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Saraceno C, Cervellati C, Trentini A, Crescenti D, Longobardi A, Geviti A, Bonfiglio NS, Bellini S, Nicsanu R, Fostinelli S, Mola G, Riccetti R, Moretti DV, Zanetti O, Binetti G, Zuliani G, Ghidoni R. Serum Beta-Secretase 1 Activity Is a Potential Marker for the Differential Diagnosis between Alzheimer's Disease and Frontotemporal Dementia: A Pilot Study. Int J Mol Sci 2024; 25:8354. [PMID: 39125924 PMCID: PMC11313328 DOI: 10.3390/ijms25158354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Revised: 07/23/2024] [Accepted: 07/28/2024] [Indexed: 08/12/2024] Open
Abstract
Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the two major neurodegenerative diseases causing dementia. Due to similar clinical phenotypes, differential diagnosis is challenging without specific biomarkers. Beta-site Amyloid Precursor Protein cleaving enzyme 1 (BACE1) is a β-secretase pivotal in AD pathogenesis. In AD and mild cognitive impairment subjects, BACE1 activity is increased in brain/cerebrospinal fluid, and plasma levels appear to reflect those in the brain. In this study, we aim to evaluate serum BACE1 activity in FTD, since, to date, there is no evidence about its role. The serum of 30 FTD patients and 30 controls was analyzed to evaluate (i) BACE1 activity, using a fluorescent assay, and (ii) Glial Fibrillary Acid Protein (GFAP) and Neurofilament Light chain (NfL) levels, using a Simoa kit. As expected, a significant increase in GFAP and NfL levels was observed in FTD patients compared to controls. Serum BACE1 activity was not altered in FTD patients. A significant increase in serum BACE1 activity was shown in AD vs. FTD and controls. Our results support the hypothesis that serum BACE1 activity is a potential biomarker for the differential diagnosis between AD and FTD.
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Affiliation(s)
- Claudia Saraceno
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
| | - Carlo Cervellati
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121 Ferrara, Italy; (C.C.); (G.M.); (G.Z.)
| | - Alessandro Trentini
- Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy; (A.T.); (R.R.)
| | - Daniela Crescenti
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
| | - Antonio Longobardi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
| | - Andrea Geviti
- Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (A.G.); (N.S.B.)
| | - Natale Salvatore Bonfiglio
- Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (A.G.); (N.S.B.)
| | - Sonia Bellini
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
| | - Roland Nicsanu
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
| | - Silvia Fostinelli
- MAC–Memory Clinic and Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (S.F.); (G.B.)
| | - Gianmarco Mola
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121 Ferrara, Italy; (C.C.); (G.M.); (G.Z.)
| | - Raffaella Riccetti
- Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy; (A.T.); (R.R.)
| | - Davide Vito Moretti
- Alzheimer’s Rehabilitation Operative Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy;
| | - Orazio Zanetti
- Alzheimer’s Research Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy;
| | - Giuliano Binetti
- MAC–Memory Clinic and Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (S.F.); (G.B.)
| | - Giovanni Zuliani
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121 Ferrara, Italy; (C.C.); (G.M.); (G.Z.)
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy; (C.S.); (D.C.); (A.L.); (S.B.); (R.N.)
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Xie W, Hsu S, Lin Y, Xie L, Jin X, Zhu Z, Guo Y, Chen C, Huang D, Boltze J, Li P. Malignancy-associated ischemic stroke: Implications for diagnostic and therapeutic workup. CNS Neurosci Ther 2024; 30:e14619. [PMID: 38532275 PMCID: PMC10965754 DOI: 10.1111/cns.14619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/02/2024] [Accepted: 01/08/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Patients with malignancies have an increased risk of suffering ischemic stroke via several mechanisms such as coagulation dysfunction and other malignancy-related effects as well as iatrogenic causes. Moreover, stroke can be the first sign of an occult malignancy, termed as malignancy-associated ischemic stroke (MAS). Therefore, timely diagnostic assessment and targeted management of this complex clinical situation are critical. FINDINGS Patients with both stroke and malignancy have atypical ages, risk factors, and often exhibit malignancy-related symptoms and multiple lesions on neuroimaging. New biomarkers such as eicosapentaenoic acid and blood mRNA profiles may help in distinguishing MAS from other strokes. In terms of treatment, malignancy should not be considered a contraindication, given comparable rates of recanalization and complications between stroke patients with or without malignancies. CONCLUSION In this review, we summarize the latest developments in diagnosing and managing MAS, especially stroke with occult malignancies, and provide new recommendations from recently emerged clinical evidence for diagnostic and therapeutic workup strategies.
