Tim Mulnix

Count-Rate Dependent Component-Based Normalization for the HRRT

Component-based normalization is an important technique for PET scanners with a high number of lines of response (LOR), e.g., 4.5 times 109 for the HRRT. It reduces the problem of measuring the sensitivity of each LOR to that of estimating the individual crystal efficiencies(epsiv), e.g., 119808 for the HRRT. We propose a component-based method to compute epsiv for the HRRT. In addition, the block design of the HRRT produces pulse pile-up which causes apparent changes in epsiv with count rate. These effects occur within the block and between the front (LSO) and back (LYSO) crystal layers. We use a rotating source to measure the values and a decaying uniform phantom to account for variations with count rate. The computation of efficiencies is achieved with ~1% statistical noise with an acquisition of ~1 h. Count rate dependency of epsiv is implemented as a linear model in terms of block singles rate. Four approaches to modify epsiv with count rate were compared. Among them, an independent parameter for each crystal produced the best results, both visually and quantitatively. Failure to account for the count rate dependency in epsiv leads to high resolution artifacts in the reconstructed images, most visible in the transverse plane, in the center of the field-of-view.

List-Mode PET Motion Correction Using Markerless Head Tracking: Proof-of-Concept With Scans of Human Subject

A custom designed markerless tracking system was demonstrated to be applicable for positron emission tomography (PET) brain imaging. Precise head motion registration is crucial for accurate motion correction (MC) in PET imaging. State-of-the-art tracking systems applied with PET brain imaging rely on markers attached to the patients head. The marker attachment is the main weakness of these systems. A healthy volunteer participating in a cigarette smoking study to image dopamine release was scanned twice for 2 h with 11C-racolopride on the high resolution research tomograph (HRRT) PET scanner. Head motion was independently measured, with a commercial marker-based device and the proposed vision-based system. A list-mode event-by-event reconstruction algorithm using the detected motion was applied. A phantom study with hand-controlled continuous random motion was obtained. Motion was time-varying with long drift motions of up to 18 mm and regular step-wise motion of 1-6 mm. The evaluated measures were significantly better for motion-corrected images compared to no MC. The demonstrated system agreed with a commercial integrated system. Motion-corrected images were improved in contrast recovery of small structures.

Ex Vivo and In Vivo Evaluation of the Norepinephrine Transporter Ligand [11C]MRB for Brown Adipose Tissue Imaging

INTRODUCTION It has been suggested that brown adipose tissue (BAT) in humans may play a role in energy balance and obesity. We conducted ex vivo and in vivo evaluation using [(11)C]MRB, a highly selective NET (norepinephrine transporter) ligand for BAT imaging at room temperature, which is not achievable with [(18)F]FDG. METHODS PET images of male Sprague-Dawley rats with [(18)F]FDG and [(11)C]MRB were compared. Relative [(18)F]FDG or [(11)C]MRB retention at 20, 40 and 60 min post-injection was quantified on awake rats after exposing to cold (4°C for 4h) or remaining at room temperature. Rats pretreated with unlabeled MRB or nisoxetine 30 min before [(11)C]MRB injection were also assessed. The [(11)C]MRB metabolite profile in BAT was evaluated. RESULTS PET imaging demonstrated intense [(11)C]MRB uptake (SUV of 2.9 to 3.3) in the interscapular BAT of both room temperature and cold-exposed rats and this uptake was significantly diminished by pretreatment with unlabeled MRB; in contrast, [(18)F]FDG in BAT was only detected in rats treated with cold. Ex vivo results were concordant with the imaging findings; i.e. the uptake of [(11)C]MRB in BAT was 3 times higher than that of [(18)F]FDG at room temperature (P=0.009), and the significant cold-stimulated uptake in BAT with [(18)F]FDG (10-fold, P=0.001) was not observed with [(11)C]MRB (P=0.082). HPLC analysis revealed 94%-99% of total radioactivity in BAT represented unchanged [(11)C]MRB. CONCLUSIONS Our study demonstrates that BAT could be specifically labeled with [(11)C]MRB at room temperature and under cold conditions, supporting a NET-PET strategy for imaging BAT in humans under basal conditions.

