Advancing Positron Emission Tomography Image Quantification: Artificial Intelligence-Driven Methods, Clinical Challenges, and Emerging Opportunities in Long-Axial Field-of-View Positron Emission Tomography/Computed Tomography Imaging.

Positron emission tomography/computed tomography (PET/CT) imaging plays a pivotal role in oncology, aiding tumor metabolism assessment, disease staging, and therapy response evaluation. Traditionally, semi-quantitative metrics such as SUVmax have been extensively used, though these methods face limitations in reproducibility and predictive capability. Recent advancements in artificial intelligence (AI), particularly deep learning, have revolutionized PET imaging, significantly enhancing image quantification accuracy, and biomarker extraction capabilities, thereby enabling more precise clinical decision-making.