Application and evaluation of a measured spatially variant system model for PET image reconstruction

A modified orthogonal-distance ray-tracer method applied to dual rotation PET systems

Objective.a new projector, orthogonal-distance ray-tracer varying-full width at half maximum (OD-RT-VF), was developed to model a shift-variant elliptical point-spread function (PSF) response to improve the image quality (IQ) of a preclinical dual-rotation PET system.Approach.the OD-RT-VF projector models different FWHM values of the PSF in multiple directions, using half-height and half-width tube-of-response (ToR) values. The OD-RT-VF method's performance was evaluated against the original OD-RT method and a ToR model with constant response. The evaluation involved simulations of NEMA NU 4-2008 IQ and Derenzo phantoms, as well as a real mouse injected with [18F]-NaF scanned with the easyPET.3D system.Main results.the OD-RT-VF method demonstrated superior image resolution and uniformity (11.9% vs 15.9%) compared to the OD-RT model. In micro-derenzo phantom simulations, it resolved rods down to 1.0 mm, outperforming the other methods. For IQ phantom simulations, the OD-RT-VF projector at convergency achieved hot rods recovery coefficients ranging from 22.4% to 93.3% and lower spillover ratios in cold regions of 0.22 and 0.33 for air and water, respectively. For bone radiotracer imaging, OD-RT-VF produced clearer images of major skeletal parts, with less noise compared to OD-RT and better resolution compared to ToR projectors.Significance.the study shows that the OD-RT-VF projector method enhances PET imaging by providing better resolution, uniformity, and IQ. This model, in addition to a list-mode and GPU-based reconstruction addressing the data sparsity of dual-rotation PET geometries, unlocks their imaging potential for small animal imaging.

3D in-system calibration method for PET detectors

BACKGROUND

Light-sharing detector designs for positron emission tomography (PET) systems have sparked interest in the scientific community. Particularly, (semi-)monoliths show generally good performance characteristics regarding 2D positioning, energy-, and timing resolution, as well as readout area. This is combined with intrinsic depth-of-interaction (DOI) capability to ensure a homogeneous spatial resolution across the entire field of view (FoV). However, complex positioning calibration processes limit their use in PET systems, especially in large-scale clinical systems.

PURPOSE

This work proposes a new 3D positioning in-system calibration method for fast and convenient (re-)calibration and quality control of assembled PET scanners. The method targets all kinds of PET detectors that achieve the best performance with individual calibration, including complex segmented detector designs. The in-system calibration method is evaluated and empirically compared to a state-of-the-art fan-beam calibration for a small-diameter proof of concept (PoC) scanner. A simulation study evaluates the method's applicability to different scanner geometries.

METHODS

A PoC scanner geometry of 120 mm inner diameter and 150 mm axial extent was set up consisting of five identical finely segmented slab detectors (one detector under test and four collimation detectors). A 2 2Na point source was moved in a circular path inside the FoV. Utilizing virtual collimation and by selecting gamma rays incident approximately perpendicular to the detector normal of the detector under test, training data was created for the training of a 2D positioning model with the machine-learning technique gradient tree boosting (GTB). Data with oblique ray angles was acquired in the same measurement for subsequent angular DOI calibration. For this, a 2D position estimate in the detector under test was calculated first. On this basis, the DOI label was calculated geometrically from the ray path within the detector to finally establish up to 3D training data.

RESULTS

With a mean absolute error (MAE) of 0.8  and 1.19 mm full-width at half maximum (FWHM) along the planar-monolithic slab dimension, the in-system methods performed similarly within 1% to the fan-beam collimator results. The DOI performance was at ∼90% with 1.13 mm MAE and 2.47 mm FWHM to the fan-beam collimator. Analytical calculations suggest an improved performance for larger scanner geometries.

CONCLUSION

The functionality of the 3D in-system positioning calibration method was successfully demonstrated with the measurements within a PoC scanner configuration with similar positioning performance as the bench-top fan-beam setup. The in-system calibration method can be used to calibrate and test fully assembled PET systems to enable more complex light-sharing detector architectures in, for example, large PET systems with many detectors. The acquired data can further be used for more complex energy and time calibrations.

Assessment of lesion insertion tool in pelvis PET/MR data with applications to attenuation correction method development

BACKGROUND

In modern positron emission tomography (PET) with multi-modality imaging (e.g., PET/CT and PET/MR), the attenuation correction (AC) is the single largest correction factor for image reconstruction. One way to assess AC methods and other reconstruction parameters is to utilize software-based simulation tools, such as a lesion insertion tool. Extensive validation of these simulation tools is required to ensure results of the study are clinically meaningful.

PURPOSE

To evaluate different PET AC methods using a synthetic lesion insertion tool that simulates lesions in a patient cohort that has both PET/MR and PET/CT images. To further demonstrate how lesion insertion tool may be used to extend knowledge of PET reconstruction parameters, including but not limited to AC.

METHODS

Lesion quantitation is compared using conventional Dixon-based MR-based AC (MRAC) to that of using CT-based AC (CTAC, a "ground truth"). First, the pre-existing lesions were simulated in a similar environment; a total of 71 lesions were identified in 18 pelvic PET/MR patient images acquired with a time-of-flight simultaneous PET/MR scanner, and matched lesions were inserted contralaterally on the same axial slice. Second, synthetic lesions were inserted into four anatomic target locations in a cohort of four patients who didn't have any observed clinical lesions in the pelvis.

RESULTS

The matched lesion insertions resulted in unity between the lesion error ratios (mean SUVs), demonstrating that the inserted lesions successfully simulated the original lesions. In the second study, the inserted lesions had distinct characteristics by target locations and demonstrated negative max-SUV%diff trends for bone-dominant sites across the patient cohort.

CONCLUSIONS

The current work demonstrates that the applied lesion insertion tool can simulate uptake in pelvic lesions and their expected SUV values, and that the lesion insertion tool can be extended to evaluate further PET reconstruction corrections and algorithms and their impact on quantitation accuracy and precision.

Simultaneous assessment of blood flow and myelin content in the brain white matter with dynamic [11 C]PiB PET: a test-retest study in healthy controls

BACKGROUND

Exploring the relationship between oxygen supply and myelin damage would benefit from a simultaneous quantification of myelin and cerebral blood flow (CBF) in the brain's white matter (WM). To validate an analytical method for quantifying both CBF and myelin content in the WM using dynamic [11C]PiB positron emission tomography (PET).

METHODS

A test-retest study was performed on eight healthy subjects who underwent two consecutive dynamic [11 C]PiB-PET scans. Three quantitative approaches were compared: simplified reference tissue model 2 (SRTM2), LOGAN graphical model, and standardized uptake value ratio (SUVR). The sensitivity of methods to the size of the region of interest was explored by simulating lesion masks obtained from 36 subjects with multiple sclerosis. Reproducibility was assessed using the relative difference and interclass correlation coefficient. Repeated measures correlations were used to test for cross-correlations between metrics.

RESULTS

Among the CBF measures, the relative delivery (R1) of the simplified reference tissue model 2 (SRTM2) displayed the best reproducibility in the white matter, with a strong influence of the size of regions analyzed, the test-retest variability being below 10% for regions above 68 mm3 in the supratentorial white matter. [11C]PiB PET-derived proxies of CBF demonstrated lower perfusion of white matter compared to grey matter with an overall ratio equal to 1.71 ± 0.09 when the SRTM2-R1 was employed. Tissue binding in the white matter was well estimated by the Logan graphical model through estimation of the distribution volume ratio (LOGAN-DVR) and SRTM2 distribution volume ratio (SRTM2-DVR), with test-retest variability being below 10% for regions exceeding 106 mm3 for LOGAN-DVR and 300 mm3 for SRTM2-DVR. SRTM2-DVR provided a better contrast between white matter and grey matter. The interhemispheric variability was also dependent on the size of the region analyzed, being below 10% for regions above 103 mm3 for SRTM2-R1 and above 110 mm3 for LOGAN-DVR. Whereas the 1 to 8-minute standardized uptake value ratio (SUVR1-8) showed an intermediary reproducibility for CBF assessment, SUVR0-2 for perfusion or SUVR50-70 for tissue binding showed poor reproducibility and correlated only mildly with SRTM2-R1 and LOGAN-DVR estimations respectively.

CONCLUSIONS

[11C]PiB PET imaging can simultaneously quantify perfusion and myelin content in WM diseases associated with focal lesions. For longitudinal studies, SRTM2-R1 and DVR should be preferred over SUVR for the assessment of regional CBF and myelin content, respectively.

TRIAL REGISTRATION

European Union Clinical Trials Register EUDRACT; EudraCT Number: 2008-004174-40; Date: 2009-03-06; https//www.clinicaltrialsregister.eu ; number 2008-004174-40.

Efficient image reconstruction for a small animal PET system with dual-layer-offset detector design

BACKGROUND

A compact PET/SPECT/CT system Inliview-3000B has been developed to provide multi-modality information on small animals for biomedical research. Its PET subsystem employed a dual-layer-offset detector design for depth-of-interaction capability and higher detection efficiency, but the irregular design caused some difficulties in calculating the normalization factors and the sensitivity map. Besides, the relatively larger (2 mm) crystal cross-section size also posed a challenge to high-resolution image reconstruction.

PURPOSE

We present an efficient image reconstruction method to achieve high imaging performance for the PET subsystem of Inliview-3000B.

