Dan J. Kadrmas

Impact of Time-of-Flight on PET Tumor Detection

Time-of-flight (TOF) PET uses very fast detectors to improve localization of events along coincidence lines-of-response. This information is then utilized to improve the tomographic reconstruction. This work evaluates the effect of TOF upon an observers performance for detecting and localizing focal warm lesions in noisy PET images. Methods: An advanced anthropomorphic lesion-detection phantom was scanned 12 times over 3 days on a prototype TOF PET/CT scanner (Siemens Medical Solutions). The phantom was devised to mimic whole-body oncologic 18F-FDG PET imaging, and a number of spheric lesions (diameters 6–16 mm) were distributed throughout the phantom. The data were reconstructed with the baseline line-of-response ordered-subsets expectation-maximization algorithm, with the baseline algorithm plus point spread function model (PSF), baseline plus TOF, and with both PSF+TOF. The lesion-detection performance of each reconstruction was compared and ranked using localization receiver operating characteristics (LROC) analysis with both human and numeric observers. The phantom results were then subjectively compared to 2 illustrative patient scans reconstructed with PSF and with PSF+TOF. Results: Inclusion of TOF information provides a significant improvement in the area under the LROC curve compared to the baseline algorithm without TOF data (P = 0.002), providing a degree of improvement similar to that obtained with the PSF model. Use of both PSF+TOF together provided a cumulative benefit in lesion-detection performance, significantly outperforming either PSF or TOF alone (P < 0.002). Example patient images reflected the same image characteristics that gave rise to improved performance in the phantom data. Conclusion: Time-of-flight PET provides a significant improvement in observer performance for detecting focal warm lesions in a noisy background. These improvements in image quality can be expected to improve performance for the clinical tasks of detecting lesions and staging disease. Further study in a large clinical population is warranted to assess the benefit of TOF for various patient sizes and count levels, and to demonstrate effective performance in the clinical environment.

An Assessment of the Impact of Incorporating Time-of-Flight Information into Clinical PET/CT Imaging

The introduction of fast scintillators with good stopping power for 511-keV photons has renewed interest in time-of-flight (TOF) PET. The ability to measure the difference between the arrival times of a pair of photons originating from positron annihilation improves the image signal-to-noise ratio (SNR). The level of improvement depends upon the extent and distribution of the positron activity and the time resolution of the PET scanner. While specific estimates can be made for phantom imaging, the impact of TOF PET is more difficult to quantify in clinical situations. The results presented here quantify the benefit of TOF in a challenging phantom experiment and then assess both qualitatively and quantitatively the impact of incorporating TOF information into the reconstruction of clinical studies. A clear correlation between patient body mass index and gain in SNR was observed in this study involving 100 oncology patient studies, with a gain due to TOF ranging from 1.1 to 1.8, which is consistent with the 590-ps time resolution of the TOF PET scanner. The visual comparison of TOF and non-TOF images performed by two nuclear medicine physicians confirmed the advantages of incorporating TOF into the reconstruction, advantages that include better definition of small lesions and image details, improved uniformity, and noise reduction.

Fast Implementations of Reconstruction-Based Scatter Compensation in Fully 3D SPECT Image Reconstruction

Accurate scatter compensation in SPECT can be performed by modelling the scatter response function during the reconstruction process. This method is called reconstruction-based scatter compensation (RBSC). It has been shown that RBSC has a number of advantages over other methods of compensating for scatter, but using RBSC for fully 3D compensation has resulted in prohibitively long reconstruction times. In this work we propose two new methods that can be used in conjunction with existing methods to achieve marked reductions in RBSC reconstruction times. The first method, coarse-grid scatter modelling, significantly accelerates the scatter model by exploiting the fact that scatter is dominated by low-frequency information. The second method, intermittent RBSC, further accelerates the reconstruction process by limiting the number of iterations during which scatter is modelled. The fast implementations were evaluated using a Monte Carlo simulated experiment of the 3D MCAT phantom with 99mTc tracer, and also using experimentally acquired data with 201Tl tracer. Results indicated that these fast methods can reconstruct, with fully 3D compensation, images very similar to those obtained using standard RBSC methods, and in reconstruction times that are an order of magnitude shorter. Using these methods, fully 3D iterative reconstruction with RBSC can be performed well within the realm of clinically realistic times (under 10 minutes for 64 x 64 x 24 image reconstruction).

