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  • 1
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    Longitudinal brain age prediction and cognitive function after stroke
    Elsevier BV ; 2023
    In:  Neurobiology of Aging Vol. 122 ( 2023-02), p. 55-64
    Details
    In: Neurobiology of Aging, Elsevier BV, Vol. 122 ( 2023-02), p. 55-64
    Type of Medium: Online Resource
    ISSN: 0197-4580
    URL: Article
    DOI: 10.1016/j.neurobiolaging.2022.10.007
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
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    SSG: 12
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  • 2
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    Diagnostic imaging strategies of acute intracerebral hemorrhage in European academic hospitals—a decision-making analysis
    Springer Science and Business Media LLC ; 2023
    In:  Neuroradiology Vol. 65, No. 4 ( 2023-04), p. 729-736
    Details
    In: Neuroradiology, Springer Science and Business Media LLC, Vol. 65, No. 4 ( 2023-04), p. 729-736
    Type of Medium: Online Resource
    ISSN: 0028-3940 , 1432-1920
    URL: Article
    DOI: 10.1007/s00234-022-03110-9
    RVK:
    XA 10000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 123305-1
    detail.hit.zdb_id: 1462953-7
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  • 3
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    Clinically accessible neuroimaging predictors of post-stroke neurocognitive disorder: a prospective observational study
    Springer Science and Business Media LLC ; 2021
    In:  BMC Neurology Vol. 21, No. 1 ( 2021-12)
    Details
    In: BMC Neurology, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2021-12)
    Abstract: Neurocognitive disorder (NCD) is common in stroke survivors. We aimed to identify clinically accessible imaging markers of stroke and chronic pathology that are associated with early post-stroke NCD. Methods We included 231 stroke survivors from the “Norwegian Cognitive Impairment after Stroke (Nor-COAST)” study who underwent a standardized cognitive assessment 3 months after the stroke. Any NCD (mild cognitive impairment and dementia) and major NCD (dementia) were diagnosed according to “Diagnostic and Statistical Manual of Mental Disorders (DSM-5)” criteria. Clinically accessible imaging findings were analyzed on study-specific brain MRIs in the early phase after stroke. Stroke lesion volumes were semi automatically quantified and strategic stroke locations were determined by an atlas based coregistration. White matter hyperintensities (WMH) and medial temporal lobe atrophy (MTA) were visually scored. Logistic regression was used to identify neuroimaging findings associated with major NCD and any NCD. Results Mean age was 71.8 years (SD 11.1), 101 (43.7%) were females, mean time from stroke to imaging was 8 (SD 16) days. At 3 months 63 (27.3%) had mild NCD and 65 (28.1%) had major NCD. Any NCD was significantly associated with WMH pathology (odds ratio (OR) = 2.73 [1.56 to 4.77], p  = 0.001), MTA pathology (OR = 1.95 [1.12 to 3.41], p  = 0.019), and left hemispheric stroke (OR = 1.8 [1.05 to 3.09], p  = 0.032). Major NCD was significantly associated with WMH pathology (OR = 2.54 [1.33 to 4.84], p  = 0.005) and stroke lesion volume (OR (per ml) =1.04 [1.01 to 1.06], p  = 0.001). Conclusion WMH pathology, MTA pathology and left hemispheric stroke were associated with the development of any NCD. Stroke lesion volume and WMH pathology were associated with the development of major NCD 3 months after stroke. These imaging findings may be used in the routine clinical setting to identify patients at risk for early post-stroke NCD. Trial registration ClinicalTrials.gov, NCT02650531 , Registered 8 January 2016 – Retrospectively registered.
    Type of Medium: Online Resource
    ISSN: 1471-2377
    URL: Article
    DOI: 10.1186/s12883-021-02117-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041347-6
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  • 4
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    Abstract P66: Prediction of Early Post-Stroke Major Neurocognitive Disorder Using Support Vector Machines
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Stroke Vol. 52, No. Suppl_1 ( 2021-03)
    Details
    In: Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 52, No. Suppl_1 ( 2021-03)
    Abstract: Neurocognitive disorder (NCD) appears in 10% of survivors of a first-ever stroke and in 30% after a recurrent one. We aimed to classify clinical- and imaging factors related to the development of major NCD 3 months post stroke, so as to examine whether early development ( 〈 1 yr) is mainly of a neurodegenerative or vascular origin. Based on previous literature we hypothesized that early post-stroke major NCD would mainly be of neurodegenerative origin. 227 stroke survivors (age = 71.69 (11.25), NIHSS = 3.79 (4.75), females (43,61%)) were included from the ‘Norwegian COgnitive Impairment After STroke’ study. Clinical- and MRI data at baseline, and neuropsychological data at baseline and 3 months was used. Cortical thicknesses were automatically measured using Freesurfer and white matter hyperintensity (WMH) volumes were semi-automatically measured using FSL Bianca. Stroke lesion volumes were semi-automatically measured using ITK-snap. Support Vector Machine (SVM) classification was used in order to investigate the prognostic value of the neuroimaging findings and the clinical factors. Model performance was measured using Area Under Receiving Operating Characteristics (ROC) and -Curve (AUC). The best model correctly predicted major NCD in 88% of the patients and was driven by 19 features, with the top five features being stroke volume, WMH volume, left hemisphere occipital- and temporal thickness, and right hemisphere cingulate thickness. In conclusion, clinical- and MRI findings may be used in prediction of cognitive outcome for stroke patients. Various meta-studies of post-stroke major NCD prediction show levels ranging from .48 to .91, showing that the current model is performing well. Early development of major NCD seems dependent not on neurodegenerative causes alone, but also on vascular factors, as well as aspects of the stroke itself. This highlights the complexity of post-stroke NCD and thus also its prediction. Figure 1: ROC curve of SVM model, with an AUC of .88.