METHODS

List mode reconstruction with efficient system modeling was used for the PET imaging. We adopt an on-the-fly multi-ray tracing method with random crystal sampling to model the solid angle, crystal penetration and object attenuation effect, and modify the system response model during each iteration to improve the reconstruction performance and computational efficiency. We estimate crystal efficiency with a novel iterative approach that combines measured cylinder phantom data with simulated line-of-response (LOR)-based factors for normalization correction before reconstruction. Since it is necessary to calculate normalization factors and the sensitivity map, we stack the two crystal layers together and extend the conventional data organization method here to index all useful LORs. Simulations and experiments were performed to demonstrate the feasibility and advantage of the proposed method.

RESULTS

Simulation results showed that the iterative algorithm for crystal efficiency estimation could achieve good accuracy. NEMA image quality phantom studies have demonstrated the superiority of random sampling, which is able to achieve good imaging performance with much less computation than traditional uniform sampling. In the spatial resolution evaluation based on the mini-Derenzo phantom, 1.1 mm hot rods could be identified with the proposed reconstruction method. Reconstruction of double mice and a rat showed good spatial resolution and a high signal-to-noise ratio, and organs with higher uptake could be recognized well.

CONCLUSION

The results validated the superiority of introducing randomness into reconstruction, and demonstrated its reliability for high-performance imaging. The Inliview-3000B PET subsystem with the proposed image reconstruction can provide rich and detailed information on small animals for preclinical research.

Image Quality and Quantitative PET Parameters of Low-Dose [18F]FDG PET in a Long Axial Field-of-View PET/CT Scanner

PET/CT scanners with a long axial field-of-view (LAFOV) provide increased sensitivity, enabling the adjustment of imaging parameters by reducing the injected activity or shortening the acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectability, and the quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min scan time) were included in this analysis. The PET raw data was rebinned for shorter frame durations to simulate 5 min scans with lower activities in the high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n = 82) were assessed using a 5-point Likert scale. The coefficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Subjective image ratings were generally superior in UHS compared to the HS mode. At 0.5 MBq/kg, lesion detectability decreased to 95% (HS) and to 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7 ± 0.6) and 0.5 MBq/kg in UHS (5.5 ± 0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing the [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a LAFOV PET/CT provides diagnostic image quality without statistically significant changes in the uptake parameters. The UHS mode improves image quality, noise, and lesion detectability compared to the HS mode.

Impact of list-mode reconstruction and image-space point spread function correction on PET image contrast and quantitative value using SiPM-based PET/CT system

We evaluate the effects of list-mode reconstruction and the image-space point spread function (iPSF) on the contrast and quantitative values of positron emission tomography (PET) images using a SiPM-PET/CT system. The evaluation is conducted on an NEMA body phantom and clinical images using a Cartesion Prime SiPM-PET/CT system. The signal-to-background ratio (SBR) of the phantom is set to 2, 4, 6, and 8, and all the PET image data are obtained and reconstructed using 3D-OSEM, time-of-flight, iPSF (-/ +), and a 4-mm Gaussian filter with several iterations. The evaluation criteria include % background variability (NB,10 mm), % contrast (QH,10 mm), iPSF change in QH,10 mm (ΔQH,10 mm) for edge artifact evaluation, profile curves, visual evaluation of edge artifacts, clinical imaging for the standardized uptake value (SUV) of lung nodules, and SNRliver. NB,10 mm demonstrates no significant difference in all SBRs with and without iPSF, whereas QH,10 mm is higher based on the SBR with and without iPSF. ΔQH,10 mm indicates increased iterations and a larger rate of change (> 5%) for small spheres of < 17 mm. The profile curves portrayed almost real concentrations, except for the 10-mm sphere of SBR2 without iPSF; however, with iPSF, an overshoot was observed in the 13-mm sphere of all SBRs. The degree of overshoot increased with increasing iteration and SBR. Edge artifacts were detected at values ≥ 17-22 mm in SBRs other than SBR2 with iPSF. Irrespective of the nodal size, SUV and SNRliver improved considerably after iPSF adjustment. Therefore, the effects of list-mode reconstruction and iPSF on PET image contrast were limited, and the overcorrection of the quantitative values was validated using iPSF.

Optimization of BMI-Based Images for Overweight and Obese Patients - Implications on Image Quality, Quantification, and Radiation Dose in Whole Body 18F-FDG PET/CT Imaging

Purpose

In PET/CT imaging, the activity of the 18F-FDG activity is injected either based on patient body weight (BW) or body mass index (BMI). The purpose of this study was to optimise BMI-based whole body 18F-FDG PET images obtained from overweight and obese patients and assess their image quality, quantitative value and radiation dose in comparison to BW-based images.

Methods

The NEMA-IEC-body phantom was scanned using the mCT 128-slice scanner. The spheres and background were filed with F-18 activity. Spheres-to-background ratio was 4:1. Data was reconstructed using the OSEM-TOF-PSF routine reconstruction. The optimization was performed by varying number of iterations and subsets, filter's size and type, and matrix size. The optimized reconstruction was applied to 17 patients' datasets. The optimized BMI-, routine BMI- and the BW-based images were compared visually and using contrast-to-noise ratio (CNR) and standardized uptake values (SUV) measurements.

Results

The visual assessment of the optimized phantom images showed better image quality and contrast-recovery-coefficients (CRCs) values compared to the routine reconstruction. Using patient data, the optimized BMI-based images provided better image quality compared to BW-based images in 87.5% of the overweight cases and 66.7% for obese cases. The optimized BMI-based images resulted in more than 50% reduction of radiation dose. No significant differences were found between the three series of images in SUV measurements.

Conclusion

The optimized BMI-based approach using 1 iteration, 21 subsets, and 3 mm Hamming filter improves image quality, reduces radiation dose, and provides, at least, similar quantification compared to the BW-based approach for overweight and obese patients.

Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm

Objective. Deep image prior (DIP) has recently attracted attention owing to its unsupervised positron emission tomography (PET) image reconstruction method, which does not require any prior training dataset. In this paper, we present the first attempt to implement an end-to-end DIP-based fully 3D PET image reconstruction method that incorporates a forward-projection model into a loss function.Approach. A practical implementation of a fully 3D PET image reconstruction could not be performed at present because of a graphics processing unit memory limitation. Consequently, we modify the DIP optimization to a block iteration and sequential learning of an ordered sequence of block sinograms. Furthermore, the relative difference penalty (RDP) term is added to the loss function to enhance the quantitative accuracy of the PET image.Main results. We evaluated our proposed method using Monte Carlo simulation with [18F]FDG PET data of a human brain and a preclinical study on monkey-brain [18F]FDG PET data. The proposed method was compared with the maximum-likelihood expectation maximization (EM), maximuma posterioriEM with RDP, and hybrid DIP-based PET reconstruction methods. The simulation results showed that, compared with other algorithms, the proposed method improved the PET image quality by reducing statistical noise and better preserved the contrast of brain structures and inserted tumors. In the preclinical experiment, finer structures and better contrast recovery were obtained with the proposed method.Significance.The results indicated that the proposed method could produce high-quality images without a prior training dataset. Thus, the proposed method could be a key enabling technology for the straightforward and practical implementation of end-to-end DIP-based fully 3D PET image reconstruction.

Phantom and methodology for comparison of small lesion detectability in PET

PURPOSE

The main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.

METHODS

We previously developed a small-lesion detection phantom and described initial results using a head-size phantom. Unlike most fillable nuclear medicine phantoms, this phantom offers a semi-realistic heterogenous background and wall-less contrast features. In this work, the methodology is extended to include (a) the use of both head- and body-sized phantoms and (b) a multi-scan data collection and analysis method. We present an example use case of the phantom and detection estimation methodology, comparing the small-lesion detection performance across four commercial PET/CT systems.

RESULTS

Repeat acquisitions of the phantom enabled estimation of model observer performance and surrogates of detectability. As anticipated, estimated detectability increased with the square root of system sensitivity and TOF offered marked improvement in detectability, especially for the body sized object. The proposed approach characterizing detectability at different times during the decay of the phantom enabled comparison of small lesion detectability at matched activity concentrations (and scan durations) across different scanners.

CONCLUSION

The proposed approach offers a reproducible tool for evaluating relative tradeoffs of system performance on small lesion detectability.

Hot spot imaging in cardiovascular diseases: an information statement from SNMMI, ASNC, and EANM

This information statement from the Society of Nuclear Medicine and Molecular Imaging, American Society of Nuclear Cardiology, and European Association of Nuclear Medicine describes the performance, interpretation, and reporting of hot spot imaging in nuclear cardiology. The field of nuclear cardiology has historically focused on cold spot imaging for the interpretation of myocardial ischemia and infarction. Hot spot imaging has been an important part of nuclear medicine, particularly for oncology or infection indications, and the use of hot spot imaging in nuclear cardiology continues to expand. This document focuses on image acquisition and processing, methods of quantification, indications, protocols, and reporting of hot spot imaging. Indications discussed include myocardial viability, myocardial inflammation, device or valve infection, large vessel vasculitis, valve calcification and vulnerable plaques, and cardiac amyloidosis. This document contextualizes the foundations of image quantification and highlights reporting in each indication for the cardiac nuclear imager.

