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1.  Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences 
With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions.
To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously.
The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation.
Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals can be separated into components based on the differences in the kinetics, provided their kinetic behaviors are distinct.
PMCID: PMC3812387  PMID: 23636489
Dynamic PET; Quantitation; Brain imaging
2.  Proton Therapy Verification with PET Imaging 
Theranostics  2013;3(10):731-740.
Proton therapy is very sensitive to uncertainties introduced during treatment planning and dose delivery. PET imaging of proton induced positron emitter distributions is the only practical approach for in vivo, in situ verification of proton therapy. This article reviews the current status of proton therapy verification with PET imaging. The different data detecting systems (in-beam, in-room and off-line PET), calculation methods for the prediction of proton induced PET activity distributions, and approaches for data evaluation are discussed.
PMCID: PMC3840408  PMID: 24312147
proton therapy; proton range verification; PET imaging.
3.  Ready for prime time? Dual tracer PET and SPECT imaging 
Dual isotope single photon emission computed tomography (SPECT) and dual tracer positron emission tomography (PET) imaging have great potential in clinical and molecular applications in the pediatric as well as the adult populations in many areas of brain, cardiac, and oncologic imaging as it allows the exploration of different physiological and molecular functions (e.g., perfusion, neurotransmission, metabolism, apoptosis, angiogenesis) under the same physiological and physical conditions. This is crucial when the physiological functions studied depend on each other (e.g., perfusion and metabolism) hence requiring simultaneous assessment under identical conditions, and can reduce greatly the quantitation errors associated with physical factors that can change between acquisitions (e.g., human subject or animal motion, change in the attenuation map as a function of time) as is detailed in this editorial. The clinical potential of simultaneous dual isotope SPECT, dual tracer PET and dual SPECT/PET imaging are explored and summarized. In this issue of AJNMMI (, Chapman et al. explore the feasibility of simultaneous and sequential SPECT/PET imaging and conclude that down-scatter and crosstalk from 511 keV photons preclude obtaining useful SPECT information in the presence of PET radiotracers. They report on an alternative strategy that consists of performing sequential SPECT and PET studies in hybrid microPET/SPECT/CT scanners, now widely available for molecular imaging. They validate their approach in a phantom consisting of a 96-well plate with variable 99mTc and 18F concentrations and illustrate the utility of such approaches in two sequential SPECT-PET/CT studies that include 99mTc-MAA/18F-NaF and 99mTc-Pentetate/18F-NaF. These approaches will need to be proven reproducible, accurate and robust to variations in the experimental conditions before they can be accepted by the molecular imaging community and be implemented in routine molecular microPET and microSPECT explorations. Although currently not accepted as standard procedures in the molecular imaging community, such approaches have the potential to open the way to new SPECT/PET explorations that allow studying molecular mechanisms and pathways in the living animal under similar physiological conditions. Although still premature for the clinical setting, these approaches can be extended to clinical research once proven accurate and precise in vivo in small and large animal models.
PMCID: PMC3484417  PMID: 23145358
Dualisotope; dual tracer; positron emission tomography (PET); single photon emission tomography (SPECT); quantitative imaging
4.  Reproducibility and Accuracy of Quantitative Myocardial Blood Flow Using 82Rb-PET: Comparison with 13N-Ammonia 
82Rb cardiac PET allows the assessment of myocardial perfusion using a column generator in clinics that lack a cyclotron. We and others have previously shown that quantitation of myocardial blood flow (MBF) and coronary flow reserve (CFR) is feasible using dynamic 82Rb PET and factor and compartment analyses. The aim of the present work was to determine the intra- and inter-observer variability of MBF estimation using 82Rb PET as well as the reproducibility of our generalized factor + compartment analyses methodology to estimate MBF and assess its accuracy by comparing, in the same subjects, 82Rb estimates of MBF to those obtained using 13N-ammonia.
Twenty-two subjects were included in the reproducibility and twenty subjects in the validation study. Patients were injected with 60±5mCi of 82Rb and imaged dynamically for 6 minutes at rest and during dipyridamole stress Left and right ventricular (LV+RV) time-activity curves were estimated by GFADS and used as input to a 2-compartment kinetic analysis that estimates parametric maps of myocardial tissue extraction (K1) and egress (k2), as well as LV+RV contributions (fv,rv).
