Improvement of MRI examination in cerebral thromboembolism

dc.contributor.authorQaynarbekova Mokhinur
dc.contributor.authorAblyazov A.A
dc.contributor.authorZulunov Azizbek
dc.date.accessioned2026-01-01T10:17:51Z
dc.date.issued2022-11-22
dc.description.abstractBackground Cerebral venous thrombosis (CVT) is a rare disease, and with poor prognosis. Computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly used image modalities for patients with non-specific neurologic symptoms. We present here a meta-analysis to assess the accuracy of CT and MRI in the differential diagnosis of CVT and cerebral venous sinus thrombosis (CVST). Materials and Methods A comprehensive search of the PubMed, EMBASE, Web of Science, Cochrane Database and Chinese Biomedical (CBM) databases was conducted. In this report, we assess the methodological quality of each article individually and perform a meta-analysis to obtain the summary of the diagnostic accuracy MRI in correctly identifying CVT and CVST. Results Twenty-four eligible articles comprising 48 studies (4,595 cases) were included. The pooled sensitivity for CT–CVT/CT–CVST groups is 0.79 (95% confidence interval,with an area under the curve (AUC) for the summary receiver operating characteristic (SROC) of 0.9314/0.9161
dc.formatapplication/pdf
dc.identifier.urihttps://zienjournals.com/index.php/tjms/article/view/2792
dc.identifier.uri10.62480/tjms.2022.vol14.pp130-132
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/59478
dc.language.isoeng
dc.publisherZien Journals
dc.relationhttps://zienjournals.com/index.php/tjms/article/view/2792/2341
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0
dc.sourceTexas Journal of Medical Science; Vol. 14 (2022): TJMS; 130-132
dc.source2770-2936
dc.subjectquality
dc.subjectComputed tomography
dc.subjectmagnetic resonance tomography
dc.subjectintracranial thrombosis
dc.titleImprovement of MRI examination in cerebral thromboembolism
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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