Literature DB >> 31948951

Assessment of a Bayesian Vitrea CT Perfusion Analysis to Predict Final Infarct and Penumbra Volumes in Patients with Acute Ischemic Stroke: A Comparison with RAPID.

R A Rava1,2, K V Snyder3,2, M Mokin4, M Waqas3,2, A B Allman5,2, J L Senko5,2, A R Podgorsak5,3,6,2, M M Shiraz Bhurwani5,2, Y Hoi7, A H Siddiqui3,2, J M Davies3,2, E I Levy3,2, C N Ionita5,3,2.   

Abstract

BACKGROUND AND
PURPOSE: Brain CTP is used to estimate infarct and penumbra volumes to determine endovascular treatment eligibility for patients with acute ischemic stroke. We aimed to assess the accuracy of a Bayesian CTP algorithm in determining penumbra and final infarct volumes.
MATERIALS AND METHODS: Data were retrospectively collected for 105 patients with acute ischemic stroke (55 patients with successful recanalization [TICI 2b/2c/3] and large-vessel occlusions and 50 patients without interventions). Final infarct volumes were calculated using DWI and FLAIR 24 hours following CTP imaging. RAPID and the Vitrea Bayesian CTP algorithm (with 3 different settings) predicted infarct and penumbra volumes for comparison with final infarct volumes to assess software performance. Vitrea settings used different combinations of perfusion maps (MTT, TTP, CBV, CBF, delay time) for infarct and penumbra quantification. Patients with and without interventions were included for assessment of predicted infarct and penumbra volumes, respectively.
RESULTS: RAPID and Vitrea default setting had the most accurate final infarct volume prediction in patients with interventions ([Spearman correlation coefficient, mean infarct difference] default versus FLAIR: [0.77, 4.1 mL], default versus DWI: [0.72, 4.7 mL], RAPID versus FLAIR: [0.75, 7.5 mL], RAPID versus DWI: [0.75, 6.9 mL]). Default Vitrea and RAPID were the most and least accurate in determining final infarct volume for patients without an intervention, respectively (default versus FLAIR: [0.76, -0.4 mL], default versus DWI: [0.71, -2.6 mL], RAPID versus FLAIR: [0.68, -49.3 mL], RAPID versus DWI: [0.65, -51.5 mL]).
CONCLUSIONS: Compared with RAPID, the Vitrea default setting was noninferior for patients with interventions and superior in penumbra estimation for patients without interventions as indicated by mean infarct differences and correlations with final infarct volumes.
© 2020 by American Journal of Neuroradiology.

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Year:  2020        PMID: 31948951      PMCID: PMC7015204          DOI: 10.3174/ajnr.A6395

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  21 in total

1.  Determinants of the distribution and severity of hypoperfusion in patients with ischemic stroke.

Authors:  O Y Bang; J L Saver; J R Alger; S Starkman; B Ovbiagele; D S Liebeskind
Journal:  Neurology       Date:  2008-11-25       Impact factor: 9.910

2.  Comparison of three commonly used CT perfusion software packages in patients with acute ischemic stroke.

Authors:  Miou S Koopman; Olvert A Berkhemer; Ralph R E G Geuskens; Bart J Emmer; Marianne A A van Walderveen; Sjoerd F M Jenniskens; Wim H van Zwam; Robert J van Oostenbrugge; Aad van der Lugt; Diederik W J Dippel; Ludo F Beenen; Yvo B W E M Roos; Henk A Marquering; Charles B L M Majoie
Journal:  J Neurointerv Surg       Date:  2019-06-15       Impact factor: 5.836

3.  Achieving comparable perfusion results across vendors. The next step in standardizing stroke care: a technical report.

Authors:  Girish Bathla; Kaustubh Limaye; Bruno Policeni; Ernst Klotz; Markus Juergens; Colin Derdeyn
Journal:  J Neurointerv Surg       Date:  2019-05-22       Impact factor: 5.836

Review 4.  2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association.

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:  2018-01-24       Impact factor: 7.914

5.  Significance of hyperintense vessels on FLAIR MRI in acute stroke.

Authors:  S Kamran; V Bates; R Bakshi; P Wright; W Kinkel; R Miletich
Journal:  Neurology       Date:  2000-07-25       Impact factor: 9.910

6.  Bayesian estimation of cerebral perfusion using reduced-contrast-dose dynamic susceptibility contrast perfusion at 3T.

Authors:  K Nael; B Mossadeghi; T Boutelier; W Kubal; E A Krupinski; J Dagher; J P Villablanca
Journal:  AJNR Am J Neuroradiol       Date:  2014-11-27       Impact factor: 3.825

7.  Early diffusion-weighted imaging reversal after endovascular reperfusion is typically transient in patients imaged 3 to 6 hours after onset.

Authors:  Manabu Inoue; Michael Mlynash; Soren Christensen; Hayley M Wheeler; Matus Straka; Aaryani Tipirneni; Stephanie M Kemp; Greg Zaharchuk; Jean-Marc Olivot; Roland Bammer; Maarten G Lansberg; Gregory W Albers
Journal:  Stroke       Date:  2014-02-20       Impact factor: 7.914

8.  Hypoperfusion ratio predicts infarct growth during transfer for thrombectomy.

Authors:  Adrien Guenego; Michael Mlynash; Soren Christensen; Stephanie Kemp; Jeremy J Heit; Maarten G Lansberg; Gregory W Albers
Journal:  Ann Neurol       Date:  2018-09-23       Impact factor: 10.422

9.  Differences in CT perfusion maps generated by different commercial software: quantitative analysis by using identical source data of acute stroke patients.

