GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 11
    Online Resource
    Online Resource
    Table_1.xlsx
    Frontiers Media SA ; 2021
    In:  Frontiers in Neuroscience Vol. 15 ( 2021-7-12)
    Details
    In: Frontiers in Neuroscience, Frontiers Media SA, Vol. 15 ( 2021-7-12)
    Abstract: Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes. Methods We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask–WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA). Results Radiomic features were predictive of WMH burden ( R 2 = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p -values CV 1 – 6 & lt; 0.001, p -value CV 7 = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes. Conclusion Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients’ brain health.
    Type of Medium: Online Resource
    ISSN: 1662-453X
    URL: Article
    URL: Article
    DOI: 10.3389/fnins.2021.691244
    DOI: 10.3389/fnins.2021.691244.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2411902-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 12
    Online Resource
    Online Resource
    The relevance of rich club regions for functional outcome post‐stroke is enhanced in women
    Wiley ; 2023
    In:  Human Brain Mapping Vol. 44, No. 4 ( 2023-03), p. 1579-1592
    Details
    In: Human Brain Mapping, Wiley, Vol. 44, No. 4 ( 2023-03), p. 1579-1592
    Abstract: This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich‐club) brain regions on functional outcome post‐stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3‐months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI‐GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas‐defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS  〉  2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non‐rich club regions. In spatial specificity analyses, we randomized the split into “rich club” and “non‐rich club” regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex‐specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female‐specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club‐combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long‐term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.
    Type of Medium: Online Resource
    ISSN: 1065-9471 , 1097-0193
    URL: Issue
    URL: Article
    DOI: 10.1002/hbm.v44.4
    DOI: 10.1002/hbm.26159
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1492703-2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 13
    Online Resource
    Online Resource
    Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study
    Elsevier BV ; 2016
    In:  The Lancet Neurology Vol. 15, No. 2 ( 2016-02), p. 174-184
    Details
    In: The Lancet Neurology, Elsevier BV, Vol. 15, No. 2 ( 2016-02), p. 174-184
    Type of Medium: Online Resource
    ISSN: 1474-4422
    URL: Article
    DOI: 10.1016/S1474-4422(15)00338-5
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 14
    Online Resource
    Online Resource
    White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Neurology Vol. 95, No. 1 ( 2020-07-07), p. e79-e88
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 95, No. 1 ( 2020-07-07), p. e79-e88
    Abstract: To examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS). Methods For the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool–based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes. Results Patients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all p 〈 0.001). Median WMHv in all patients with AIS was 5.86 cm 3 (interquartile range 2.18–14.61 cm 3 ) and differed significantly across CCS subtypes ( p 〈 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all p 〈 0.001), and diabetes mellitus ( p = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes ( p 〈 0.001). Conclusion In this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000009728
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 15
    Online Resource
    Online Resource
    Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome
    Ovid Technologies (Wolters Kluwer Health) ; 2022
    In:  Neurology Vol. 99, No. 13 ( 2022-09-27), p. e1364-e1379
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 99, No. 13 ( 2022-09-27), p. e1364-e1379
    Abstract: To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern–specific ways. Methods MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3–6 months after stroke were obtained from the MRI–Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning–based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score 〉 2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age 2 , sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts. Results A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location–specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location. Discussion Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.0000000000200926
