Evidence map›Paper›PMID 38803646›Full record

ArticleFrontiers in neurology2024

CT texture analysis of vertebrobasilar artery calcification to identify culprit plaques.

Bo Liu, Chen Xue, Haoyu Lu, Cuiyan Wang, Shaofeng Duan, Huan Yang

Abstract read
In one paragraph

Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Bo LiuQilu Hospital, Shandong University, Jinan, Shandong, China.
Chen XueSchool of Medical Imaging, Binzhou Medical University, Binzhou, Shandong, China.
Haoyu LuShandong Cancer Hospital and Institute, Shandong First Medical University, Tai'an, Shandong, China.
Cuiyan WangShandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Shaofeng DuanGE Healthcare, Shanghai, China.
Huan YangShandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The aim of this study was to extract radiomic features from vertebrobasilar artery calcification (VBAC) on head computed tomography (CT) images and investigate its diagnostic performance to identify culprit lesions responsible for acute cerebral infarctions. Methods: Patients with intracranial atherosclerotic disease who underwent vessel wall MRI (VW-MRI) and head CT examinations from a single center were retrospectively assessed for VBAC visual and textural analyses. Each calcified plaque was classified by the likelihood of having caused an acute cerebral infarction identified on VW-MRI as culprit or non-culprit. A predefined set of texture features extracted from VBAC segmentation was assessed using the minimum redundancy and maximum relevance method. Five key features were selected to integrate as a radiomic model using logistic regression by the Aikaike Information Criteria. The diagnostic value of the radiomic model was calculated for discriminating culprit lesions over VBAC visual assessments. Results: A total of 1,218 radiomic features were extracted from 39 culprit and 50 non-culprit plaques, respectively. In the VBAC visual assessment, culprit plaques demonstrated more observed presence of multiple calcifications, spotty calcification, and intimal predominant calcification than non-culprit lesions (all Conclusion: Culprit plaques in the vertebrobasilar artery exhibit distinct calcification radiomic features compared to non-culprit plaques. CT texture analysis of VBAC has potential value in identifying lesions responsible for acute cerebral infarctions, which may be helpful for stroke risk stratification in clinical practice.

Indexed as

calcificationcomputed tomographyplaqueradiomicstexture analysis

Identifiers

PMID38803646
PMCPMC11128659

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.