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Affiliation(s)
- Wanqing Xie
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Szuyao Hsu
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yuxuan Lin
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Lv Xie
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xia Jin
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Ziyu Zhu
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yunlu Guo
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Caiyang Chen
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Dan Huang
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | | | - Peiying Li
- Department of Anesthesiology, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Research Center, Renji HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
- Outcomes Research ConsortiumClevelandOhioUSA
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Perosa V, Zanon Zotin MC, Schoemaker D, Sveikata L, Etherton MR, Charidimou A, Greenberg SM, Viswanathan A. Association Between Hippocampal Volumes and Cognition in Cerebral Amyloid Angiopathy. Neurology 2024; 102:e207854. [PMID: 38165326 PMCID: PMC10870737 DOI: 10.1212/wnl.0000000000207854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 10/03/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Accumulating evidence suggests that gray matter atrophy, often considered a marker of Alzheimer disease (AD), can also result from cerebral small vessel disease (CSVD). Cerebral amyloid angiopathy (CAA) is a form of sporadic CSVD, diagnosed through neuroimaging criteria, that often co-occurs with AD pathology and leads to cognitive impairment. We sought to identify the role of hippocampal integrity in the development of cognitive impairment in a cohort of patients with possible and probable CAA. METHODS Patients were recruited from an ongoing CAA study at Massachusetts General Hospital. Composite scores defined performance in the cognitive domains of memory, language, executive function, and processing speed. Hippocampal subfields' volumes were measured from 3T MRI, using an automated method, and multivariate linear regression models were used to estimate their association with each cognitive domain and relationship to CAA-related neuroimaging markers. RESULTS One hundred twenty patients, 36 with possible (age mean [range]: 75.6 [65.6-88.9]), 67 with probable CAA (75.9 [59.0-94.0]), and 17 controls without cognitive impairment and CSVD (72.4 [62.5-82.7]; 76.4% female patients), were included in this study. We found a positive association between all investigated hippocampal subfields and memory and language, whereas specific subfields accounted for executive function (CA4 [Estimate = 5.43; 95% CI 1.26-9.61; p = 0.020], subiculum [Estimate = 2.85; 95% CI 0.67-5.02; p = 0.022]), and processing speed (subiculum [Estimate = 1.99; 95% CI 0.13-3.85; p = 0.036]). These findings were independent of other CAA-related markers, which did not have an influence on cognition in this cohort. Peak width of skeletonized mean diffusivity (PSMD), a measure of white matter integrity, was negatively associated with hippocampal subfields' volumes (CA3 [Estimate = -0.012; 95% CI -0.020 to -0.004; p = 0.034], CA4 [Estimate = -0.010; 95% CI -0.020 to -0.0007; p = 0.037], subiculum [Estimate = -0.019; 95% CI -0.042 to -0.0001; p = 0.003]). DISCUSSION These results suggest that hippocampal integrity is an independent contributor to cognitive impairment in patients with CAA and that it might be related to loss of integrity in the white matter. Further studies exploring potential causes and directionality of the relationship between white matter and hippocampal integrity may be warranted.
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Affiliation(s)
- Valentina Perosa
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Maria Clara Zanon Zotin
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Dorothee Schoemaker
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Lukas Sveikata
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Mark R Etherton
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Andreas Charidimou
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Steven M Greenberg
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Anand Viswanathan
- From the J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
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Chhoa H, Chabriat H, Chevret S, Biard L. Comparison of models for stroke-free survival prediction in patients with CADASIL. Sci Rep 2023; 13:22443. [PMID: 38105268 PMCID: PMC10725863 DOI: 10.1038/s41598-023-49552-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 12/09/2023] [Indexed: 12/19/2023] Open
Abstract
Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, which is caused by mutations of the NOTCH3 gene, has a large heterogeneous progression, presenting with declines of various clinical scores and occurrences of various clinical event. To help assess disease progression, this work focused on predicting the composite endpoint of stroke-free survival time by comparing the performance of Cox proportional hazards regression to that of machine learning models using one of four feature selection approaches applied to demographic, clinical and magnetic resonance imaging observational data collected from a study cohort of 482 patients. The quality of the modeling process and the predictive performance were evaluated in a nested cross-validation procedure using the time-dependent Brier Score and AUC at 5 years from baseline, the former measuring the overall performance including calibration and the latter highlighting the discrimination ability, with both metrics taking into account the presence of right-censoring. The best model for each metric was the componentwise gradient boosting model with a mean Brier score of 0.165 and the random survival forest model with a mean AUC of 0.773, both combined with the LASSO feature selection method.
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Affiliation(s)
- Henri Chhoa
- ECSTRRA Team, Université Paris Cité, UMR1153, INSERM, Paris, France
| | - Hugues Chabriat
- Centre NeuroVasculaire Translationnel - Centre de Référence CERVCO, DMU NeuroSciences, Hôpital Lariboisière, GHU APHP-Nord, Université Paris Cité, Paris, France
- INSERM NeuroDiderot UMR 1141, GenMedStroke Team, Paris, France
| | - Sylvie Chevret
- ECSTRRA Team, Université Paris Cité, UMR1153, INSERM, Paris, France
| | - Lucie Biard
- ECSTRRA Team, Université Paris Cité, UMR1153, INSERM, Paris, France.