    Type of Medium: Online Resource
    ISSN: 0039-2499 , 1524-4628
    URL: Article
    DOI: 10.1161/str.52.suppl_1.P66
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
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    detail.hit.zdb_id: 1467823-8
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  • 5
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    Analysis of diffusion tensor imaging metrics for gliomas grading at 3T
    Elsevier BV ; 2014
    In:  European Journal of Radiology Vol. 83, No. 3 ( 2014-03), p. e156-e165
    Details
    In: European Journal of Radiology, Elsevier BV, Vol. 83, No. 3 ( 2014-03), p. e156-e165
    Type of Medium: Online Resource
    ISSN: 0720-048X
    URL: Article
    DOI: 10.1016/j.ejrad.2013.12.023
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
    detail.hit.zdb_id: 138815-0
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  • 6
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    Proton magnetic resonance spectroscopy in the distinction of high-grade cerebral gliomas from single metastatic brain tumors
    SAGE Publications ; 2010
    In:  Acta Radiologica Vol. 51, No. 3 ( 2010-04), p. 316-325
    Details
    In: Acta Radiologica, SAGE Publications, Vol. 51, No. 3 ( 2010-04), p. 316-325
    Abstract: Background: Brain metastases and primary high-grade gliomas, including glioblastomas multiforme (GBM) and anaplastic astrocytomas (AA), may be indistinguishable by conventional magnetic resonance (MR) imaging. Identification of these tumors may have therapeutic consequences. Purpose: To assess the value of MR spectroscopy (MRS) using short and intermediate echo time (TE) in differentiating solitary brain metastases and high-grade gliomas on the basis of differences in metabolite ratios in the intratumoral and peritumoral region. Material and Methods: We performed MR imaging and MRS in 73 patients with histologically verified intraaxial brain tumors: 53 patients with high-grade gliomas (34 GBM and 19 AA) and 20 patients with metastatic brain tumors. The metabolite ratios of Cho/Cr, Cho/NAA, and NAA/Cr at intermediate TE and the presence of lipids at short TE were assessed from spectral maps in the tumoral core, peritumoral edema, and contralateral normal-appearing white matter. The differences in the metabolite ratios between high-grade gliomas/GBM/AA and metastases were analyzed statistically. Cutoff values of Cho/Cr, Cho/NAA, and NAA/Cr ratios in the peritumoral edema, as well as Cho/Cr and NAA/Cr ratios in the tumoral core for distinguishing high-grade gliomas/GBM/AA from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Significant differences were noted in the peritumoral Cho/Cr, Cho/NAA, and NAA/ Cr ratios between high-grade gliomas/GBM/AA and metastases. ROC analysis demonstrated a cutoff value of 1.24 for peritumoral Cho/Cr ratio to provide sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 100%, 88.9%, 80.0%, and 100%, respectively, for discrimination between high-grade gliomas and metastases. By using a cutoff value of 1.11 for peritumoral Cho/NAA ratio, the sensitivity was 100%, the specificity was 91.1%, the PPV was 83.3%, and the NPV was 100%. Conclusion: The results of this study demonstrate that MRS can differentiate high-grade gliomas from metastases, especially with peritumoral measurements, supporting the hypothesis that MRS can detect infiltration of tumor cells in the peritumoral edema.
