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Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke

The hyperdense sign is a marker of thrombus in non-contrast computed tomography (NCCT) datasets. The aim of this work was to determine optimal Hounsfield unit (HU) thresholds for thrombus segmentation in thin-slice non-contrast CT (NCCT) and use these thresholds to generate 3D thrombus models. Patie...

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Autores principales: Qazi, Shakeel, Qazi, Emmad, Wilson, Alexis T., McDougall, Connor, Al-Ajlan, Fahad, Evans, James, Gensicke, Henrik, Hill, Michael D., Lee, Ting, Goyal, Mayank, Demchuk, Andrew M., Menon, Bijoy K., Forkert, Nils D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534393/
https://www.ncbi.nlm.nih.gov/pubmed/34679617
http://dx.doi.org/10.3390/diagnostics11101919
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author Qazi, Shakeel
Qazi, Emmad
Wilson, Alexis T.
McDougall, Connor
Al-Ajlan, Fahad
Evans, James
Gensicke, Henrik
Hill, Michael D.
Lee, Ting
Goyal, Mayank
Demchuk, Andrew M.
Menon, Bijoy K.
Forkert, Nils D.
author_facet Qazi, Shakeel
Qazi, Emmad
Wilson, Alexis T.
McDougall, Connor
Al-Ajlan, Fahad
Evans, James
Gensicke, Henrik
Hill, Michael D.
Lee, Ting
Goyal, Mayank
Demchuk, Andrew M.
Menon, Bijoy K.
Forkert, Nils D.
author_sort Qazi, Shakeel
collection PubMed
description The hyperdense sign is a marker of thrombus in non-contrast computed tomography (NCCT) datasets. The aim of this work was to determine optimal Hounsfield unit (HU) thresholds for thrombus segmentation in thin-slice non-contrast CT (NCCT) and use these thresholds to generate 3D thrombus models. Patients with thin-slice baseline NCCT (≤2.5 mm) and MCA-M1 occlusions were included. CTA was registered to NCCT, and three regions of interest (ROIs) were placed in the NCCT, including: the thrombus, contralateral brain tissue, and contralateral patent MCA-M1 artery. Optimal HU thresholds differentiating the thrombus from non-thrombus tissue voxels were calculated using receiver operating characteristic analysis. Linear regression analysis was used to predict the optimal HU threshold for discriminating the clot only based on the average contralateral vessel HU or contralateral parenchyma HU. Three-dimensional models from 70 participants using standard (45 HU) and patient-specific thresholds were generated and compared to CTA clot characteristics. The optimal HU threshold discriminating thrombus in NCCT from other structures varied with a median of 51 (IQR: 49–55). Experts chose 3D models derived using patient-specific HU models as corresponding better to the thrombus seen in CTA in 83.8% (31/37) of cases. Patient-specific HU thresholds for segmenting the thrombus in NCCT can be derived using normal parenchyma. Thrombus segmentation using patient-specific HU thresholds is superior to conventional 45 HU thresholds.
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spelling pubmed-85343932021-10-23 Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke Qazi, Shakeel Qazi, Emmad Wilson, Alexis T. McDougall, Connor Al-Ajlan, Fahad Evans, James Gensicke, Henrik Hill, Michael D. Lee, Ting Goyal, Mayank Demchuk, Andrew M. Menon, Bijoy K. Forkert, Nils D. Diagnostics (Basel) Article The hyperdense sign is a marker of thrombus in non-contrast computed tomography (NCCT) datasets. The aim of this work was to determine optimal Hounsfield unit (HU) thresholds for thrombus segmentation in thin-slice non-contrast CT (NCCT) and use these thresholds to generate 3D thrombus models. Patients with thin-slice baseline NCCT (≤2.5 mm) and MCA-M1 occlusions were included. CTA was registered to NCCT, and three regions of interest (ROIs) were placed in the NCCT, including: the thrombus, contralateral brain tissue, and contralateral patent MCA-M1 artery. Optimal HU thresholds differentiating the thrombus from non-thrombus tissue voxels were calculated using receiver operating characteristic analysis. Linear regression analysis was used to predict the optimal HU threshold for discriminating the clot only based on the average contralateral vessel HU or contralateral parenchyma HU. Three-dimensional models from 70 participants using standard (45 HU) and patient-specific thresholds were generated and compared to CTA clot characteristics. The optimal HU threshold discriminating thrombus in NCCT from other structures varied with a median of 51 (IQR: 49–55). Experts chose 3D models derived using patient-specific HU models as corresponding better to the thrombus seen in CTA in 83.8% (31/37) of cases. Patient-specific HU thresholds for segmenting the thrombus in NCCT can be derived using normal parenchyma. Thrombus segmentation using patient-specific HU thresholds is superior to conventional 45 HU thresholds. MDPI 2021-10-16 /pmc/articles/PMC8534393/ /pubmed/34679617 http://dx.doi.org/10.3390/diagnostics11101919 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qazi, Shakeel
Qazi, Emmad
Wilson, Alexis T.
McDougall, Connor
Al-Ajlan, Fahad
Evans, James
Gensicke, Henrik
Hill, Michael D.
Lee, Ting
Goyal, Mayank
Demchuk, Andrew M.
Menon, Bijoy K.
Forkert, Nils D.
Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title_full Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title_fullStr Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title_full_unstemmed Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title_short Identifying Thrombus on Non-Contrast CT in Patients with Acute Ischemic Stroke
title_sort identifying thrombus on non-contrast ct in patients with acute ischemic stroke
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534393/
https://www.ncbi.nlm.nih.gov/pubmed/34679617
http://dx.doi.org/10.3390/diagnostics11101919
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