Authors:  Kohsuke Kudo; Makoto Sasaki; Kei Yamada; Suketaka Momoshima; Hidetsuna Utsunomiya; Hiroki Shirato; Kuniaki Ogasawara
Journal:  Radiology       Date:  2010-01       Impact factor: 11.105

10.  A Comparison of Relative Time to Peak and Tmax for Mismatch-Based Patient Selection.

Authors:  Anke Wouters; Søren Christensen; Matus Straka; Michael Mlynash; John Liggins; Roland Bammer; Vincent Thijs; Robin Lemmens; Gregory W Albers; Maarten G Lansberg
Journal:  Front Neurol       Date:  2017-10-13       Impact factor: 4.003

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  13 in total

1.  Effect of computed tomography perfusion post-processing algorithms on optimal threshold selection for final infarct volume prediction.

Authors:  Ryan A Rava; Kenneth V Snyder; Maxim Mokin; Muhammad Waqas; Ariana B Allman; Jillian L Senko; Alexander R Podgorsak; Mohammad Mahdi Shiraz Bhurwani; Jason M Davies; Elad I Levy; Adnan H Siddiqui; Ciprian N Ionita
Journal:  Neuroradiol J       Date:  2020-06-23

2.  Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke.

Authors:  Shota Ichikawa; Hiroyuki Yamamoto; Takumi Morita
Journal:  Radiol Med       Date:  2021-01-19       Impact factor: 3.469

3.  Investigation of convolutional neural networks using multiple computed tomography perfusion maps to identify infarct core in acute ischemic stroke patients.

Authors:  Ryan A Rava; Alexander R Podgorsak; Muhammad Waqas; Kenneth V Snyder; Maxim Mokin; Elad I Levy; Jason M Davies; Adnan H Siddiqui; Ciprian N Ionita
Journal:  J Med Imaging (Bellingham)       Date:  2021-02-10

4.  Use of a convolutional neural network to identify infarct core using computed tomography perfusion parameters.

Authors:  Ryan A Rava; Alexander R Podgorsak; Muhammad Waqas; Kenneth V Snyder; Elad I Levy; Jason M Davies; Adnan H Siddiqui; Ciprian N Ionita
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2021-02-15

5.  Validation of an artificial intelligence-driven large vessel occlusion detection algorithm for acute ischemic stroke patients.

Authors:  Ryan A Rava; Blake A Peterson; Samantha E Seymour; Kenneth V Snyder; Maxim Mokin; Muhammad Waqas; Yiemeng Hoi; Jason M Davies; Elad I Levy; Adnan H Siddiqui; Ciprian N Ionita
Journal:  Neuroradiol J       Date:  2021-03-03

6.  Enhancing performance of a computed tomography perfusion software for improved prediction of final infarct volume in acute ischemic stroke patients.

Authors:  Ryan A Rava; Kenneth V Snyder; Maxim Mokin; Muhammad Waqas; Alexander R Podgorsak; Ariana B Allman; Jillian Senko; Mohammad Mahdi Shiraz Bhurwani; Yiemeng Hoi; Jason M Davies; Elad I Levy; Adnan H Siddiqui; Ciprian N Ionita
Journal:  Neuroradiol J       Date:  2021-01-21

Review 7.  How to Improve the Management of Acute Ischemic Stroke by Modern Technologies, Artificial Intelligence, and New Treatment Methods.

Authors:  Kamil Zeleňák; Antonín Krajina; Lukas Meyer; Jens Fiehler; Daniel Behme; Deniz Bulja; Jildaz Caroff; Amar Ajay Chotai; Valerio Da Ros; Jean-Christophe Gentric; Jeremy Hofmeister; Omar Kass-Hout; Özcan Kocatürk; Jeremy Lynch; Ernesto Pearson; Ivan Vukasinovic
Journal:  Life (Basel)       Date:  2021-05-27

8.  Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.

Authors:  Chengyan Wang; Zhang Shi; Ming Yang; Lixiang Huang; Wenxing Fang; Li Jiang; Jing Ding; He Wang
Journal:  J Cereb Blood Flow Metab       Date:  2021-06-08       Impact factor: 6.960

9.  NIHSS-the Alberta Stroke Program Early CT Score mismatch in guiding thrombolysis in patients with acute ischemic stroke.

Authors:  Pan-Pan Deng; Na Wu; Xiao-Jie Chen; Feng-Ling Chen; Heng-Shi Xu; Guan-Shui Bao
Journal:  J Neurol       Date:  2021-07-27       Impact factor: 6.682

10.  The Application of Computed Tomography Perfusion in the Alberta Stroke Program Early Computed Tomography Score for Endovascular Treatment of Acute Ischemic Stroke in the Anterior Circulation.

Authors:  Wei-Yong Zhang; Shi-Feng Xiang; Su-Jun Yang; Yi-Ping Wu; Jun-Tao Li; Guo-Kun Liu; Jian-Fei Li; Wei-Wei Wang
Journal:  Int J Gen Med       Date:  2021-05-17
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