Automated neuroradiological support systems for multiple cerebrovascular disease markers — A systematic review and meta-analysis

IF 4.9 2区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer methods and programs in biomedicine Pub Date : 2025-03-15 DOI:10.1016/j.cmpb.2025.108715
Jesse Phitidis , Alison Q. O’Neil , William N. Whiteley , Beatrice Alex , Joanna M. Wardlaw , Miguel O. Bernabeu , Maria Valdés Hernández
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Abstract

Cerebrovascular diseases (CVD) can lead to stroke and dementia. Stroke is the second leading cause of death world wide and dementia incidence is increasing by the year. There are several markers of CVD that are visible on brain imaging, including: white matter hyperintensities (WMH), acute and chronic ischaemic stroke lesions (ISL), lacunes, enlarged perivascular spaces (PVS), acute and chronic haemorrhagic lesions, and cerebral microbleeds (CMB). Brain atrophy also occurs in CVD. These markers are important for patient management and intervention, since they indicate elevated risk of future stroke and dementia. We systematically reviewed automated systems designed to support radiologists reporting on these CVD imaging findings. We considered commercially available software and research publications which identify at least two CVD markers. In total, we included 29 commercial products and 13 research publications. Two distinct types of commercial support system were available: those which identify acute stroke lesions (haemorrhagic and ischaemic) from computed tomography (CT) scans, mainly for the purpose of patient triage; and those which measure WMH and atrophy regionally and longitudinally. In research, WMH and ISL were the markers most frequently analysed together, from magnetic resonance imaging (MRI) scans; lacunes and PVS were each targeted only twice and CMB only once. For stroke, commercially available systems largely support the emergency setting, whilst research systems consider also follow-up and routine scans. The systems to quantify WMH and atrophy are focused on neurodegenerative disease support, where these CVD markers are also of significance. There are currently no openly validated systems, commercially, or in research, performing a comprehensive joint analysis of all CVD markers (WMH, ISL, lacunes, PVS, haemorrhagic lesions, CMB, and atrophy).
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脑血管疾病(CVD)可导致中风和痴呆。中风是全球第二大死因,痴呆症的发病率也在逐年上升。脑成像可显示多种心血管疾病的标志物,包括:白质高密度(WMH)、急性和慢性缺血性卒中病变(ISL)、裂隙、扩大的血管周围间隙(PVS)、急性和慢性出血性病变以及脑微小出血(CMB)。心血管疾病也会导致脑萎缩。这些标志物对患者管理和干预非常重要,因为它们预示着未来中风和痴呆风险的升高。我们系统回顾了旨在支持放射医师报告这些心血管疾病成像结果的自动化系统。我们考虑了市场上可买到的软件和研究出版物,这些软件至少能识别两种心血管疾病标志物。我们总共收录了 29 种商业产品和 13 篇研究出版物。有两种不同类型的商业支持系统:一种是从计算机断层扫描(CT)中识别急性卒中病变(出血性和缺血性),主要用于患者分流;另一种是从区域和纵向测量 WMH 和萎缩。在研究中,WMH 和 ISL 是磁共振成像(MRI)扫描中最常同时分析的标记物;裂隙和 PVS 只分别针对两次,CMB 只针对一次。对于脑卒中,市售系统主要支持急诊环境,而研究系统还考虑随访和常规扫描。量化 WMH 和萎缩的系统主要用于支持神经退行性疾病,这些心血管疾病标记物在神经退行性疾病中也很重要。目前还没有经过公开验证的商业或研究系统能对所有 CVD 标记(WMH、ISL、裂隙、PVS、出血性病变、CMB 和萎缩)进行全面的联合分析。
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来源期刊
Computer methods and programs in biomedicine
Computer methods and programs in biomedicine 工程技术-工程:生物医学
CiteScore
12.30
自引率
6.60%
发文量
601
审稿时长
135 days
期刊介绍: To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine. Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.
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