LOR-OSEM: statistical PET reconstruction from raw line-of-response histograms

Iterative statistical reconstruction methods are becoming the standard in positron emission tomography (PET). Conventional maximum-likelihood expectation-maximization (MLEM) and ordered-subsets (OSEM) algorithms act on data which have been pre-processed into corrected, evenly-spaced histograms; however, such pre-processing corrupts the Poisson statistics. Recent advances have incorporated attenuation, scatter and randoms compensation into the iterative reconstruction. The objective of this work was to incorporate the remaining pre-processing steps, including arc correction, to reconstruct directly from raw unevenly-spaced line-of-response (LOR) histograms. This exactly preserves Poisson statistics and full spatial information in a manner closely related to listmode ML, making full use of the ML statistical model. The LOR-OSEM algorithm was implemented using a rotation-based projector which maps directly to the unevenly-spaced LOR grid. Simulation and phantom experiments were performed to characterize resolution, contrast and noise properties for 2D PET. LOR-OSEM provided a beneficial noise-resolution tradeoff, outperforming AW-OSEM by about the same margin that AW-OSEM outperformed pre-corrected OSEM. The relationship between LOR-ML and listmode ML algorithms was explored, and implementation differences are discussed. LOR-OSEM is a viable alternative to AW-OSEM for histogram-based reconstruction with improved spatial resolution and noise properties.

Simultaneous technetium-99m/thallium-201 SPECT imaging with model-based compensation for cross-contaminating effects

Simultaneous acquisition of dual-isotope SPECT data offers a number of advantages over separately acquired data; however, simultaneous acquisition can result in cross-contamination between isotopes. In this work we propose and evaluate two frameworks for iterative model-based compensation of cross-contamination in dual-isotope SPECT. The methods were applied to cardiac imaging with technetium-99m-sestamibi and thallium-201, and they were compared with a subtraction-based compensation method using a cross-talk estimate obtained from an auxiliary energy window. Monte Carlo simulations were performed to carefully study aspects of bias and noise for the methods, and a torso phantom with cardiac insert was used to evaluate the performance of the methods for experimentally acquired data. The cross-talk compensation methods substantially improved lesion contrast and significantly reduced quantitative errors for simultaneously acquired data. Thallium image normalized mean square error (NMSE) was reduced from 0.522 without cross-talk compensation to as low as 0.052 with model-based cross-talk compensation. This is compared with a NMSE of 0.091 for the subtraction-based compensation method. The application of a preliminary model for cross-talk arising from lead fluorescence x-rays and collimator scatter gave promising results, and the future development of a more accurate model for collimator interactions would probably benefit simultaneous Tc/Tl imaging. Model-based compensation methods provide feasible cross-talk compensation in clinically acceptable times, and they may ultimately make simultaneous dual-isotope protocols an effective alternative for many imaging procedures.

4D maximum a posteriori reconstruction in dynamic SPECT using a compartmental model-based prior

A 4D ordered-subsets maximum a posteriori (OSMAP) algorithm for dynamic SPECT is described which uses a temporal prior that constrains each voxels behaviour in time to conform to a compartmental model. No a priori limitations on kinetic parameters are applied; rather, the parameter estimates evolve as the algorithm iterates to a solution. The estimated parameters and time-activity curves are used within the reconstruction algorithm to model changes in the activity distribution as the camera rotates, avoiding artefacts due to inconsistencies of data between projection views. This potentially allows for fewer, longer-duration scans to be used and may have implications for noise reduction. The algorithm was evaluated qualitatively using dynamic 99mTc-teboroxime SPECT scans in two patients, and quantitatively using a series of simulated phantom experiments. The OSMAP algorithm resulted in images with better myocardial uniformity and definition, gave time-activity curves with reduced noise variations, and provided wash-in parameter estimates with better accuracy and lower statistical uncertainty than those obtained from conventional ordered-subsets expectation-maximization (OSEM) processing followed by compartmental modelling. The new algorithm effectively removed the bias in k21 estimates due to inconsistent projections for sampling schedules as slow as 60 s per timeframe, but no improvement in wash-out parameter estimates was observed in this work. The proposed dynamic OSMAP algorithm provides a flexible framework which may benefit a variety of dynamic tomographic imaging applications.

Estimating myocardial perfusion from dynamic contrast-enhanced CMR with a model-independent deconvolution method

BackgroundModel-independent analysis with B-spline regularization has been used to quantify myocardial blood flow (perfusion) in dynamic contrast-enhanced cardiovascular magnetic resonance (CMR) studies. However, the model-independent approach has not been extensively evaluated to determine how the contrast-to-noise ratio between blood and tissue enhancement affects estimates of myocardial perfusion and the degree to which the regularization is dependent on the noise in the measured enhancement data. We investigated these questions with a model-independent analysis method that uses iterative minimization and a temporal smoothness regularizer. Perfusion estimates using this method were compared to results from dynamic 13N-ammonia PET.ResultsAn iterative model-independent analysis method was developed and tested to estimate regional and pixelwise myocardial perfusion in five normal subjects imaged with a saturation recovery turboFLASH sequence at 3 T CMR. Estimates of myocardial perfusion using model-independent analysis are dependent on the choice of the regularization weight parameter, which increases nonlinearly to handle large decreases in the contrast-to-noise ratio of the measured tissue enhancement data. Quantitative perfusion estimates in five subjects imaged with 3 T CMR were 1.1 ± 0.8 ml/min/g at rest and 3.1 ± 1.7 ml/min/g at adenosine stress. The perfusion estimates correlated with dynamic 13N-ammonia PET (y = 0.90x + 0.24, r = 0.85) and were similar to results from other validated CMR studies.ConclusionThis work shows that a model-independent analysis method that uses iterative minimization and temporal regularization can be used to quantify myocardial perfusion with dynamic contrast-enhanced perfusion CMR. Results from this method are robust to choices in the regularization weight parameter over relatively large ranges in the contrast-to-noise ratio of the tissue enhancement data.

