Realistic total-body J-PET geometry optimization: Monte Carlo study

Abstract

Background: Total-body (TB) Positron Emission Tomography (PET) is one of the most promising medical diagnostics modalities, opening new perspectives for personalized medicine, low-dose imaging, multi-organ dynamic imaging or kinetic modeling. The high sensitivity provided by total-body technology can be advantageous for novel tomography methods like positronium imaging, demanding the registration of triple coincidences. Currently, state-of-the-art PET scanners use inorganic scintillators. However, the high acquisition cost reduces the accessibility of TB PET technology. Several efforts are ongoing to mitigate this problem. Among the alternatives, the Jagiellonian PET (J-PET) technology, based on axially arranged plastic scintillator strips, offers a low-cost alternative solution for TB PET.

Purpose: The work aimed to compare five total-body J-PET geometries with plastic scintillators suitable for multi-organ and positronium tomography as a possible next-generation J-PET scanner design.

Methods: We present comparative studies of performance characteristics of the cost-effective total-body PET scanners using J-PET technology. We investigated in silico five TB scanner geometries, varying the number of rings, scanner radii, and other parameters. Monte Carlo simulations of the anthropomorphic XCAT phantom, the extended 2-m sensitivity line source and positronium sensitivity phantoms were used to assess the performance of the geometries. Two hot spheres were placed in the lungs and in the liver of the XCAT phantom to mimic the pathological changes. We compared the sensitivity profiles and performed quantitative analysis of the reconstructed images by using quality metrics such as contrast recovery coefficient, background variability and root mean squared error. The studies are complemented by the determination of sensitivity for the positronium lifetime tomography and the relative cost analysis of the studied setups.

Results: The analysis of the reconstructed XCAT images reveals the superiority of the seven-ring scanners over the three-ring setups. However, the three-ring scanners would be approximately 2-3 times cheaper. The peak sensitivity values for two-gamma vary from 20 to 34 cps/kBq and are dominated by the differences in geometrical acceptance of the scanners. The sensitivity curves for the positronium tomography have a similar shape to the two-gamma sensitivity profiles. The peak values are lower compared to the two-gamma cases, from about 20-28 times, with a maximum value of 1.66 cps/kBq. This can be contrasted with the 50-cm one-layer J-PET modular scanner used to perform the first in-vivo positronium imaging with a sensitivity of 0.06 cps/kBq.

Conclusions: The results show the feasibility of multi-organ imaging of all the systems to be considered for the next generation of TB J-PET designs. Among the scanner parameters, the most important ones are related to the axial field-of-view coverage. The two-gamma sensitivity and XCAT image reconstruction analyzes show the advantage of seven-ring scanners. However, the cost of the scintillator materials and SiPMs is more than two times higher for the longer modalities compared to the three-ring solutions. Nevertheless, the relative cost for all the scanners is about 10-4 times lower compared to the cost of the uExplorer. These properties coupled together with J-PET cost-effectiveness and triggerless acquisition mode enabling three-gamma positronium imaging, make the J-PET technology an attractive solution for broad application in clinics.

Keywords: J‐PET; Monte Carlo simulations; TB PET.

FIGURE 1

(Left) Visualization of the single module, made of plastic scintillators (light blue) with the WLS layer (green elements) and the casing (violet ‐ not included in the simulation model). (Right) Visualization of the seven‐ring S5 scanner with a total FOV of 243 cm. The length of the scintillators in each ring is equal to 33 cm. The gap between adjacent rings is equal to 2 cm. Two layers of the scanners are shown (yellow and red strips). FOV, field‐of‐view; WLS, wavelength shifter.

FIGURE 2

TOF uncertainty sources in the J‐PET scanner. Apart from the uncertainty along the line of response (marked in red), additional distortion due to the hit registration resolution along the plastic scintillator (green) is present. Example lines of responses are shown in magenta. J‐PET, Jagiellonian positron emission tomography; TOF, time‐of‐flight.

FIGURE 3

Sensitivity profiles for tested TB J‐PET geometries. J‐PET, Jagiellonian positron emission tomography; TB, total‐body.

FIGURE 4

Multi‐gamma imaging sensitivity profiles for tested TB J‐PET geometries. J‐PET, Jagiellonian positron emission tomography; TB, total‐body.

FIGURE 5

Simulated (REF label) and reconstructed XCAT phantom images (TOF label) for five different Gaussian TOF kernel widths for the sagittal (top panel) and axial (center and bottom panel) views. The center and bottom panels show the slice through the hot spot in the lungs and liver, respectively. PET images are overlayed onto CT scans. Given slices are for S5. 50^th iteration images are shown. PET, positron emission tomographs; TOF, time‐of‐flight; XCAT, extended cardiac‐torso phantom.

FIGURE 6

The Q metric distributions for lungs (panel A) and liver (panel B) for the scanner S5.

FIGURE 7

Simulated (REF panel) and reconstructed (S1–S5) XCAT phantom images for five different scanner types for the sagittal (top panel) and axial (center and bottom panel) views. The center and bottom panels show the slices through the hot spot in the lungs and liver, respectively. PET images are overlayed onto CT scans. For each scanner, the 50^th iteration image is shown. PET, positron emission tomographs; TOF, time‐of‐flight; XCAT, extended cardiac‐torso phantom.

FIGURE 8

CRC (first column), BV (second column), Q (third column) and RMSE (fourth column) characteristics for the liver (top row) and lungs (bottom row) regions calculated based on the reconstructed XCAT phantom images for all five scanners. Shaded regions indicate the one standard deviation region. BV, background variability; CRC, contrast recovery coefficient; RMSE, Root Mean Square Error; XCAT, extended cardiac‐torso phantom.