A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F17%3A00068495" target="_blank" >RIV/00159816:_____/17:00068495 - isvavai.cz</a>
Výsledek na webu
<a href="https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.12015" target="_blank" >https://aapm.onlinelibrary.wiley.com/doi/pdf/10.1002/mp.12015</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/mp.12015" target="_blank" >10.1002/mp.12015</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography
Popis výsledku v původním jazyce
Purpose: Early identification of ischemic stroke plays a significant role in treatment and potential recovery of damaged brain tissue. In noncontrast CT (ncCT), the differences between ischemic changes and healthy tissue are usually very subtle during the hyperacute phase (< 8 h from the stroke onset). Therefore, visual comparison of both hemispheres is an important step in clinical assessment. A quantitative symmetry-based analysis of texture features of ischemic lesions in noncontrast CT images may provide an important information for differentiation of ischemic and healthy brain tissue in this phase. Methods: One hundred thirty-nine (139) ncCT scans of hyperacute ischemic stroke with follow-up magnetic resonance diffusion-weighted (MR-DW) images were collected. The regions of stroke were identified in the MR-DW images, which were spatially aligned to corresponding ncCT images. A state-of-the-art symmetric diffeomorphic image registration was utilized for the alignment of CT and MR-DW, for identification of individual brain hemispheres, and for localization of the region representing healthy tissue contralateral to the stroke cores. Texture analysis included extraction and classification of co-occurrence and run-length texture-based image features in the regions of ischemic stroke and their contralateral regions. Results: The classification schemes achieved area under the receiver operating characteristic [Az] approximate to 0.82 for the whole dataset. There was no statistically significant difference in the performance of classifiers for the data sets with time between 2 and 8 hours from symptom onset. The performance of the classifiers did not depend on the size of the stroke regions. Conclusions: The results provide a set of optimal texture features which are suitable for distinguishing between hyperacute ischemic lesions and their corresponding contralateral brain tissue in noncontrast CT. This work is an initial step toward development of an automated decision support system for detection of hyperacute ischemic stroke lesions on noncontrast CT of the brain. (C) 2016 American Association of Physicists in Medicine
Název v anglickém jazyce
A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography
Popis výsledku anglicky
Purpose: Early identification of ischemic stroke plays a significant role in treatment and potential recovery of damaged brain tissue. In noncontrast CT (ncCT), the differences between ischemic changes and healthy tissue are usually very subtle during the hyperacute phase (< 8 h from the stroke onset). Therefore, visual comparison of both hemispheres is an important step in clinical assessment. A quantitative symmetry-based analysis of texture features of ischemic lesions in noncontrast CT images may provide an important information for differentiation of ischemic and healthy brain tissue in this phase. Methods: One hundred thirty-nine (139) ncCT scans of hyperacute ischemic stroke with follow-up magnetic resonance diffusion-weighted (MR-DW) images were collected. The regions of stroke were identified in the MR-DW images, which were spatially aligned to corresponding ncCT images. A state-of-the-art symmetric diffeomorphic image registration was utilized for the alignment of CT and MR-DW, for identification of individual brain hemispheres, and for localization of the region representing healthy tissue contralateral to the stroke cores. Texture analysis included extraction and classification of co-occurrence and run-length texture-based image features in the regions of ischemic stroke and their contralateral regions. Results: The classification schemes achieved area under the receiver operating characteristic [Az] approximate to 0.82 for the whole dataset. There was no statistically significant difference in the performance of classifiers for the data sets with time between 2 and 8 hours from symptom onset. The performance of the classifiers did not depend on the size of the stroke regions. Conclusions: The results provide a set of optimal texture features which are suitable for distinguishing between hyperacute ischemic lesions and their corresponding contralateral brain tissue in noncontrast CT. This work is an initial step toward development of an automated decision support system for detection of hyperacute ischemic stroke lesions on noncontrast CT of the brain. (C) 2016 American Association of Physicists in Medicine
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
30224 - Radiology, nuclear medicine and medical imaging
Návaznosti výsledku
Projekt
<a href="/cs/project/ED1.100%2F02%2F0123" target="_blank" >ED1.100/02/0123: Fakultní nemocnice u sv. Anny v Brně - Mezinárodní centrum klinického výzkumu (FNUSA - ICRC)</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Medical physics
ISSN
0094-2405
e-ISSN
—
Svazek periodika
44
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
8
Strana od-do
192-199
Kód UT WoS článku
000397038500019
EID výsledku v databázi Scopus
—