Skip to main content
Top
Published in: BMC Neurology 1/2022

Open Access 01-12-2022 | Magnetic Resonance Imaging | Research

The robust UCATR algorithm enhances the specificity and sensitivity to detect the infarct of acute ischaemic stroke within 6 hours of onset via non-contrast computed tomography images

Authors: Jianping Yu, Zhi Zhang, Qingping Xue, Tao He, Chun Luo, Kaimin Zhuo, Qian Yang, Tianzhu Xu, Jing Zhang, Fan Xu

Published in: BMC Neurology | Issue 1/2022

Login to get access

Abstract

Problem background

Early detection of acute ischemic stroke (AIS) may provide patients with benefits against harmful health and financial impacts. The use of non-contrast computed tomography images for early detect of the infarct remains controversial.

Materials & methods

Here, we used the UCATR algorithm to extract the pixel values of the infarct and the corresponding contralateral healthy area as the control surface in each NCCT slice for the whole brain. Magnetic resonance imaging results were used to verify both areas. We found significant pathological changes in the infarct compared with the corresponding contralateral healthy area in each NCCT slice.

Attained results

Our approach validated that NCCT can be used to detect the lesion area in the early stage of AIS.

Conclusions

With obvious advantages such as saving time and the ability to quantify the infarct volume, this approach could help more patients survive the fatal and irreversible pathological process of AIS and improve their quality of life after AIS treatment.
Appendix
Available only for authorised users
Literature
1.
go back to reference GBD 2016 Stroke Collaborators. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 2019;18:439–58.CrossRef GBD 2016 Stroke Collaborators. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 2019;18:439–58.CrossRef
2.
go back to reference Johnson CO, Nguyen M, Roth GA, Nichols E, Alam T, Abate D, et al. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 2019;18:439–58.CrossRef Johnson CO, Nguyen M, Roth GA, Nichols E, Alam T, Abate D, et al. Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 2019;18:439–58.CrossRef
3.
go back to reference Desai SM, Rocha M, Jovin TG, Jadhav AP. High variability in neuronal loss. Stroke. 2019;50:34–7.CrossRef Desai SM, Rocha M, Jovin TG, Jadhav AP. High variability in neuronal loss. Stroke. 2019;50:34–7.CrossRef
4.
go back to reference Vilela P, Rowley HA. Brain ischemia: CT and MRI techniques in acute ischemic stroke. Eur J Radiol. 2017;96:162–72.CrossRef Vilela P, Rowley HA. Brain ischemia: CT and MRI techniques in acute ischemic stroke. Eur J Radiol. 2017;96:162–72.CrossRef
5.
go back to reference El-Koussy M, Schroth G, Brekenfeld C, Arnold M. Imaging of acute ischemic stroke. Eur Neurol. 2014;72:309–16.CrossRef El-Koussy M, Schroth G, Brekenfeld C, Arnold M. Imaging of acute ischemic stroke. Eur Neurol. 2014;72:309–16.CrossRef
6.
go back to reference Qiu W, Kuang H, Teleg E, Ospel JM, Sohn SI, Almekhlafi M, et al. Machine learning for detecting early infarction in acute stroke with non-contrast-enhanced CT. Radiology. 2020;294:638–44.CrossRef Qiu W, Kuang H, Teleg E, Ospel JM, Sohn SI, Almekhlafi M, et al. Machine learning for detecting early infarction in acute stroke with non-contrast-enhanced CT. Radiology. 2020;294:638–44.CrossRef
7.
go back to reference Khan R, Nael K, Erly W. Acute stroke imaging: what clinicians need to know. Am J Med. 2013;126:379–86.CrossRef Khan R, Nael K, Erly W. Acute stroke imaging: what clinicians need to know. Am J Med. 2013;126:379–86.CrossRef
8.
go back to reference Nowinski WL, Gupta V, Qian G, He J, Poh LE, Ambrosius W, et al. Automatic detection, localization, and volume estimation of ischemic infarcts in noncontrast computed tomographic scans: method and preliminary results. Invest Radiol. 2013;48:661–70.CrossRef Nowinski WL, Gupta V, Qian G, He J, Poh LE, Ambrosius W, et al. Automatic detection, localization, and volume estimation of ischemic infarcts in noncontrast computed tomographic scans: method and preliminary results. Invest Radiol. 2013;48:661–70.CrossRef
9.
go back to reference Gomolka RS, Chrzan RM, Urbanik A, Nowinski WL. A quantitative method using head noncontrast CT scans to detect hyperacute nonvisible ischemic changes in patients with stroke. J Neuroimaging. 2016;26:581–7.CrossRef Gomolka RS, Chrzan RM, Urbanik A, Nowinski WL. A quantitative method using head noncontrast CT scans to detect hyperacute nonvisible ischemic changes in patients with stroke. J Neuroimaging. 2016;26:581–7.CrossRef
10.
go back to reference Peter R, Korfiatis P, Blezek D, Oscar Beitia A, Stepan-Buksakowska I, Horinek D, et al. A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography. Med Phys. 2017;44:192–9.CrossRef Peter R, Korfiatis P, Blezek D, Oscar Beitia A, Stepan-Buksakowska I, Horinek D, et al. A quantitative symmetry-based analysis of hyperacute ischemic stroke lesions in noncontrast computed tomography. Med Phys. 2017;44:192–9.CrossRef
11.
go back to reference Kuang H, Menon BK, Qiu W. Semi-automated infarct segmentation from follow-up noncontrast CT scans in patients with acute ischemic stroke. Med Phys. 2019;46:4037–45.CrossRef Kuang H, Menon BK, Qiu W. Semi-automated infarct segmentation from follow-up noncontrast CT scans in patients with acute ischemic stroke. Med Phys. 2019;46:4037–45.CrossRef
12.
go back to reference von Kummer R, Bourquain H, Bastianello S, Bozzao L, Manelfe C, Meier D, et al. Early prediction of irreversible brain damage after ischemic stroke at CT. Radiology. 2001;219:95–100.CrossRef von Kummer R, Bourquain H, Bastianello S, Bozzao L, Manelfe C, Meier D, et al. Early prediction of irreversible brain damage after ischemic stroke at CT. Radiology. 2001;219:95–100.CrossRef
Metadata
Title
The robust UCATR algorithm enhances the specificity and sensitivity to detect the infarct of acute ischaemic stroke within 6 hours of onset via non-contrast computed tomography images
Authors
Jianping Yu
Zhi Zhang
Qingping Xue
Tao He
Chun Luo
Kaimin Zhuo
Qian Yang
Tianzhu Xu
Jing Zhang
Fan Xu
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2022
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-022-02825-9

Other articles of this Issue 1/2022

BMC Neurology 1/2022 Go to the issue