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Automatic comprehensive aspects reports in clinical acute stroke MRIs
The Alberta Stroke Program Early CT Score (ASPECTS) is a simple visual system to assess the extent and location of ischemic stroke core. The capability of ASPECTS for selecting patients’ treatment, however, is affected by the variability in human evaluation. In this study, we developed a fully autom...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992659/ https://www.ncbi.nlm.nih.gov/pubmed/36882475 http://dx.doi.org/10.1038/s41598-023-30242-6 |
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author | Liu, Chin-Fu Li, Jintong Kim, Ganghyun Miller, Michael I. Hillis, Argye E. Faria, Andreia V. |
author_facet | Liu, Chin-Fu Li, Jintong Kim, Ganghyun Miller, Michael I. Hillis, Argye E. Faria, Andreia V. |
author_sort | Liu, Chin-Fu |
collection | PubMed |
description | The Alberta Stroke Program Early CT Score (ASPECTS) is a simple visual system to assess the extent and location of ischemic stroke core. The capability of ASPECTS for selecting patients’ treatment, however, is affected by the variability in human evaluation. In this study, we developed a fully automatic system to calculate ASPECTS comparable with consensus expert readings. Our system was trained in 400 clinical diffusion weighted images of patients with acute infarcts and evaluated with an external testing set of 100 cases. The models are interpretable, and the results are comprehensive, evidencing the features that lead to the classification. This system adds to our automated pipeline for acute stroke detection, segmentation, and quantification in MRIs (ADS), which outputs digital infarct masks and the proportion of diverse brain regions injured, in addition to the predicted ASPECTS, the prediction probability and the explanatory features. ADS is public, free, accessible to non-experts, has very few computational requirements, and run in real time in local CPUs with a single command line, fulfilling the conditions to perform large-scale, reproducible clinical and translational research. |
format | Online Article Text |
id | pubmed-9992659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-99926592023-03-09 Automatic comprehensive aspects reports in clinical acute stroke MRIs Liu, Chin-Fu Li, Jintong Kim, Ganghyun Miller, Michael I. Hillis, Argye E. Faria, Andreia V. Sci Rep Article The Alberta Stroke Program Early CT Score (ASPECTS) is a simple visual system to assess the extent and location of ischemic stroke core. The capability of ASPECTS for selecting patients’ treatment, however, is affected by the variability in human evaluation. In this study, we developed a fully automatic system to calculate ASPECTS comparable with consensus expert readings. Our system was trained in 400 clinical diffusion weighted images of patients with acute infarcts and evaluated with an external testing set of 100 cases. The models are interpretable, and the results are comprehensive, evidencing the features that lead to the classification. This system adds to our automated pipeline for acute stroke detection, segmentation, and quantification in MRIs (ADS), which outputs digital infarct masks and the proportion of diverse brain regions injured, in addition to the predicted ASPECTS, the prediction probability and the explanatory features. ADS is public, free, accessible to non-experts, has very few computational requirements, and run in real time in local CPUs with a single command line, fulfilling the conditions to perform large-scale, reproducible clinical and translational research. Nature Publishing Group UK 2023-03-07 /pmc/articles/PMC9992659/ /pubmed/36882475 http://dx.doi.org/10.1038/s41598-023-30242-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Liu, Chin-Fu Li, Jintong Kim, Ganghyun Miller, Michael I. Hillis, Argye E. Faria, Andreia V. Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title | Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title_full | Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title_fullStr | Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title_full_unstemmed | Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title_short | Automatic comprehensive aspects reports in clinical acute stroke MRIs |
title_sort | automatic comprehensive aspects reports in clinical acute stroke mris |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9992659/ https://www.ncbi.nlm.nih.gov/pubmed/36882475 http://dx.doi.org/10.1038/s41598-023-30242-6 |
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