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用于阿尔茨海默病诊断与监测的放射组学和人工智能:该领域研究的系统综述

Radiomics and Artificial Intelligence for the Diagnosis and Monitoring of Alzheimer's Disease: A Systematic Review of Studies in the Field.

作者信息

Bevilacqua Roberta, Barbarossa Federico, Fantechi Lorenzo, Fornarelli Daniela, Paci Enrico, Bolognini Silvia, Giammarchi Cinzia, Lattanzio Fabrizia, Paciaroni Lucia, Riccardi Giovanni Renato, Pelliccioni Giuseppe, Biscetti Leonardo, Maranesi Elvira

机构信息

Scientific Direction, IRCCS INRCA, 60124 Ancona, Italy.

Unit of Nuclear Medicine, IRCCS INRCA, 60127 Ancona, Italy.

出版信息

J Clin Med. 2023 Aug 21;12(16):5432. doi: 10.3390/jcm12165432.

Abstract

The use of radiomics and artificial intelligence applied for the diagnosis and monitoring of Alzheimer's disease has developed in recent years. However, this approach is not yet completely applicable in clinical practice. The aim of this paper is to provide a systematic analysis of the studies that have included the use of radiomics from different imaging techniques and artificial intelligence for the diagnosis and monitoring of Alzheimer's disease in order to improve the clinical outcomes and quality of life of older patients. A systematic review of the literature was conducted in February 2023, analyzing manuscripts and articles of the last 5 years from the PubMed, Scopus and Embase databases. All studies concerning discrimination among Alzheimer's disease, Mild Cognitive Impairment and healthy older people performing radiomics analysis through machine and deep learning were included. A total of 15 papers were included. The results showed a very good performance of this approach in the differentiating Alzheimer's disease patients-both at the dementia and pre-dementia phases of the disease-from healthy older people. In summary, radiomics and AI can be valuable tools for diagnosing and monitoring the progression of Alzheimer's disease, potentially leading to earlier and more accurate diagnosis and treatment. However, the results reported by this review should be read with great caution, keeping in mind that imaging alone is not enough to identify dementia due to Alzheimer's.

摘要

近年来,将放射组学和人工智能应用于阿尔茨海默病的诊断和监测有了一定发展。然而,这种方法尚未完全适用于临床实践。本文旨在对那些将来自不同成像技术的放射组学和人工智能用于阿尔茨海默病诊断和监测的研究进行系统分析,以改善老年患者的临床结局和生活质量。2023年2月进行了一项文献系统综述,分析了来自PubMed、Scopus和Embase数据库的过去5年的手稿和文章。纳入了所有通过机器学习和深度学习进行放射组学分析以区分阿尔茨海默病、轻度认知障碍和健康老年人的研究。共纳入15篇论文。结果表明,这种方法在区分阿尔茨海默病患者(包括疾病的痴呆阶段和痴呆前期阶段)与健康老年人方面表现非常出色。总之,放射组学和人工智能可能是诊断和监测阿尔茨海默病进展的有价值工具,有可能实现更早、更准确的诊断和治疗。然而,应非常谨慎地看待本综述报告的结果,要记住仅靠影像学不足以确诊阿尔茨海默病所致痴呆。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0b4/10455452/34effa1990e8/jcm-12-05432-g001.jpg

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