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 16
    Online Resource
    Online Resource
    The Association of SUR1 Polymorphisms with Acute Infarct Size: The MRI-GENIE Study (1348)
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Neurology Vol. 94, No. 15_supplement ( 2020-04-14)
    Details
    In: Neurology, Ovid Technologies (Wolters Kluwer Health), Vol. 94, No. 15_supplement ( 2020-04-14)
    Type of Medium: Online Resource
    ISSN: 0028-3878 , 1526-632X
    URL: Article
    DOI: 10.1212/WNL.94.15_supplement.1348
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 17
    Online Resource
    Online Resource
    Data_Sheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Neuroscience Vol. 16 ( 2022-8-25)
    Details
    In: Frontiers in Neuroscience, Frontiers Media SA, Vol. 16 ( 2022-8-25)
    Abstract: A substantial number of patients with acute ischemic stroke (AIS) experience multiple acute lesions (MAL). We here aimed to scrutinize MAL in a large radiologically deep-phenotyped cohort. Materials and methods Analyses relied upon imaging and clinical data from the international MRI-GENIE study. Imaging data comprised both Fluid-attenuated inversion recovery (FLAIR) for white matter hyperintensity (WMH) burden estimation and diffusion-weighted imaging (DWI) sequences for the assessment of acute stroke lesions. The initial step featured the systematic evaluation of occurrences of MAL within one and several vascular supply territories. Associations between MAL and important imaging and clinical characteristics were subsequently determined. The interaction effect between single and multiple lesion status and lesion volume was estimated by means of Bayesian hierarchical regression modeling for both stroke severity and functional outcome. Results We analyzed 2,466 patients (age = 63.4 ± 14.8, 39% women), 49.7% of which presented with a single lesion. Another 37.4% experienced MAL in a single vascular territory, while 12.9% featured lesions in multiple vascular territories. Within most territories, MAL occurred as frequently as single lesions (ratio ∼1:1). Only the brainstem region comprised fewer patients with MAL (ratio 1:4). Patients with MAL presented with a significantly higher lesion volume and acute NIHSS (7.7 vs. 1.7 ml and 4 vs. 3, p FDR & lt; 0.001). In contrast, patients with a single lesion were characterized by a significantly higher WMH burden (6.1 vs. 5.3 ml, p FDR = 0.048). Functional outcome did not differ significantly between patients with single versus multiple lesions. Bayesian analyses suggested that the association between lesion volume and stroke severity between single and multiple lesions was the same in case of anterior circulation stroke. In case of posterior circulation stroke, lesion volume was linked to a higher NIHSS only among those with MAL. Conclusion Multiple lesions, especially those within one vascular territory, occurred more frequently than previously reported. Overall, multiple lesions were distinctly linked to a higher acute stroke severity, a higher total DWI lesion volume and a lower WMH lesion volume. In posterior circulation stroke, lesion volume was linked to a higher stroke severity in multiple lesions only.
    Type of Medium: Online Resource
    ISSN: 1662-453X
    URL: Article
    URL: Article
    DOI: 10.3389/fnins.2022.994458
    DOI: 10.3389/fnins.2022.994458.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2411902-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 18
    Online Resource
    Online Resource
    Abstract WMP56: Genetics of Acute Ischemic Lesion Volume: the MRI-Genetics Interface Exploration (MRI-GENIE) Study
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Stroke Vol. 49, No. Suppl_1 ( 2018-01-22)
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 49, No. Suppl_1 ( 2018-01-22)
    Abstract: Introduction: Genome-wide association (GWA) studies have contributed substantially to the understanding of complex vascular traits including ischemic stroke; however, genetic determinants of acute cerebral ischemia remain to be elucidated. Objective: To investigate the genetic architecture of cerebral infarct lesion burden in patients with acute ischemic stroke (AIS). Methods: Twelve international sites contributed 3,301 AIS subjects with acute MRI and genome-wide genotyping to the MRI-GENIE study. In a preliminary analysis of 657 subjects of European ancestry, acute cerebral infarct lesions were outlined on diffusion-weighted images (DWI) using a semi-automated volumetric method. Standard quality control measures were performed per single nucleotide polymorphism (SNP) and per subject. SNPs were imputed to the Haplotype Reference Consortium