Short-duration dynamic FDG PET imaging: Optimization and clinical application

Abstract

We aimed to investigate whether short dynamic PET imaging started at injection, complemented with routine clinical acquisition at 60-min post-injection (static), can achieve reliable kinetic analysis. Methods: Dynamic and static 18F-2-fluoro-2-deoxy-D-glucose (FDG) PET data were generated using realistic simulations to assess uncertainties due to statistical noise as well as bias. Following image reconstructions, kinetic parameters obtained from a 2-tissue-compartmental model (2TCM) were estimated, making use of the static image, and the time duration of dynamic PET data were incrementally shortened. We also investigated, in the first 2-min, different frame sampling rates, towards optimized dynamic PET imaging. Kinetic parameters from shortened dynamic datasets were additionally estimated for 9 patients (15 scans) with liver metastases of colorectal cancer, and were compared with those derived from full dynamic imaging using correlation and Passing-Bablok regression analyses. Results: The results showed that by reduction of dynamic scan times from 60-min to as short as 5-min, while using static data at 60-min post-injection, bias and variability stayed comparable in estimated kinetic parameters. Early frame samplings of 5, 24 and 30 s yielded highest biases compared to other schemes. An early frame sampling of 10 s generally kept both bias and variability to a minimum. In clinical studies, strong correlation (r ≥ 0.97, P < 0.0001) existed between all kinetic parameters in full vs. shortened scan protocols. Conclusions: Shortened 5-min dynamic scan, sampled as 12 × 10 + 6 × 30 s, followed by 3-min static image at 60min post-injection, enables accurate and robust estimation of 2TCM parameters, while enabling generation of SUV estimates.

Fast dynamic brain PET imaging using stochastic variational prediction for recurrent frame generation

“…Samimi et al reported ~10% bias for kinetic parameters estimation when decreasing the dynamic scanning time to 5 minutes supplemented by a whole body PET scan 60 minutes postinjection. 30 A similar trend was also reported in two other studies where the bias in K i estimates was ~5% 28 and 9% 27 when decreasing dynamic scanning time from 60 to 40 minutes and from 60 to 30 minutes respectively.…”

“…The quantitative evaluation of predicted images showed less than 7% bias for , and less than 14% bias for in most brain regions. Samimi et al reported ~10% bias for kinetic parameters estimation when decreasing the dynamic scanning time to 5 min supplemented by a whole body PET scan 60 min post-injection 30 . A…”

“…More recently, Samimi et al . showed that a fast 5 minutes dynamic scan, accompanied with a 3 minutes static scan acquired 60 minutes post‐injection enables to estimate accurately standardized uptake value (SUV) and 2‐tissue‐compartmental model parameters 30 . To the best of our knowledge, there is a lack of works using deep learning to decrease the acquisition time in dynamic PET imaging or to generate late dynamic frames from initial ones.…”

“…29 More recently, Samimi et al showed that a fast 5 minutes dynamic scan, accompanied with a 3 minutes static scan acquired 60 minutes post-injection enables to estimate accurately standardized uptake value (SUV) and 2-tissue-compartmental model parameters. 30 To the best of our knowledge, there is a lack of works using deep learning to decrease the acquisition time in dynamic PET imaging or to generate late dynamic frames from initial ones. In this work, we used a novel recurrent frame generation model, referred to as Stochastic Adversarial Video Prediction (SAVP), to reduce the acquisition time by estimating half of the late frames of dynamic 18 F-DOPA PET images from its first half frames.…”

Is Dynamic Total-body PET Imaging Feasible in the Clinical Daily Practice?

“…Although the dPET acquisition time might be reduced by a factor of 2, in the routine clinical diagnosis SUV derived from static PET imaging is still of importance. Samimi et al [32] suggested a short dPET coupled with static PET acquisition as an alternative approach. However, its feasibility in total-body dPET imaging was unknown.…”