Literature DB >> 28596195

e-ASPECTS Correlates with and Is Predictive of Outcome after Mechanical Thrombectomy.

J Pfaff1, C Herweh1, S Schieber2, S Schönenberger2, J Bösel2, P A Ringleb2, M Möhlenbruch1, M Bendszus1, S Nagel3.   

Abstract

BACKGROUND AND
PURPOSE: The e-ASPECTS software is a tool for the automated use of ASPECTS. Our aim was to analyze whether baseline e-ASPECT scores correlate with outcome after mechanical thrombectomy.
MATERIALS AND METHODS: Patients with ischemic strokes in the anterior circulation who were admitted between 2010 and 2015, diagnosed by CT, and received mechanical thrombectomy were included. The ASPECTS on baseline CT was scored by e-ASPECTS and 3 expert raters, and interclass correlation coefficients were calculated. The e-ASPECTS was correlated with functional outcome (modified Rankin Scale) at 3 months by using the Spearman rank correlation coefficient. Unfavorable outcome was defined as mRS 4-6 at 3 months, and a poor scan was defined as e-ASPECTS 0-5.
RESULTS: Two hundred twenty patients were included, and 147 (67%) were treated with bridging protocols. The median e-ASPECTS was 9 (interquartile range, 8-10). Intraclass correlation coefficients between e-ASPECTS and raters were 0.72, 0.74, and 0.76 (all, P < .001). e-ASPECTS (Spearman rank correlation coefficient = -0.15, P = .027) correlated with mRS at 3 months. Patients with unfavorable outcome had lower e-ASPECTS (median, 8; interquartile range, 7-10 versus median, 9; interquartile range, 8-10; P = .014). Sixteen patients (7.4%) had a poor scan, which was associated with unfavorable outcome (OR, 13.6; 95% CI, 1.8-104). Independent predictors of unfavorable outcome were e-ASPECTS (OR, 0.79; 95% CI, 0.63-0.99), blood sugar (OR, 1.01; 95% CI, 1.004-1.02), atrial fibrillation (OR, 2.64; 95% CI, 1.22-5.69), premorbid mRS (OR, 1.77; 95% CI, 1.21-2.58), NIHSS (OR, 1.11; 95% CI, 1.04-1.19), general anesthesia (OR, 0.24; 95% CI, 0.07-0.84), failed recanalization (OR, 8.47; 95% CI, 3.5-20.2), and symptomatic intracerebral hemorrhage (OR, 25.8; 95% CI, 2.5-268).
CONCLUSIONS: The e-ASPECTS correlated with mRS at 3 months and was predictive of unfavorable outcome after mechanical thrombectomy, but further studies in patients with poor scan are needed.
© 2017 by American Journal of Neuroradiology.

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Mesh:

Year:  2017        PMID: 28596195     DOI: 10.3174/ajnr.A5236

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


  14 in total

1.  Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19.

Authors:  Kiruba Nagaratnam; George Harston; Enrico Flossmann; Clara Canavan; Rui Carmelo Geraldes; Chani Edwards
Journal:  Future Healthc J       Date:  2020-06

2.  Automated ASPECT rating: comparison between the Frontier ASPECT Score software and the Brainomix software.

Authors:  Juliane Goebel; Elena Stenzel; Nika Guberina; Isabel Wanke; Martin Koehrmann; Christoph Kleinschnitz; Lale Umutlu; Michael Forsting; Christoph Moenninghoff; Alexander Radbruch
Journal:  Neuroradiology       Date:  2018-09-15       Impact factor: 2.804

3.  Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.

Authors:  Nika Guberina; U Dietrich; A Radbruch; J Goebel; C Deuschl; A Ringelstein; M Köhrmann; C Kleinschnitz; M Forsting; C Mönninghoff
Journal:  Neuroradiology       Date:  2018-07-31       Impact factor: 2.804

Review 4.  [Imaging in acute ischemic stroke using automated postprocessing algorithms].

Authors:  K Egger; C Strecker; E Kellner; H Urbach
Journal:  Nervenarzt       Date:  2018-08       Impact factor: 1.214

5.  Automated versus manual imaging assessment of early ischemic changes in acute stroke: comparison of two software packages and expert consensus.

Authors:  Friederike Austein; Fritz Wodarg; Nora Jürgensen; Monika Huhndorf; Johannes Meyne; Thomas Lindner; Olav Jansen; Naomi Larsen; Christian Riedel
Journal:  Eur Radiol       Date:  2019-05-10       Impact factor: 5.315

6.  Automated ASPECTS in Acute Ischemic Stroke: A Comparative Analysis with CT Perfusion.

Authors:  V K Sundaram; J Goldstein; D Wheelwright; A Aggarwal; P S Pawha; A Doshi; J T Fifi; R De Leacy; J Mocco; J Puig; K Nael
Journal:  AJNR Am J Neuroradiol       Date:  2019-11-14       Impact factor: 3.825

7.  Alberta Stroke Program Early CT Score Versus Computed Tomographic Perfusion to Predict Functional Outcome After Successful Reperfusion in Acute Ischemic Stroke.

Authors:  Jelle Demeestere; Lauranne Scheldeman; Sandra A Cornelissen; Sam Heye; Anke Wouters; Patrick Dupont; Sören Christensen; Michael Mlynash; Gregory W Albers; Maarten Lansberg; Robin Lemmens
Journal:  Stroke       Date:  2018-10       Impact factor: 7.914

8.  Correlation between ASPECTS and Core Volume on CT Perfusion: Impact of Time since Stroke Onset and Presence of Large-Vessel Occlusion.

Authors:  S Nannoni; F Ricciardi; D Strambo; G Sirimarco; M Wintermark; V Dunet; P Michel
Journal:  AJNR Am J Neuroradiol       Date:  2021-01-28       Impact factor: 3.825

Review 9.  Artificial Intelligence and Acute Stroke Imaging.

Authors:  J E Soun; D S Chow; M Nagamine; R S Takhtawala; C G Filippi; W Yu; P D Chang
Journal:  AJNR Am J Neuroradiol       Date:  2020-11-26       Impact factor: 3.825

Review 10.  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
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