Abstract：
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.
摘要：
基于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）成像已在许多类型的恶性疾病中进行诊断和监测。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观察者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，在医学成像领域引起了越来越多的兴趣。AI和PET成像的结合可能为管理患者的医生提供很大的帮助。Radiomics,人工智能在医学成像中的一个重要分支，可以提取图像的数百个抽象数学特征进行进一步分析。在这次审查中,概述了人工智能在PET成像中的应用，专注于图像增强，肿瘤检测，在几种类型的肿瘤中，响应和预后预测以及与病理或特定基因突变的相关性分析。我们的目的是描述基于AI的PET成像在恶性疾病中的最新临床应用，并着重于描述未来可能的发展。