Bayesian penalized likelihood PET reconstruction impact on quantitative metrics in diffuse large B-cell lymphoma

Evaluate the quantitative, subjective (Deauville score [DS]) and reader agreement differences between standard ordered subset expectation maximization (OSEM) and Bayesian penalized likelihood (BPL) positron emission tomography (PET) reconstruction methods. A retrospective review of 104 F-18 fluorodeoxyglucose PET/computed tomography (CT) exams among 52 patients with diffuse large B-cell lymphoma. An unblinded radiologist moderator reviewed both BPL and OSEM PET/CT exams. Four blinded radiologists then reviewed the annotated cases to provide a visual DS for each annotated lesion. Significant (P < .001) differences in BPL and OSEM PET methods were identified with greater standard uptake value (SUV) maximum and SUV mean for BPL. The DS was altered in 25% of cases when BPL and OSEM were reviewed by the same radiologist. Interobserver DS agreement was higher for OSEM (>1 cm lesion = 0.89 and ≤1 cm lesion = 0.84) compared to BPL (>1 cm lesion = 0.85 and ≤1 cm lesion = 0.81). Among the 4 readers, average intraobserver visual DS agreement between OSEM and BPL was 0.67 for lesions >1cm and 0.4 for lesions ≤1 cm. F-18 Fluorodeoxyglucose PET/CT of diffuse large B-cell lymphoma reconstructed with BPL has higher SUV values, altered DSs and reader agreement when compared to OSEM. This report finds volumetric PET measurements such as metabolic tumor volume to be similar between BPL and OSEM PET reconstructions. Efforts such as adoption of European Association Research Ltd accreditation should be made to harmonize PET data with an aim at balancing the need for harmonization and sensitivity for lesion detection.

A new brain dedicated PET scanner with 4D detector information

In this article, we present the geometrical design and preliminary results of a high sensitivity organ-specific Positron Emission Tomography (PET) system dedicated to the study of the human brain. The system, called 4D-PET, will allow accurate imaging of brain studies due to its expected high sensitivity, high 3D spatial resolution and, by including precise photon time of flight (TOF) information, a boosted signal-to-noise ratio (SNR).

The 4D-PET system incorporates an innovative detector design based on crystal slabs (semi-monolithic) that enables accurate 3D photon impact positioning (including photon Depth of Interaction (DOI) measurement), while providing a precise determination of the photon arrival time to the detector. The detector includes a novel readout system that reduces the number of detector signals in a ratio of 4:1 thus, alleviating complexity and cost. The analog output signals are fed to the TOFPET2 ASIC (PETsys) for scalability purposes.

The present manuscript reports the evaluation of the 4D-PET detector, achieving best values 3D resolution values of <1.6 mm (pixelated axis), 2.7±0.5 mm (monolithic axis) and 3.4±1.1 (DOI axis) mm; 359 ± 7 ps coincidence time resolution (CTR); 10.2±1.5 % energy resolution; and sensitivity of 16.2% at the center of the scanner (simulated). Moreover, a comprehensive description of the 4D-PET architecture (that includes 320 detectors), some pictures of its mechanical assembly, and simulations on the expected image quality are provided.

Effect of iterations and time of flight on normal distributions of 82Rb PET relative perfusion and myocardial blood flow

BACKGROUND

As clinical use of myocardial blood flow (MBF) increases, dynamic series are becoming part of the typical workflow. The methods and parameters used to reconstruct these series require investigation to ensure accurate quantification.

METHODS

Fifty-nine rest/stress dynamic 82Rb PET studies, acquired on a Biograph mCT, from a combination of normal volunteers and low-likelihood patients were reconstructed with and without time of flight (TOF) for varying iterations and processed to obtain relative perfusion and MBF polar maps. Regional values from mean polar maps were fit to a linear mixed-effect model to quantify convergence and select the optimal number of iterations.

RESULTS

TOF reconstructions converged faster and yielded more uniform relative perfusion polar maps. However, the stress MBF distribution for TOF reconstructions was more heterogeneous, with a higher-intensity septal wall. This phenomenon requires further investigation, with right ventricle blood pool spillover possibly having an effect. Optimal reconstructions were defined as 5-iteration non-TOF (24-subset) reconstructions and 3-iteration TOF (21-subset) reconstructions.

CONCLUSION

Optimal cardiac reconstructions were identified for non-TOF and TOF reconstructions of dynamic series. TOF reconstruction presents as the more accurate method, given the more uniform relative perfusion distribution.

Attenuation Coefficient Estimation for PET/MRI With Bayesian Deep Learning Pseudo-CT and Maximum-Likelihood Estimation of Activity and Attenuation

A major remaining challenge for magnetic resonance-based attenuation correction methods (MRAC) is their susceptibility to sources of magnetic resonance imaging (MRI) artifacts (e.g., implants and motion) and uncertainties due to the limitations of MRI contrast (e.g., accurate bone delineation and density, and separation of air/bone). We propose using a Bayesian deep convolutional neural network that in addition to generating an initial pseudo-CT from MR data, it also produces uncertainty estimates of the pseudo-CT to quantify the limitations of the MR data. These outputs are combined with the maximum-likelihood estimation of activity and attenuation (MLAA) reconstruction that uses the PET emission data to improve the attenuation maps. With the proposed approach uncertainty estimation and pseudo-CT prior for robust MLAA (UpCT-MLAA), we demonstrate accurate estimation of PET uptake in pelvic lesions and show recovery of metal implants. In patients without implants, UpCT-MLAA had acceptable but slightly higher root-mean-squared-error (RMSE) than Zero-echotime and Dixon Deep pseudo-CT when compared to CTAC. In patients with metal implants, MLAA recovered the metal implant; however, anatomy outside the implant region was obscured by noise and crosstalk artifacts. Attenuation coefficients from the pseudo-CT from Dixon MRI were accurate in normal anatomy; however, the metal implant region was estimated to have attenuation coefficients of air. UpCT-MLAA estimated attenuation coefficients of metal implants alongside accurate anatomic depiction outside of implant regions.

[18F]-sodium fluoride PET/MR for painful lumbar facet joint degeneration - a randomized controlled clinical trial

BACKGROUND CONTEXT

[18F]-sodium fluoride (NaF) PET/MR is a modern diagnostic modality for imaging increased bone turnover. Its merits in detecting painful facet joint osteoarthritis in patients with lumbar back pain are unknown.

PURPOSE

To perform a prospective randomized controlled study investigating [18F]-NaF PET/MR for detecting painful facet joints in comparison to the standard of care (SOC), including clinical examination and conventional MRI.

STUDY DESIGN/SETTING

Randomized controlled clinical study.

PATIENT SAMPLE

Thirty-nine patients.

OUTCOME MEASURES

Visual analog pain scale (VAS) before and at several time points after facet joint infiltration.

METHODS

Patients with low back pain and suspected facet joint osteoarthritis underwent lumbar [18F]-NaF PET/MR, besides conventional MRI and clinical examination. After randomization, they either received local anesthetics/ corticosteroid infiltration of facet joints as defined by clinical examination and conventional MRI (SOC), or according to the hot spots on PET/MR. VAS was documented at 15 minutes, 1 day, 1 week and 1 month after infiltration. Thirty-nine patients underwent PET/MR before the study was stopped due to new Good Manufacturing Practice requirement and new regulations by radiation protection authorities limiting staff radiation exposure during the production of this radiotracer.

RESULTS

Significant pain reduction compared to baseline was shown at every timepoint in both groups, except at 1 month after infiltration in the SOC group. Pain levels did not differ between SOC (n=17) and PET/MR patients (n=12) before infiltration and at 15 minutes, 1 day, 1 week and 1 month after infiltration. No significant correlation was detected between the sum of the PET/MR activity and the initial pain scores or relative reduction of pain after 15 minutes. The constructed study groups of patients with infiltration of all facet joints being PET/MR-positive (n=18) had significantly less pain after 1 months than patients with infiltration in PET/MR-negative facet joints (n=11) (VAS: 4 [0, 9] vs. 7 [2, 10], p=.046).

CONCLUSIONS

There is no correlation of pain to NaF activity nor a relevant superiority of [18F]-NaF PET/MR for identification of painful facet joints compared to the standard of care.

Advances in Preclinical PET

The classical intent of PET imaging is to obtain the most accurate estimate of the amount of positron-emitting radiotracer in the smallest possible volume element located anywhere in the imaging subject at any time using the least amount of radioactivity. Reaching this goal, however, is confounded by an enormous array of interlinked technical issues that limit imaging system performance. As a result, advances in PET, human or animal, are the result of cumulative innovations across each of the component elements of PET, from data acquisition to image analysis. In the report that follows, we trace several of these advances across the imaging process with a focus on small animal PET.

Effect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma

OBJECTIVE

Recently, a new Bayesian penalty likelihood (BPL) reconstruction algorithm has been applied in PET, which is expected to provide better image resolution than the widely used ordered subset expectation maximization (OSEM). The purpose of this study is to compare the differences between these two algorithms in terms of image quality and effects on clinical diagnostics and quantification of lymphoma.

METHODS

A total of 246 FDG-positive lesions in 70 patients with lymphoma were retrospectively analyzed by using BPL and OSEM + time-of-flight + point spread function algorithms. Visual analysis was used to evaluate the effects of different reconstruction algorithms on clinical image quality and diagnostic certainty. Quantitative analysis was used to compare the differences between pathology and lesion size.

RESULTS

There were significant differences in lesion-related SUVmax, total-lesion-glycolysis (TLG), and signal-to-background ratio (SBR) (P < 0.01). The variation Δ SUVmax% and Δ SBR% caused by the two reconstruction algorithms were negatively correlated with tumor diameter, while Δ MTV% and Δ TLG% were positively correlated with tumor diameter. In the grouped analysis based on pathology, there were significant differences in lesion SUVmax, lesion SUVmean, and SBR. In non-Hodgkin's lymphoma (diffuse large B cells and follicular lymphoma), diversities were significantly found in SUVmax, SUVmean, SBR, and TLG of the lesions (P < 0.05). According to the grouped analysis based on lesion size, for lesions smaller than 1 cm and 2 cm, there was a significant difference in SUVmean, SUVmax, SBR, and MTV, but not in lesions larger than or equal to 2 cm (P > 0.05), and the liver background SUVmean (P > 0.05) remained unchanged.

