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Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke

PURPOSE: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was designed for semi-quantitative assessment of early ischemic changes on non-contrast computed tomography (NCCT) for acute ischemic stroke (AIS). We evaluated two automated ASPECTS software in comparison with reference s...

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Autores principales: Chen, Zhongping, Shi, Zhenzhen, Lu, Fei, Li, Linna, Li, Mingyang, Wang, Shuo, Wang, Wenxin, Li, Yongxin, Luo, Yu, Tong, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116051/
https://www.ncbi.nlm.nih.gov/pubmed/37090971
http://dx.doi.org/10.3389/fneur.2023.1170955
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author Chen, Zhongping
Shi, Zhenzhen
Lu, Fei
Li, Linna
Li, Mingyang
Wang, Shuo
Wang, Wenxin
Li, Yongxin
Luo, Yu
Tong, Dan
author_facet Chen, Zhongping
Shi, Zhenzhen
Lu, Fei
Li, Linna
Li, Mingyang
Wang, Shuo
Wang, Wenxin
Li, Yongxin
Luo, Yu
Tong, Dan
author_sort Chen, Zhongping
collection PubMed
description PURPOSE: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was designed for semi-quantitative assessment of early ischemic changes on non-contrast computed tomography (NCCT) for acute ischemic stroke (AIS). We evaluated two automated ASPECTS software in comparison with reference standard. METHODS: NCCT of 276 AIS patients were retrospectively reviewed (March 2018–June 2020). A three-radiologist consensus for ASPECTS was used as reference standard. Imaging data from both baseline and follow-up were evaluated for reference standard. Automated ASPECTS were calculated from baseline NCCT with 1-mm and 5-mm slice thickness, respectively. Agreement between automated ASPECTS and reference standard was assessed using intra-class correlation coefficient (ICC). Correlation of automated ASPECTS with baseline stroke severity (NIHSS) and follow-up ASPECTS were evaluated using Spearman correlation analysis. RESULTS: In score-based analysis, automated ASPECTS calculated from 5-mm slice thickness images agreed well with reference standard (software A: ICC = 0.77; software B: ICC = 0.65). Bland–Altman analysis revealed that the mean differences between automated ASPECTS and reference standard were ≤ 0.6. In region-based analysis, automated ASPECTS derived from 5-mm slice thickness images by software A showed higher sensitivity (0.60 vs. 0.54), lower specificity (0.91 vs. 0.94), and higher AUC (0.76 vs. 0.74) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS derived from 5-mm slice thickness images by software B showed higher sensitivity (0.56 vs. 0.51), higher specificity (0.87 vs. 0.81), higher accuracy (0.80 vs. 0.73), and higher AUC (0.71 vs. 0.66) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS were significantly associated with baseline NIHSS and follow-up ASPECTS. CONCLUSION: Automated ASPECTS showed good reliability and 5 mm was the optimal slice thickness.
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spelling pubmed-101160512023-04-21 Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke Chen, Zhongping Shi, Zhenzhen Lu, Fei Li, Linna Li, Mingyang Wang, Shuo Wang, Wenxin Li, Yongxin Luo, Yu Tong, Dan Front Neurol Neurology PURPOSE: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was designed for semi-quantitative assessment of early ischemic changes on non-contrast computed tomography (NCCT) for acute ischemic stroke (AIS). We evaluated two automated ASPECTS software in comparison with reference standard. METHODS: NCCT of 276 AIS patients were retrospectively reviewed (March 2018–June 2020). A three-radiologist consensus for ASPECTS was used as reference standard. Imaging data from both baseline and follow-up were evaluated for reference standard. Automated ASPECTS were calculated from baseline NCCT with 1-mm and 5-mm slice thickness, respectively. Agreement between automated ASPECTS and reference standard was assessed using intra-class correlation coefficient (ICC). Correlation of automated ASPECTS with baseline stroke severity (NIHSS) and follow-up ASPECTS were evaluated using Spearman correlation analysis. RESULTS: In score-based analysis, automated ASPECTS calculated from 5-mm slice thickness images agreed well with reference standard (software A: ICC = 0.77; software B: ICC = 0.65). Bland–Altman analysis revealed that the mean differences between automated ASPECTS and reference standard were ≤ 0.6. In region-based analysis, automated ASPECTS derived from 5-mm slice thickness images by software A showed higher sensitivity (0.60 vs. 0.54), lower specificity (0.91 vs. 0.94), and higher AUC (0.76 vs. 0.74) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS derived from 5-mm slice thickness images by software B showed higher sensitivity (0.56 vs. 0.51), higher specificity (0.87 vs. 0.81), higher accuracy (0.80 vs. 0.73), and higher AUC (0.71 vs. 0.66) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS were significantly associated with baseline NIHSS and follow-up ASPECTS. CONCLUSION: Automated ASPECTS showed good reliability and 5 mm was the optimal slice thickness. Frontiers Media S.A. 2023-04-06 /pmc/articles/PMC10116051/ /pubmed/37090971 http://dx.doi.org/10.3389/fneur.2023.1170955 Text en Copyright © 2023 Chen, Shi, Lu, Li, Li, Wang, Wang, Li, Luo and Tong. 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
Chen, Zhongping
Shi, Zhenzhen
Lu, Fei
Li, Linna
Li, Mingyang
Wang, Shuo
Wang, Wenxin
Li, Yongxin
Luo, Yu
Tong, Dan
Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title_full Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title_fullStr Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title_full_unstemmed Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title_short Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke
title_sort validation of two automated aspects software on non-contrast computed tomography scans of patients with acute ischemic stroke
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116051/
https://www.ncbi.nlm.nih.gov/pubmed/37090971
http://dx.doi.org/10.3389/fneur.2023.1170955
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