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Hotz I, Deschwanden PF, Mérillat S, Jäncke L. Associations between white matter hyperintensities, lacunes, entorhinal cortex thickness, declarative memory and leisure activity in cognitively healthy older adults: A 7-year study. Neuroimage 2023; 284:120461. [PMID: 37981203 DOI: 10.1016/j.neuroimage.2023.120461] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 11/02/2023] [Accepted: 11/16/2023] [Indexed: 11/21/2023] Open
Abstract
INTRODUCTION Cerebral small vessel disease (cSVD) is a growing epidemic that affects brain health and cognition. Therefore, a more profound understanding of the interplay between cSVD, brain atrophy, and cognition in healthy aging is of great importance. In this study, we examined the association between white matter hyperintensities (WMH) volume, number of lacunes, entorhinal cortex (EC) thickness, and declarative memory in cognitively healthy older adults over a seven-year period, controlling for possible confounding factors. Because there is no cure for cSVD to date, the neuroprotective potential of an active lifestyle has been suggested. Supporting evidence, however, is scarce. Therefore, a second objective of this study is to examine the relationship between leisure activities, cSVD, EC thickness, and declarative memory. METHODS We used a longitudinal dataset, which consisted of five measurement time points of structural MRI and psychometric cognitive ability and survey data, collected from a sample of healthy older adults (baseline N = 231, age range: 64-87 years, age M = 70.8 years), to investigate associations between cSVD MRI markers, EC thickness and verbal and figural memory performance. Further, we computed physical, social, and cognitive leisure activity scores from survey-based assessments and examined their associations with brain structure and declarative memory. To provide more accurate estimates of the trajectories and cross-domain correlations, we applied latent growth curve models controlling for potential confounders. RESULTS Less age-related thinning of the right (β = 0.92, p<.05) and left EC (β = 0.82, p<.05) was related to less declarative memory decline; and a thicker EC at baseline predicted less declarative memory loss (β = 0.54, p<.05). Higher baseline levels of physical (β = 0.24, p<.05), and social leisure activity (β = 0.27, p<.01) predicted less thinning of right EC. No relation was found between WMH or lacunes and declarative memory or between leisure activity and declarative memory. Higher education was initially related to more physical activity (β = 0.16, p<.05) and better declarative memory (β = 0.23, p<.001), which, however, declined steeper in participants with higher education (β = -.35, p<.05). Obese participants were less physically (β = -.18, p<.01) and socially active (β = -.13, p<.05) and had thinner left EC (β = -.14, p<.05) at baseline. Antihypertensive medication use (β = -.26, p<.05), and light-to-moderate alcohol consumption (β = -.40, p<.001) were associated with a smaller increase in the number of lacunes whereas a larger increase in the number of lacunes was observed in current smokers (β = 0.30, p<.05). CONCLUSIONS Our results suggest complex relationships between cSVD MRI markers (total WMH, number of lacunes, right and left EC thickness), declarative memory, and confounding factors such as antihypertensive medication, obesity, and leisure activitiy. Thus, leisure activities and having good cognitive reserve counteracting this neurodegeneration. Several confounding factors seem to contribute to the extent or progression/decline of cSVD, which needs further investigation in the future. Since there is still no cure for cSVD, modifiable confounding factors should be studied more intensively in the future to maintain or promote brain health and thus cognitive abilities in older adults.
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Affiliation(s)
- Isabel Hotz
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland.
| | - Pascal Frédéric Deschwanden
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
| | - Susan Mérillat
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
| | - Lutz Jäncke
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
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Chhoa H, Chabriat H, Anato AJ, Bamba M, Zittoun F, Chevret S, Biard L. Improvement of an External Predictive Model Based on New Information Using a Synthetic Data Approach: Application to CADASIL. Neurol Genet 2023; 9:e200091. [PMID: 38235365 PMCID: PMC10691224 DOI: 10.1212/nxg.0000000000200091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 06/07/2023] [Indexed: 01/19/2024]
Abstract
Background and Objectives Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most frequent hereditary cerebral small vessel disease. It is caused by mutations of the NOTCH3 gene. The disease evolves progressively over decades leading to stroke, disability, cognitive decline, and functional dependency. The course and clinical severity of CADASIL seem heterogeneous. Predictive models are thus needed to improve prognostic evaluation and inform future clinical trials. A predictive model of the 3-year variation in the Mattis Dementia Rating Scale (MDRS), which reflects the global cognitive performance of patients with CADASIL, was previously proposed. This model made predictions based on demographic, clinical, and MRI data. We aimed to improve this existing predictive model by integrating a new potential factor, the location of the genetic mutation in the different epidermal growth factor (EGFr) domains of the NOTCH3 gene, dichotomized into EGFr domains 1 to 6 or 7 to 34. Methods We used a new synthetic data approach to improve the initial predictive model by incorporating additional genetic information. This method combined the predicted outcomes from the previous model and 5 "synthetic" data sets with the observed outcome in a new data set. We then applied a multiple imputation method for missing data on the mutation location. Results The new data set included 367 patients who were followed up for 30 to 42 months. In the multivariable model with synthetic data, patients with NOTCH3 mutations in EGFr domains 7 to 34 had an additional average decrease of -1.4 points (standard error 0.67, p = 0.035) in their MDRS score variation over 3 years compared with patients with mutations located in EGFr domains 1 to 6. Cross-validation results highlighted the improved predictive performance of the enhanced model. Moreover, the model estimation was found to be more robust than fitting a model without synthetic data. Discussion The use of synthetic data improved the predictive model of MDRS change over 3 years in CADASIL. The predictive performance and estimation robustness of the predictive model were enhanced using this approach, whether genetic information was used. A statistically significant association between the location of the mutation in the NOTCH3 gene and the 3-year MDRS score variation was detected.
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Affiliation(s)
- Henri Chhoa
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Hugues Chabriat
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Adelina Joanita Anato
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Mamadou Bamba
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Florent Zittoun
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Sylvie Chevret
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
| | - Lucie Biard
- From the ECSTRRA Team (H. Chhoa, S.C., L.B.), Université Paris-Cité, UMR1153, INSERM; Translational Neurovascular Centre (H. Chabriat), GH Saint-Louis-Lariboisière, Assistance Publique des Hôpitaux de Paris APHP, Université Paris-Cité and DHU NeuroVasc Sorbonne Paris-Cité; UMR 1161 (H. Chabriat), INSERM; and ENSAI (A.J.A., M.B., F.Z.), Ecole d'ingénieur statistique, data science et big data, Bruz, France
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Bennett J, van Dinther M, Voorter P, Backes W, Barnes J, Barkhof F, Captur G, Hughes AD, Sudre C, Treibel TA. Assessment of Microvascular Disease in Heart and Brain by MRI: Application in Heart Failure with Preserved Ejection Fraction and Cerebral Small Vessel Disease. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1596. [PMID: 37763715 PMCID: PMC10534635 DOI: 10.3390/medicina59091596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023]
Abstract
The objective of this review is to investigate the commonalities of microvascular (small vessel) disease in heart failure with preserved ejection fraction (HFpEF) and cerebral small vessel disease (CSVD). Furthermore, the review aims to evaluate the current magnetic resonance imaging (MRI) diagnostic techniques for both conditions. By comparing the two conditions, this review seeks to identify potential opportunities to improve the understanding of both HFpEF and CSVD.