CONCLUSION

BPL reconstruction algorithm could effectively improve clinical image quality and diagnostic certainty. In quantitative analysis, there were no significant differences among different pathological groups, but there were significant diversities in lesion sizes. Especially for small lesions, lesion SUVmax increased and SBR was significantly improved, which may better assist in the diagnosis of small lesions of lymphoma.

Estimation of the Internal Dose Imparted by 18F-Fluorodeoxyglucose to Tissues by Using Fricke Dosimetry in a Phantom and Positron Emission Tomography

Purpose

Assessment of the radiation dose delivered to a tumor and different organs is a major issue when using radiolabelled compounds for diagnostic imaging or endoradiotherapy. The present article reports on a study to correlate the mean 18F-fluorodeoxyglucose (18F-FDG) activity in different tissues measured in a mouse model by positron emission tomography (PET) imaging, with the dose assessed in vitro by Fricke dosimetry.

Methods

The dose-response relationship of the Fricke dosimeter and PET data was determined at different times after adding 18F-FDG (0-80 MBq) to a Fricke solution (1 mM ferrous ammonium sulfate in 0.4 M sulfuric acid). The total dose was assessed at 24 h (~13 half-lives of 18F-FDG). The number of coincident events produced in 3 mL of Fricke solution or 3 mL of deionized water that contained 60 MBq of 18F-FDG was measured using the Triumph/LabPET8TM preclinical PET/CT scanner. The total activity concentration measured by PET was correlated with the calculated dose from the Fricke dosimeter, at any exposure activity of 18F-FDG.

Results

The radiation dose measured with the Fricke dosimeter increased rapidly during the first 4 h after adding 18F-FDG and then gradually reached a plateau. Presence of non-radioactive-FDG did not alter the Fricke dosimetry. The characteristic responses of the dosimeter and PET imaging clearly exhibit linearity with injected activity of 18F-FDG. The dose (Gy) to time-integrated activity (MBq.h) relationship was measured, yielding a conversion factor of 0.064 ± 0.06 Gy/MBq.h in the present mouse model. This correlation provides an efficient alternative method to measure, three-dimensionally, the total and regional dose absorbed from 18F-radiotracers.

Conclusions

The Fricke dosimeter can be used to calibrate a PET scanner, thus enabling the determination of dose from the measured radioactivity emitted by 18F-FDG in tissues. The method should be applicable to radiotracers with other positron-emitting radionuclides.

Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging

OBJECTIVE

In quantitative positron emission tomography (PET) of the brain, partial volume effect due mainly to the finite spatial resolution of the PET scanner (> 3 mm full width at half maximum [FWHM]) is a primary source of error in the measurement of tracer uptake, especially in small structures such as the cerebral cortex (typically < 3 mm thickness). The aim of this study was to evaluate the partial volume correction (PVC) performance of point spread function-incorporated reconstruction (PSF reconstruction) in combination with the latest digital PET scanner. This evaluation was performed through direct comparisons with magnetic resonance imaging (MR)-based PVC (used as a reference method) in a human brain study.

METHODS

Ten healthy subjects underwent brain ¹⁸F-FDG PET (30-min acquisition) on a digital PET/CT system (Siemens Biograph Vision, 3.5-mm FWHM scanner resolution at the center of the field of view) and anatomical T1-weighted MR imaging for MR-based PVC. PSF reconstruction was applied with a wide range of iterations (4 to 256; 5 subsets). FDG uptake in the cerebral cortex was evaluated using the standardized uptake value ratio (SUVR) and compared between PSF reconstruction and MR-based PVC.

RESULTS

Cortical structures were visualized by PSF reconstruction with several tens of iterations and were anatomically well matched with the MR-derived cortical segments. Higher numbers of iterations resulted in higher cortical SUVRs, which approached those of MR-based PVC (1.76), although even with the maximum number of iterations they were still smaller by 16% (1.47), corresponding to approximately 1.5-mm FWHM of the effective spatial resolution.

CONCLUSION

With the latest digital PET scanner, PSF reconstruction can be used as a PVC technique in brain PET, albeit with suboptimal resolution recovery. A relative advantage of PSF reconstruction is that it can be applied not only to cerebral cortical regions, but also to various small structures such as small brain nuclei that are hardly visualized on anatomical T1-weighted imaging, and thus hardly recovered by MR-based PVC.

Photoacoustic Tomography Image Restoration With Measured Spatially Variant Point Spread Functions

The spatial resolution of photoacoustic tomography (PAT) can be characterized by the point spread function (PSF) of the imaging system. Due to the tomographic detection geometry, the PAT image degradation model could be generally described by using spatially variant PSFs. Deconvolution of the PAT image with these PSFs could restore image resolution and recover object details. Previous PAT image restoration algorithms assume that the degraded images can be restored by either a single uniform PSF, or some blind estimation of the spatially variant PSFs. In this work, we propose a PAT image restoration method to improve image quality and resolution based on experimentally measured spatially variant PSFs. Using photoacoustic absorbing microspheres, we design a rigorous PSF measurement procedure, and successfully acquire a dense set of spatially variant PSFs for a commercial cross-sectional PAT system. A pixel-wise PSF map is further obtained by employing a multi-Gaussian-based fitting and interpolation algorithm. To perform image restoration, an optimization-based iterative restoration model with two kinds of regularizations is proposed. We perform phantom and in vivo mice imaging experiments to verify the proposed method, and the results show significant image quality and resolution improvement.

Pitfalls on PET/CT Due to Artifacts and Instrumentation

PET/CT has become a preferred imaging modality over PET-only scanners in clinical practice. However, along with the significant improvement in diagnostic accuracy and patient throughput, pitfalls on PET/CT are reported as well. This review provides a general overview on the potential influence of the limitations with respect to PET/CT instrumentation and artifacts associated with the modality integration on the image appearance and quantitative accuracy of PET. Approaches proposed in literature to address the limitations or minimize the artifacts are discussed as well as their current challenges for clinical applications. Although the CT component can play an important role in assisting clinical diagnosis, we concentrate on the imaging scenarios where CT is used to provide auxiliary information for attenuation compensation and scatter correction in PET.

OMEGA-open-source emission tomography software

In this paper we present OMEGA, an open-source software, for efficient and fast image reconstruction in positron emission tomography (PET). OMEGA uses the scripting language of MATLAB and GNU Octave allowing reconstruction of PET data with a MATLAB or GNU Octave interface. The goal of OMEGA is to allow easy and fast reconstruction of any PET data, and to provide a computationally efficient, easy-access platform for development of new PET algorithms with built-in forward and backward projection operations available to the user as a MATLAB/Octave class. OMEGA also includes direct support for GATE simulated data, facilitating easy evaluation of the new algorithms using Monte Carlo simulated PET data. OMEGA supports parallel computing by utilizing OpenMP for CPU implementations and OpenCL for GPU allowing any hardware to be used. OMEGA includes built-in function for the computation of normalization correction and allows several other corrections to be applied such as attenuation, randoms or scatter. OMEGA includes several different maximum-likelihood and maximum a posteriori (MAP) algorithms with several different priors. The user can also input their own priors to the built-in MAP functions. The image reconstruction in OMEGA can be computed either by using an explicitly computed system matrix or with a matrix-free formalism, where the latter can be accelerated with OpenCL. We provide an overview on the software and present some examples utilizing the different features of the software.

Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging

Background

The Siemens high-resolution research tomograph (HRRT - a dedicated brain PET scanner) is to this day one of the highest resolution PET scanners; thus, it can serve as useful benchmark when evaluating performance of newer scanners. Here, we report results from a cross-validation study between the HRRT and the whole-body GE SIGNA PET/MR focusing on brain imaging.

Phantom data were acquired to determine recovery coefficients (RCs), % background variability (%BG), and image voxel noise (%). Cross-validation studies were performed with six healthy volunteers using [¹¹C]DTBZ, [¹¹C]raclopride, and [¹⁸F]FDG. Line profiles, regional time-activity curves, regional non-displaceable binding potentials (BP_ND) for [¹¹C]DTBZ and [¹¹C]raclopride scans, and radioactivity ratios for [¹⁸F]FDG scans were calculated and compared between the HRRT and the SIGNA PET/MR.

Results

Phantom data showed that the PET/MR images reconstructed with an ordered subset expectation maximization (OSEM) algorithm with time-of-flight (TOF) and TOF + point spread function (PSF) + filter revealed similar RCs for the hot spheres compared to those obtained on the HRRT reconstructed with an ordinary Poisson-OSEM algorithm with PSF and PSF + filter. The PET/MR TOF + PSF reconstruction revealed the highest RCs for all hot spheres. Image voxel noise of the PET/MR system was significantly lower. Line profiles revealed excellent spatial agreement between the two systems. BP_ND values revealed variability of less than 10% for the [¹¹C]DTBZ scans and 19% for [¹¹C]raclopride (based on one subject only). Mean [¹⁸F]FDG ratios to pons showed less than 12% differences.

