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- Fazekas, F., et al.
(författare)
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Brain Magnetic Resonance Imaging Findings Fail to Suspect Fabry Disease in Young Patients With an Acute Cerebrovascular Event
- 2015
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 46:6
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose-Fabry disease (FD) may cause stroke and is reportedly associated with typical brain findings on magnetic resonance imaging (MRI). In a large group of young patients with an acute cerebrovascular event, we wanted to test whether brain MRI findings can serve to suggest the presence of FD. Methods-The Stroke in Young Fabry Patients (SIFAP 1) study prospectively collected clinical, laboratory, and radiological data of 5023 patients (18-55 years) with an acute cerebrovascular event. Their MRI was interpreted centrally and blinded to all other information. Biochemical findings and genetic testing served to diagnose FD in 45 (0.9%) patients. We compared the imaging findings between FD and non-FD patients in patients with at least a T2-weighted MRI of good quality. Results-A total of 3203 (63.8%) patients had the required MRI data set. Among those were 34 patients with a diagnosis of FD (1.1%), which was definite in 21 and probable in 13 cases. The median age of patients with FD was slightly lower (45 versus 46 years) and women prevailed (70.6% versus 40.7%; P<0.001). Presence or extent of white matter hyperintensities, infarct localization, vertebrobasilar artery dilatation, T1-signal hyperintensity of the pulvinar thalami, or any other MRI finding did not distinguish patients with FD from non-FD cerebrovascular event patients. Pulvinar hyperintensity was not present in a single patient with FD but seen in 6 non-FD patients. Conclusions-Brain MRI findings cannot serve to suspect FD in young patients presenting with an acute cerebrovascular event. This deserves consideration in the search for possible causes of young patients with stroke.
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| 2. |
- Jokinen, H., et al.
(författare)
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Global Burden of Small Vessel Disease-Related Brain Changes on MRI Predicts Cognitive and Functional Decline
- 2020
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 51:1, s. 170-178
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple types of small vessel disease-related brain changes and examined their individual and combined predictive value on cognitive and functional abilities. Methods- Magnetic resonance imaging scans of 560 older individuals from LADIS (Leukoaraiosis and Disability Study) were analyzed using automated atlas- and convolutional neural network-based segmentation methods yielding volumetric measures of white matter hyperintensities, lacunes, enlarged perivascular spaces, chronic cortical infarcts, and global and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years. Results- The strongest predictors of cognitive performance and functional outcome over time were the total volumes of white matter hyperintensities, gray matter, and hippocampi (P<0.001 for global cognitive function, processing speed, executive functions, and memory and P<0.001 for poor functional outcome). Volumes of lacunes, enlarged perivascular spaces, and cortical infarcts were significantly associated with part of the outcome measures, but their contribution was weaker. In a multivariable linear mixed model, volumes of white matter hyperintensities, lacunes, gray matter, and hippocampi remained as independent predictors of cognitive impairment. A combined measure of these markers based on Z scores strongly predicted cognitive and functional outcomes (P<0.001) even above the contribution of the individual brain changes. Conclusions- Global burden of small vessel disease-related brain changes as quantified by an image segmentation tool is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of white matter hyperintensities, lacunar, gray matter, and hippocampal volumes could be used as an imaging marker associated with vascular cognitive impairment.
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| 3. |
- Schmidt, R., et al.
(författare)
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White Matter Lesion Progression in LADIS Frequency, Clinical Effects, and Sample Size Calculations
- 2012
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 43:10, s. 2643-2647
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose-White matter lesion (WML) progression has been advocated as a surrogate marker in intervention trials on cerebral small vessel disease. We assessed the rate of visually rated WML progression, studied correlations between lesion progression and cognition, and estimated sample sizes for clinical trials with pure WML progression vs combined WML progression-cognitive outcomes. Methods-Those 394 participants of the Leukoaraiosis and Disability Study (LADIS) study with magnetic resonance imaging scanning at baseline and 3-year follow-up were analyzed. WML progression rating relied on the modified Rotterdam Progression Scale. The Vascular Dementia Assessment Scale global score and a composite score of specific executive function tests assessed longitudinal change in cognition. Sample size calculations were based on the assumption that treatment reduces WML progression by 1 grade on the Rotterdam Progression Scale. Results-WML progression related to deterioration in cognitive functioning. This relationship was less pronounced in subjects with early confluent and confluent lesions. Consequently, studies in which the outcome is cognitive change resulting from treatment effects on lesion progression will need between 1809 subjects per treatment arm when using executive tests and up to 18 853 subjects when using the Vascular Dementia Assessment Scale score. Studies having WML progression as the sole outcome will need only 58 or 70 individuals per treatment arm. Conclusions-WML progression is an interesting outcome for proof-of-concept studies in cerebral small vessel disease. If cognitive outcome measures are added to protocols, then sample size estimates increase substantially. Our data support the use of an executive test battery rather than the Vascular Dementia Assessment Scale as the primary cognitive outcome measure. (Stroke. 2012; 43:2643-2647.)
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| 4. |
- Thijs, V., et al.
(författare)
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Dolichoectasia and Small Vessel Disease in Young Patients With Transient Ischemic Attack and Stroke
- 2017
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 48:9, s. 2361-
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose-We evaluated whether basilar dolichoectasia is associated with markers of cerebral small vessel disease in younger transient ischemic attack and ischemic stroke patients. Methods-We used data from the SIFAP1 study (Stroke in Young Fabry Patients), a large prospective, hospital-based, screening study for Fabry disease in young (<55 years) transient ischemic attack/stroke patients in whom detailed clinical data and brain MRI were obtained, and stroke subtyping with TOAST classification (Trial of ORG 10172 in Acute Stroke Treatment) was performed. Results-Dolichoectasia was found in 508 of 3850 (13.2%) of patients. Dolichoectasia was associated with older age (odds ratio per decade, 1.26; 95% confidence interval, 1.09-1.44), male sex (odds ratio, 1.96; 95% confidence interval, 1.592.42), and hypertension (odds ratio, 1.39; 95% confidence interval, 1.13-1.70). Dolichoectasia was more common in patients with small infarctions (33.9% versus 29.8% for acute lesions, P=0.065; 29.1% versus 16.5% for old lesions, P<0.001), infarct location in the brain stem (12.4% versus 6.9%, P<0.001), and in white matter (27.8% versus 21.1%, P=0.001). Microbleeds (16.3% versus 4.7%, P=0.001), higher grades of white matter hyperintensities (P<0.001), and small vessel disease subtype (18.1% versus 12.4%, overall P for differences in TOAST (P=0.018) were more often present in patients with dolichoectasia. Conclusions-Dolichoectasia is associated with imaging markers of small vessel disease and brain stem localization of acute and old infarcts in younger patients with transient ischemic attack and ischemic stroke.
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| 5. |
- Wu, O., et al.
(författare)
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Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- 2019
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Ingår i: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 50:7, s. 1734-1741
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (rho=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm(3) (0.9-16.6 cm(3)). Patients with small artery occlusion stroke subtype had smaller lesion volumes (P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.
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