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Affiliation(s)
- Jonathan Bennett
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Department of Cardiology, Barts Heart Centre, London EC1A 7BE, UK
| | - Maud van Dinther
- Department of Neurology, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6211 LX Maastricht, The Netherlands
| | - Paulien Voorter
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Walter Backes
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6211 LX Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Josephine Barnes
- Dementia Research Centre, UCL Queens Square Institute of Neurology, University College London, London WC1E 6BT, UK
| | - Frederick Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Vrije University, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
- Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK
- Centre for Medical Image Computing, University College London, London WC1E 6BT, UK
| | - Gabriella Captur
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
- Centre for Inherited Heart Muscle Conditions, Cardiology Department, The Royal Free Hospital, London NW3 2QG, UK
| | - Alun D. Hughes
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
| | - Carole Sudre
- Dementia Research Centre, UCL Queens Square Institute of Neurology, University College London, London WC1E 6BT, UK
- Centre for Medical Image Computing, University College London, London WC1E 6BT, UK
- Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London WC1E 6BT, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | - Thomas A. Treibel
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Department of Cardiology, Barts Heart Centre, London EC1A 7BE, UK
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8
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Duering M, Biessels GJ, Brodtmann A, Chen C, Cordonnier C, de Leeuw FE, Debette S, Frayne R, Jouvent E, Rost NS, Ter Telgte A, Al-Shahi Salman R, Backes WH, Bae HJ, Brown R, Chabriat H, De Luca A, deCarli C, Dewenter A, Doubal FN, Ewers M, Field TS, Ganesh A, Greenberg S, Helmer KG, Hilal S, Jochems ACC, Jokinen H, Kuijf H, Lam BYK, Lebenberg J, MacIntosh BJ, Maillard P, Mok VCT, Pantoni L, Rudilosso S, Satizabal CL, Schirmer MD, Schmidt R, Smith C, Staals J, Thrippleton MJ, van Veluw SJ, Vemuri P, Wang Y, Werring D, Zedde M, Akinyemi RO, Del Brutto OH, Markus HS, Zhu YC, Smith EE, Dichgans M, Wardlaw JM. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol 2023; 22:602-618. [PMID: 37236211 DOI: 10.1016/s1474-4422(23)00131-x] [Citation(s) in RCA: 149] [Impact Index Per Article: 149.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/03/2023] [Accepted: 03/28/2023] [Indexed: 05/28/2023]
Abstract
Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.
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Affiliation(s)
- Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center, University of Basel, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
| | - Geert Jan Biessels
- Department of Neurology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Christopher Chen
- Department of Pharmacology, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychological Medicine, Memory Aging and Cognition Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Charlotte Cordonnier
- Université de Lille, INSERM, CHU Lille, U1172-Lille Neuroscience and Cognition (LilNCog), Lille, France
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboudumc, Nijmegen, Netherlands
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, INSERM, UMR 1219, Bordeaux, France; Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France
| | - Richard Frayne
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Centre, University of Calgary, Calgary, AB, Canada
| | - Eric Jouvent
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Natalia S Rost
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, Netherlands; School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University College of Medicine, Seoul, South Korea; Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seongn-si, South Korea
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hugues Chabriat
- Centre Neurovasculaire Translationnel, CERVCO, INSERM U1141, FHU NeuroVasc, Université Paris Cité, Paris, France
| | - Alberto De Luca
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Charles deCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Thalia S Field
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada; Vancouver Stroke Program, Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Aravind Ganesh
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Steven Greenberg
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Karl G Helmer
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A Martinos Center for Biomedical Imaging, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Saima Hilal
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Angela C C Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Hanna Jokinen
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital, University of Helsinki, Helsinki, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hugo Kuijf
- Image Sciences Institute, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Bonnie Y K Lam
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jessica Lebenberg
- AP-HP, Lariboisière Hospital, Translational Neurovascular Centre, FHU NeuroVasc, Université Paris Cité, Paris, France; Université Paris Cité, INSERM UMR 1141, NeuroDiderot, Paris, France
| | - Bradley J MacIntosh
- Sandra E Black Centre for Brain Resilience and Repair, Hurvitz Brain Sciences, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Computational Radiology and Artificial Intelligence Unit, Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Pauline Maillard
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA, USA
| | - Vincent C T Mok
- Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Margaret KL Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Leonardo Pantoni
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Salvatore Rudilosso
- Comprehensive Stroke Center, Department of Neuroscience, Hospital Clinic and August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Neurology, Boston University Medical Center, Boston, MA, USA; Framingham Heart Study, Framingham, MA, USA
| | - Markus D Schirmer
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Julie Staals
- School for Cardiovascular Diseases, Maastricht University Medical Center, Maastricht, Netherlands; Department of Neurology, Maastricht University Medical Center, Maastricht, Netherlands
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging and Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | - Yilong Wang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - David Werring
- Stroke Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marialuisa Zedde
- Neurology Unit, Stroke Unit, Department of Neuromotor Physiology and Rehabilitation, Azienda Unità Sanitaria-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Rufus O Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oscar H Del Brutto
- School of Medicine and Research Center, Universidad de Especialidades Espiritu Santo, Ecuador
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Eric E Smith
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; German Centre for Cardiovascular Research (DZHK), Munich, Germany
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK.