Conclusions

These results demonstrated comparable performances of the two systems in terms of RCs with lower voxel-level noise (%) present in the PET/MR system. Comparison of in vivo human data confirmed the comparability of the two systems. The whole-body GE SIGNA PET/MR system is well suited for high-resolution brain imaging as no significant performance degradation was found compared to that of the reference standard HRRT.

Impact of the Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

Background

Q.Clear is a new Bayesian penalized-likelihood PET reconstruction algorithm. It has been documented that Q.Clear increases the SUVmax values of different malignant lesions.

Purpose

SUVmax values are crucial for the interpretation of PET/CT images in patients with lymphoma, particularly when the early and final responses to treatment are evaluated. The aim of the study was to systematically analyse the impact of the use of Q.Clear on the interpretation of PET/CT in patients with lymphoma.

Methods

A total of 280 ¹⁸F-FDG PET/CT scans in patients with lymphoma were performed for staging (sPET), for early treatment response (iPET), after the end of treatment (ePET) and when a relapse of lymphoma was suspected (rPET). Scans were separately reconstructed with two algorithms, Q.Clear and OSEM, and further compared.

Results

The stage of lymphoma was concordantly diagnosed in 69/70 patients with both algorithms on sPET. Discordant assessment of the Deauville score (p < 0.001) was found in 11 cases (15.7%) of 70 iPET scans and in 11 cases of 70 ePET scans. An upgrade from a negative to a positive scan by Q.Clear occurred in 3 cases (4.3%) of iPET scans and 7 cases (10.0%) of ePET scans. The results of all 70 rPET scans were concordant. The SUVmax values of the target lymphoma lesions measured with Q.Clear were higher than those measured with OSEM in 88.8% of scans.

Conclusion

Although the Q.Clear algorithm may alter the interpretations of PET/CT in only a small proportion of patients, we recommend using standard OSEM reconstruction for the assessment of treatment response.

Evaluation of quantitative, efficient image reconstruction for VersaPET, a compact PET system

PURPOSE

Previously we developed a high-resolution positron emission tomography (PET) system-VersaPET-characterized by a block geometry with relatively large axial and transaxial interblock gaps and a compact geometry susceptible to parallax blurring effects. In this work, we report the qualitative and quantitative evaluation of a graphic processing unit (GPU)-accelerated maximum-likelihood by expectation-maximization (MLEM) image reconstruction framework for VersaPET which features accurate system geometry and projection space point-spread-function (PSF) modeling.

METHODS

We combined the ray-tracing module from software for tomographic image reconstruction (STIR), an open-source PET image reconstruction package, with VersaPET's exact block geometry for the geometric system matrix. Point-spread-function modeling of crystal penetration and scattering was achieved by a custom Monte-Carlo simulation for projection space blurring in all dimensions. We also parallelized the reconstruction in GPU taking advantage of the system's symmetry for PSF computation. To investigate the effects of PSF width, we generated and studied multiple kernels between one that reflects the true LYSO density in the MC simulation and another that reflects geometry only (no PSF). GATE simulations of hot and cold-sphere phantoms with spheres of different sizes, real microDerenzo phantom, and human blood vessel data were used to characterize the quantitative and qualitative performances of the reconstruction.

RESULTS

Reconstruction with an accurate system geometry effectively improved image quality compared to STIR (version 3.0) which assumes an idealized system geometry. Reconstructions of GATE-simulated hot-sphere phantom data showed that all PSF kernels achieved superior performance in contrast recovery and bias reduction compared to using no PSF, but may introduce edge artifact and lumped background noise pattern depending on the width of PSF kernels. Cold-sphere phantom simulation results also indicated improvement in contrast recovery and quantification with PSF modeling (compared to no PSF) for 5 and 10 mm cold spheres. Real microDerenzo phantom images with the PSF kernel that reflects the true LYSO density showed degraded resolving power of small sectors that could be resolved more clearly by underestimated PSF kernels, which is consistent with recent literature despite differences in scanner geometries and in approaches to system model estimation. The human vessel results resemble those of the hot-sphere phantom simulation with the PSF kernel that reflects the true LYSO density achieving the highest peak in the time activity curve (TAC) and similar lumped noise pattern.

CONCLUSIONS

We fully evaluated a practical MLEM reconstruction framework that we developed for VersaPET in terms of qualitative and quantitative performance. Different PSF kernels may be adopted for improving the results of specific imaging tasks but the underlying reasons for the variation in optimal kernel for the real and simulation studies requires further study.

Comments on the NEMA NU 4-2008 Standard on Performance Measurement of Small Animal Positron Emission Tomographs

The National Electrical Manufacturers Association’s (NEMA) NU 4-2008 standard specifies methodology for evaluating the performance of small-animal PET scanners. The standard’s goal is to enable comparison of different PET scanners over a wide range of technologies and geometries used. In this work, we discuss if the NEMA standard meets these goals and we point out potential flaws and improvements to the standard.For the evaluation of spatial resolution, the NEMA standard mandates the use of filtered backprojection reconstruction. This reconstruction method can introduce star-like artifacts for detectors with an anisotropic spatial resolution, usually caused by parallax error. These artifacts can then cause a strong dependence of the resulting spatial resolution on the size of the projection window in image space, whose size is not fully specified in the NEMA standard. If the PET ring has detectors which are perpendicular to a Cartesian axis, then the resolution along this axis will typically improve with larger projection windows.We show that the standard’s equations for the estimation of the random rate for PET systems with intrinsic radioactivity are circular and not satisfiable. However, a modified version can still be used to determine an approximation of the random rates under the assumption of negligible random rates for small activities and a constant scatter fraction. We compare the resulting estimated random rates to random rates obtained using a delayed coincidence window and two methods based on the singles rates. While these methods give similar estimates, the estimation method based on the NEMA equations overestimates the random rates.In the NEMA standard’s protocol for the evaluation of the sensitivity, the standard specifies to axially step a point source through the scanner and to take a different scan for each source position. Later, in the data analysis section, the standard does not specify clearly how the different scans have to be incorporated into the analysis, which can lead to unclear interpretations of publicized results.The standard’s definition of the recovery coefficients in the image quality phantom includes the maximum activity in a region of interest, which causes a positive correlation of noise and recovery coefficients. This leads to an unintended trade-off between desired uniformity, which is negatively correlated with variance (i.e., noise), and recovery.With this work, we want to start a discussion on possible improvements in a next version of the NEMA NU-4 standard.

The value of Bayesian penalized likelihood reconstruction for improving lesion conspicuity of malignant lung tumors on 18F-FDG PET/CT: comparison with ordered subset expectation maximization reconstruction incorporating time-of-flight model and point spread function correction

OBJECTIVE

To evaluate the value of Bayesian penalized likelihood (BPL) reconstruction for improving lesion conspicuity of malignant lung tumors on ¹⁸F-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography computed tomography (PET/CT) as compared with the ordered subset expectation maximization (OSEM) reconstruction incorporating time-of-flight (TOF) model and point-spread-function (PSF) correction.

METHODS

Twenty-nine patients with primary or metastatic lung cancers who underwent ¹⁸F-FDG PET/CT were retrospectively studied. PET images were reconstructed with OSEM + TOF, OSEM + TOF + PSF, and BPL with noise penalty strength β-value of 200, 400, 600, and 800. The signal-to-noise ratio (SNR) was determined in normal liver parenchyma. Lung lesion conspicuity was evaluated in 50 lung lesions by using a 4-point scale (0, no visible; 1, poor; 2, good; 3, excellent conspicuity). Two observers were independently asked to choose the most preferred reconstruction for detecting the lung lesions on a per-patient level. The maximum standardized uptake value (SUV_max) was measured in each of the 50 lung lesions.

RESULTS

Liver SNR on the images reconstructed by BPL with β-value of 600 and 800 (17.8 ± 3.7 and 22.5 ± 4.6, respectively) was significantly higher than that by OSEM + TOF + PSF (15.0 ± 3.4, p < 0.0001). BPL with β-value of 600 was chosen most frequently as the preferred reconstruction algorithm for lung lesion assessment by both observers. The conspicuity score of the lung lesions < 10 mm in diameter on images reconstructed by BPL with β-value of 600 was significantly greater than that with OSEM + TOF + PSF (2.2 ± 0.8 vs 1.6 ± 0.9, p < 0.0001), while the conspicuity score of the lesions ≥ 10 mm in diameter was not significantly different between BPL with β-value of 600 and OSEM + TOF + PSF. The mean SUV_max was increased by BPL with β-value of 600 for the lung lesions with < 10 mm in diameter, compared to OSEM + TOF + PSF (3.4 ± 3.1 to 4.2 ± 3.5, p = 0.001). In contrast, BPL with β-value of 600 did not provide increased SUV_max for the lesions  ≥ 10 mm in diameter.

CONCLUSION

BPL reconstruction significantly improves the detection of small inconspicuous malignant tumors in the lung, improving the diagnostic performance of PET/CT.

Noise reduction using a Bayesian penalized-likelihood reconstruction algorithm on a time-of-flight PET-CT scanner

PURPOSE

Q.Clear is a block sequential regularized expectation maximization (BSREM) penalized-likelihood reconstruction algorithm for PET. It tries to improve image quality by controlling noise amplification during image reconstruction. In this study, the noise properties of this BSREM were compared to the ordered-subset expectation maximization (OSEM) algorithm for both phantom and patient data acquired on a state-of-the-art PET/CT.

