We are developing a 1-mm3resolution, high-sensitivity positron emission tomography (PET) system for loco-regional cancer imaging. The completed system will comprise two 16.5 × 10 cm detector panels and contain 4608 position sensitive avalanche photodiodes (PSAPDs) coupled to arrays of 0.9 × 0.9 × 1 mm3LYSO crystal elements for a total of 294912 crystal elements. For the first time, this paper summarizes the design and reports the performance of a significant portion of the final clinical PET system, comprising 1 536 PSAPDs, 98304 crystal elements, and an active field-of-view (FOV) of 16.5 × 3.3 cm. The sub-system performance parameters, such as energy, time, and spatial resolutions are predictive of the performance of the final system due to the modular design. Analysis of the multiplexed crystal flood histograms shows 84% of the crystal elements have > 99% crystal identification accuracy. The 511 keV photopeak energy resolution was 11.34 ± 0.06% full-width half maximum (FWHM), and coincidence timing resolution was 13.92 ± 0.01 ns FWHM at 511 keV. The spatial resolution was measured using maximum likelihood expectation maximization reconstruction of a grid of point sources suspended in warm background. The averaged resolution over the central 6 cm of the FOV is 1.01 ± 0.13 mm in the X-direction, 1.84 ± 0.20 mm in the Y-direction, and 0.84 ± 0.11 mm in the Z-direction. Quantitative analysis of acquired micro-Derenzo phantom images shows better than 1.2 mm resolution at the center of the FOV, with subsequent resolution degradation in the y-direction toward the edge of the FOV caused by limited angle tomography effects.

Despite the great promise of integrated positron emission tomography (PET)/magnetic resonance (MR) imaging to add molecular information to anatomical and functional MR, its potential impact in medicine is diminished by a very high cost, limiting its dissemination. An RF-penetrable PET ring that can be inserted into any existing MR system has been developed to address this issue. Employing optical signal transmission along with battery power enables the PET ring insert to electrically float with respect to the MR system. Then, inter-modular gaps of the PET ring allow the RF transmit field from the standard built-in body coil to penetrate into the PET fields-of-view (FOV) with some attenuation that can be compensated for. MR performance, including RF noise, magnetic susceptibility, RF penetrability through and $B_{1}$ uniformity within the PET insert, and MR image quality, were analyzed with and without the PET ring present. The simulated and experimentally measured RF field attenuation factors with the PET ring present were -2.7 and -3.2 dB, respectively. The magnetic susceptibility effect (0.063 ppm) and noise emitted from the PET ring in the MR receive channel were insignificant. $B_{1}$ homogeneity of a spherical agar phantom within the PET ring FOV dropped by 8.4% and MR image SNR was reduced by 3.5 and 4.3 dB with the PET present for gradient-recalled echo and fast-spin echo, respectively. This paper demonstrates, for the first time, an RF-penetrable PET insert comprising a full ring of operating detectors that achieves simultaneous PET/MR using the standard built-in body coil as the RF transmitter.

Positron emission tomography (PET) relies on accurate timing information to pair two 511-keV photons into a coincidence event. Calibration of time delays between detectors becomes increasingly important as the timing resolution of detector technology improves, as a calibration error can quickly become a dominant source of error. Previous work has shown that the maximum likelihood estimate of these delays can be calculated by least squares estimation, but an approach is not tractable for complex systems and degrades in the presence of randoms. We demonstrate the original problem to be solvable iteratively using the LSMR algorithm. Using the LSMR, we solve for 60 030 delay parameters, including energy-dependent delays, in 4.5 s, using 1 000 000 coincidence events for a two-panel system dedicated to clinical locoregional imaging. We then extend the original least squares problem to be robust to random coincidences and low statistics by implementing 11-norm minimization using the alternating direction method of the multipliers (ADMM) algorithm. The ADMM algorithm converges after six iterations, or 20.6 s, and improves the timing resolution from 64.7 ± 0.1s full width at half maximum (FWHM) uncalibrated to 15.63 ± 0.02ns FWHM. We also demonstrate this algorithm's applicability to commercial systems using a GE Discovery 690 PET/CT. We scan a rotating transmission source, and after subtracting the 511-keV photon time-of-flight due to the source position, we calculate 13 824 per-crystal delays using 5 000 000 coincidence events in 3.78 s with three iterations, while showing a timing resolution improvement that is significantly better than previous calibration methods in the literature.

