Quantitative Histogram Analysis on Intracranial Atherosclerotic Plaques: A High-Resolution Magnetic Resonance Imaging Study.


Journal

Stroke
ISSN: 1524-4628
Titre abrégé: Stroke
Pays: United States
ID NLM: 0235266

Informations de publication

Date de publication:
07 2020
Historique:
entrez: 23 6 2020
pubmed: 23 6 2020
medline: 5 11 2020
Statut: ppublish

Résumé

Intracranial atherosclerosis is one of the main causes of stroke, and high-resolution magnetic resonance imaging provides useful imaging biomarkers related to the risk of ischemic events. This study aims to evaluate differences in histogram features between culprit and nonculprit intracranial atherosclerosis using high-resolution magnetic resonance imaging. Two hundred forty-seven patients with intracranial atherosclerosis who underwent high-resolution magnetic resonance imaging sequentially between January 2015 and December 2016 were recruited. Quantitative features, including stenosis, plaque burden, minimum luminal area, intraplaque hemorrhage, enhancement ratio, and dispersion of signal intensity (coefficient of variation), were analyzed based on T2-, T1-, and contrast-enhanced T1-weighted images. Step-wise regression analysis was used to identify key determinates differentiating culprit and nonculprit plaques and to calculate the odds ratios (ORs) with 95% CIs. In total, 190 plaques were identified, of which 88 plaques (37 culprit and 51 nonculprit) were located in the middle cerebral artery and 102 (57 culprit and 45 nonculprit) in the basilar artery. Nearly 90% of culprit lesions had a degree of luminal stenosis of <70%. Multiple logistic regression analyses showed that intraplaque hemorrhage (OR, 16.294 [95% CI, 1.043-254.632]; Features characterized by high-resolution magnetic resonance imaging provided complementary values over luminal stenosis in defined lesion type for intracranial atherosclerosis; the dispersion of signal intensity in histogram analysis was a particularly effective predictive parameter.

Sections du résumé

BACKGROUND AND PURPOSE
Intracranial atherosclerosis is one of the main causes of stroke, and high-resolution magnetic resonance imaging provides useful imaging biomarkers related to the risk of ischemic events. This study aims to evaluate differences in histogram features between culprit and nonculprit intracranial atherosclerosis using high-resolution magnetic resonance imaging.
METHODS
Two hundred forty-seven patients with intracranial atherosclerosis who underwent high-resolution magnetic resonance imaging sequentially between January 2015 and December 2016 were recruited. Quantitative features, including stenosis, plaque burden, minimum luminal area, intraplaque hemorrhage, enhancement ratio, and dispersion of signal intensity (coefficient of variation), were analyzed based on T2-, T1-, and contrast-enhanced T1-weighted images. Step-wise regression analysis was used to identify key determinates differentiating culprit and nonculprit plaques and to calculate the odds ratios (ORs) with 95% CIs.
RESULTS
In total, 190 plaques were identified, of which 88 plaques (37 culprit and 51 nonculprit) were located in the middle cerebral artery and 102 (57 culprit and 45 nonculprit) in the basilar artery. Nearly 90% of culprit lesions had a degree of luminal stenosis of <70%. Multiple logistic regression analyses showed that intraplaque hemorrhage (OR, 16.294 [95% CI, 1.043-254.632];
CONCLUSIONS
Features characterized by high-resolution magnetic resonance imaging provided complementary values over luminal stenosis in defined lesion type for intracranial atherosclerosis; the dispersion of signal intensity in histogram analysis was a particularly effective predictive parameter.

Identifiants

pubmed: 32568660
doi: 10.1161/STROKEAHA.120.029062
pmc: PMC7306260
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2161-2169

Subventions

Organisme : British Heart Foundation
ID : CH/2000003/12800
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/15/26/31441
Pays : United Kingdom

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Auteurs

Zhang Shi (Z)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.
Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.).

Jing Li (J)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.

Ming Zhao (M)

Department of Neurology (M.Z.), Changhai Hospital, Naval Medical University, Shanghai, China.

Wenjia Peng (W)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.

Zakaria Meddings (Z)

Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.).

Tao Jiang (T)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.

Qi Liu (Q)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.

Zhongzhao Teng (Z)

Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.).
Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, China (Z.T.).

Jianping Lu (J)

Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China.

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