METHODS

The NEMA IQ phantom and a whole-body patient study were acquired on a GE DMI 3-rings system in list mode and different datasets with varying noise levels were generated. Phantom data was evaluated using four different contrast ratios. These were reconstructed using BSREM with different β-factors of 300-3000 and with a clinical setting used for OSEM including point spread function (PSF) and time-of-flight (TOF) information. Contrast recovery (CR), background noise levels (coefficient of variation, COV), and contrast-to-noise ratio (CNR) were used to determine the performance in the phantom data. Findings based on the phantom data were compared with clinical data. For the patient study, the SUV ratio, metabolic active tumor volumes (MATVs), and the signal-to-noise ratio (SNR) were evaluated using the liver as the background region.

RESULTS

Based on the phantom data for the same count statistics, BSREM resulted in higher CR and CNR and lower COV than OSEM. The CR of OSEM matches to the CR of BSREM with β = 750 at high count statistics for 8:1. A similar trend was observed for the ratios 6:1 and 4:1. A dependence on sphere size, counting statistics, and contrast ratio was confirmed by the CNR of the ratio 2:1. BSREM with β = 750 for 2.5 and 1.0 min acquisition has comparable COV to the 10 and 5.0 min acquisitions using OSEM. This resulted in a noise reduction by a factor of 2-4 when using BSREM instead of OSEM. For the patient data, a similar trend was observed, and SNR was reduced by at least a factor of 2 while preserving contrast.

CONCLUSION

The BSREM reconstruction algorithm allowed a noise reduction without a loss of contrast by a factor of 2-4 compared to OSEM reconstructions for all data evaluated. This reduction can be used to lower the injected dose or shorten the acquisition time.

Differences in edge artifacts between 68Ga- and 18F-PET images reconstructed using point spread function correction

OBJECTIVE

Edge artifacts have been reported on in relation to F-PET using point spread function correction algorithms. The positron range of Ga is longer than F, and this difference is thought to result in different edge artifacts. The purpose of this study is to clarify the difference in edge artifacts in PET images using point spread function correction in Ga- and F-PET.

METHODS

We used a National Electrical Manufacturers Association International Electrotechnical Commission body phantom. The phantom was filled severally with Ga and F solution. The PET data were obtained over a 90 minutes period using a True Point Biograph 16 scanner. The images were then reconstructed with the ordered subset expectation maximization with point spread function correction. The phantom image analyses were performed by a visual assessment of the PET images and profiles, and an absolute recovery coefficient, which was the ratio of the maximum radioactivity of any given hot sphere to its true radioactivity.

RESULTS

The ring-like edge artifacts of Ga-PET were less prominent than those in F-PET. The relative radioactivity profiles of Ga-PET showed low overshoots of the maximum radioactivity although high overshoots did appear in F-PET. The absolute recovery coefficients of Ga-PET were smaller than those of F-PET.

CONCLUSION

The edge artifacts of Ga-PET were less prominent than those of F-PET, and their overshoots were smaller. The difference in the positron range between Ga and F may possibly result in the difference in edge artifacts of images reconstructed using the point spread function correction algorithm.

Resolution modeling in projection space using a factorized multi-block detector response function for PET image reconstruction

Positron emission tomography (PET) images usually suffer from limited resolution and statistical uncertainties. However, a technique known as resolution modeling (RM) can be used to improve image quality by accurately modeling the system's detection process within the iterative reconstruction. In this study, we present an accurate RM method in projection space based on a simulated multi-block detector response function (DRF) and evaluate it on the Siemens hybrid MR-BrainPET system. The DRF is obtained using GATE simulations that consider nearly all the possible annihilation photons from the field-of-view (FOV). Intrinsically, the multi-block DRF allows the block crosstalk to be modeled. The RM blurring kernel is further generated by factorizing the blurring matrix of one line-of-response (LOR) into two independent detector responses, which can then be addressed with the DRF. Such a kernel is shift-variant in 4D projection space without any distance or angle compression, and is integrated into the image reconstruction for the BrainPET insert with single instruction multiple data (SIMD) and multi-thread support. Evaluation of simulations and measured data demonstrate that the reconstruction with RM yields significantly improved resolutions and reduced mean squared error (MSE) values at different locations of the FOV, compared with reconstruction without RM. Furthermore, the shift-variant RM kernel models the varying blurring intensity for different LORs due to the depth-of-interaction (DOI) dependencies, thus avoiding severe edge artifacts in the images. Additionally, compared to RM in single-block mode, the multi-block mode shows significantly improved resolution and edge recovery at locations beyond 10 cm from the center of BrainPET insert in the transverse plane. However, the differences have been observed to be low for patient data between single-block and multi-block mode RM, due to the brain size and location as well as the geometry of the BrainPET insert. In conclusion, the RM method proposed in this study can yield better reconstructed images in terms of resolution and MSE value, compared to conventional reconstruction without RM.

Performance evaluation of the 5-Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2-2012 Standard

The GE Discovery MI PET/CT system has a modular digital detector design allowing three, four, or five detector block rings that extend the axial field-of-view (FOV) from 15 to 25 cm in 5 cm increments. This study investigated the performance of the 5-ring system and compared it to 3- and 4-ring systems; the GE Discovery IQ system that uses conventional photomultiplier tubes; and the GE Signa PET/MR system that has a reduced transaxial FOV.

METHODS

PET performance was evaluated at three different institutions. Spatial resolution, sensitivity, counting rate performance, accuracy, and image quality were measured in accordance with National Electrical Manufacturers Association NU 2-2012 standards. The mean energy resolution, mean timing resolution, and PET/CT subsystem alignment were also measured. Phantoms were used to determine the effects of varying acquisition time and reconstruction parameters on image quality. Retrospective patient scans were reconstructed with various scan durations to evaluate the impact on image quality.

RESULTS

Results from all three institutions were similar. Radial/tangential/axial full width at half maximum spatial resolution measurements using the filtered back projection algorithm were 4.3/4.3/5.0 mm, 5.5/4.6/6.5 mm, and 7.4/5.0/6.6 mm at 1, 10, and 20 cm from the center of the FOV, respectively. Measured sensitivity at the center of the FOV (20.84 cps/kBq) was significantly higher than systems with reduced axial FOV. The peak noise-equivalent counting rate was 266.3 kcps at 20.8 kBq/ml, with a corresponding scatter fraction of 40.2%. The correction accuracy for count losses up to the peak noise-equivalent counting rate was 3.6%. For the 10-, 13-, 17-, 22-, 28-, and 37-mm spheres, contrast recoveries in the image quality phantom were measured to be 46.2%, 54.3%, 66.1%, 71.1%, 85.3%, and 89.3%, respectively. The mean energy and timing resolution were 9.55% and 381.7 ps, respectively. Phantom and patient images demonstrated excellent image quality, even at short acquisition times or low injected activity.

CONCLUSION

Compared to other PET/CT models, the extended axial FOV improved the overall PET performance of the 5-ring GE Discovery MI scanner. This system offers the potential to reduce scan times or injected activities through increased sensitivity.

Dynamic 11C-PiB PET Shows Cerebrospinal Fluid Flow Alterations in Alzheimer Disease and Multiple Sclerosis

Cerebrospinal fluid (CSF) plays an important role in solute clearance and maintenance of brain homeostasis. ¹¹C-Pittsburgh compound B (PiB) PET was recently proposed as a tool for detection of CSF clearance alterations in Alzheimer disease. The current study investigates the magnitude of ¹¹C-PiB PET signal in the lateral ventricles of an independent group of Alzheimer and mild cognitive impairment subjects. We have also evaluated multiple sclerosis as a model of disease with CSF clearance alterations without amyloid-β tissue accumulation. Methods: A set of 11 Alzheimer and 12 mild cognitive impairment subjects and a set of 20 multiple sclerosis subjects with matched controls underwent MRI and dynamic ¹¹C-PiB PET. Lateral ventricle regions of interest were generated manually from MRI data. PET data were analyzed using cerebellum or a supervised reference region for the Alzheimer and multiple sclerosis data sets, respectively. The magnitude of ¹¹C-PiB signal in the lateral ventricles was calculated as area under the curve from 35 to 80 min and SUV ratio (SUVR) from 50 to 70 min. Compartmental modeling analysis was performed on a separate data set containing 11 Alzheimer and matched control subjects; this analysis included an arterial input function, to further understand the kinetics of the lateral ventricular ¹¹C-PiB signal. Results: ANOVA revealed significant group differences in lateral ventricular SUVR across the Alzheimer, mild cognitive impairment, and healthy control groups (P = 0.004). Pairwise comparisons revealed significantly lower lateral ventricular SUVR in Alzheimer subjects than in healthy controls (P < 0.001) or mild cognitive impairment subjects (P = 0.029). Lateral ventricular SUVR was significantly lower in multiple sclerosis subjects than in healthy controls (P = 0.008). Compartmental modeling analysis revealed significantly lower uptake rates of ¹¹C-PiB signal from blood (P = 0.005) and brain tissue (P = 0.004) to the lateral ventricles and significantly lower ¹¹C-PiB signal clearance out of the lateral ventricles (P = 0.002) in Alzheimer subjects than in healthy controls. Conclusion: These results indicate that dynamic ¹¹C-PiB PET can be used to observe pathologic changes in CSF dynamics. We have replicated previous work demonstrating CSF clearance deficits in Alzheimer disease associated with amyloid-β deposits and have extended the observations to include ventricular CSF clearance deficits in mild cognitive impairment and multiple sclerosis.

