Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Abstract

Purpose Efforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body 18F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup. Methods The research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate Ki. Results Ki and K1 derived from the DTW protocol showed overall good consistency (P < 0.01) with the reference from the 60-min dynamic scan with 10-min early scan and 5-min late scan (Ki correlation: 0.971, 0.990, and 0.990; K1 correlation: 0.820, 0.940, and 0.975 in the cerebral cortex, muscle, and tumor lesion, respectively). Similar correlationss were found for other micro-parameters. The DTW protocol had the lowest bias relative to standard Ki than any of the quantification methods, followed by FUR and Patlak. SUV had the weakest correlation with Ki. The whole-body Ki and K1 images generated by the DTW protocol were consistent with the reference parametric images. Conclusions Using the DTW protocol, the dynamic total-body FDG scan time can be reduced to 15 min while obtaining accurate Ki and K1 quantification and acceptable visual performance in parametric images. However, the trade-off between quantification accuracy and protocol implementation feasibility must be considered in practice. We recommend that the DTW protocol be used when the clinical task requires reliable visual assessment or quantifying multiple micro-parameters; FUR with a hybrid input function may be a more feasible approach to quantifying regional metabolic rate with a known lesion position or organs of interest.

Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis

“…Advanced algorithms have also been written to reduce the long dynamic scan time without sacrificing acquired information. Wang et al [30] explored the feasibility of a dual-time-window protocol for 18 F-FDG imaging on an uEXPLORER scanner. The protocol involved a 10-min duration scan immediately postinjection followed by a 5-min scan at 1 h post-injection, and showed good consistency with the reference quantification, minimal bias, and consistent parametric images.…”

The role of dynamic, static, and delayed total-body PET imaging in the detection and differential diagnosis of oncological lesions

“…To the best of our knowledge, this study is the first one to conduct a head-to-head comparison of FDG dynamic and delayed imaging for oncologic applications. Total-body scanner was known to have ultra-high sensitivity that can provide better image quality than conventional PET/CT scanner [ 24 , 29 , 32 , 33 ]. In addition, dynamic PET imaging was previously restricted to single-bed positions and time-consuming invasive blood sampling.…”

“…K i image was transformed to an MRFDG image (µmoL/g/min) by multiplying the blood glucose levels measured before the scan. IDIF was extracted from the ascending aorta by drawing a 10-mm-diameter region-of-interest (ROI) on six consecutive slices in an image obtained by summing early frames (0–60 s [ 29 ]). The delay (arrival time) between the body tissue and the aorta was computed using the leading-edge method [ 30 ].…”

Forecasting the Pharmacokinetics With Limited Early Frames in Dynamic Brain PET Imaging Using Neural Ordinary Differential Equation

“…The recent efforts were made to reduce the scanning time while allowing the parametric images to be drawn [17,19,20,[35][36][37][38]. As the proposed model predicts the entire frames of the dynamic PET given a few early frames alone, it provides the solution to reduce the scanning time while deriving the pharmacokinetics of interest in brain studies such as perfusion or binding perfusion.…”