MCDONOUGH, R. V., W. QIU, J. M. OSPEL, B. K. MENON, Petra CIMFLOVÁ and M. GOYAL. Multiphase CTA-derived tissue maps aid in detection of medium vessel occlusions. NEURORADIOLOGY. NEW YORK: SPRINGER, 2022, vol. 64, No 5, p. 887-896. ISSN 0028-3940. Available from: https://dx.doi.org/10.1007/s00234-021-02830-8.
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Basic information
Original name Multiphase CTA-derived tissue maps aid in detection of medium vessel occlusions
Authors MCDONOUGH, R. V., W. QIU, J. M. OSPEL, B. K. MENON, Petra CIMFLOVÁ (203 Czech Republic, belonging to the institution) and M. GOYAL (guarantor).
Edition NEURORADIOLOGY, NEW YORK, SPRINGER, 2022, 0028-3940.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30224 Radiology, nuclear medicine and medical imaging
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 2.800
RIV identification code RIV/00216224:14110/22:00125371
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1007/s00234-021-02830-8
UT WoS 000708810800003
Keywords in English Acute ischemic stroke; Endovascular treatment; Medium vessel occlusions; Multiphase computed tomography; Treatment selection
Tags 14110119, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 28/4/2022 11:05.
Abstract
Purpose Medium vessel occlusions (MeVOs) can be challenging to detect on imaging. Multiphase computed tomography angiography (mCTA) has been shown to improve large vessel occlusion (LVO) detection and endovascular treatment (EVT) selection. The aims of this study were to determine if mCTA-derived tissue maps can (1) accurately detect MeVOs and (2) predict infarction on 24-h follow-up imaging with comparable accuracy to CT perfusion (CTP). Methods Two readers assessed mCTA tissue maps of 116 ischemic stroke patients (58 MeVOs, 58 non-MeVOs) and determined by consensus: (1) MeVO (yes/no) and (2) occlusion site, blinded to clinical or imaging data. Sensitivity, specificity, and area under the curve (AUC) for MeVO detection were estimated in comparison to reference standards of (1) expert readings of baseline mCTA and (2) CTP maps. Volumetric and spatial agreement between mCTA- and CTP-predicted infarcts was assessed using concordance/intraclass correlation and Dice coefficients. Interrater agreement for MeVO detection on mCTA tissue maps was estimated with Cohen's kappa. Results MeVO detection from mCTA-derived tissue maps had a sensitivity of 91% (95% CI: 80-97), specificity of 82% (95% CI: 70-90), and AUC of 0.87 (95% CI: 0.80-0.93) compared to expert reads of baseline mCTA. Interrater reliability was good (0.72, 95% CI: 0.60-0.85). Compared to CTP maps, sensitivity was 87% (95% CI: 75-95), specificity was 78% (95%CI: 65-88), and AUC was 0.83 (95% CI: 0.76-0.90). The mean difference between mCTA- and CTP-predicted final infarct volume was 4.8 mL (limits of agreement: - 58.5 to 68.1) with a Dice coefficient of 33.5%. Conclusion mCTA tissue maps can be used to reliably detect MeVO stroke and predict tissue fate.
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