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Bickel MA, Csik B, Gulej R, Ungvari A, Nyul-Toth A, Conley SM. Cell non-autonomous regulation of cerebrovascular aging processes by the somatotropic axis. Front Endocrinol (Lausanne) 2023; 14:1087053. [PMID: 36755922 PMCID: PMC9900125 DOI: 10.3389/fendo.2023.1087053] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/04/2023] [Indexed: 01/24/2023] Open
Abstract
Age-related cerebrovascular pathologies, ranging from cerebromicrovascular functional and structural alterations to large vessel atherosclerosis, promote the genesis of vascular cognitive impairment and dementia (VCID) and exacerbate Alzheimer's disease. Recent advances in geroscience, including results from studies on heterochronic parabiosis models, reinforce the hypothesis that cell non-autonomous mechanisms play a key role in regulating cerebrovascular aging processes. Growth hormone (GH) and insulin-like growth factor 1 (IGF-1) exert multifaceted vasoprotective effects and production of both hormones is significantly reduced in aging. This brief overview focuses on the role of age-related GH/IGF-1 deficiency in the development of cerebrovascular pathologies and VCID. It explores the mechanistic links among alterations in the somatotropic axis, specific macrovascular and microvascular pathologies (including capillary rarefaction, microhemorrhages, impaired endothelial regulation of cerebral blood flow, disruption of the blood brain barrier, decreased neurovascular coupling, and atherogenesis) and cognitive impairment. Improved understanding of cell non-autonomous mechanisms of vascular aging is crucial to identify targets for intervention to promote cerebrovascular and brain health in older adults.
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Affiliation(s)
- Marisa A. Bickel
- Department of Cell Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Boglarka Csik
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Rafal Gulej
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Anna Ungvari
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- International Training Program in Geroscience, Department of Public Health, Semmelweis University, Budapest, Hungary
| | - Adam Nyul-Toth
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- International Training Program in Geroscience, Department of Public Health, Semmelweis University, Budapest, Hungary
- Institute of Biophysics, Biological Research Centre, Eötvös Lorand Research Network (ELKH), Szeged, Hungary
| | - Shannon M. Conley
- Department of Cell Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
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10
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Lebenberg J, Zhang R, Grosset L, Guichard JP, Fernandes F, Jouvent E, Chabriat H. Segmentation of incident lacunes during the course of ischemic cerebral small vessel diseases. Front Neurol 2023; 14:1113644. [PMID: 37034061 PMCID: PMC10076773 DOI: 10.3389/fneur.2023.1113644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/22/2023] [Indexed: 04/11/2023] Open
Abstract
Background Lacunes represent key imaging markers of cerebral small vessel diseases (cSVDs). During their progression, incident lacunes are related to stroke manifestations and contribute to progressive cognitive and/or motor decline. Assessing new lesions has become crucial but remains time-consuming and error-prone, even for an expert. We, thus, sought to develop and validate an automatic segmentation method of incident lacunes in CADASIL caused by cysteine mutation in the EGFr domains of the NOTCH3 gene, a severe and progressive monogenic form of cSVD. Methods Incident lacunes were identified based on difference maps of 3D T1-weighted MRIs obtained at the baseline and 2 years later. These maps were thresholded using clustering analysis and compared with results obtained by expert visual analysis, which is considered the gold standard approach. Results The median number of lacunes at the baseline in 30 randomly selected patients was 7 (IQR = [2, 11]). The median number of incident lacunes was 2 (IQR = [0, 3]) using the automatic method (mean time-processing: 25 s/patient) and 0.5 (IQR = [0, 2]) using the standard visual approach (mean time-processing: 8 min/patient). The complementary analysis of segmentation results is enabled to quickly remove false positives detected in specific locations and to identify true incident lesions not previously detected by the standard analysis (2 min/case). A combined approach based on automatic segmentation of incident lacunes followed by quick corrections of false positives allowed to reach high individual sensitivity (median at 0.66, IQR = [0.21, 1.00]) and global specificity scores (0.80). Conclusion The automatic segmentation of incident lacunes followed by quick corrections of false positives appears promising for properly and rapidly quantifying incident lacunes in large cohorts of cSVDs.