A maximum likelihood expectation maximization (MLEM) method is proposed for joint estimation of emission activity distribution and photon attenuation map from positron emission tomography (PET) emission data alone. The method is appealing since: (i) it guarantees monotonic likelihood increase to a local extremum, (ii) does not require arbitrary parameters, and (iii) guarantees the positivity of the estimated distributions. Moreover, we propose a discrete Poisson data acquisition model and numerical algorithm for: (i) efficient graphics processing unit (GPU) based formulation, and (ii) a closed form exact solution for the MLEM update equations, which is essential for accurate and robust estimation. Numerical experiments indicate that in the presence of noise, joint EMAA estimation converges to the true emission activity distribution with root mean square errors of 4% and 0.5% respectively in estimation of lung- and myocardial emission activity distributions for a computational XCAT thorax phantom.

A recent entry into the rapidly evolving field of integrated PET/MR scanners is presented in this paper: a whole body hybrid PET/MR system (SIGNA PET/MR, GE Healthcare) capable of simultaneous acquisition of both time-of-flight (TOF) PET and high resolution MR data. The PET ring was integrated into an existing 3T MR system resulting in a (patient) bore opening of 60 cm diameter, with a 25 cm axial FOV. PET performance was evaluated both on the standalone PET ring and on the same detector integrated into the MR system, to assess the level of mutual interference between both subsystems. In both configurations we obtained detector performance data. PET detector performance was not significantly affected by integration into the MR system. The global energy resolution was within 2% (10.3% versus 10.5%), and the system coincidence time resolution showed a maximum change of < 3% (385 ps versus 394 ps) when measured outside MR and during simultaneous PET/MRI acquisitions, respectively. To evaluate PET image quality and resolution, the NEMA IQ phantom was acquired with MR idle and with MR active. Impact of PET on MR IQ was assessed by comparing SNR with PET acquisition on and off. B0 and B1 homogeneities were acquired before and after the integration of the PET ring inside the magnet. In vivo brain and whole body head-to-thighs data were acquired to demonstrate clinical image quality.

Nuclear medicine imaging detectors are commonly multiplexed to reduce the number of readout channels. Because the underlying detector signals have a sparse representation, sparse recovery methods such as compressed sensing may be used to develop new multiplexing schemes. Random methods may be used to create sensing matrices that satisfy the restricted isometry property. However, the restricted isometry property provides little guidance for developing multiplexing networks with good signal-to-noise recovery capability. In this work, we describe compressed sensing using a maximum likelihood framework and develop a new method for constructing multiplexing (sensing) matrices that can recover signals more accurately in a mean square error sense compared to sensing matrices constructed by random construction methods. Signals can then be recovered by maximum likelihood estimation constrained to the support recovered by either greedy l₀ iterative algorithms or l₁-norm minimization techniques. We show that this new method for constructing and decoding sensing matrices recovers signals with 4%-110% higher SNR than random Gaussian sensing matrices, up to 100% higher SNR than partial DCT sensing matrices 50%-2400% higher SNR than cross-strip multiplexing, and 22%-210% higher SNR than Anger multiplexing for photoelectric events.

The processing speed for positron emission tomography (PET) image reconstruction has been greatly improved in recent years by simply dividing the workload to multiple processors of a graphics processing unit (GPU). However, if this strategy is generalized to a multi-GPU cluster, the processing speed does not improve linearly with the number of GPUs. This is because large data transfer is required between the GPUs after each iteration, effectively reducing the parallelism. This paper proposes a novel approach to reformulate the maximum likelihood expectation maximization (MLEM) algorithm so that it can scale up to many GPU nodes with less frequent inter-node communication. While being mathematically different, the new algorithm maximizes the same convex likelihood function as MLEM, thus converges to the same solution. Experiments on a multi-GPU cluster demonstrate the effectiveness of the proposed approach.