Our results show excellent reproducibility of the quantitative dynamic approach itself with coefficients of repeatability of 1.7% for estimation of MBF at rest, 1.4% for MBF at peak stress and 2.8% for CFR estimation. The inter-observer reproducibility between the four observers that participated in this study was also very good with correlation coefficients greater than 0.87 between any two given observers when estimating coronary flow reserve. The reproducibility of MBF in repeated 82Rb studies was good at rest and excellent at peak stress (r2=0.835). Furthermore, the slope of the correlation line was very close to 1 when estimating stress MBF and CFR in repeated 82Rb studies. The correlation between myocardial flow estimates obtained at rest and during peak stress in 82Rb and 13N-ammonia studies was very good at rest (r2=0.843) and stress (r2=0.761). The Bland-Altman plots show no significant presence of proportional error at rest or stress, nor a dependence of the variations on the amplitude of the myocardial blood flow at rest or stress. A small systematic overestimation of 13N-ammonia MBF was observed with 82Rb at rest (0.129 ml/g/min) and the opposite, i.e., underestimation, at stress (0.22 ml/g/min).
Our results show that absolute quantitation of myocardial bloof flow is reproducible and accurate with 82Rb dynamic cardiac PET as compared to 13N-ammonia. The reproducibility of the quantitation approach itself was very good as well as inter-observer reproducibility.
PMCID: PMC3133618  PMID: 19525467
82Rb cardiac 2D PET; 13N-ammonia cardiac PET; Quantitation of myocardial blood flow
5.  Quantitative Simultaneous PET-MR Imaging 
Simultaneous PET-MR is a novel and promising imaging modality that is generating substantial interest in the medical imaging community, while offering many challenges and opportunities. In this study, we investigated whether MR surface coils need to be accounted for in PET attenuation correction. Furthermore, we integrated motion correction, attenuation correction, and point spread function modeling into a single PET reconstruction framework. We applied our reconstruction framework to in vivo animal and patient PET-MR studies. We have demonstrated that our approach greatly improved PET image quality.
PMCID: PMC4306197  PMID: 25632403
PET-MR; PET attenuation correction; surface coils; point spread function modeling; motion correction
6.  Bias atlases for segmentation-based PET attenuation correction using PET-CT and MR 
IEEE transactions on nuclear science  2013;60(5):3373-3382.
This study was to obtain voxel-wise PET accuracy and precision using tissue-segmentation for attenuation correction. We applied multiple thresholds to the CTs of 23 patients to classify tissues. For six of the 23 patients, MR images were also acquired. The MR fat/in-phase ratio images were used for fat segmentation. Segmented tissue classes were used to create attenuation maps, which were used for attenuation correction in PET reconstruction. PET bias images were then computed using the PET reconstructed with the original CT as the reference. We registered the CTs for all the patients and transformed the corresponding bias images accordingly. We then obtained the mean and standard deviation bias atlas using all the registered bias images. Our CT-based study shows that four-class segmentation (air, lungs, fat, other tissues), which is available on most PET-MR scanners, yields 15.1%, 4.1%, 6.6%, and 12.9% RMSE bias in lungs, fat, non-fat soft-tissues, and bones, respectively. An accurate fat identification is achievable using fat/in-phase MR images. Furthermore, we have found that three-class segmentation (air, lungs, other tissues) yields less than 5% standard deviation of bias within the heart, liver, and kidneys. This implies that three-class segmentation can be sufficient to achieve small variation of bias for imaging these three organs. Finally, we have found that inter- and intra-patient lung density variations contribute almost equally to the overall standard deviation of bias within the lungs.
PMCID: PMC4067048  PMID: 24966415
PET-MR; attenuation correction
7.  Clinical Application of in-room PET for in vivo Treatment Monitoring in Proton Radiotherapy 
The purpose of this study is to evaluate the potential of using an in-room PET for treatment verification in proton therapy and to derive suitable PET scan times.
Nine patients undergoing passive scattering proton therapy were scanned immediately after treatment with an in-room PET scanner. The scanner was positioned next to the treatment head after treatment. The Monte Carlo (MC) method was employed to reproduce PET activities for each patient. To assess the proton beam range uncertainty we designed a novel concept where the measured PET activity surface distal to the target at the end of range was compared with MC predictions. The repositioning of patients for the PET scan took on average about 2 minutes. The PET images were reconstructed considering varying scan times to test the scan time dependency of the method.