Evaluation of motion correction methods in human brain PET imaging—A simulation study based on human motion data

PURPOSE Motion correction in PET has become more important as system resolution has improved. The purpose of this study was to evaluate the accuracy of event-by-event and frame-based MC methods in human brain PET imaging. METHODS Motion compensated image reconstructions were performed with static and dynamic simulated high resolution research tomograph data with frame-based image reconstructions, using a range of measured human head motion data. Image intensities in high-contrast regions of interest (ROI) and parameter estimates in tracer kinetic models were assessed to evaluate the accuracy of the motion correction methods. RESULTS Given accurate motion data, event-by-event motion correction can reliably correct for head motions. The average ROI intensities and the kinetic parameter estimates VT and BPND were comparable to the true values. The frame-based motion correction methods with correctly aligned attenuation map using the average of externally acquired motion data or motion data derived from image registration give comparable quantitative accuracy. For large intraframe (>5 mm) motion, the frame-based methods produced ≈ 9% bias in ROI intensities, ≈ 5% in VT, and ≈ 10% in BPND estimates. In addition, in real studies that lack a ground truth, the normalized weighted residual sum of squared difference is a potential figure-of-merit to evaluate the accuracy of motion correction methods. CONCLUSIONS The authors conclude that frame-based motion correction methods are accurate when the intraframe motion is less than 5 mm and when the attenuation map is accurately aligned. Given accurate motion data, event-by-event motion correction can reliably correct for head motion in human brain PET studies.

Awake Nonhuman Primate Brain PET Imaging with Minimal Head Restraint: Evaluation of GABAA-Benzodiazepine Binding with 11C-Flumazenil in Awake and Anesthetized Animals

Neuroreceptor imaging in the nonhuman primate (NHP) is valuable for translational research approaches in humans. However, most NHP studies are conducted under anesthesia, which affects the interpretability of receptor binding measures. The aims of this study were to develop awake NHP imaging with minimal head restraint and to compare in vivo binding of the γ-aminobutyric acid type A (GABAA)-benzodiazepine radiotracer 11C-flumazenil under anesthetized and awake conditions. We hypothesized that 11C-flumazenil binding potential (BPND) would be higher in isoflurane-anesthetized monkeys. Methods: The small animal PET scanner was fitted to a mechanical device that raised and tilted the scanner 45° while the awake NHP was tilted back 35° in a custom chair for optimal brain positioning, which required acclimation of the animals to the chair, touch-screen tasks, intravenous catheter insertion, and tilting. For PET studies, the bolus–plus–constant infusion method was used for 11C-flumazenil administration. Two rhesus monkeys were scanned under the awake (n = 6 scans) and isoflurane-anesthetized (n = 4 scans) conditions. An infrared camera was used to track head motion during PET scans. Under the awake condition, emission and head motion-tracking data were acquired for 40–75 min after injection. Anesthetized monkeys were scanned for 90 min. Cortisol measurements were acquired during awake and anesthetized scans. Equilibrium analysis was used for both the anesthetized (n = 4) and the awake (n = 5) datasets to compute mean BPND images in NHP template space, using the pons as a reference region. The percentage change per minute in radioactivity concentration was calculated in high- and low-binding regions to assess the quality of equilibrium. Results: The monkeys acclimated to procedures in the NHP chair necessary to perform awake PET imaging. Image quality was comparable between awake and anesthetized conditions. The relationship between awake and anesthetized values was BPND (awake) = 0.94 BPND (anesthetized) + 0.36 (r2 = 0.95). Cortisol levels were significantly higher under the awake condition (P < 0.05). Conclusion: We successfully performed awake NHP imaging with minimal head restraint. There was close agreement in 11C-flumazenil BPND values between awake and anesthetized conditions.

