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An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms
Background: VWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534502/ https://www.ncbi.nlm.nih.gov/pubmed/34679440 http://dx.doi.org/10.3390/diagnostics11101742 |
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author | Veeturi, Sricharan S. Pinter, Nandor K. Monteiro, Andre Baig, Ammad A. Rai, Hamid H. Waqas, Muhammad Siddiqui, Adnan H. Rajabzadeh-Oghaz, Hamidreza Tutino, Vincent M. |
author_facet | Veeturi, Sricharan S. Pinter, Nandor K. Monteiro, Andre Baig, Ammad A. Rai, Hamid H. Waqas, Muhammad Siddiqui, Adnan H. Rajabzadeh-Oghaz, Hamidreza Tutino, Vincent M. |
author_sort | Veeturi, Sricharan S. |
collection | PubMed |
description | Background: VWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a tool for the visualization, quantification and objective identification of regions with VWE. Methods: N = 41 3D T1-MRI and 3D TOF-MRA IA images from 38 patients were obtained and co-registered. A contrast-enhanced MRI was normalized by the enhancement intensity of the pituitary stalk and signal intensities were mapped onto the surface of IA models generated from segmented MRA. N = 30 IAs were used to identify the optimal signal intensity value to distinguish the enhancing and non-enhancing regions (marked by an experienced neuroradiologist). The remaining IAs (n = 11) were used to validate the threshold. We tested if the enhancement area ratio (EAR—ratio of the enhancing area to the IA surface-area) could identify high risk aneurysms as identified by the ISUIA clinical score. Results: A normalized intensity of 0.276 was the optimal threshold to delineate enhancing regions, with a validation accuracy of 81.7%. In comparing the overlap between the identified enhancement regions against those marked by the neuroradiologist, our method had a dice coefficient of 71.1%. An EAR of 23% was able to discriminate high-risk cases with an AUC of 0.7. Conclusions: We developed and validated a pipeline for the visualization and objective identification of VWE regions that could potentially help evaluation of IAs become more reliable and consistent. |
format | Online Article Text |
id | pubmed-8534502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85345022021-10-23 An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms Veeturi, Sricharan S. Pinter, Nandor K. Monteiro, Andre Baig, Ammad A. Rai, Hamid H. Waqas, Muhammad Siddiqui, Adnan H. Rajabzadeh-Oghaz, Hamidreza Tutino, Vincent M. Diagnostics (Basel) Article Background: VWE in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for the evaluation of IA. The common practice to identify IAs with VWE is mainly based on a visual inspection of MR images, which is subject to errors and inconsistencies. Here, we develop and validate a tool for the visualization, quantification and objective identification of regions with VWE. Methods: N = 41 3D T1-MRI and 3D TOF-MRA IA images from 38 patients were obtained and co-registered. A contrast-enhanced MRI was normalized by the enhancement intensity of the pituitary stalk and signal intensities were mapped onto the surface of IA models generated from segmented MRA. N = 30 IAs were used to identify the optimal signal intensity value to distinguish the enhancing and non-enhancing regions (marked by an experienced neuroradiologist). The remaining IAs (n = 11) were used to validate the threshold. We tested if the enhancement area ratio (EAR—ratio of the enhancing area to the IA surface-area) could identify high risk aneurysms as identified by the ISUIA clinical score. Results: A normalized intensity of 0.276 was the optimal threshold to delineate enhancing regions, with a validation accuracy of 81.7%. In comparing the overlap between the identified enhancement regions against those marked by the neuroradiologist, our method had a dice coefficient of 71.1%. An EAR of 23% was able to discriminate high-risk cases with an AUC of 0.7. Conclusions: We developed and validated a pipeline for the visualization and objective identification of VWE regions that could potentially help evaluation of IAs become more reliable and consistent. MDPI 2021-09-22 /pmc/articles/PMC8534502/ /pubmed/34679440 http://dx.doi.org/10.3390/diagnostics11101742 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 Veeturi, Sricharan S. Pinter, Nandor K. Monteiro, Andre Baig, Ammad A. Rai, Hamid H. Waqas, Muhammad Siddiqui, Adnan H. Rajabzadeh-Oghaz, Hamidreza Tutino, Vincent M. An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title | An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title_full | An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title_fullStr | An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title_full_unstemmed | An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title_short | An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms |
title_sort | image-based workflow for objective vessel wall enhancement quantification in intracranial aneurysms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534502/ https://www.ncbi.nlm.nih.gov/pubmed/34679440 http://dx.doi.org/10.3390/diagnostics11101742 |
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