    Type of Medium: Online Resource
    ISSN: 0284-1851 , 1600-0455
    URL: Article
    DOI: 10.3109/02841850903482901
    RVK:
    XA 10000
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2010
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    detail.hit.zdb_id: 2024579-8
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  • 7
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    Pre-stroke cognitive impairment is associated with vascular imaging pathology: a prospective observational study
    Springer Science and Business Media LLC ; 2021
    In:  BMC Geriatrics Vol. 21, No. 1 ( 2021-12)
    Details
    In: BMC Geriatrics, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2021-12)
    Abstract: Chronic brain pathology and pre-stroke cognitive impairment (PCI) is predictive of post-stroke dementia. The aim of the current study was to measure pre-stroke neurodegenerative and vascular disease burden found on brain MRI and to assess the association between pre-stroke imaging pathology and PCI, whilst also looking for potential sex differences. Methods This prospective brain MRI cohort is part of the multicentre Norwegian cognitive impairment after stroke (Nor-COAST) study. Patients hospitalized with acute ischemic or hemorrhagic stroke were included from five participating stroke units. Visual rating scales were used to categorize baseline MRIs ( N  = 410) as vascular, neurodegenerative, mixed, or normal, based on the presence of pathological imaging findings. Pre-stroke cognition was assessed by interviews of patients or caregivers using the Global Deterioration Scale (GDS). Stroke severity was assessed with the National Institute of Health Stroke Scale (NIHSS). Univariate and multiple logistic regression analyses were performed to investigate the association between imaging markers, PCI, and sex. Results Patients’ ( N  = 410) mean (SD) age was 73.6 (±11) years; 182 (44%) participants were female, the mean (SD) NIHSS at admittance was 4.1 (±5). In 68% of the participants, at least one pathological imaging marker was found. Medial temporal lobe atrophy (MTA) was present in 30% of patients, white matter hyperintensities (WMH) in 38% of patients and lacunes in 35% of patients. PCI was found in 30% of the patients. PCI was associated with cerebrovascular pathology (OR 2.5; CI = 1.4 to 4.5, p  = 0.001) and mixed pathology (OR 3.4; CI = 1.9 to 6.1, p  = 0.001) but was not associated with neurodegeneration (OR 1.0; CI = 0.5 to 2.2; p  = 0.973). Pathological MRI markers, including MTA and lacunes, were more prevalent among men, as was a history of clinical stroke prior to the index stroke. The OR of PCI for women was not significantly increased (OR 1.2; CI = 0.8 to 1.9; p  = 0.3). Conclusions Pre-stroke chronic brain pathology is common in stroke patients, with a higher prevalence in men. Vascular pathology and mixed pathology are associated with PCI. There were no significant sex differences for the risk of PCI. Trial registration NCT02650531 , date of registration: 08.01.2016.
    Type of Medium: Online Resource
    ISSN: 1471-2318
    URL: Article
    DOI: 10.1186/s12877-021-02327-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2059865-8
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  • 8
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    Is Frailty Index a better predictor than pre-stroke modified Rankin Scale for neurocognitive outcomes 3-months post-stroke?
    Springer Science and Business Media LLC ; 2022
    In:  BMC Geriatrics Vol. 22, No. 1 ( 2022-12)
    Details
    In: BMC Geriatrics, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2022-12)
    Abstract: The prognostic value of frailty measures for post-stroke neurocognitive disorder (NCD) remains to be evaluated. Aims The aim of this study was to compare the predictive value of pre-stroke FI with pre-stroke modified Rankin Scale (mRS) for post-stroke cognitive impairment. Further, we explored the added value of including FI in prediction models for cognitive prognosis post-stroke. Methods We generated a 36-item Frailty Index (FI), based on the Rockwood FI, to measure frailty based on pre-stroke medical conditions recorded in the Nor-COAST multicentre prospective study baseline assessments. Consecutive participants with a FI score and completed cognitive test battery at three months were included. We generated Odds Ratio (OR) with NCD as the dependent variable. The predictors of primary interest were pre-stroke frailty and mRS. We also measured the predictive values of mRS and FI by the area (AUC) under the receiver operating characteristic curve. Results 598 participants (43.0% women, mean/SD age = 71.6/11.9, mean/SD education = 12.5/3.8, mean/SD pre-stroke mRS = 0.8/1.0, mean/SD GDS pre-stroke = 1.4/0.8, mean/SD NIHSS day 1 3/4), had a FI mean/SD score = 0.14/0.10. The logistic regression analyses showed that FI (OR 3.09), as well as the mRS (OR 2.21), were strong predictors of major NCD. When FI and mRS were entered as predictors simultaneously, the OR for mRS decreased relatively more than that for FI. AUC for NCD post-stroke was higher for FI than for mRS, both for major NCD (0.762 vs 0.677) and for any NCD (0.681 vs 0.638). Conclusions FI is a stronger predictor of post-stroke NCD than pre-stroke mRS and could be a part of the prediction models for cognitive prognosis post-stroke. Trial Registration ClinicalTrials.gov Identifier: NCT02650531 .