v1.1 panel. Natural log-transformed DWI volume was used for GWA analysis with allelic dosage per SNP, age, sex and principal components 1-5 of genetic ancestry as covariates. Results: GWA testing for DWI volume in 7.7 million SNPs yielded no signal crossing the Bonferroni-corrected genome-wide significance threshold of p 〈 5*10 -8 . However, several loci passed the nominal significance threshold of p 〈 1*10 -6 (Figure 1), including a locus on chromosome 2 in the SPATA3-AS1 (spermatogenesis associated 3 antisense RNA 1) gene (lead SNP: rs2368999, MAF=36%, p =8.4*10 -7 ) and an intronic locus on chromosome 10 in the ATRNL1 (Attractin like 1) gene (lead SNP: rs592284, MAF=10%, p =9.1*10 -7 ). Conclusion: In this first-to-date, preliminary GWAS of acute cerebral infarct volume in AIS patients, we identified several new, nominally significant loci including a locus in ATRNL1, a gene previously linked to carotid plaque burden. Further analyses of the MRI-GENIE cohort to replicate these findings, to include stroke subtype specific analyses, and to increase the overall statistical power of the study are ongoing.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/str.49.suppl_1.WMP56
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
    detail.hit.zdb_id: 1467823-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 19
    Online Resource
    Online Resource
    Abstract WP204: Genetic Variant in VCAM1 Mediates Acute Infarct Size in Ischemic Stroke Patients
    Ovid Technologies (Wolters Kluwer Health) ; 2017
    In:  Stroke Vol. 48, No. suppl_1 ( 2017-02)
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 48, No. suppl_1 ( 2017-02)
    Abstract: Introduction: Even though neuroinflammation is increasingly recognized as an essential contributor to ischemic brain injury, the exact underlying mechanisms remain unclear. Higher expression of the vascular cell adhesion molecule 1 (VCAM-1) increases leukocyte-brain endothelium interaction and has been associated with larger infarct size following acute ischemic stroke (AIS). The activation of the TGF-β signaling pathways can down-regulate VCAM-1 expression and ameliorate deleterious tissue outcome during neuroinflammation. Hypothesis: We sought to investigate whether genetic variation in the TGF-beta pathway and adhesion molecule genes is associated with acute stroke lesion size. Methods: We completed genome-wide association (GWA) testing and diffusion-weighted imaging lesion volume (DWIv) analysis in a discovery cohort of 532 AIS patients of European ancestry enrolled within 48 hours of symptom onset. An independent European ancestry cohort of 724 AIS patients with GWA data and automated DWIv served as replication cohort. GWA testing per SNP was performed using linear regression modeling of natural log-transformed DWIv adjusted for age, sex and relevant principal components. We selected 42 inflammatory genes in the TGF-beta pathway for a gene-based analysis using VEGAS (Versatile Gene-based -Association Study) software. A pre-specified discovery phase Bonferroni-corrected threshold was set at p 〈 0.001. In the replication phase, 14 SNPs overlapping were tested at the Bonferroni-corrected p-value threshold of p 〈 0.004. Results: Of all genes in the TGF-beta pathway, VCAM1 (p=0.0006) was significantly associated with DWIv in the discovery AIS cohort (age: 66 ± 14.9 years, sex: 63.4% male, DWIv: 2.2cm 3 (IQR: 0.6-11.7cm 3 )). A single SNP within the VCAM1 gene boundaries (rs3176876 (BETA=0.2341, p=0.003)) was significantly associated with DWIv in the replication AIS cohort (age: 65 ± 14.1 years, sex: 68.6% male, DWIv: 4cm 3 (IQR: 1.3-17.2cm 3 )). Conclusion: The genetic variant rs3176876 in the VCAM1 gene is associated with larger infarct lesion size measured on brain MRI of AIS patients. These findings suggest genetic contribution to the pro-inflammatory mechanisms in acute cerebral ischemia and warrant further investigation.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/str.48.suppl_1.wp204
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2017
    detail.hit.zdb_id: 1467823-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 20
    Online Resource
    Online Resource
    Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
    Ovid Technologies (Wolters Kluwer Health) ; 2019
    In:  Stroke Vol. 50, No. 7 ( 2019-07), p. 1734-1741
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 50, No. 7 ( 2019-07), p. 1734-1741
    Abstract: 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 (ρ=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.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/STROKEAHA.119.025373
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2019
    detail.hit.zdb_id: 1467823-8
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...