Clinical application of AI-based PET images in oncological patients
Clinical application of AI-based PET images in oncological patients
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DOI：
10.1016/j.semcancer.2023.03.005
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发表时间：
2023-03-20
影响因子：
14.5
通讯作者：
Tian, Rong
中科院分区：
文献类型：
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作者：
Dai, Jiaona;Wang, Hui;Tian, Rong
基于其揭示肿瘤细胞功能状态和分子表达的优势，正电子发射断层扫描（PET）已被应用于多种恶性疾病的诊断和监测。然而，图像质量不足，缺乏令人信服的评估工具以及人类工作中的观察者内部和观察者之间的差异是众所周知的核医学成像的局限性，并限制了其临床应用。人工智能（AI）由于其强大的信息收集和解释能力，在医学影像领域受到越来越多的关注。人工智能和PET成像的结合可能为医生管理患者提供巨大的帮助。放射组学是人工智能应用于医学成像的一个重要分支，它可以提取图像的数百个抽象数学特征进行进一步分析。本文综述了人工智能在PET成像中的应用，重点介绍了几种类型肿瘤的图像增强、肿瘤检测、反应和预后预测以及与病理或特定基因突变的相关性分析。我们的目的是描述最近基于人工智能的PET成像在恶性疾病中的临床应用，并重点描述可能的未来发展。
Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has been performed in numerous types of malignant diseases for diagnosis and monitoring. However, insufficient image quality, the lack of a convincing evaluation tool and intra-and interobserver variation in human work are well-known limitations of nuclear medicine imaging and restrict its clinical application. Artificial intelligence (AI) has gained increasing interest in the field of medical imaging due to its powerful information collection and interpretation ability. The combination of AI and PET imaging potentially provides great assistance to physicians managing patients. Radiomics, an important branch of AI applied in medical imaging, can extract hundreds of abstract mathematical features of images for further analysis. In this review, an overview of the applications of AI in PET imaging is provided, focusing on image enhancement, tumor detection, response and prognosis prediction and correlation analyses with pathology or specific gene mutations in several types of tumors. Our aim is to describe recent clinical applications of AI-based PET imaging in malignant diseases and to focus on the description of possible future developments.