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Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design
INTRODUCTION: Haemorrhagic stroke is of significant healthcare concern due to its association with high mortality and lasting impact on the survivors’ quality of life. Treatment decisions and clinical outcomes depend strongly on the size, spread and location of the haematoma. Non-contrast CT (NCCT)...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5914893/ https://www.ncbi.nlm.nih.gov/pubmed/29674371 http://dx.doi.org/10.1136/bmjopen-2017-020260 |
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author | Chinda, Betty Medvedev, George Siu, William Ester, Martin Arab, Ali Gu, Tao Moreno, Sylvain D’Arcy, Ryan C N Song, Xiaowei |
author_facet | Chinda, Betty Medvedev, George Siu, William Ester, Martin Arab, Ali Gu, Tao Moreno, Sylvain D’Arcy, Ryan C N Song, Xiaowei |
author_sort | Chinda, Betty |
collection | PubMed |
description | INTRODUCTION: Haemorrhagic stroke is of significant healthcare concern due to its association with high mortality and lasting impact on the survivors’ quality of life. Treatment decisions and clinical outcomes depend strongly on the size, spread and location of the haematoma. Non-contrast CT (NCCT) is the primary neuroimaging modality for haematoma assessment in haemorrhagic stroke diagnosis. Current procedures do not allow convenient NCCT-based haemorrhage volume calculation in clinical settings, while research-based approaches are yet to be tested for clinical utility; there is a demonstrated need for developing effective solutions. The project under review investigates the development of an automatic NCCT-based haematoma computation tool in support of accurate quantification of haematoma volumes. METHODS AND ANALYSIS: Several existing research methods for haematoma volume estimation are studied. Selected methods are tested using NCCT images of patients diagnosed with acute haemorrhagic stroke. For inter-rater and intrarater reliability evaluation, different raters will analyse haemorrhage volumes independently. The efficiency with respect to time of haematoma volume assessments will be examined to compare with the results from routine clinical evaluations and planimetry assessment that are known to be more accurate. The project will target the development of an enhanced solution by adapting existing methods and integrating machine learning algorithms. NCCT-based information of brain haemorrhage (eg, size, volume, location) and other relevant information (eg, age, sex, risk factor, comorbidities) will be used in relation to clinical outcomes with future project development. Validity and reliability of the solution will be examined for potential clinical utility. ETHICS AND DISSEMINATION: The project including procedures for deidentification of NCCT data has been ethically approved. The study involves secondary use of existing data and does not require new consent of participation. The team consists of clinical neuroimaging scientists, computing scientists and clinical professionals in neurology and neuroradiology and includes patient representatives. Research outputs will be disseminated following knowledge translation plans towards improving stroke patient care. Significant findings will be published in scientific journals. Anticipated deliverables include computer solutions for improved clinical assessment of haematoma using NCCT. |
format | Online Article Text |
id | pubmed-5914893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-59148932018-04-27 Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design Chinda, Betty Medvedev, George Siu, William Ester, Martin Arab, Ali Gu, Tao Moreno, Sylvain D’Arcy, Ryan C N Song, Xiaowei BMJ Open Neurology INTRODUCTION: Haemorrhagic stroke is of significant healthcare concern due to its association with high mortality and lasting impact on the survivors’ quality of life. Treatment decisions and clinical outcomes depend strongly on the size, spread and location of the haematoma. Non-contrast CT (NCCT) is the primary neuroimaging modality for haematoma assessment in haemorrhagic stroke diagnosis. Current procedures do not allow convenient NCCT-based haemorrhage volume calculation in clinical settings, while research-based approaches are yet to be tested for clinical utility; there is a demonstrated need for developing effective solutions. The project under review investigates the development of an automatic NCCT-based haematoma computation tool in support of accurate quantification of haematoma volumes. METHODS AND ANALYSIS: Several existing research methods for haematoma volume estimation are studied. Selected methods are tested using NCCT images of patients diagnosed with acute haemorrhagic stroke. For inter-rater and intrarater reliability evaluation, different raters will analyse haemorrhage volumes independently. The efficiency with respect to time of haematoma volume assessments will be examined to compare with the results from routine clinical evaluations and planimetry assessment that are known to be more accurate. The project will target the development of an enhanced solution by adapting existing methods and integrating machine learning algorithms. NCCT-based information of brain haemorrhage (eg, size, volume, location) and other relevant information (eg, age, sex, risk factor, comorbidities) will be used in relation to clinical outcomes with future project development. Validity and reliability of the solution will be examined for potential clinical utility. ETHICS AND DISSEMINATION: The project including procedures for deidentification of NCCT data has been ethically approved. The study involves secondary use of existing data and does not require new consent of participation. The team consists of clinical neuroimaging scientists, computing scientists and clinical professionals in neurology and neuroradiology and includes patient representatives. Research outputs will be disseminated following knowledge translation plans towards improving stroke patient care. Significant findings will be published in scientific journals. Anticipated deliverables include computer solutions for improved clinical assessment of haematoma using NCCT. BMJ Publishing Group 2018-04-19 /pmc/articles/PMC5914893/ /pubmed/29674371 http://dx.doi.org/10.1136/bmjopen-2017-020260 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Neurology Chinda, Betty Medvedev, George Siu, William Ester, Martin Arab, Ali Gu, Tao Moreno, Sylvain D’Arcy, Ryan C N Song, Xiaowei Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title | Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title_full | Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title_fullStr | Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title_full_unstemmed | Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title_short | Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
title_sort | automation of ct-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5914893/ https://www.ncbi.nlm.nih.gov/pubmed/29674371 http://dx.doi.org/10.1136/bmjopen-2017-020260 |
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