The measured PET images show overall good spatial correlations with MC predictions. Some discrepancies could be attributed to uncertainties in the local elemental composition and biological washout. For 8 patients treated with a single field, the average range differences between PET measurements and CT-image-based MC results were less than 5 mm (< 3 mm for 6 of 8 patients) and root-mean-square deviations (RMSD) were 4-11 mm with PET-CT image co-registration errors of about 2 mm. Our results also show that a short-length PET scan of 5 minutes can yield similar results compared to a 20 minutes PET scan.
Our first clinical trials of 9 patients using an in-room PET system demonstrated its potential for in vivo treatment monitoring in proton therapy. For a quantitative range prediction with arbitrary shape of target volume, we suggest employing the distal PET activity surface.
PMCID: PMC3640852  PMID: 23391817
Proton therapy; In vivo dose; In-room PET; Monte Carlo simulation
8.  Clinical Impact of Time-of-Flight and Point Response Modeling in PET Reconstructions: A Lesion Detection Study 
Physics in medicine and biology  2013;58(5):1465-1478.
Time-of-flight (TOF) and point spread function (PSF) modeling have been shown to improve PET reconstructions, but the impact on physicians in the clinical setting has not been thoroughly investigated. A lesion detection and localization study was performed using simulated lesions in real patient images. Four reconstruction schemes were considered: ordinary Poisson OSEM (OP) alone and combined with TOF, PSF, and TOF+PSF. The images were presented to physicians experienced in reading PET images, and the performance of each was quantified using localization receiver operating characteristic (LROC). Numerical observers (non-prewhitening and Hotelling) were used to identify optimal reconstruction parameters, and observer SNR was compared to the performance of the physicians. The numerical models showed good agreement with human performance, and best performance was achieved by both when using TOF+PSF. These findings suggest a large potential benefit of TOF+PSF for oncology PET studies, especially in the detection of small, low-intensity, focal disease in larger patients.
PMCID: PMC3616316  PMID: 23403399
9.  MR-based Motion Correction for PET Imaging 
Seminars in nuclear medicine  2013;43(1):60-67.
PET image quality is limited by patient motion. Emission data are blurred due to cardiac and/or respiratory motion. Although spatial resolution is 4 mm for standard clinical whole-body PET scanners, the effective resolution can be a low as 1 cm due to motion. Additionally, the deformation of attenuation medium causes image artifacts. Previously, gating is used to “freeze” the motion, but leads to significantly increased noise level. Simultaneous PET-MR modality offers a new way to perform PET motion correction. MR can be used to measure 3D motion fields, which can then be incorporated into the iterative PET reconstruction to obtain motion corrected PET images. In this report, we present MR imaging techniques to acquire dynamic images, a non-rigid image registration algorithm to extract motion fields from acquired MR images, and a PET reconstruction algorithm with motion correction. We also present results from both phantom and in-vivo animal PET-MR studies. We demonstrate that MR-based PET motion correction using simultaneous PET-MR improves image quality and lesion detectability compared to gating and to no motion correction.
PMCID: PMC3508789  PMID: 23178089
10.  Novel scatter compensation of list-mode PET data using spatial and energy dependent corrections 
With the widespread use of PET crystals with greatly improved energy resolution (e.g., 11.5% with LYSO as compared to 20% with BGO) and of list-mode acquisitions, the use of the energy of individual events in scatter correction schemes becomes feasible. We propose a novel scatter approach that incorporates the energy of individual photons in the scatter correction and reconstruction of list-mode PET data in addition to the spatial information presently used in clinical scanners. First, we rewrite the Poisson likelihood function of list-mode PET data including the energy distributions of primary and scatter coincidences and show that this expression yields an MLEM reconstruction algorithm containing both energy and spatial dependent corrections. To estimate the spatial distribution of scatter coincidences we use the single scatter simulation (SSS). Next, we derive two new formulae which allow estimation of the 2D (coincidences) energy probability density functions (E-PDF) of primary and scatter coincidences from the 1D (photons) E-PDFs associated with each photon. We also describe an accurate and robust object-specific method for estimating these 1D E-PDFs based on a decomposition of the total energy spectra detected across the scanner into primary and scattered components. Finally, we show that the energy information can be used to accurately normalize the scatter sinogram to the data. We compared the performance of this novel scatter correction incorporating both the position and energy of detected coincidences to that of the traditional approach modeling only the spatial distribution of scatter coincidences in 3D Monte Carlo simulations of a medium cylindrical phantom and a large, non uniform NCAT phantom. Incorporating the energy information in the scatter correction decreased bias in the activity distribution estimation by ~20% and ~40% in the cold regions of the large NCAT phantom at energy resolutions 11.5 and 20% at 511 keV, respectively, compared to when using the spatial information alone.