Activity painting: PET images of freely defined activity distributions applying a novel phantom technique

The aim of this work was to develop a novel phantom that supports the construction of highly reproducible phantoms with arbitrary activity distributions for PET imaging. It could offer a methodology for answering questions related to texture measurements in PET imaging. The basic idea is to move a point source on a 3-D trajectory in the field of view, while continuously acquiring data. The reconstruction results in a 3-D activity concentration map according to the pathway of the point source. A 22Na calibration point source was attached to a high precision robotic arm system, where the 3-D movement was software controlled. 3-D activity distributions of a homogeneous cube, a sphere, a spherical shell and a heart shape were simulated. These distributions were used to measure uniformity and to characterize reproducibility. Two potential applications using the lesion simulation method are presented: evaluation in changes of textural properties related to the position in the PET field of view; scanner comparison based on visual and quantitative evaluation of texture features. A lesion with volume of 50x50x50 mm3 can be simulated during approximately 1 hour. The reproducibility of the movement was found to be >99%. The coefficients of variation of the voxels within a simulated homogeneous cube was 2.34%. Based on 5 consecutive and independent measurements of a 36 mm diameter hot sphere, the coefficient of variation of the mean activity concentration was 0.68%. We obtained up to 18% differences within the values of investigated textural indexes, when measuring a lesion in different radial positions of the PET field of view. In comparison of two different human PET scanners the percentage differences between heterogeneity parameters were in the range of 5-55%. After harmonizing the voxel sizes this range reduced to 2-16%. The general activity distributions provided by the two different vendor show high similarity visually. For the demonstration of the flexibility of this method, the same pattern was also simulated on a small animal PET scanner giving similar results, both quantitatively and visually. 3-D motion of a point source in the PET field of view is capable to create an irregular shaped activity distribution with high reproducibility.

Validation of the physiological background correction method for the suppression of the spill-in effect near highly radioactive regions in positron emission tomography

Background

Positron emission tomography (PET) imaging has a wide applicability in oncology, cardiology and neurology. However, a major drawback when imaging very active regions such as the bladder is the spill-in effect, leading to inaccurate quantification and obscured visualisation of nearby lesions. Therefore, this study aims at investigating and correcting for the spill-in effect from high-activity regions to the surroundings as a function of activity in the hot region, lesion size and location, system resolution and application of post-filtering using a recently proposed background correction technique. This study involves analytical simulations for the digital XCAT2 phantom and validation acquiring NEMA phantom and patient data with the GE Signa PET/MR scanner. Reconstructions were done using the ordered subset expectation maximisation (OSEM) algorithm. Dedicated point-spread function (OSEM+PSF) and a recently proposed background correction (OSEM+PSF+BC) were incorporated into the reconstruction for spill-in correction. The standardised uptake values (SUV) were compared for all reconstruction algorithms.

Results

The simulation study revealed that lesions within 15–20 mm from the hot region were predominantly affected by the spill-in effect, leading to an increased bias and impaired lesion visualisation within the region. For OSEM, lesion SUV_max converged to the true value at low bladder activity, but as activity increased, there was an overestimation as much as 19% for proximal lesions (distance around 15–20 mm from the bladder edge) and 2–4% for distant lesions (distance larger than 20 mm from the bladder edge). As bladder SUV increases, the % SUV change for proximal lesions is about 31% and 6% for SUV_max and SUV_mean, respectively, showing that the spill-in effect is more evident for the SUV_max than the SUV_mean. Also, the application of post-filtering resulted in up to 65% increment in the spill-in effect around the bladder edges. For proximal lesions, PSF has no major improvement over OSEM because of the spill-in effect, coupled with the blurring effect by post-filtering. Within two voxels around the bladder, the spill-in effect in OSEM is 42% (32%), while for OSEM+PSF, it is 31% (19%), with (and without) post-filtering, respectively. But with OSEM+PSF+BC, the spill-in contribution from the bladder was relatively low (below 5%, either with or without post-filtering). These results were further validated using the NEMA phantom and patient data for which OSEM+PSF+BC showed about 70–80% spill-in reduction around the bladder edges and increased contrast-to-noise ratio up to 36% compared to OSEM and OSEM+PSF reconstructions without post-filtering.

Conclusion

The spill-in effect is dependent on the activity in the hot region, lesion size and location, as well as post-filtering; and this is more evident in SUV_max than SUV_mean. However, the recently proposed background correction method facilitates stability in quantification and enhances the contrast in lesions with low uptake.

Electronic supplementary material

The online version of this article (10.1186/s40658-018-0233-8) contains supplementary material, which is available to authorized users.

How to harmonize SUVs obtained by hybrid PET/CT scanners with and without point spread function correction

State of the art point-spread function (PSF) corrections implemented in positron emission tomography/computed tomography (PET/CT) reconstruction improved image quality and diagnostic performance but caused an increase in the standardized uptake value (SUV) compared to a conventional OSEM reconstruction system. The EANM suggested one produce two reconstructions, one optimised for maximum lesion detection and one for semi-quantitative analysis. In this work we investigated an alternative methodology, using a single reconstruction data set together with a post-reconstruction algorithm for SUV harmonization. Data acquisition was performed on a Siemens Biograph mCT system equipped with lutetium oxyorthosilicat crystals, PSF and time-of-flight algorithms and on a General Electric Discovery STE system equipped with BGO crystals. Both a EANM double reconstruction method and a dedicated post-reconstruction algorithm (marketed as EQ-filter) were tested to harmonize the quantitative values of the two PET/CT scanners. For phantom measurements we used a NEMA IQ phantom and a Jaszczak cylindrical phantom equipped with small spheres (lesion to background ratios of 8:1 and 4:1). Several different reconstruction settings were tested in order to provide a general methodology. Data obtained by phantom measurements were validated on seven oncologic patients who performed a one-bed extra acquisition on a different scanner. The evaluation regarded 39 small lesions (diameters: 0.3-2.6 cm) and was performed by two experienced nuclear medicine physicians. The SUV recoveries measured with the PSF reconstruction exceeded those obtained by the OSEM reconstruction with deviations ranging from 16% to 150%. These discrepancies resulted below 7% applying the optimized value of the EQ.filter or the double-reconstruction methods. For each reconstruction setting the optimal value of the EQ.filter was identified in order to minimize these discrepancies. Patient data, analyzed by Wilcoxon statistical test, confirmed and validated phantom measurements. EQ.filter can harmonize SUV values between different PET/CT scanners using a single reconstruction optimized to maximum lesion detectability. In this way, the second reconstruction proposed by EANM/EARL is avoided.

Calibration Software for Quantitative PET/CT Imaging Using Pocket Phantoms

Multicenter clinical trials that use positron emission tomography (PET) imaging frequently rely on stable bias in imaging biomarkers to assess drug effectiveness. Many well-documented factors cause variability in PET intensity values. Two of the largest scanner-dependent errors are scanner calibration and reconstructed image resolution variations. For clinical trials, an increase in measurement error significantly increases the number of patient scans needed. We aim to provide a robust quality assurance system using portable PET/computed tomography “pocket” phantoms and automated image analysis algorithms with the goal of reducing PET measurement variability. A set of the “pocket” phantoms was scanned with patients, affixed to the underside of a patient bed. Our software analyzed the obtained images and estimated the image parameters. The analysis consisted of 2 steps, automated phantom detection and estimation of PET image resolution and global bias. Performance of the algorithm was tested under variations in image bias, resolution, noise, and errors in the expected sphere size. A web-based application was implemented to deploy the image analysis pipeline in a cloud-based infrastructure to support multicenter data acquisition, under Software-as-a-Service (SaaS) model. The automated detection algorithm localized the phantom reliably. Simulation results showed stable behavior when image properties and input parameters were varied. The PET “pocket” phantom has the potential to reduce and/or check for standardized uptake value measurement errors.

A novel depth-of-interaction rebinning strategy for ultrahigh resolution PET

Small animal positron emission tomography (PET) imaging often requires high resolution (∼few hundred microns) to enable accurate quantitation in small structures such as animal brains. Recently, we have developed a prototype ultrahigh resolution depth-of-interaction (DOI) PET system that uses CdZnTe detectors with a detector pixel size of 350 μm and eight DOI layers with a 250 μm depth resolution. Due to the large number of line-of-response (LOR) combinations of DOIs, the system matrix for reconstruction is 64 times larger than that without DOI. While a high resolution virtual ring geometry can be employed to simplify the system matrix and create a sinogram, the LORs in such a sinogram tend to be sparse and irregular, leading to potential degradation of the reconstructed image quality. In this paper, we propose a novel high resolution sinogram rebinning method in which a uniform sub-sampling DOI strategy is employed. However, even with the high resolution rebinning strategy, the reconstructed image tends to be very noisy due to insufficient photon counts in many high resolution sinogram pixels. To reduce noise effects, we developed a penalized maximum likelihood reconstruction framework with the Poisson log-likelihood and a non-convex total variation penalty. Here, an ordered subsets separable quadratic surrogate and alternating direction method of multipliers are utilized to solve the optimization. To evaluate the performance of the proposed sub-sampling method and the penalized maximum likelihood reconstruction technique, we perform simulations and preliminary point source experiments. By comparing the reconstructed images and profiles based on sinograms without DOI, with rebinned DOI and with sub-sampled DOI, we demonstrate that the proposed method with sub-sampled DOIs can significantly improve the image quality with lower dose and yield a high resolution of  <300 μm.

