The EXPLORER project aims to build a 2-meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20-minute whole-body PET scan with an injection of 25 MBq 18F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.

This article and updated information are available at: http://jnm.snmjournals.org/site/subscriptions/online.xhtml Information about subscriptions to JNM can be found at: http://jnm.snmjournals.org/site/misc/permission.xhtml

A 194-cm-long total-body positron emission tomography/computed tomography (PET/CT) scanner (uEXPLORER), has been constructed to offer a transformative platform for human radiotracer imaging in clinical research and healthcare. Its total-body coverage and exceptional sensitivity provide opportunities for innovative studies of physiology, biochemistry, and pharmacology. The objective of this study is to develop a method to perform ultrahigh (100 ms) temporal resolution dynamic PET imaging by combining advanced dynamic image reconstruction paradigms with the uEXPLORER scanner. We aim to capture the fast dynamics of initial radiotracer distribution, as well as cardiac motion, in the human body. The results show that we can visualize radiotracer transport in the body on timescales of 100 ms and obtain motion-frozen images with superior image quality compared to conventional methods. The proposed method has applications in studying fast tracer dynamics, such as blood flow and the dynamic response to neural modulation, as well as performing real-time motion tracking (e.g., cardiac and respiratory motion, and gross body motion) without any external monitoring device (e.g., electrocardiogram, breathing belt, or optical trackers).

In this study we present a method of 3D system response calculation for analytical computer simulation and statistical image reconstruction for a magnetic resonance imaging (MRI) compatible positron emission tomography (PET) insert system that uses a dual-layer offset (DLO) crystal design. The general analytical system response functions (SRFs) for detector geometric and inter-crystal penetration of coincident crystal pairs are derived first. We implemented a 3D ray-tracing algorithm with 4π sampling for calculating the SRFs of coincident pairs of individual DLO crystals. The determination of which detector blocks are intersected by a gamma ray is made by calculating the intersection of the ray with virtual cylinders with radii just inside the inner surface and just outside the outer-edge of each crystal layer of the detector ring. For efficient ray-tracing computation, the detector block and ray to be traced are then rotated so that the crystals are aligned along the X-axis, facilitating calculation of ray/crystal boundary intersection points. This algorithm can be applied to any system geometry using either single-layer (SL) or multi-layer array design with or without offset crystals. For effective data organization, a direct lines of response (LOR)-based indexed histogram-mode method is also presented in this work. SRF calculation is performed on-the-fly in both forward and back projection procedures during each iteration of image reconstruction, with acceleration through use of eight-fold geometric symmetry and multi-threaded parallel computation. To validate the proposed methods, we performed a series of analytical and Monte Carlo computer simulations for different system geometry and detector designs. The full-width-at-half-maximum of the numerical SRFs in both radial and tangential directions are calculated and compared for various system designs. By inspecting the sinograms obtained for different detector geometries, it can be seen that the DLO crystal design can provide better sampling density than SL or dual-layer no-offset system designs with the same total crystal length. The results of the image reconstruction with SRFs modeling for phantom studies exhibit promising image recovery capability for crystal widths of 1.27-1.43 mm and top/bottom layer lengths of 4/6 mm. In conclusion, we have developed efficient algorithms for system response modeling of our proposed PET insert with DLO crystal arrays. This provides an effective method for both 3D computer simulation and quantitative image reconstruction, and will aid in the optimization of our PET insert system with various crystal designs.

The aim of this study is to evaluate the benefit of long axial field-of-view (AFOV) PET scanners on region of interest (ROI) quantification. We simulated a series of PET scanners with an AFOV ranging from 22 cm to 220 cm. A theoretical framework was used to predict the contrast recovery coefficient (CRC) and the variance of ROI quantification in penalized maximum likelihood (ML) image reconstruction, in which the resolution and noise tradeoff was controlled by a regularization parameter with a quadratic penalty function. The characterization was based on the converged penalized ML reconstruction with an accurate system model. We examined quantification of a 2 mm ROI and 10 mm ROI in a clinically relevant scan range of 110 cm. Multiple bed positions with 50% overlap were used for scanners with shorter AFOV to provide a relatively uniform sensitivity across the 110 cm axial range. A uniform water cylinder of 20 cm in diameter and 230 cm in length was chosen to model the attenuation and background activity. We computed the variance reduction factor at fixed resolution. Effects of different detector capabilities, including TOF (time-of-flight) resolution (320 ps, 500 ps, and non-TOF) and DOI (depth-of-interaction) resolution (4 mm, 10 mm, and no DOI), were evaluated. The results show that at a normal activity level (370 MBq), the 220 cm AFOV scanner offers a  ∼17-fold variance reduction for the 2 mm ROI and  ∼26-fold variance reduction for the 10 mm ROI (both measured at CRC  =  0.5) over the 22 cm AFOV scanner when both using detectors with 500 ps TOF resolution no DOI capability. The variance reduction factors of trues-only are higher than those of including scatters and randoms. Combining 320 ps TOF and 4 mm DOI, the 220 cm long scanner offers a  ∼45-fold variance reduction over the 22 cm long reference scanner (500 ps TOF, no DOI) for imaging 2 mm and 10 mm ROIs. The variance reduction factors are higher at a lower activity level due to lower random fraction. In conclusion, our study demonstrates that a long AFOV scanner can greatly improve the quantitative accuracy of PET imaging compared to current state-of-the-art clinical PET scanners.

The first generation Tachyon PET (Tachyon-I) is a demonstration single-ring PET scanner that reaches a coincidence timing resolution of 314 ps using LSO scintillator crystals coupled to conventional photomultiplier tubes. The objective of this study was to quantify the improvement in both lesion detection and quantification performance resulting from the improved time-of-flight (TOF) capability of the Tachyon-I scanner. We developed a quantitative TOF image reconstruction method for the Tachyon-I and evaluated its TOF gain for lesion detection and quantification. Scans of either a standard NEMA torso phantom or healthy volunteers were used as the normal background data. Separately scanned point source and sphere data were superimposed onto the phantom or human data after accounting for the object attenuation. We used the bootstrap method to generate multiple independent noisy datasets with and without a lesion present. The signal-to-noise ratio (SNR) of a channelized hotelling observer (CHO) was calculated for each lesion size and location combination to evaluate the lesion detection performance. The bias versus standard deviation trade-off of each lesion uptake was also calculated to evaluate the quantification performance. The resulting CHO-SNR measurements showed improved performance in lesion detection with better timing resolution. The detection performance was also dependent on the lesion size and location, in addition to the background object size and shape. The results of bias versus noise trade-off showed that the noise (standard deviation) reduction ratio was about 1.1-1.3 over the TOF 500 ps and 1.5-1.9 over the non-TOF modes, similar to the SNR gains for lesion detection. In conclusion, this Tachyon-I PET study demonstrated the benefit of improved time-of-flight capability on lesion detection and ROI quantification for both phantom and human subjects.