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Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke
MRI is widely used in the assessment of acute ischemic stroke. In particular, it identifies the mismatch between hypoperfused and the permanently damaged tissue, the PWI-DWI mismatch volume. It is used to help triage patients into active or supportive treatment pathways. COMBAT Stroke is an automate...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3783931/ https://www.ncbi.nlm.nih.gov/pubmed/24133479 http://dx.doi.org/10.3389/fneur.2013.00140 |
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author | Nagenthiraja, Kartheeban Walcott, Brian P. Hansen, Mikkel B. Østergaard, Leif Mouridsen, Kim |
author_facet | Nagenthiraja, Kartheeban Walcott, Brian P. Hansen, Mikkel B. Østergaard, Leif Mouridsen, Kim |
author_sort | Nagenthiraja, Kartheeban |
collection | PubMed |
description | MRI is widely used in the assessment of acute ischemic stroke. In particular, it identifies the mismatch between hypoperfused and the permanently damaged tissue, the PWI-DWI mismatch volume. It is used to help triage patients into active or supportive treatment pathways. COMBAT Stroke is an automated software tool for estimating the mismatch volume and ratio based on MRI. Herein, we validate the decision made by the software with actual clinical decision rendered. Furthermore, we evaluate the association between treatment decisions (both automated and actual) and outcomes. COMBAT Stroke was used to determine PWI-DWI mismatch volume and ratio in 228 patients from two European multi-center stroke databases. We performed confusion matrix analysis to summarize the agreement between the automated selection and the clinical decision. Finally, we evaluated the clinical and imaging outcomes of the patients in the four entries of the confusion matrix (true positive, true negative, false negative, and false positive). About 186 of 228 patients with acute stroke underwent thrombolytic treatment, with the remaining 42 receiving supportive treatment only. Selection based on radiographic criteria using COMBAT Stroke classified 142 patients as potential candidates for thrombolytic treatment and 86 for supportive treatment; 60% sensitivity and 29% specificity. The patients deemed eligible for thrombolytic treatment by COMBAT Stroke demonstrated significantly higher rates of compromised tissue salvage, less neurological deficit, and were more likely to experience thrombus dissolving and reestablishment of normal blood flow at 24 h follow-up compared to those who were treated without substantial PWI-DWI mismatch. These results provide evidence that COMBAT Stroke, in addition to clinical assessment, may offer an optimal framework for a fast, efficient, and standardized clinical support tool to select patients for thrombolysis in acute ischemic stroke. |
format | Online Article Text |
id | pubmed-3783931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-37839312013-10-16 Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke Nagenthiraja, Kartheeban Walcott, Brian P. Hansen, Mikkel B. Østergaard, Leif Mouridsen, Kim Front Neurol Neuroscience MRI is widely used in the assessment of acute ischemic stroke. In particular, it identifies the mismatch between hypoperfused and the permanently damaged tissue, the PWI-DWI mismatch volume. It is used to help triage patients into active or supportive treatment pathways. COMBAT Stroke is an automated software tool for estimating the mismatch volume and ratio based on MRI. Herein, we validate the decision made by the software with actual clinical decision rendered. Furthermore, we evaluate the association between treatment decisions (both automated and actual) and outcomes. COMBAT Stroke was used to determine PWI-DWI mismatch volume and ratio in 228 patients from two European multi-center stroke databases. We performed confusion matrix analysis to summarize the agreement between the automated selection and the clinical decision. Finally, we evaluated the clinical and imaging outcomes of the patients in the four entries of the confusion matrix (true positive, true negative, false negative, and false positive). About 186 of 228 patients with acute stroke underwent thrombolytic treatment, with the remaining 42 receiving supportive treatment only. Selection based on radiographic criteria using COMBAT Stroke classified 142 patients as potential candidates for thrombolytic treatment and 86 for supportive treatment; 60% sensitivity and 29% specificity. The patients deemed eligible for thrombolytic treatment by COMBAT Stroke demonstrated significantly higher rates of compromised tissue salvage, less neurological deficit, and were more likely to experience thrombus dissolving and reestablishment of normal blood flow at 24 h follow-up compared to those who were treated without substantial PWI-DWI mismatch. These results provide evidence that COMBAT Stroke, in addition to clinical assessment, may offer an optimal framework for a fast, efficient, and standardized clinical support tool to select patients for thrombolysis in acute ischemic stroke. Frontiers Media S.A. 2013-09-26 /pmc/articles/PMC3783931/ /pubmed/24133479 http://dx.doi.org/10.3389/fneur.2013.00140 Text en Copyright © 2013 Nagenthiraja, Walcott, Hansen, Østergaard and Mouridsen. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 | Neuroscience Nagenthiraja, Kartheeban Walcott, Brian P. Hansen, Mikkel B. Østergaard, Leif Mouridsen, Kim Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title | Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title_full | Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title_fullStr | Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title_full_unstemmed | Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title_short | Automated Decision-Support System for Prediction of Treatment Responders in Acute Ischemic Stroke |
title_sort | automated decision-support system for prediction of treatment responders in acute ischemic stroke |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3783931/ https://www.ncbi.nlm.nih.gov/pubmed/24133479 http://dx.doi.org/10.3389/fneur.2013.00140 |
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