Simultaneous Estimation of Bias and Resolution in PET Images With a Long-Lived "Pocket" Phantom System

A challenge in multicenter trials that use quantitative positron emission tomography (PET) imaging is the often unknown variability in PET image values, typically measured as standardized uptake values, introduced by intersite differences in global and resolution-dependent biases. We present a method for the simultaneous monitoring of scanner calibration and reconstructed image resolution on a per-scan basis using a PET/computed tomography (CT) "pocket" phantom. We use simulation and phantom studies to optimize the design and construction of the PET/CT pocket phantom (120 × 30 × 30 mm). We then evaluate the performance of the PET/CT pocket phantom and accompanying software used alongside an anthropomorphic phantom when known variations in global bias (±20%, ±40%) and resolution (3-, 6-, and 12-mm postreconstruction filters) are introduced. The resulting prototype PET/CT pocket phantom design uses 3 long-lived sources (15-mm diameter) containing germanium-68 and a CT contrast agent in an epoxy matrix. Activity concentrations varied from 30 to 190 kBq/mL. The pocket phantom software can accurately estimate global bias and can detect changes in resolution in measured phantom images. The pocket phantom is small enough to be scanned with patients and can potentially be used on a per-scan basis for quality assurance for clinical trials and quantitative PET imaging in general. Further studies are being performed to evaluate its performance under variations in clinical conditions that occur in practice.

Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images

Positron emission tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as magnetic resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior to other Dixon-based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure.

Joint estimation of activity and attenuation for PET using pragmatic MR-based prior: application to clinical TOF PET/MR whole-body data for FDG and non-FDG tracers

Accurate and robust attenuation correction remains challenging in hybrid PET/MR particularly for torsos because it is difficult to segment bones, lungs and internal air in MR images. Additionally, MR suffers from susceptibility artifacts when a metallic implant is present. Recently, joint estimation (JE) of activity and attenuation based on PET data, also known as maximum likelihood reconstruction of activity and attenuation, has gained considerable interest because of (1) its promise to address the challenges in MR-based attenuation correction (MRAC), and (2) recent advances in time-of-flight (TOF) technology, which is known to be the key to the success of JE. In this paper, we implement a JE algorithm using an MR-based prior and evaluate the algorithm using whole-body PET/MR patient data, for both FDG and non-FDG tracers, acquired from GE SIGNA PET/MR scanners with TOF capability. The weight of the MR-based prior is spatially modulated, based on MR signal strength, to control the balance between MRAC and JE. Large prior weights are used in strong MR signal regions such as soft tissue and fat (i.e. MR tissue classification with a high degree of certainty) and small weights are used in low MR signal regions (i.e. MR tissue classification with a low degree of certainty). The MR-based prior is pragmatic in the sense that it is convex and does not require training or population statistics while exploiting synergies between MRAC and JE. We demonstrate the JE algorithm has the potential to improve the robustness and accuracy of MRAC by recovering the attenuation of metallic implants, internal air and some bones and by better delineating lung boundaries, not only for FDG but also for more specific non-FDG tracers such as 68Ga-DOTATOC and 18F-Fluoride.

Optimization of PET/CT image quality using the GE 'Sharp IR' point-spread function reconstruction algorithm

OBJECTIVE

The objective of this study was to quantify any improvement with the GE 'Sharp IR' point-spread function (PSF) reconstruction algorithm in addition to ordered subsets expectation maximum (OSEM) and time-of-flight (TOF) reconstruction algorithms and establish the optimum parameters to be used in clinical studies.

MATERIALS AND METHODS

We conducted a range of experiments using the National Electrical Manufacturers Association image quality phantom filled with a 4 : 1 signal-to-background ratio. We scanned the phantom using the GE Discovery 690 PET/CT scanner. We varied iteration number and Gaussian filtration. Results were compared for OSEM, OSEM+TOF and OSEM+TOF+PSF reconstructions. A sample of 15 whole-body fluorine-18-fluorodeoxyglucose were reconstructed with OSEM+TOF and OSEM+TOF+PSF using a selection of optimum reconstruction parameters determined in phantom studies. Clinicians qualitatively ranked their preferred images to choose optimum parameters.

RESULTS

The addition of PSF improved signal-to-noise ratios (SNRs), contrast, hot contrast recovery coefficients and noise over OSEM and OSEM+TOF reconstruction algorithms. SNRs were the highest at two iterations and with 0 or 2 mm filters with OSEM+TOF+PSF reconstruction in all phantom studies. Clinicians generally favoured OSEM+TOF+PSF reconstruction with three iterations and a 2 mm filter.

CONCLUSION

PSF reconstruction significantly improved image quality for both clinical and phantom studies. We recommended the optimum reconstruction parameters using three iterations, 24 subsets and a 2 mm filter, which improved SNRs by up to 28.8% for small lesions (P<0.05).

Sinogram Blurring Matrix Estimation From Point Sources Measurements With Rank-One Approximation for Fully 3-D PET

An accurate system matrix is essential in positron emission tomography (PET) for reconstructing high quality images. To reduce storage size and image reconstruction time, we factor the system matrix into a product of a geometry projection matrix and a sinogram blurring matrix. The geometric projection matrix is computed analytically and the sinogram blurring matrix is estimated from point source measurements. Previously, we have estimated a 2-D blurring matrix for a preclinical PET scanner. The 2-D blurring matrix only considers blurring effects within a transaxial sinogram and does not compensate for inter-sinogram blurring effects. For PET scanners with a long axial field of view, inter-sinogram blurring can be a major problem influencing the image quality in the axial direction. Hence, the estimation of a 4-D blurring matrix is desirable to further improve the image quality. The 4-D blurring matrix estimation is an ill-conditioned problem due to the large number of unknowns. Here, we propose a rank-one approximation for each blurring kernel image formed by a row vector of the sinogram blurring matrix to improve the stability of the 4-D blurring matrix estimation. The proposed method is applied to the simulated data as well as the real data obtained from an Inveon microPET scanner. The results show that the newly estimated 4-D blurring matrix can improve the image quality over those obtained with a 2-D blurring matrix and requires less point source scans to achieve similar image quality compared with an unconstrained 4-D blurring matrix estimation.

PET Imaging Stability Measurements During Simultaneous Pulsing of Aggressive MR Sequences on the SIGNA PET/MR System

The recent introduction of simultaneous whole-body PET/MR scanners has enabled new research taking advantage of the complementary information obtainable with PET and MRI. One such application is kinetic modeling, which requires high levels of PET quantitative stability. To accomplish the required PET stability levels, the PET subsystem must be sufficiently isolated from the effects of MR activity. Performance measurements have previously been published, demonstrating sufficient PET stability in the presence of MR pulsing for typical clinical use; however, PET stability during radiofrequency (RF)-intensive and gradient-intensive sequences has not previously been evaluated for a clinical whole-body scanner. In this work, PET stability of the GE SIGNA PET/MR was examined during simultaneous scanning of aggressive MR pulse sequences. Methods: PET performance tests were acquired with MR idle and during simultaneous MR pulsing. Recent system improvements mitigating RF interference and gain variation were used. A fast recovery fast spin echo MR sequence was selected for high RF power, and an echo planar imaging sequence was selected for its high heat-inducing gradients. Measurements were performed to determine PET stability under varying MR conditions using the following metrics: sensitivity, scatter fraction, contrast recovery, uniformity, count rate performance, and image quantitation. A final PET quantitative stability assessment for simultaneous PET scanning during functional MRI studies was performed with a spiral in-and-out gradient echo sequence. Results: Quantitation stability of a ⁶⁸Ge flood phantom was demonstrated within 0.34%. Normalized sensitivity was stable during simultaneous scanning within 0.3%. Scatter fraction measured with a ⁶⁸Ge line source in the scatter phantom was stable within the range of 40.4%-40.6%. Contrast recovery and uniformity were comparable for PET images acquired simultaneously with multiple MR conditions. Peak noise equivalent count rate was 224 kcps at an effective activity concentration of 18.6 kBq/mL, and the count rate curves and scatter fraction curve were consistent for the alternating MR pulsing states. A final test demonstrated quantitative stability during a spiral functional MRI sequence. Conclusion: PET stability metrics demonstrated that PET quantitation was not affected during simultaneous aggressive MRI. This stability enables demanding applications such as kinetic modeling.

Simulating effects of brain atrophy in longitudinal PET imaging with an anthropomorphic brain phantom

In longitudinal positron emission tomography (PET), the presence of volumetric changes over time can lead to an overestimation or underestimation of the true changes in the quantified PET signal due to the partial volume effect (PVE) introduced by the limited spatial resolution of existing PET cameras and reconstruction algorithms. Here, a 3D-printed anthropomorphic brain phantom with attachable striata in three sizes was designed to enable controlled volumetric changes. Using a method to eliminate the non-radioactive plastic wall, and manipulating BP levels by adding different number of events from list-mode acquisitions, we investigated the artificial volume dependence of BP due to PVE, and potential bias arising from varying BP. Comparing multiple reconstruction algorithms we found that a high-resolution ordered-subsets maximization algorithm with spatially variant point-spread function resolution modeling provided the most accurate data. For striatum, the BP changed by 0.08% for every 1% volume change, but for smaller volumes such as the posterior caudate the artificial change in BP was as high as 0.7% per 1% volume change. A simple gross correction for striatal volume is unsatisfactory, as the amplitude of the PVE on the BP differs depending on where in the striatum the change occurred. Therefore, to correctly interpret age-related longitudinal changes in the BP, we must account for volumetric changes also within a structure, rather than across the whole volume. The present 3D-printing technology, combined with the wall removal method, can be implemented to gain knowledge about the predictable bias introduced by the PVE differences in uptake regions of varying shape.