In this work, we propose a new method to increase the accuracy of identifying true coincidence events for positron emission tomography (PET). This approach requires 3-D detectors with the ability to position each photon interaction in multi-interaction photon events. When multiple interactions occur in the detector, the incident direction of the photon can be estimated using the Compton scatter kinematics (Compton Collimation). If the difference between the estimated incident direction of the photon relative to a second, coincident photon lies within a certain angular range around colinearity, the line of response between the two photons is identified as a true coincidence and used for image reconstruction. We present an algorithm for choosing the incident photon direction window threshold that maximizes the noise equivalent counts of the PET system. For simulated data, the direction window removed 56%-67% of random coincidences while retaining > 94% of true coincidences from image reconstruction as well as accurately extracted 70% of true coincidences from multiple coincidences.

We are developing a dual panel breast-dedicated positron emission tomography (PET) system using LSO scintillators coupled to position sensitive avalanche photodiodes (PSAPD). The charge output is amplified and read using NOVA RENA-3 ASICs. This paper shows that the coincidence timing resolution of the RENA-3 ASIC can be improved using certain list-mode calibrations. We treat the calibration problem as a convex optimization problem and use the RENA-3's analog-based timing system to correct the measured data for time dispersion effects from correlated noise, PSAPD signal delays and varying signal amplitudes. The direct solution to the optimization problem involves a matrix inversion that grows order (n(3)) with the number of parameters. An iterative method using single-coordinate descent to approximate the inversion grows order (n). The inversion does not need to run to convergence, since any gains at high iteration number will be low compared to noise amplification. The system calibration method is demonstrated with measured pulser data as well as with two LSO-PSAPD detectors in electronic coincidence. After applying the algorithm, the 511 keV photopeak paired coincidence time resolution from the LSO-PSAPD detectors under study improved by 57%, from the raw value of 16.3 ±0.07 ns full-width at half-maximum (FWHM) to 6.92 ±0.02 ns FWHM ( 11.52 ±0.05 ns to 4.89 ±0.02 ns for unpaired photons).

List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach.

Positron emission tomography (PET) is used in the clinic andin vivosmall animal research to study certain molecular processes associated with diseases such as cancer, heart disease, and neurological disorders and guide the discovery and development of new treatments. New PET molecular probes and associated small animal imaging assays are under development to target, visualize, and quantify subtle molecular and cellular processes such as protein–protein interactions in signal transduction pathways, cancer cell trafficking, therapeutic stem cells and their progeny, interaction of the immune system and tumor cells, and gene delivery and expression in living animals. These next-generation PET molecular imaging assays require an order of magnitude increase in PET's ability to detect, visualize, and quantify low concentrations of probe interacting with its target, which we will refer to asmolecular sensitivity, in order to study the subtle signatures associated with these molecular processes. The molecular sensitivity is determined by a combination of the probe and biological/physiological properties of the subject that determine its specificity for the target, and the performance capabilities of the imaging system that determine how well the resulting signal can be measured. This paper focuses on the second aspect: the challenges of advancing PET technology and some of the new imaging system technologies under investigation to substantially enhance PET's molecular sensitivity. If successful, these novel imaging system technology advances, together with new probe molecules that target specific molecular processes associated with disease, will substantially enhance the molecular sensitivity of PET and thus increase its role in preclinical and clinical research as well as evaluating and managing disease in the clinic.

We present a phantom study to evaluate the performance of the eXplore Optix (Advanced Research Technologies-GE Healthcare), the first commercially available time-domain tomography system for small animal fluorescence imaging, and compare its capabilities with the widely used IVIS 200 (Xenogen Corporation-Caliper) continuous wave planar imaging system. The eXplore Optix, based on point-wise illumination and collection scheme, is found to be a log order more sensitive with significantly higher detection depth and spatial resolution as compared with the wide-area illumination IVIS 200 under the conditions tested. A time-resolved detection system allows the eXplore Optix to measure the arrival time distribution of fluorescence photons. This enables fluorescence lifetime measurement, absorption mapping, and estimation of fluorescent inclusion depth, which in turn is used by a reconstruction algorithm to calculate the volumetric distribution of the fluorophore concentration. An increased acquisition time and lack of ability to image multiple animals simultaneously are the main drawbacks of the eXplore Optix as compared with the IVIS 200.