Cargando…

Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory

Recurrence is a significant adverse outcome of ischemic stroke (IS), particularly in cases of intracranial arteriosclerosis (ICAS). In this study, we investigated the impact of imaging features of culprit plaque using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) on the predicti...

Descripción completa

Detalles Bibliográficos
Autores principales: Quan, Guanmin, Wang, Xuelian, Liu, Yawu, Gao, Lijuan, Gao, Guodong, Tan, Guojun, Yuan, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458285/
https://www.ncbi.nlm.nih.gov/pubmed/37603950
http://dx.doi.org/10.1016/j.nicl.2023.103487
_version_ 1785097130708303872
author Quan, Guanmin
Wang, Xuelian
Liu, Yawu
Gao, Lijuan
Gao, Guodong
Tan, Guojun
Yuan, Tao
author_facet Quan, Guanmin
Wang, Xuelian
Liu, Yawu
Gao, Lijuan
Gao, Guodong
Tan, Guojun
Yuan, Tao
author_sort Quan, Guanmin
collection PubMed
description Recurrence is a significant adverse outcome of ischemic stroke (IS), particularly in cases of intracranial arteriosclerosis (ICAS). In this study, we investigated the impact of imaging features of culprit plaque using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) on the prediction of IS recurrence. A total of 86 patients diagnosed with ICAS-related IS within the middle cerebral artery (MCA) territory were included, of which 23.25% experienced recurrent IS within one year. Our findings revealed significant differences between the recurrence and non-recurrence groups in terms of age (p = 0.007), diabetes mellitus (p = 0.031), hyperhomocysteinemia (p = 0.021), artery-artery embolism (AAE) infarction (p = 0.019), prominent enhancement (p = 0.013), and surface irregularity of the culprit plaque (p = 0.009). Age (HR = 1.063, p = 0.005), AAE infarction (HR = 5.708, p = 0.008), and prominent enhancement of the culprit plaque (HR = 4.105, p = 0.025) were identified as independent risk factors for stroke recurrence. The areas under the receiver operating characteristic curve (AUCs) for predicting IS recurrence using clinical factors, conventional imaging findings, HR-MR-VWI plaque features, and a combination of clinical and conventional imaging models were 0.728, 0.645, 0.705, and 0.814, respectively. Notably, the combination model demonstrated superior predictive performance with an AUC of 0.870. Similarly, AUC of combination model for predicting IS recurrence in validation cohort which enrolled another 37 patients was 0.865. In conclusion, the presence of obvious enhancement in culprit plaque on HR-MR-VWI is a valuable factor in predicting IS recurrence in ICAS-related strokes within the MCA territory. Furthermore, our combination model, incorporating plaque features, exhibited improved prediction accuracy.
format Online
Article
Text
id pubmed-10458285
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-104582852023-08-27 Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory Quan, Guanmin Wang, Xuelian Liu, Yawu Gao, Lijuan Gao, Guodong Tan, Guojun Yuan, Tao Neuroimage Clin Regular Article Recurrence is a significant adverse outcome of ischemic stroke (IS), particularly in cases of intracranial arteriosclerosis (ICAS). In this study, we investigated the impact of imaging features of culprit plaque using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) on the prediction of IS recurrence. A total of 86 patients diagnosed with ICAS-related IS within the middle cerebral artery (MCA) territory were included, of which 23.25% experienced recurrent IS within one year. Our findings revealed significant differences between the recurrence and non-recurrence groups in terms of age (p = 0.007), diabetes mellitus (p = 0.031), hyperhomocysteinemia (p = 0.021), artery-artery embolism (AAE) infarction (p = 0.019), prominent enhancement (p = 0.013), and surface irregularity of the culprit plaque (p = 0.009). Age (HR = 1.063, p = 0.005), AAE infarction (HR = 5.708, p = 0.008), and prominent enhancement of the culprit plaque (HR = 4.105, p = 0.025) were identified as independent risk factors for stroke recurrence. The areas under the receiver operating characteristic curve (AUCs) for predicting IS recurrence using clinical factors, conventional imaging findings, HR-MR-VWI plaque features, and a combination of clinical and conventional imaging models were 0.728, 0.645, 0.705, and 0.814, respectively. Notably, the combination model demonstrated superior predictive performance with an AUC of 0.870. Similarly, AUC of combination model for predicting IS recurrence in validation cohort which enrolled another 37 patients was 0.865. In conclusion, the presence of obvious enhancement in culprit plaque on HR-MR-VWI is a valuable factor in predicting IS recurrence in ICAS-related strokes within the MCA territory. Furthermore, our combination model, incorporating plaque features, exhibited improved prediction accuracy. Elsevier 2023-08-07 /pmc/articles/PMC10458285/ /pubmed/37603950 http://dx.doi.org/10.1016/j.nicl.2023.103487 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Quan, Guanmin
Wang, Xuelian
Liu, Yawu
Gao, Lijuan
Gao, Guodong
Tan, Guojun
Yuan, Tao
Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title_full Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title_fullStr Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title_full_unstemmed Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title_short Refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
title_sort refined imaging features of culprit plaques improve the prediction of recurrence in intracranial atherosclerotic stroke within the middle cerebral artery territory
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458285/
https://www.ncbi.nlm.nih.gov/pubmed/37603950
http://dx.doi.org/10.1016/j.nicl.2023.103487
work_keys_str_mv AT quanguanmin refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT wangxuelian refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT liuyawu refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT gaolijuan refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT gaoguodong refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT tanguojun refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory
AT yuantao refinedimagingfeaturesofculpritplaquesimprovethepredictionofrecurrenceinintracranialatheroscleroticstrokewithinthemiddlecerebralarteryterritory