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Affiliation(s)
- Jessica Lebenberg
- APHP, Lariboisière Hospital, Translational Neurovascular Centre, FHU Neurovasc, Université Paris Cité, Paris, France
- U1141, Université Paris Cité, Inserm, Neurodiderot, Paris, France
| | - Ruiting Zhang
- U1141, Université Paris Cité, Inserm, Neurodiderot, Paris, France
- Department of Radiology, School of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Lina Grosset
- U1141, Université Paris Cité, Inserm, Neurodiderot, Paris, France
- APHP, Lariboisière Hospital, Department of Neurology, FHU NeuroVasc, Université Paris Cité, Paris, France
- Faculté de Santé, Université Paris Cité, Paris, France
| | - Jean Pierre Guichard
- APHP, Lariboisière Hospital, Department of Neuroradiology, Université Paris Cité, Paris, France
| | - Fanny Fernandes
- APHP, Lariboisière Hospital, Translational Neurovascular Centre, FHU Neurovasc, Université Paris Cité, Paris, France
| | - Eric Jouvent
- U1141, Université Paris Cité, Inserm, Neurodiderot, Paris, France
- APHP, Lariboisière Hospital, Department of Neurology, FHU NeuroVasc, Université Paris Cité, Paris, France
- Faculté de Santé, Université Paris Cité, Paris, France
| | - Hugues Chabriat
- APHP, Lariboisière Hospital, Translational Neurovascular Centre, FHU Neurovasc, Université Paris Cité, Paris, France
- U1141, Université Paris Cité, Inserm, Neurodiderot, Paris, France
- Faculté de Santé, Université Paris Cité, Paris, France
- *Correspondence: Hugues Chabriat
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11
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Tao W, Cheng Y, Guo W, Kwapong WR, Ye C, Wu B, Zhang S, Liu M. Clinical features and imaging markers of small vessel disease in symptomatic acute subcortical cerebral microinfarcts. BMC Neurol 2022; 22:311. [PMID: 35999494 PMCID: PMC9396904 DOI: 10.1186/s12883-022-02824-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/03/2022] [Indexed: 11/30/2022] Open
Abstract
Background As currently defined, recent small subcortical infarcts (RSSI) do not have a lower size boundary, and the smallest diffusion-weighted imaging (DWI) infarcts, which we term acute subcortical cerebral microinfarcts (As-CMI) with lesion diameter less than 5 mm, might have clinical implications distinct from RSSI. We aimed to investigate the distinct characteristics of As-CMI as compared to the larger size of RSSI regarding vascular risk factors, clinical manifestation, radiological markers of SVD distribution, and outcomes. Methods In a consecutive cohort, patients were selected with a magnetic resonance DWI-confirmed RSSI between January 2010 and November 2020. We measured axial infarct diameter and classified patients into two groups: The As-CMI group (diameter < 5 mm) versus the Larger RSSI group (diameter 5-20 mm). Clinical variables, including vascular risk factors, clinical symptoms/signs, lesion locations, and radiological markers of cerebral small vessel disease (SVD) on MRI were analyzed between the two groups. Patients were followed up for 12 months and functional outcomes were measured by the modified ranking scale (mRS). Results In a total of 584 patients with RSSI, 23 (3.9%) were defined as As-CMI. The most common neurological deficits with As-CMI were hemiparalysis (n = 20), followed by central facial/lingual palsy (n = 10) and hemidysesthesia (n = 10). Most As-CMIs were located in the basal ganglia (n = 11), followed by the thalamus (n = 5) and centrum semiovale (n = 4). No different regional distributions and symptoms/signs frequencies were found between the two groups except for a lower percentage of dysarthria in the As-CMI group (p = 0.008). In a multivariate analysis, patients with As-CMI were independently associated with the presence of lacunes (adjusted odds ratio [aOR] 2.88; 95% confidence interval [CI] 1.21–6.84), multiple lacunes (aOR 3.5, CI 1.29–9.48) and higher total SVD burden (aOR 1.68, CI 1.11–2.53). Patients with As-CMI did not show a better functional outcome after 12 months of follow-up. Conclusions Patients with As-CMI had a non-specific clinical profile but a higher burden of SVD, indicating As-CMI might be s sign of more severe small vascular injury. Whether its vascular features are associated with worse cognitive outcomes requires further investigation.
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Affiliation(s)
- Wendan Tao
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China
| | - Yajun Cheng
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Wen Guo
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China
| | - William Robert Kwapong
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China
| | - Chen Ye
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China
| | - Bo Wu
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China
| | - Shuting Zhang
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China.
| | - Ming Liu
- Center of Cerebrovascular Disease, Department of Neurology, West China Hospital, Sichuan University, Sichuan Province, No. 37 Guo Xue Xiang, Chengdu, 610041, People's Republic of China.
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12
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Cai M, Jacob MA, van Loenen MR, Bergkamp M, Marques J, Norris DG, Duering M, Tuladhar AM, de Leeuw FE. Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up. Stroke 2022; 53:2789-2798. [PMID: 35506383 PMCID: PMC9389939 DOI: 10.1161/strokeaha.121.038099] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD. METHODS Five hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers. RESULTS A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up. CONCLUSIONS SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.
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Affiliation(s)
- Mengfei Cai
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.C., M.A.J., M.B., A.M.T., F.-E.d.L.)
| | - Mina A Jacob
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.C., M.A.J., M.B., A.M.T., F.-E.d.L.)
| | - Mark R van Loenen
- Center for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.R.v.L., J.M., D.G.N.)
| | - Mayra Bergkamp
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.C., M.A.J., M.B., A.M.T., F.-E.d.L.)
| | - José Marques
- Center for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.R.v.L., J.M., D.G.N.)
| | - David G Norris
- Center for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.R.v.L., J.M., D.G.N.)
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Switzerland (M.D.)
| | - Anil M Tuladhar
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.C., M.A.J., M.B., A.M.T., F.-E.d.L.)
| | - Frank-Erik de Leeuw
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour; Nijmegen, the Netherlands. (M.C., M.A.J., M.B., A.M.T., F.-E.d.L.)
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13
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van Veluw SJ, Arfanakis K, Schneider JA. Neuropathology of Vascular Brain Health: Insights From Ex Vivo Magnetic Resonance Imaging-Histopathology Studies in Cerebral Small Vessel Disease. Stroke 2022; 53:404-415. [PMID: 35000425 PMCID: PMC8830602 DOI: 10.1161/strokeaha.121.032608] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Sporadic cerebral small vessel disease (SVD) is a major contributor to vascular cognitive impairment and dementia in the aging human brain. On neuropathology, sporadic SVD is characterized by abnormalities to the small vessels of the brain predominantly in the form of cerebral amyloid angiopathy and arteriolosclerosis. These pathologies frequently coexist with Alzheimer disease changes, such as plaques and tangles, in a single brain. Conversely, during life, magnetic resonance imaging (MRI) only captures the larger manifestations of SVD in the form of parenchymal brain abnormalities. There appears to be a major knowledge gap regarding the underlying neuropathology of individual MRI-detectable SVD abnormalities. Ex vivo MRI in postmortem human brain tissue is a powerful tool to bridge this gap. This review summarizes current insights into the histopathologic correlations of MRI manifestations of SVD, their underlying cause, presumed pathophysiology, and associated secondary tissue injury. Moreover, we discuss the advantages and limitations of ex vivo MRI-guided histopathologic investigations and make recommendations for future studies.