    Type of Medium: Online Resource
    ISSN: 1471-2318
    URL: Article
    DOI: 10.1186/s12877-022-02840-y
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2059865-8
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  • 9
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    Table_1.DOCX
    Frontiers Media SA ; 2023
    In:  Frontiers in Neurology Vol. 14 ( 2023-9-28)
    Details
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 14 ( 2023-9-28)
    Abstract: Radiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentations produced from three-dimensional deep learning AI model that was developed using non-contrast computed tomography (CT) imaging data external to the current study. Methods Non-contrast CT imaging data from 1263 patients were accessed across seven data sources (referred to as sites) in Norway and Sweden. Patients were included based on ICH, TBI-bleed, or mild TBI diagnosis. Initial non-contrast CT images were available for all participants. Hemorrhage location frequency maps were generated. The number of estimated haematoma clusters was correlated with the total haematoma volume. Ground truth expert annotations were available for one ICH site; hence, a comparison was made with the estimated haematoma volumes. Segmentation volume estimates were used in a receiver operator characteristics (ROC) analysis for all samples (i.e., bleed detected) and then specifically for one site with few TBI-bleed cases. Results The hemorrhage frequency maps showed spatial patterns of estimated lesions consistent with ICH or TBI-bleed presentations. There was a positive correlation between the estimated number of clusters and total haematoma volume for each site (correlation range: 0.45–0.74; each p -value & lt; 0.01) and evidence of ICH between-site differences. Relative to hand-drawn annotations for one ICH site, the VIOLA-AI segmentation mask achieved a median Dice Similarity Coefficient of 0.82 (interquartile range: 0.78 and 0.83), resulting in a small overestimate in the haematoma volume by a median of 0.47 mL (interquartile range: 0.04 and 1.75 mL). The bleed detection ROC analysis for the whole sample gave a high area-under-the-curve (AUC) of 0.92 (with sensitivity and specificity of 83.28% and 95.41%); however, when considering only the mild head injury site, the TBI-bleed detection gave an AUC of 0.70. Discussion An open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fneur.2023.1244672
    DOI: 10.3389/fneur.2023.1244672.s001
    DOI: 10.3389/fneur.2023.1244672.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2564214-5
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  • 10
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    Data_Sheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Neurology Vol. 13 ( 2022-6-3)
    Details
    In: Frontiers in Neurology, Frontiers Media SA, Vol. 13 ( 2022-6-3)
    Abstract: Cognitive impairment is common after stroke. So is cortical- and subcortical atrophy, with studies reporting more atrophy in the ipsilesional hemisphere than the contralesional hemisphere. The current study aimed to investigate the longitudinal associations between (I) lateralization of brain atrophy and stroke hemisphere, and (II) cognitive impairment and brain atrophy after stroke. We expected to find that (I) cortical thickness and hippocampal-, thalamic-, and caudate nucleus volumes declined more in the ipsilesional than the contralesional hemisphere up to 36 months after stroke. Furthermore, we predicted that (II) cognitive decline was associated with greater stroke volumes, and with greater cortical thickness and subcortical structural volume atrophy across the 36 months. Methods Stroke survivors from five Norwegian hospitals were included from the multisite-prospective “Norwegian Cognitive Impairment After Stroke” (Nor-COAST) study. Analyses were run with clinical, neuropsychological and structural magnetic resonance imaging (MRI) data from baseline, 18- and 36 months. Cortical thicknesses and subcortical volumes were obtained via FreeSurfer segmentations and stroke lesion volumes were semi-automatically derived using ITK-SNAP. Cognition was measured using MoCA. Results Findings from 244 stroke survivors [age = 72.2 (11.3) years, women = 55.7%, stroke severity NIHSS = 4.9 (5.0)] were included at baseline. Of these, 145 (59.4%) had an MRI scan at 18 months and 72 (49.7% of 18 months) at 36 months. Most cortices and subcortices showed a higher ipsi- compared to contralesional atrophy rate, with the effect being more prominent in the right hemisphere. Next, greater degrees of atrophy particularly in the medial temporal lobe after left-sided strokes and larger stroke lesion volumes after right-sided strokes were associated with cognitive decline over time. Conclusion Atrophy in the ipsilesional hemisphere was greater than in the contralesional hemisphere over time. This effect was found to be more prominent in the right hemisphere, pointing to a possible higher resilience to stroke of the left hemisphere. Lastly, greater atrophy of the cortex and subcortex, as well as larger stroke volume, were associated with worse cognition over time and should be included in risk assessments of cognitive decline after stroke.
    Type of Medium: Online Resource
    ISSN: 1664-2295
    URL: Article
    URL: Article
    DOI: 10.3389/fneur.2022.856919
    DOI: 10.3389/fneur.2022.856919.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2564214-5
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