A Potreck1, E Scheidecker1, C S Weyland1, U Neuberger1, C Herweh1, M A Möhlenbruch1, M Chen2, S Nagel2, M Bendszus1, F Seker3. 1. From the Departments of Neuroradiology (A.P., E.S., C.S.W., U.N., C.H., M.A.M., M.B., F.S.). 2. Department of Neurology (M.C., S.N.), Heidelberg University Hospital, Heidelberg, Germany. 3. From the Departments of Neuroradiology (A.P., E.S., C.S.W., U.N., C.H., M.A.M., M.B., F.S.) fatih.seker@med.uni-heidelberg.de.
Abstract
BACKGROUND AND PURPOSE: Information of collateral flow may help to determine eligibility for thrombectomy. Our aim was to identify CT perfusion-based surrogate parameters of good collateral status in acute anterior circulation ischemic stroke. MATERIALS AND METHODS: In this retrospective study, we assessed the collateral status of 214 patients who presented with acute ischemic stroke due to occlusion of the MCA M1 segment or the carotid terminus. Collaterals were assessed on dynamic CTA images analogous to the multiphase CTA score by Menon et al. CT perfusion parameters (time-to-maximum, relative CBF, hypoperfusion intensity ratio, and CBV-index) were assessed with RAPID software. The Spearman rank correlation and receiver operating characteristic analyses were performed to identify the parameters that correlate with collateral scores and good collateral supply (defined as a collateral score of ≥4). RESULTS: The Spearman rank correlation was highest for a relative CBF < 38% volume (ρ = -0.66, P < .001), followed by the hypoperfusion intensity ratio (ρ = -0.49, P < .001), CBV-index (ρ = 0.51, P < .001), and time-to-maximum > 8 seconds (ρ = -0.54, P < .001). Good collateral status was better identified by a relative CBF < 38% at a lesion size <27 mL (sensitivity of 75%, specificity of 80%) compared with a hypoperfusion intensity ratio of <0.4 (sensitivity of 75%, specificity of 62%), CBV-index of >0.8 (sensitivity of 60%, specificity of 78%), and time-to-maximum > 8 seconds (sensitivity of 68%, specificity of 76%). CONCLUSIONS: Automated CT perfusion analysis allows accurate identification of collateral status in acute ischemic stroke. A relative CBF < 38% may be a better perfusion-based indicator of good collateral supply compared with time-to-maximum, the hypoperfusion intensity ratio, and the CBV-index.
BACKGROUND AND PURPOSE: Information of collateral flow may help to determine eligibility for thrombectomy. Our aim was to identify CT perfusion-based surrogate parameters of good collateral status in acute anterior circulation ischemic stroke. MATERIALS AND METHODS: In this retrospective study, we assessed the collateral status of 214 patients who presented with acute ischemic stroke due to occlusion of the MCA M1 segment or the carotid terminus. Collaterals were assessed on dynamic CTA images analogous to the multiphase CTA score by Menon et al. CT perfusion parameters (time-to-maximum, relative CBF, hypoperfusion intensity ratio, and CBV-index) were assessed with RAPID software. The Spearman rank correlation and receiver operating characteristic analyses were performed to identify the parameters that correlate with collateral scores and good collateral supply (defined as a collateral score of ≥4). RESULTS: The Spearman rank correlation was highest for a relative CBF < 38% volume (ρ = -0.66, P < .001), followed by the hypoperfusion intensity ratio (ρ = -0.49, P < .001), CBV-index (ρ = 0.51, P < .001), and time-to-maximum > 8 seconds (ρ = -0.54, P < .001). Good collateral status was better identified by a relative CBF < 38% at a lesion size <27 mL (sensitivity of 75%, specificity of 80%) compared with a hypoperfusion intensity ratio of <0.4 (sensitivity of 75%, specificity of 62%), CBV-index of >0.8 (sensitivity of 60%, specificity of 78%), and time-to-maximum > 8 seconds (sensitivity of 68%, specificity of 76%). CONCLUSIONS: Automated CT perfusion analysis allows accurate identification of collateral status in acute ischemic stroke. A relative CBF < 38% may be a better perfusion-based indicator of good collateral supply compared with time-to-maximum, the hypoperfusion intensity ratio, and the CBV-index.
Authors: Bijoy K Menon; Christopher D d'Esterre; Emmad M Qazi; Mohammed Almekhlafi; Leszek Hahn; Andrew M Demchuk; Mayank Goyal Journal: Radiology Date: 2015-01-29 Impact factor: 11.105
Authors: Arne Potreck; Fatih Seker; Angelika Hoffmann; Johannes Pfaff; Simon Nagel; Martin Bendszus; Sabine Heiland; Mirko Pham Journal: Eur Radiol Date: 2016-05-24 Impact factor: 5.315
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Authors: Fatih Seker; Benjamin Pereira-Zimmermann; Johannes Pfaff; Jan Purrucker; Christoph Gumbinger; Silvia Schönenberger; Martin Bendszus; Markus A Möhlenbruch Journal: Clin Neuroradiol Date: 2019-11-28 Impact factor: 3.649
Authors: A M J Frölich; D Schrader; E Klotz; R Schramm; K Wasser; M Knauth; P Schramm Journal: AJNR Am J Neuroradiol Date: 2013-04-25 Impact factor: 3.825
Authors: William J Powers; Alejandro A Rabinstein; Teri Ackerson; Opeolu M Adeoye; Nicholas C Bambakidis; Kyra Becker; José Biller; Michael Brown; Bart M Demaerschalk; Brian Hoh; Edward C Jauch; Chelsea S Kidwell; Thabele M Leslie-Mazwi; Bruce Ovbiagele; Phillip A Scott; Kevin N Sheth; Andrew M Southerland; Deborah V Summers; David L Tirschwell Journal: Stroke Date: 2019-10-30 Impact factor: 7.914
Authors: Fatih Seker; Johannes Pfaff; Arne Potreck; Sibu Mundiyanapurath; Peter A Ringleb; Martin Bendszus; Markus A Möhlenbruch Journal: Brain Behav Date: 2017-07-26 Impact factor: 2.708
Authors: Emilia Scheidecker; Benjamin Pereira-Zimmermann; Arne Potreck; Dominik F Vollherbst; Markus A Möhlenbruch; Christoph Gumbinger; Martin Bendszus; Christian Herweh; Fatih Seker Journal: Neuroradiology Date: 2021-12-09 Impact factor: 2.995