Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

Abstract

Background Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades. Challenges The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results. Conclusions In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Molecular imaging for evaluation of synovitis associated with osteoarthritis: a narrative review

“…Recent advancements in imaging technology have led to the development of next-generation total-body PET scanners. These scanners offer significant improvements, including reduced dosage, faster acquisition times, and the ability for quantitative measurement of tracer uptake through dynamic image acquisition and kinetic modeling [ 116 ]. These advancements hold promise for the effective utilization of molecular imaging in OA.…”

Current progress and future perspectives in total‐body positron emission tomography/computed tomography. Part II: Clinical applications

“…Owing to its high sensitivity, resolution, and complete coverage of all organs, TB-PET not only produces superior images [2][3][4] with reduced radiation doses [7,14,16,17,20,54] and scan times [5,6,8,9] but also enables the transformation of PET from traditional single-parameter imaging to multi-parameter imaging [39,42,[47][48][49][50]52]. Previously impossible, TB-PET enables the determination of radiotracer kinetics and distribution across multiple organs, which facilitates the elucidation of interrelationships among physiological/pathological factors influencing the distribution of specific radiotracers between organs [1,11,26,41,55]. This greatly expands the research and application scope of molecular imaging.…”

“…However, the statistical noise of SAFOV PET is typically too high for the successful derivation of multiple individual kinetic parameters. This inherent limitation of SAFOV PET can be effectively mitigated by applying TB-PET [40][41][42][43][44]. This is attributed to the high sensitivity and low background noise of TB-PET.…”

Mapping18F-FDG Kinetics Together with Patient-Specific Bootstrap Assessment of Uncertainties: An Illustration with Data from a PET/CT Scanner with a Long Axial Field of View

“…The current focus has been on dynamic PET studies with 18 F-FDG using the well-established Huang–Sokoloff 2-compartment (2C) modeling framework ( 1 – 3 ). Although 2C modeling has had widespread application in PET imaging, far beyond the brain setting in which it was developed, the biochemical understanding of the transporters involved in the metabolism of 18 F-FDG and their distribution across normal and cancerous tissues has evolved in the years since the Huang–Sokoloff construct was proposed ( 4 – 7 ). The temporal and spatial resolutions of emerging scanners have transformed the ability to objectively assess the accuracy of the 2C framework to represent 18 F-FDG time-course data across the diverse tissues encountered in the human body.…”