Quantification of myocardial blood flow with 82Rb: Validation with 15O-water using time-of-flight and point-spread-function modeling

BackgroundWe quantified myocardial blood flow with 82Rb PET using parameters of the generalized Renkin-Crone model estimated from 82Rb and 15O-water images reconstructed with time-of-flight and point spread function modeling. Previous estimates of rubidium extraction have used older-generation scanners without time-of-flight or point spread function modeling. We validated image-derived input functions with continuously collected arterial samples.MethodsNine healthy subjects were scanned at rest and under pharmacological stress on the Siemens Biograph mCT with 82Rb and 15O-water PET, undergoing arterial blood sampling with each scan. Image-derived input functions were estimated from the left ventricle cavity and corrected with tracer-specific population-based scale factors determined from arterial data. Kinetic parametric images were generated from the dynamic PET images by fitting the one-tissue compartment model to each voxel’s time activity curve. Mean myocardial blood flow was determined from each subject’s 15O-water k2 images. The parameters of the generalized Renkin-Crone model were estimated from these water-based flows and mean myocardial 82Rb K1 estimates.ResultsImage-derived input functions showed improved agreement with arterial measurements after a scale correction. The Renkin-Crone model fit (a = 0.77, b = 0.39) was similar to those previously published, though b was lower.ConclusionsWe have presented parameter estimates for the generalized Renkin-Crone model of extraction for 82Rb PET using human 82Rb and 15O-water PET from high-resolution images using a state-of-the-art time-of-flight-capable scanner. These results provide a state-of-the-art methodology for myocardial blood flow measurement with 82Rb PET.

Event-by-event respiratory motion correction for PET with 3D internal-1D external motion correlation.

PURPOSE Respiratory motion during PET∕CT imaging can cause substantial image blurring and underestimation of tracer concentration for both static and dynamic studies. In this study, the authors developed an event-by-event respiratory motion correction method that used three-dimensional internal-one-dimensional external motion correlation (INTEX3D) in listmode reconstruction. The authors aim to fully correct for organ/tumor-specific rigid motion caused by respiration using all detected events to eliminate both intraframe and interframe motion, and investigate the quantitative improvement in static and dynamic imaging. METHODS The positional translation of an internal organ or tumor during respiration was first determined from the reconstructions of multiple phase-gated images. A level set (active contour) method was used to segment the targeted internal organs/tumors whose centroids were determined. The mean displacement of the external respiratory signal acquired by the Anzai system that corresponded to each phase-gated frame was determined. Three linear correlations between the 1D Anzai mean displacements and the 3D centroids of the internal organ/tumor were established. The 3D internal motion signal with high temporal resolution was then generated by applying each of the three correlation functions to the entire Anzai trace (40 Hz) to guide event-by-event motion correction in listmode reconstruction. The reference location was determined as the location where CT images were acquired to facilitate phase-matched attenuation correction and anatomical-based postfiltering. The proposed method was evaluated with a NEMA phantom driven by a QUASAR respiratory motion platform, and human studies with two tracers: pancreatic beta cell tracer [(18)F]FP(+)DTBZ and tumor hypoxia tracer [(18)F]fluoromisonidazole (FMISO). An anatomical-based postreconstruction filter was applied to the motion-corrected images to reduce noise while preserving quantitative accuracy and organ boundaries in the patient studies. RESULTS The INTEX3D method yielded an increase of 5%-9% and 32%-40% in contrast recovery coefficient on the hot spheres in the NEMA phantom, compared to the reconstructions with only 1D motion correction (INTEX1D) and no motion correction, respectively. The proposed method also increased the mean activities of the pancreas and kidney by 9.3% and 11.2%, respectively, across three subjects in the FPDTBZ studies, and the average lesion-to-blood ratio by 20% across three lesions in the FMISO study, compared to the reconstructions without motion correction. In addition, the proposed method reduced intragate motion as compared to phase-gated images. The application of the anatomical-based postreconstruction filter further reduced noise in the background by >50% compared to reconstructions without postfiltering, while preserving quantitative accuracy and organ boundaries. Finally, the measurements of the time-activity curves from a subject with FPDTBZ showed that INTEX3D yielded 18% and 11% maximum increases in tracer concentration in the pancreas and kidney cortex, respectively. CONCLUSIONS These results suggest that the proposed method can effectively compensate for both intragate and intergate respiratory motion while preserving all the counts, and is applicable to dynamic studies.