PMCID: PMC3120772  PMID: 21118770
absolute quantification; energy information; fully 3D reconstruction; list-mode PET data; scatter correction
11.  Impact of TOF PET on whole-body oncologic studies: a human observer lesion detection and localization study 
Phantom studies have shown improved lesion detection performance with time-of-flight (TOF) PET. In this study we evaluate the benefit of fully-3D, TOF PET in clinical whole-body oncology using human observers to localize and detect lesions in realistic patient anatomic backgrounds. Our hypothesis is that with TOF imaging we achieve improved lesion detection and localization for clinically challenging tasks with a bigger impact in large patients.
100 patient studies with normal 18F-fluoro-deoxyglucose (18F-FDG) uptake were chosen. 10-mm diameter spheres were imaged in air at variable locations in the scanner field-of-view (FOV) corresponding to lung and liver locations within each patient. Sphere data were corrected for attenuation and merged with patient data to produce fused list data files with lesions added to normal patients. All list files were reconstructed with full corrections and with or without the TOF kernel using a list-mode iterative algorithm. The images were presented to readers to localize and report with a confidence level the presence/absence of a lesion. The interpretation results were then analyzed to calculate the probability of correct localization and detection, and the area under the localized receiver operating characteristic (LROC) curve. The results were analyzed as a function of scan time per bed position, patient body-mass index (BMI < 26 and BMI ≥ 26), and type of imaging (TOF and Non-TOF).
Our results showed that longer scan times led to improved area under the LROC curve for all patient sizes. With TOF imaging there was a bigger increase in the area under the LROC curve for larger patients (BMI ≥ 26). Finally, combining longer scan times with TOF imaging we saw smaller differences in the area under the LROC curve for large and small patients.
A combination of longer scan time (3 minutes in this study) together with TOF imaging provides the best performance for imaging large patients and/or a low uptake lesion in small or large patients. This imaging protocol also provides similar performance over all patient sizes for lesions in the same organ type with similar relative uptake, indicating an ability to provide a uniform clinical diagnostic capability in most oncologic lesion detection tasks.
PMCID: PMC3104282  PMID: 21498523
Lesion detection; human observers; LROC; Time-of-Flight PET
12.  Realistic PET Monte Carlo Simulation With Pixelated Block Detectors, Light Sharing, Random Coincidences and Dead-Time Modeling 
We have developed and validated a realistic simulation of random coincidences, pixelated block detectors, light sharing among crystal elements and dead-time in 2D and 3D positron emission tomography (PET) imaging based on the SimSET Monte Carlo simulation software. Our simulation was validated by comparison to a Monte Carlo transport code widely used for PET modeling, GATE, and to measurements made on a PET scanner.
We have modified the SimSET software to allow independent tracking of single photons in the object and septa while taking advantage of existing voxel based attenuation and activity distributions and validated importance sampling techniques implemented in SimSET. For each single photon interacting in the detector, the energy-weighted average of interaction points was computed, a blurring model applied to account for light sharing and the associated crystal identified. Detector dead-time was modeled in every block as a function of the local single rate using a variance reduction technique. Electronic dead-time was modeled for the whole scanner as a function of the prompt coincidences rate. Energy spectra predicted by our simulation were compared to GATE. NEMA NU-2 2001 performance tests were simulated with the new simulation as well as with SimSET and compared to measurements made on a Discovery ST (DST) camera.
Errors in simulated spatial resolution (full width at half maximum, FWHM) were 5.5% (6.1%) in 2D (3D) with the new simulation, compared with 42.5% (38.2%) with SimSET. Simulated (measured) scatter fractions were 17.8% (21.3%) in 2D and 45.8% (45.2%) in 3D. Simulated and measured sensitivities agreed within 2.3 % in 2D and 3D for all planes and simulated and acquired count rate curves (including NEC) were within 12.7% in 2D in the [0: 80 kBq/cc] range and in 3D in the [0: 35 kBq/cc] range. The new simulation yielded significantly more realistic singles’ and coincidences’ spectra, spatial resolution, global sensitivity and lesion contrasts than the SimSET software.
PMCID: PMC2600659  PMID: 19079776
Block detectors; dead-time; light sharing; Monte Carlo simulation; positron emission tomography; random coincidences

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