The evolution of Positron Emission Tomography (PET), culminating in the Total-Body PET (TB-PET) system, represents a paradigm shift in medical imaging. This paper explores the transformative role of Artificial Intelligence (AI) in enhancing clinical and research applications of TB-PET imaging. Clinically, TB-PET’s superior sensitivity facilitates rapid imaging, low-dose imaging protocols, improved diagnostic capabilities and higher patient comfort. In research, TB-PET shows promise in studying systemic interactions and enhancing our understanding of human physiology and pathophysiology. In parallel, AI’s integration into PET imaging workflows—spanning from image acquisition to data analysis—marks a significant development in nuclear medicine. This review delves into the current and potential roles of AI in augmenting TB-PET/CT’s functionality and utility. We explore how AI can streamline current PET imaging processes and pioneer new applications, thereby maximising the technology’s capabilities. The discussion also addresses necessary steps and considerations for effectively integrating AI into TB-PET/CT research and clinical practice. The paper highlights AI’s role in enhancing TB-PET’s efficiency and addresses the challenges posed by TB-PET’s increased complexity. In conclusion, this exploration emphasises the need for a collaborative approach in the field of medical imaging. We advocate for shared resources and open-source initiatives as crucial steps towards harnessing the full potential of the AI/TB-PET synergy. This collaborative effort is essential for revolutionising medical imaging, ultimately leading to significant advancements in patient care and medical research.

中文翻译：

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从全身 PET/CT 图像数据中提取价值 - 人工智能的新兴作用

正电子发射断层扫描 (PET) 的发展最终形成了全身 PET (TB-PET) 系统，代表了医学成像的范式转变。本文探讨了人工智能 (AI) 在增强 TB-PET 成像的临床和研究应用方面的变革性作用。在临床上，TB-PET 卓越的灵敏度有利于快速成像、低剂量成像方案、改进的诊断能力和更高的患者舒适度。在研究中，TB-PET 在研究系统相互作用和增强我们对人类生理学和病理生理学的理解方面显示出前景。与此同时，人工智能与 PET 成像工作流程的集成（从图像采集到数据分析）标志着核医学的重大发展。本综述深入探讨了人工智能在增强 TB-PET/CT 功能和实用性方面当前和潜在的作用。我们探索人工智能如何简化当前 PET 成像流程并开拓新应用，从而最大限度地发挥技术的能力。讨论还讨论了将人工智能有效整合到 TB-PET/CT 研究和临床实践中的必要步骤和注意事项。该论文强调了人工智能在提高 TB-PET 效率方面的作用，并解决了 TB-PET 复杂性增加带来的挑战。总之，这一探索强调了医学成像领域采取协作方法的必要性。我们主张共享资源和开源计划，作为充分发挥 AI/TB-PET 协同作用潜力的关键步骤。这种协作努力对于彻底改变医学成像至关重要，最终导致患者护理和医学研究的重大进步。