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Affiliation(s)
- Susanne J. van Veluw
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA,Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Konstantinos Arfanakis
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA,Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Julie A. Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA,Departments of Pathology and Neurological Sciences, Rush University Medical Center, Chicago IL, USA
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Hotz I, Deschwanden PF, Mérillat S, Liem F, Kollias S, Jäncke L. Associations of subclinical cerebral small vessel disease and processing speed in non-demented subjects: A 7-year study. Neuroimage Clin 2021; 32:102884. [PMID: 34911190 PMCID: PMC8633374 DOI: 10.1016/j.nicl.2021.102884] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/26/2021] [Accepted: 11/16/2021] [Indexed: 12/22/2022]
Abstract
Markers of cerebral small vessel disease (CSVD) have previously been associated with age-related cognitive decline. Using longitudinal data of cognitively healthy, older adults (N = 216, mean age at baseline = 70.9 years), we investigated baseline status and change in white matter hyperintensities (WMH) (total, periventricular, deep), normal appearing white matter (NAWM), brain parenchyma volume (BPV) and processing speed over seven years as well as the impact of different covariates by applying latent growth curve (LGC) models. Generally, we revealed a complex pattern of associations between the different CSVD markers. More specifically, we observed that changes of deep WMH (dWMH), as compared to periventricular WMH (pWMH), were more strongly related to the changes of other CSVD markers and also to baseline processing speed performance. Further, the number of lacunes rather than their volume reflected the severity of CSVD. With respect to the studied covariates, we revealed that higher education had a protective effect on subsequent total WMH, pWMH, lacunar number, NAWM volume, and processing speed performance. The indication of antihypertensive drugs was associated with lower lacunar number and volume at baseline and the indication of antihypercholesterolemic drugs came along with higher processing speed performance at baseline. In summary, our results confirm previous findings, and extend them by providing information on true within-person changes, relationships between the different CSVD markers and brain-behavior associations. The moderate to strong associations between changes of the different CSVD markers indicate a common pathological relationship and, thus, support multidimensional treatment strategies.
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Affiliation(s)
- Isabel Hotz
- Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.
| | - Pascal Frédéric Deschwanden
- University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Franziskus Liem
- University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Spyridon Kollias
- Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Lutz Jäncke
- Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.
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Wan L, Liu T, Chen T, Chi H, Zhou Z, Tang Z, Hu Q, Teng J, Sun Y, Liu H, Cheng X, Ye J, Su Y, Lu Y, Yang C, Shi H. The high prevalence of abnormal MRI findings in non-neuropsychiatric patients with persistently positive antiphospholipid antibodies. Rheumatology (Oxford) 2021; 61:SI30-SI38. [PMID: 34559215 DOI: 10.1093/rheumatology/keab649] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 08/06/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES Thrombosis occurring in the central nerve system is common in antiphospholipid syndrome (APS) patients, leading to neuropsychiatric symptoms. We investigated the prevalence of silent brain abnormalities on magnetic resonance imaging (MRI) in primary antiphospholipid syndrome (PAPS) patients and antiphospholipid antibodies (aPL) carriers and assessed the association between the vascular risk factors, aPL profile, clinical manifestations, and MRI abnormalities. METHODS We consecutively included 44 PAPS patients, 24 aPL carriers and 23 healthy controls with comparable age and gender in a single-center, observational cross-sectional study. None of the patients had a history of stroke, TIA, migraine, dementia, epilepsy and bipolar disorders. On cerebral MRI, we assessed the imaging features and location of abnormality. Multivariate analysis was performed to identify the risk factors contributing to the MRI abnormalities. RESULTS 38 (55.88%) patients persisted abnormal MRI findings, while only one healthy control showed some abnormalities in the MR findings. Lacunes were the most frequent MRI abnormality in aPL (+) group (31/68, 45.59%), which were followed by white matter hyperintensities (20/68, 29.41%). In all study population, age (OR = 1.086, p= 0.016) and LA positivity (OR = 5.191, p= 0.002) were the independent associated factors with the brain MRI abnormalities. When analyzed only in the aPL (+) group, age (OR = 1.116, p= 0.007), female gender (OR = 7.519, p= 0.025) and thrombocytopenia (OR = 8.336, p= 0.047) were the significant independent risk factors with abnormal MRI. CONCLUSIONS PAPS patients and aPL carriers showed a high prevalence of brain MRI abnormalities, indicating an increased cerebrovascular risk, which emphasized attention to silent cerebral lesions in persistently aPL positive patients.
