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      Prognostic value of changes in resting-state functional connectivity patterns in cognitive recovery after stroke: A 3T fMRI pilot study

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          Abstract

          Resting-state studies conducted with stroke patients are scarce. First objective was to explore whether patients with good cognitive recovery showed differences in resting-state functional patterns of brain activity when compared to patients with poor cognitive recovery. Second objective was to determine whether such patterns were correlated with cognitive performance. Third objective was to assess the existence of prognostic factors for cognitive recovery. Eighteen right-handed stroke patients and eighteen healthy controls were included in the study. Stroke patients were divided into two groups according to their cognitive improvement observed at three months after stroke. Probabilistic independent component analysis was used to identify resting-state brain activity patterns. The analysis identified six networks: frontal, fronto-temporal, default mode network, secondary visual, parietal, and basal ganglia. Stroke patients showed significant decrease in brain activity in parietal and basal ganglia networks and a widespread increase in brain activity in the remaining ones when compared with healthy controls. When analyzed separately, patients with poor cognitive recovery ( n = 10) showed the same pattern as the whole stroke patient group, while patients with good cognitive recovery ( n = 8) showed increased activity only in the default mode network and fronto-temporal network, and decreased activity in the basal ganglia. We observe negative correlations between basal ganglia network activity and performance in Semantic Fluency test and Part A of the Trail Making Test for patients with poor cognitive recovery. A reverse pattern was observed between frontal network activity and the abovementioned tests for the same group. Hum Brain Mapp 35:3819–3831, 2014.

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          Development and validation of a geriatric depression screening scale: a preliminary report.

          A new Geriatric Depression Scale (GDS) designed specifically for rating depression in the elderly was tested for reliability and validity and compared with the Hamilton Rating Scale for Depression (HRS-D) and the Zung Self-Rating Depression Scale (SDS). In constructing the GDS a 100-item questionnaire was administered to normal and severely depressed subjects. The 30 questions most highly correlated with the total scores were then selected and readministered to new groups of elderly subjects. These subjects were classified as normal, mildly depressed or severely depressed on the basis of Research Diagnostic Criteria (RDC) for depression. The GDS, HRS-D and SDS were all found to be internally consistent measures, and each of the scales was correlated with the subject's number of RDC symptoms. However, the GDS and the HRS-D were significantly better correlated with RDC symptoms than was the SDS. The authors suggest that the GDS represents a reliable and valid self-rating depression screening scale for elderly populations.
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            Repairing the human brain after stroke: I. Mechanisms of spontaneous recovery.

            Stroke remains a leading cause of adult disability. Some degree of spontaneous behavioral recovery is usually seen in the weeks after stroke onset. Variability in recovery is substantial across human patients. Some principles have emerged; for example, recovery occurs slowest in those destined to have less successful outcomes. Animal studies have extended these observations, providing insight into a broad range of underlying molecular and physiological events. Brain mapping studies in human patients have provided observations at the systems level that often parallel findings in animals. In general, the best outcomes are associated with the greatest return toward the normal state of brain functional organization. Reorganization of surviving central nervous system elements supports behavioral recovery, for example, through changes in interhemispheric lateralization, activity of association cortices linked to injured zones, and organization of cortical representational maps. A number of factors influence events supporting stroke recovery, such as demographics, behavioral experience, and perhaps genetics. Such measures gain importance when viewed as covariates in therapeutic trials of restorative agents that target stroke recovery.
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              ABC/2 for rapid clinical estimate of infarct, perfusion, and mismatch volumes.

              Rapid and easy clinical assessments for volumes of infarction and perfusion mismatch are needed. We tested whether simple geometric models generated accurate estimates of these volumes. Acute diffusion-weighted image (DWI) and perfusion (mean transit time [MTT]) in 63 strokes and established infarct volumes in 50 subacute strokes were measured by computerized planimetry. Mismatch was defined as MTT/DWI > or = 1.2. Observers, blinded to planimetric values, measured lesions in three perpendicular axes A, B, and C. Geometric estimates of sphere, ellipsoid, bicone, and cylinder were compared to planimetric volume by least-squares linear regression. The ABC/2 formula (ellipsoid) was superior to other geometries for estimating volume of DWI (slope 1.16, 95% confidence interval [CI] 0.94 to 1.38; R(2) = 0.91, p = 0.001) and MTT (slope 1.11, 95% CI 0.99 to 1.23; R(2) = 0.89, p = 0.001). The intrarater and interrater reliability for ABC/2 was high for both DWI (0.992 and 0.965) and MTT (0.881 and 0.712). For subacute infarct, the ABC/2 formula also best estimated planimetric volume (slope 1.00, 95% CI 0.98 to 1.19; R(2) = 0.74, p = 0.001). In general, sphere and cylinder geometries overestimated all volumes and bicone underestimated all volumes. The positive predictive value for mismatch was 92% and negative predictive value was 33%. Of the models tested, ABC/2 is reproducible, is accurate, and provides the best simple geometric estimate of infarction and mean transit time volumes. ABC/2 has a high positive predictive value for identifying mismatch greater than 20% and might be a useful tool for rapid determination of acute stroke treatment.
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                Author and article information

                Journal
                Hum Brain Mapp
                Hum Brain Mapp
                hbm
                Human Brain Mapping
                BlackWell Publishing Ltd (Oxford, UK )
                1065-9471
                1097-0193
                August 2014
                12 February 2014
                : 35
                : 8
                : 3819-3831
                Affiliations
                [1 ]Department of Psychiatry and Clinical Psychobiology, University of Barcelona Spain
                [2 ]Department of CCIA, Group of Computational Intelligence, University of the Basque Country UPV/EHU San Sebastian, Spain
                [3 ]Institute for Brain, Cognition and Behaviour (IR3C) Barcelona, Spain
                [4 ]Department of Neurosciences, Hospital Germans Trias I Pujol, Universitat Autònoma de Barcelona Badalona, Barcelona, Spain
                [5 ]Diagnostic Center for Image, Clinic Hospital Barcelona, Spain
                [6 ]Imatge Platform of IDIBAPS Barcelona, Spain
                [7 ]Department of Methodology of Behavioral Sciences, University of Barcelona Spain
                [8 ]Institut de Diagnostic per la Imatge (IDI), Hospital Germans Trias I Pujol Badalona, Barcelona, Spain
                [9 ]MRC Cognition and Brain Sciences Unit Cambridge, United Kingdom
                Author notes
                *Correspondence to: M. Mataró, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Passeig de la Vall d'Hebron, 171, 08035 Barcelona, Spain. E-mail: mmataro@ 123456ub.edu
                Article
                10.1002/hbm.22439
                4282459
                24523262
                c444e044-bdc7-40c7-a09e-ec0feefa59f4
                Copyright © 2014 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 June 2013
                : 02 November 2013
                : 15 November 2013
                Categories
                Research Articles

                Neurology
                ischemic stroke,resting state,fmri,probabilistic independent component analysis,interhemispheric balance,cognitive recovery

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