血栓成像对急性缺血性脑卒中的预测价值:人工智能和常规研究的系统综述

Daniela Dumitriu LaGrange , Jeremy Hofmeister , Andrea Rosi , Maria Isabel Vargas , Isabel Wanke , Paolo Machi , Karl-Olof Lövblad
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引用次数: 0

摘要

急性缺血性脑卒中血栓的神经影像学征象与血栓生物学及其对治疗的反应有关。血块成像的诊断和预测价值已被传统研究证实,并成为人工智能(AI)发展的一个感兴趣的话题。我们进行了一项系统综述,以评估人工智能在血块成像中的最新技术,人工智能离临床有益还有多远,以及进一步发展需要考虑的角度。与此同时,该审查正在审查2019年至2022年8月期间关于血栓成像相关性的传统研究带来的证据。血块的自动检测和分割是人工智能在临床应用中最重要的进展。预测放射组学模型需要进一步探索和方法优化。未来的人工智能方法可以考虑传统的血块成像特征和患者特定的血管特征作为模型开发的变量。
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Predictive value of clot imaging in acute ischemic stroke: A systematic review of artificial intelligence and conventional studies

The neuroimaging signs of the clot in acute ischemic stroke are relevant for clot biology and its response to treatment. The diagnostic and predictive value of clot imaging is confirmed by conventional studies and emerges as a topic of interest for artificial intelligence (AI) developments. We performed a systematic review to evaluate the state of the art of AI in clot imaging, how far AI is from becoming clinically beneficial, and what are the perspectives to consider for further developments. In parallel, the review is examining the evidence brought by conventional studies concerning the relevance of clot imaging, from 2019 to August 2022. The automatic detection and segmentation of the clot are the most important advances towards AI implementation in the clinic. Predictive radiomics models require further exploration and methods optimization. Future AI approaches could consider conventional clot imaging characteristics and patient specific vascular features as variables for model development.

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来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
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57 days
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