Rapid dual-tracer PTSM+ATSM PET imaging of tumour blood flow and hypoxia: a simulation study

Blood flow and hypoxia are interrelated aspects of physiology that affect cancer treatment and response. Cu-PTSM and Cu-ATSM are related PET tracers for blood flow and hypoxia, and the ability to rapidly image both tracers in a single scan would bring several advantages over conventional single-tracer techniques. Using dynamic imaging with staggered injections, overlapping signals for multiple PET tracers may be recovered utilizing information from kinetics and radioactive decay. In this work, rapid dual-tracer PTSM+ATSM PET was simulated and tested as a function of injection delay, order and relative dose for several copper isotopes, and the results were compared relative to separate single-tracer data. Time-activity curves representing a broad range of tumour blood flow and hypoxia levels were simulated, and parallel dual-tracer compartment modelling was used to recover the signals for each tracer. The main results were tested further using a torso phantom simulation of PET tumour imaging. Using scans as short as 30 minutes, the dual-tracer method provided measures of blood flow and hypoxia similar to single-tracer imaging. The best performance was obtained by injecting PTSM first and using a somewhat higher dose for ATSM. Comparable results for different copper isotopes suggest that tracer kinetics with staggered injections play a more important role than radioactive decay in the signal separation process. Rapid PTSM+ATSM PET has excellent potential for characterizing both tumour blood flow and hypoxia in a single, fast scan, provided that technological hurdles related to algorithm development and routine use can be overcome.

Comparison of 18F-fluorodeoxyglucose and 18F- fluorothymidine PET in differentiating radiation necrosis from recurrent glioma

Purpose The objective was to compare 18F-fluorodeoxyglucose (FDG) and 18F-fluorothymidine (FLT) PET in differentiating radiation necrosis from recurrent glioma. Materials and Methods Visual and quantitative analyses were derived from static FDG PET and static and dynamic FLT PET in 15 patients with suspected recurrence of treated grade 2 glioma or worse with a new focus of Gd contrast enhancement on MRI. For FDG PET, SUVmax and the ratio of lesion SUVmax to the SUVmean of contralateral white matter were measured. For FLT PET, SUVmax and Patlak-derived metabolic flux parameter Kimax were measured for the same locus. A 5-point visual confidence scale was applied to FDG PET and FLT PET. Receiver operating curve analysis was applied to visual and quantitative results. Differences between recurrent tumor and radiation necrosis were tested by Kruskal-Wallis analysis. On the basis of follow-up Gd-enhanced MRI, lesion-specific recurrent tumor was defined as a definitive increase in size of the lesion, and radiation necrosis was defined as stability or regression. Results For FDG SUVmax, the FDG ratio of lesion–white matter, and FLT Kimax, there was a significant difference between mean values for recurrent tumor and radiation necrosis. Recurrent tumor was best identified by the FDG ratio of lesion–contralateral normal white matter (area under the curve of 0.98, confidence interval of 0.91 to 1.00, sensitivity of 100%, and specificity of 75% for an optimized cutoff value of 1.82). Conclusions Both quantitative and visual determinations allow accurate differentiation between recurrent glioma and radiation necrosis by both FDG and FLT PET. In this small series, FLT PET offers no advantage over FDG PET.

Feasibility of rapid multitracer PET tumor imaging

Positron emission tomography (PET) can characterize different aspects of tumor physiology using various tracers. PET scans are usually performed using only one tracer since there is no explicit signal for distinguishing multiple tracers. We tested the feasibility of rapidly imaging multiple PET tracers using dynamic imaging techniques, where the signals from each tracer are separated based upon differences in tracer half-life, kinetics, and distribution. Time-activity curve populations for FDG, acetate, ATSM, and PTSM were simulated using appropriate compartment models, and noisy dual-tracer curves were computed by shifting and adding the single-tracer curves. Single-tracer components were then estimated from dual-tracer data using two methods: principal component analysis (PCA)-based fits of single-tracer components to multitracer data, and parallel multitracer compartment models estimating single-tracer rate parameters from multitracer time-activity curves. The PCA analysis found that there is information content present for separating multitracer data, and that tracer separability depends upon tracer kinetics, injection order and timing. Multitracer compartment modeling recovered rate parameters for individual tracers with good accuracy but somewhat higher statistical uncertainty than single-tracer results when the injection delay was >10 min. These approaches to processing rapid multitracer PET data may potentially provide a new tool for characterizing multiple aspects of tumor physiology in vivo.