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Accuracy of automated intracerebral hemorrhage volume measurement on non-contrast computed tomography : a Swedish Stroke Register cohort study

Hillal, Amir LU ; Sultani, Gabriella LU ; Ramgren, Birgitta LU ; Norrving, Bo LU ; Wassélius, Johan LU and Ullberg, Teresa LU (2023) In Neuroradiology 65(3). p.479-488
Abstract

Purpose: Hematoma volume is the strongest predictor of patient outcome after intracerebral hemorrhage (ICH). The aim of this study was to validate novel fully automated software for quantification of ICH volume on non-contrast computed tomography (CT). Methods: The population was defined from the Swedish Stroke Register (RS) and included all patients with an ICH diagnosis during 2016–2019 in Region Skåne. Hemorrhage volume on their initial head CT was measured using ABC/2 and manual segmentation (Sectra IDS7 volume measurement tool) and the automated volume quantification tool (qER–NCCT) by Qure.ai. The first 500 were examined by two independent readers. Results: A total of 1649 ICH patients were included. The qER–NCCT had 97%... (More)

Purpose: Hematoma volume is the strongest predictor of patient outcome after intracerebral hemorrhage (ICH). The aim of this study was to validate novel fully automated software for quantification of ICH volume on non-contrast computed tomography (CT). Methods: The population was defined from the Swedish Stroke Register (RS) and included all patients with an ICH diagnosis during 2016–2019 in Region Skåne. Hemorrhage volume on their initial head CT was measured using ABC/2 and manual segmentation (Sectra IDS7 volume measurement tool) and the automated volume quantification tool (qER–NCCT) by Qure.ai. The first 500 were examined by two independent readers. Results: A total of 1649 ICH patients were included. The qER–NCCT had 97% sensitivity in identifying ICH. In total, there was excellent agreement between volumetric measurements of ICH volumes by qER–NCCT and manual segmentation by interclass correlation (ICC = 0.96), and good agreement (ICC = 0.86) between qER–NCCT and ABC/2 method. The qER–NCCT showed volume underestimation, mainly in large (> 30 ml) heterogenous hemorrhages. Interrater agreement by (ICC) was 0.996 (95% CI: 0.99–1.00) for manual segmentation. Conclusion: Our study showed excellent agreement in volume quantification between the fully automated software qER–NCCT and manual segmentation of ICH on NCCT. The qER–NCCT would be an important additive tool by aiding in early diagnostics and prognostication for patients with ICH and in provide volumetry on a population-wide level. Further refinement of the software should address the underestimation of ICH volume seen in a portion of large, heterogenous, irregularly shaped ICHs.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Automated image analysis software, Brain, Intracerebral hemorrhage, Non-contrast computed tomography
in
Neuroradiology
volume
65
issue
3
pages
479 - 488
publisher
Springer
external identifiers
  • pmid:36323862
  • scopus:85141129209
ISSN
0028-3940
DOI
10.1007/s00234-022-03075-9
language
English
LU publication?
yes
id
ba9b7cbb-f976-4c22-9c41-cbdda8b3a91a
date added to LUP
2022-12-21 12:27:59
date last changed
2024-04-18 17:37:41
@article{ba9b7cbb-f976-4c22-9c41-cbdda8b3a91a,
  abstract     = {{<p>Purpose: Hematoma volume is the strongest predictor of patient outcome after intracerebral hemorrhage (ICH). The aim of this study was to validate novel fully automated software for quantification of ICH volume on non-contrast computed tomography (CT). Methods: The population was defined from the Swedish Stroke Register (RS) and included all patients with an ICH diagnosis during 2016–2019 in Region Skåne. Hemorrhage volume on their initial head CT was measured using ABC/2 and manual segmentation (Sectra IDS7 volume measurement tool) and the automated volume quantification tool (qER–NCCT) by Qure.ai. The first 500 were examined by two independent readers. Results: A total of 1649 ICH patients were included. The qER–NCCT had 97% sensitivity in identifying ICH. In total, there was excellent agreement between volumetric measurements of ICH volumes by qER–NCCT and manual segmentation by interclass correlation (ICC = 0.96), and good agreement (ICC = 0.86) between qER–NCCT and ABC/2 method. The qER–NCCT showed volume underestimation, mainly in large (&gt; 30 ml) heterogenous hemorrhages. Interrater agreement by (ICC) was 0.996 (95% CI: 0.99–1.00) for manual segmentation. Conclusion: Our study showed excellent agreement in volume quantification between the fully automated software qER–NCCT and manual segmentation of ICH on NCCT. The qER–NCCT would be an important additive tool by aiding in early diagnostics and prognostication for patients with ICH and in provide volumetry on a population-wide level. Further refinement of the software should address the underestimation of ICH volume seen in a portion of large, heterogenous, irregularly shaped ICHs.</p>}},
  author       = {{Hillal, Amir and Sultani, Gabriella and Ramgren, Birgitta and Norrving, Bo and Wassélius, Johan and Ullberg, Teresa}},
  issn         = {{0028-3940}},
  keywords     = {{Automated image analysis software; Brain; Intracerebral hemorrhage; Non-contrast computed tomography}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{479--488}},
  publisher    = {{Springer}},
  series       = {{Neuroradiology}},
  title        = {{Accuracy of automated intracerebral hemorrhage volume measurement on non-contrast computed tomography : a Swedish Stroke Register cohort study}},
  url          = {{http://dx.doi.org/10.1007/s00234-022-03075-9}},
  doi          = {{10.1007/s00234-022-03075-9}},
  volume       = {{65}},
  year         = {{2023}},
}