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Affiliation(s)
- Liyan Wan
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tingting Liu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tongtong Chen
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huihui Chi
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhuochao Zhou
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zihan Tang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiongyi Hu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jialin Teng
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Sun
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Honglei Liu
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaobing Cheng
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junna Ye
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yutong Su
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yong Lu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Director's Office, Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chengde Yang
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Shi
- Department of Rheumatology and Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Voigt S, de Kruijff PC, Koemans EA, Rasing I, van Etten ES, Terwindt GM, van Osch M, van Buchem MA, van Walderveen M, Wermer M. Cerebellar hemorrhages in patients with Dutch-type hereditary cerebral amyloid angiopathy. Int J Stroke 2021; 17:637-644. [PMID: 34427476 PMCID: PMC9260473 DOI: 10.1177/17474930211043663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background Recent studies suggest that superficially located cerebellar intracerebral
hemorrhage (ICH) and microbleeds might point towards sporadic cerebral
amyloid angiopathy (CAA). Aims We investigated the proportion of cerebellar ICH and asymptomatic macro- and
microbleeds in Dutch-type hereditary CAA (D-CAA), a severe and essentially
pure form of CAA. Methods Symptomatic patients with D-CAA (defined as ≥1 symptomatic ICH) and
presymptomatic D-CAA mutation-carriers were included. We assessed magnetic
resonance imaging scans for symptomatic (cerebellar) ICH and asymptomatic
cerebellar macro- and microbleeds according to the STRIVE-criteria. Location
was assessed as superficial-cerebellar (cortex, vermis or juxta-cortical) or
deep-cerebellar (white matter, pedunculi cerebelli and gray nuclei). Results We included 63 participants (mean age 58 years, 60% women, 42 symptomatic).
In total, the 42 symptomatic patients with D-CAA had 107 symptomatic ICH
(range 1–7). None of these ICH were located in the cerebellum. Six of 42
(14%, 95%CI 4–25%) symptomatic patients and none of the 21 (0%, 95%CI 0–0%)
presymptomatic carriers had ≥ 1 asymptomatic cerebellar macrobleed(s). All
macrobleeds were superficially located. Cerebellar microbleeds were found in
40 of 63 (64%, 95%CI 52–76) participants (median 1.0, range 0–159), 81% in
symptomatic patients and 29% in presymptomatic carriers. All microbleeds
were strictly or predominantly superficially (ratio superficial versus deep
15:1) located. Conclusions Superficially located asymptomatic cerebellar macrobleeds and microbleeds are
common in D-CAA. Cerebellar microbleeds are already present in the
presymptomatic stage. Despite the high frequency of cerebellar micro and
macrobleeds, CAA pathology did not result in symptomatic cerebellar ICH in
patients with D-CAA.
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Affiliation(s)
- S Voigt
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - P C de Kruijff
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - E A Koemans
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - I Rasing
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - E S van Etten
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - G M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mjp van Osch
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - M A van Buchem
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maa van Walderveen
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mjh Wermer
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
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17
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Zanon Zotin MC, Sveikata L, Viswanathan A, Yilmaz P. Cerebral small vessel disease and vascular cognitive impairment: from diagnosis to management. Curr Opin Neurol 2021; 34:246-257. [PMID: 33630769 PMCID: PMC7984766 DOI: 10.1097/wco.0000000000000913] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE OF REVIEW We present recent developments in the field of small vessel disease (SVD)-related vascular cognitive impairment, including pathological mechanisms, updated diagnostic criteria, cognitive profile, neuroimaging markers and risk factors. We further address available management and therapeutic strategies. RECENT FINDINGS Vascular and neurodegenerative pathologies often co-occur and share similar risk factors. The updated consensus criteria aim to standardize vascular cognitive impairment (VCI) diagnosis, relying strongly on cognitive profile and MRI findings. Aggressive blood pressure control and multidomain lifestyle interventions are associated with decreased risk of cognitive impairment, but disease-modifying treatments are still lacking. Recent research has led to a better understanding of mechanisms leading to SVD-related cognitive decline, such as blood-brain barrier dysfunction, reduced cerebrovascular reactivity and impaired perivascular clearance. SUMMARY SVD is the leading cause of VCI and is associated with substantial morbidity. Tackling cardiovascular risk factors is currently the most effective approach to prevent cognitive decline in the elderly. Advanced imaging techniques provide tools for early diagnosis and may play an important role as surrogate markers for cognitive endpoints in clinical trials. Designing and testing disease-modifying interventions for VCI remains a key priority in healthcare.
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Affiliation(s)
- Maria Clara Zanon Zotin
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Center for Imaging Sciences and Medical Physics. Department of Medical Imaging, Hematology and Clinical Oncology. Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Lukas Sveikata
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute of Cardiology, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Pinar Yilmaz
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Departments of Epidemiology and Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
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Abstract
ABSTRACT Cerebral small vessel disease (SVD) is a common global brain disease that causes cognitive impairment, ischemic or hemorrhagic stroke, problems with mobility, and neuropsychiatric symptoms. The brain damage, seen as focal white and deep grey matter lesions on brain magnetic resonance imaging (MRI) or computed tomography (CT), typically accumulates "covertly" and may reach an advanced state before being detected incidentally on brain scanning or causing symptoms. Patients have typically presented to different clinical services or been recruited into research focused on one clinical manifestation, perhaps explaining a lack of awareness, until recently, of the full range and complexity of SVD.In this review, we discuss the varied clinical presentations, established and emerging risk factors, relationship to SVD features on MRI or CT, and the current state of knowledge on the effectiveness of a wide range of pharmacological and lifestyle interventions. The core message is that effective assessment and clinical management of patients with SVD, as well as future advances in diagnosis, care, and treatment, will require a more "joined-up"' approach. This approach should integrate clinical expertise in stroke neurology, cognitive, and physical dysfunctions. It requires more clinical trials in order to improve pharmacological interventions, lifestyle and dietary modifications. A deeper understanding of the pathophysiology of SVD is required to steer the identification of novel interventions. An essential prerequisite to accelerating clinical trials is to improve the consistency, and standardization of clinical, cognitive and neuroimaging endpoints.
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