hypertension On The Development Of White Matter Lesions

Introduction: The risk of degenerative disease development is closely linked to persistent and continuous systemic inflammation. Although relationships between chronic low-grade inflammation (LGI) measurements and the progression of cardiovascular diseases are becoming established, the burden of the cardio-pathology and LGI on the central nervous system has not been fully investigated. Specifically, there is limited data on how hypertension (HTN) and related LGI impact white matter lesion (WML) pathogenesis. Methods: We examined 448 subjects with a mean age of 69.3 ± 7.4 years, with 62% of the cohort being women (n=276), and 45% having hypertension (n=200). Components of the LGI score included white blood cell count, albumin levels, platelet counts, and granulocyte/lymphocyte ratio, modified after. Larger LGI scores represented an increase in measured LGI intensity at that time point. MR images were obtained on a 3T system using fluid attenuation inversion recovery (FLAIR) sequence. WML burden was ascertained using Fazekas scale, done separately for both deep WML and periventricular WML. Summated score of greater than or equal to 4 was considered high overall WML burden. Results: It was found that subjects with hypertension had significantly higher LGI score when compared to subjects without hypertension after accounting for sex and BMI (F=4.8, p=0.03). Using logistic regression. we found that LGI score was related to higher WML burden (p=0.047) within the entire cohort. However, further analyses have shown that this finding was driven by the normotensive group, in which the relationship between higher WML burden and respective LGI score was significant (p=0.007). This was not the case among hypertensive subjects. Conclusion: It is clear from the data presented that a relationship between LGI and hypertension exists, confirming that inflammation is an underlying process in cardiovascular pathogenesis. However, LGI scores were related to WML in only normotensive cohorts. We offer that the effects of chronic HTN (related to higher inflammatory score itself ) overshadow the effect of LGI among hypertensive subjects. It is worth emphasizing that even in subjects without HTN white matter damage is related to LGI