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Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy

BACKGROUND: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute change...

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Autores principales: Kis, Balázs, Neuhaus, Ain A., Harston, George, Joly, Olivier, Carone, Davide, Gerry, Stephen, Chadaide, Zoltán, Pánczél, András, Czifrus, Eszter, Csike, Viktória, Surányi, Ágnes, Szikora, István, Erőss, Loránd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797714/
https://www.ncbi.nlm.nih.gov/pubmed/36588883
http://dx.doi.org/10.3389/fneur.2022.1056532
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author Kis, Balázs
Neuhaus, Ain A.
Harston, George
Joly, Olivier
Carone, Davide
Gerry, Stephen
Chadaide, Zoltán
Pánczél, András
Czifrus, Eszter
Csike, Viktória
Surányi, Ágnes
Szikora, István
Erőss, Loránd
author_facet Kis, Balázs
Neuhaus, Ain A.
Harston, George
Joly, Olivier
Carone, Davide
Gerry, Stephen
Chadaide, Zoltán
Pánczél, András
Czifrus, Eszter
Csike, Viktória
Surányi, Ágnes
Szikora, István
Erőss, Loránd
author_sort Kis, Balázs
collection PubMed
description BACKGROUND: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute changes (most commonly Alberta Stroke Programme Early CT Score, ASPECTS, at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome. AIMS: To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT. METHODS: In 215 patients with anterior circulation stroke, who subsequently underwent EVT, automated analysis of presenting non-contrast CT scans was used to determine acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Univariate and multivariate logistic regression were used to identify significant predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT. RESULTS: For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0–2 and death at 90 days, whereas age did not reach significance in multivariate analysis. Conversely, for short-term NIHSS improvement, AIV and age were significant predictors, unlike presenting NIHSS. The interaction between age and NIHSS was similar to the interaction of AIV and atrophy for mRS 0–2 at 90 days. CONCLUSION: Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcome and may improve long-term prognostication in EVT. These results provide a basis for future development of predictive tools built into decision-aiding software in stroke.
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spelling pubmed-97977142022-12-30 Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy Kis, Balázs Neuhaus, Ain A. Harston, George Joly, Olivier Carone, Davide Gerry, Stephen Chadaide, Zoltán Pánczél, András Czifrus, Eszter Csike, Viktória Surányi, Ágnes Szikora, István Erőss, Loránd Front Neurol Neurology BACKGROUND: Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute changes (most commonly Alberta Stroke Programme Early CT Score, ASPECTS, at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome. AIMS: To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT. METHODS: In 215 patients with anterior circulation stroke, who subsequently underwent EVT, automated analysis of presenting non-contrast CT scans was used to determine acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Univariate and multivariate logistic regression were used to identify significant predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT. RESULTS: For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0–2 and death at 90 days, whereas age did not reach significance in multivariate analysis. Conversely, for short-term NIHSS improvement, AIV and age were significant predictors, unlike presenting NIHSS. The interaction between age and NIHSS was similar to the interaction of AIV and atrophy for mRS 0–2 at 90 days. CONCLUSION: Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcome and may improve long-term prognostication in EVT. These results provide a basis for future development of predictive tools built into decision-aiding software in stroke. Frontiers Media S.A. 2022-12-15 /pmc/articles/PMC9797714/ /pubmed/36588883 http://dx.doi.org/10.3389/fneur.2022.1056532 Text en Copyright © 2022 Kis, Neuhaus, Harston, Joly, Carone, Gerry, Chadaide, Pánczél, Czifrus, Csike, Surányi, Szikora and Erőss. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Kis, Balázs
Neuhaus, Ain A.
Harston, George
Joly, Olivier
Carone, Davide
Gerry, Stephen
Chadaide, Zoltán
Pánczél, András
Czifrus, Eszter
Csike, Viktória
Surányi, Ágnes
Szikora, István
Erőss, Loránd
Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title_full Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title_fullStr Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title_full_unstemmed Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title_short Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
title_sort automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797714/
https://www.ncbi.nlm.nih.gov/pubmed/36588883
http://dx.doi.org/10.3389/fneur.2022.1056532
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