A multimodal approach to image-derived input functions for brain PET

Many methods have been proposed for generating an image-derived input function (IDIF) exclusively from PET images. The purpose of this study was to assess the viability of a multimodality approach utilizing registered MR images. 3T-MR and HRRT-PET data were acquired from human subjects. Segmentation of both the left and right carotid arteries was performed in MR images using a 3D level sets method. Vessel centerlines were extracted by parameterization of the segmented voxel coordinates with either a single polynomial curve or a B-spline curve fitted to the segmented data. These centerlines were subsequently re-registered to static PET data to maximize the accurate classification of PET voxels in the ROI. The accuracy of this approach was assessed by comparison of the area under the curve (AUC) of the IDIF to that measured from conventional automated arterial blood sampling. Our method produces curves similar in shape to that of blood sampling. The mean AUC ratio of the centerline region was 0.40±0.19 before re-registration and 0.69±0.26 after re-registration. Increasing the diameter of the carotid ROI produced a smooth reduction in AUC. Thus, even with the high resolution of the HRRT, partial volume correction is still necessary. This study suggests that the combination of PET information with MR segmented regions will demonstrate an improvement over regions based solely on MR or PET alone.

Quantitative accuracy of HRRT lIST-MODE reconstructions: Effect of low statistics

Previous studies showed that iterative image reconstruction algorithms may produce overestimations of activity in low-activity regions in low-count frames. The purpose of this study was (1) to evaluate the quantitative accuracy of the MOLAR list-mode iterative reconstruction method in the context of ligand-receptor PET studies in low counts, and (2) to determine the minimum noise equivalent counts (NEC) per frame to avoid bias. Evaluation of clinical data was performed for 4 tracers using dynamic brain PET studies. True activity was estimated from high-statistics frames (300s) and ROI analysis was performed to evaluate bias in low-activity regions in short acquisition frames (10–30s) from matching times. Bias in the ROI mean values was analyzed as function of NEC. In addition, accuracy was assessed using Hoffman phantom data and simulated list mode data based on human data, but without scatter and randoms. Unlike previous results, small biases of −3±3% for low statistics region across the 4 tracers were found for NEC ≫100K in each frame. Very similar results were found in the phantom and simulation data. We conclude that the MOLAR iterative reconstruction method provides accurate results even in very low-count frames. This improved performance may be attributed to some of the unique characteristics of MOLAR including randoms estimation from singles, iterative estimation of scatter within the algorithm, component-based normalization, and incorporation of a line-spread function model in the reconstruction.

Data-driven event-by-event respiratory motion correction using TOF PET list-mode centroid of distribution

Data-driven respiratory gating techniques were developed to correct for respiratory motion in PET studies, without the help of external motion tracking systems. Due to the greatly increased image noise in gated reconstructions, it is desirable to develop a data-driven event-by-event respiratory motion correction method. In this study, using the Centroid-of-distribution (COD) algorithm, we established a data-driven event-by-event respiratory motion correction technique using TOF PET list-mode data, and investigated its performance by comparing with an external system-based correction method. Ten human scans with the pancreatic β-cell tracer 18F-FP-(+)-DTBZ were employed. Data-driven respiratory motions in superior-inferior (SI) and anterior-posterior (AP) directions were first determined by computing the centroid of all radioactive events during each short time frame with further processing. The Anzai belt system was employed to record respiratory motion in all studies. COD traces in both SI and AP directions were first compared with Anzai traces by computing the Pearson correlation coefficients. Then, respiratory gated reconstructions based on either COD or Anzai traces were performed to evaluate their relative performance in capturing respiratory motion. Finally, based on correlations of displacements of organ locations in all directions and COD information, continuous 3D internal organ motion in SI and AP directions was calculated based on COD traces to guide event-by-event respiratory motion correction in the MOLAR reconstruction framework. Continuous respiratory correction results based on COD were compared with that based on Anzai, and without motion correction. Data-driven COD traces showed a good correlation with Anzai in both SI and AP directions for the majority of studies, with correlation coefficients ranging from 63% to 89%. Based on the determined respiratory displacements of pancreas between end-expiration and end-inspiration from gated reconstructions, there was no significant difference between COD-based and Anzai-based methods. Finally, data-driven COD-based event-by-event respiratory motion correction yielded comparable results to that based on Anzai respiratory traces, in terms of contrast recovery and reduced motion-induced blur. Data-driven event-by-event respiratory motion correction using COD showed significant image quality improvement compared with reconstructions with no motion correction, and gave comparable results to the Anzai-based method.