Total-Body Dynamic Reconstruction and Parametric Imaging on the uEXPLORER

Abstract

The world's first 194-cm-long total-body PET/CT scanner (uEXPLORER) has been built by the EXPLORER Consortium to offer a transformative platform for human molecular imaging in clinical research and health care. Its total-body coverage and ultra-high sensitivity provide opportunities for more accurate tracer kinetic analysis in studies of physiology, biochemistry, and pharmacology. The objective of this study was to demonstrate the capability of total-body parametric imaging and to quantify the improvement in image quality and kinetic parameter estimation by direct and kernel reconstruction of the uEXPLORER data. Methods: We developed quantitative parametric image reconstruction methods for kinetic analysis and used them to analyze the first human dynamic total-body PET study. A healthy female subject was recruited, and a 1-h dynamic scan was acquired during and after an intravenous injection of 256 MBq of 18F-FDG. Dynamic data were reconstructed using a 3-dimensional time-of-flight list-mode ordered-subsets expectation maximization (OSEM) algorithm and a kernel-based algorithm with all quantitative corrections implemented in the forward model. The Patlak graphical model was used to analyze the 18F-FDG kinetics in the whole body. The input function was extracted from a region over the descending aorta. For comparison, indirect Patlak analysis from reconstructed frames and direct reconstruction of parametric images from the list-mode data were obtained for the last 30 min of data. Results: Images reconstructed by OSEM showed good quality with low noise, even for the 1-s frames. The image quality was further improved using the kernel method. Total-body Patlak parametric images were obtained using either indirect estimation or direct reconstruction. The direct reconstruction method improved the parametric image quality, having a better contrast-versus-noise tradeoff than the indirect method, with a 2- to 3-fold variance reduction. The kernel-based indirect Patlak method offered image quality similar to the direct Patlak method, with less computation time and faster convergence. Conclusion: This study demonstrated the capability of total-body parametric imaging using the uEXPLORER. Furthermore, the results showed the benefits of kernel-regularized reconstruction and direct parametric reconstruction. Both can achieve superior image quality for tracer kinetic studies compared with the conventional indirect OSEM for total-body imaging.

Keywords: PET; direct reconstruction; kernel method; total-body parametric imaging; tracer kinetics.

© 2020 by the Society of Nuclear Medicine and Molecular Imaging.

Figures

FIGURE 1.

(A) Count rate and random fraction of 1-h 18F-FDG dynamic scan of human subject. (B) Maximum-intensity projection of selected dynamic OSEM reconstructed images (1-s and 120-s frames). SUV images are shown in inverse gray scale with maximum set to 100 and 10. RF = random fraction.

FIGURE 2.

OSEM image–derived ROI-based blood input functions and time–activity curves (TACs). (Left) AIFs from different ROIs during first 2 min. (Middle) AIFs during whole 1-h scan zoomed in on 0–12 kBq/mL scale. (Right) Time–activity curves of major organs/tissues of interest.

FIGURE 3.

Reconstructed dynamic composite SUV images (OSEM maximum-intensity projections) of early 10-min, mid 20-min, late 30-min scans. Images were used to extract features to construct kernel matrix. SUV images are shown in inverse gray scale with maximum set to 9.

FIGURE 4.

Coronal, sagittal, and transaxial slices of OSEM and kernel-EM (KEM) reconstructions of early 1-s frame (25–26 s) and 2-s frame (60–62 s).

FIGURE 5.

(A) Coronal, sagittal, and transaxial slices of Patlak slope Ki reconstructed by indirect OSEM, indirect kernel-EM (KEM), and direct OSEM. (B) Ki contrast of gray matter to white matter vs. noise curves. SD was calculated in large ROI inside white matter. (C) Ki contrast of focal uptake lesion (red circles) in collarbone to white matter vs. noise curves. SD was calculated using same white matter ROI as in (B). Ki images are shown in inverse gray scale with maximum set to 0.06.

FIGURE 6.

Maximum-intensity projections using last 30 min of data. Indirect OSEM Patlak slope Ki uses 3 iterations and 10 subsets. Indirect kernel-EM (KEM) Patlak slope Ki uses 3 iterations and 10 subsets. Direct OSEM Patlak slope Ki uses 12 iterations and 10 subsets, with 10 subiterations of parametric update.

FIGURE 7.

Total-body dynamic 18F-FDG PET and parametric imaging. (A) Static PET images and fused PET/CT image to confirm high uptake at right sternoclavicular joint, degenerative in nature. Both PET images were obtained with 14-min duration. (B) Maximum-intensity projections of OSEM SUV image and indirect Patlak slope Ki image. Latter image is from scan 30–60 min after injection. Red circles indicate high 18F-FDG uptake in right sternoclavicular joint. p.i. = after injection.