A review of partial volume correction techniques for emission tomography and their applications in neurology, cardiology and oncology

Non-invasive measures of coronary microcirculation: Taking the long road to the clinic

Although coronary microvascular disease is now a well-recognized entity that is associated with significant morbidity and mortality, current non-invasive strategies cannot differentiate between coronary microvascular disease (CMD) and obstructive epicardial stenosis. While the evaluation of intramyocardial blood volume as a surrogate measure for microvascular health may have limited sensitivity in early-stage disease, this strategy does enable the diagnosis of CMD in the presence of concurrent epicardial disease, bringing us one step further toward improving the management of this disease. Herein, we discuss the advantages and limitations of current non-invasive measures of CMD and the need for further investment in bringing these technologies to the bedside.

Enhancement of Partial Volume Correction in MR-Guided PET Image Reconstruction by Using MRI Voxel Sizes

Positron emission tomography (PET) suffers from poor spatial resolution which results in quantitative bias when evaluating the radiotracer uptake in small anatomical regions, such as the striatum in the brain which is of importance in this paper of neurodegenerative diseases. These partial volume effects need to be compensated for by employing partial volume correction (PVC) methods in order to achieve quantitatively accurate images. Two important PVC methods applied during the reconstruction are resolution modeling, which suffers from Gibbs artifacts, and penalized likelihood using anatomical priors. The introduction of clinical simultaneous PET-MR scanners has attracted new attention for the latter methods and brought new opportunities to use MRI information to assist PET image reconstruction in order to improve image quality. In this context, MR images are usually down-sampled to the PET resolution before being used in MR-guided PET reconstruction. However, the reconstruction of PET images using the MRI voxel size could achieve a better utilization of the high resolution anatomical information and improve the PVC obtained with these methods. In this paper, we evaluate the importance of the use of MRI voxel sizes when reconstructing PET images with MR-guided maximum a posteriori (MAP) methods, specifically the modified Bowsher method. We also propose a method to avoid the artifacts that arise when PET reconstructions are performed in a higher resolution matrix than the standard for a given scanner. The MR-guided MAP reconstructions were implemented with a modified Lange prior that included anatomical information with the Bowsher method. The methods were evaluated with and without resolution modeling for simulated and real brain data. We show that the use of the MRI voxel sizes when reconstructing PET images with MR-guided MAP enhances PVC by improving the contrast and reducing the bias in six different regions of the brain using regional metrics for a single simulated data set and ensemble metrics for ten noise realizations. Similar results were obtained for real data, where a good enhancement of the contrast was achieved. The combination of MR-guided MAP reconstruction with point-spread function modeling and MRI voxel sizes proved to be an attractive method to achieve considerable enhancement of PVC, while reducing and controlling the noise level and Gibbs artifacts.

Impact of image reconstruction methods on quantitative accuracy and variability of FDG-PET volumetric and textural measures in solid tumors

OBJECTIVE

This study aims to assess the impact of different image reconstruction methods on PET/CT quantitative volumetric and textural parameters and the inter-reconstruction variability of these measurements.

METHODS

A total of 25 oncology patients with 65 lesions (between 2017 and 2018) and a phantom with signal-to-background ratios (SBR) of 2 and 4 were included. All images were retrospectively reconstructed using OSEM, PSF only, TOF only, and TOFPSF with 3-, 5-, and 6.4-mm Gaussian filters. The metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. The relative percent error (ΔMTV and ΔTLG) with respect to true values, volume recovery coefficients, and Dice similarity coefficient, as well as inter-reconstruction variabilities were quantified and assessed. In clinical scans, textural features (coefficient of variation, skewness, and kurtosis) were determined.

RESULTS

Among reconstruction methods, mean ΔMTV differed by -163.5 ± 14.1% to 6.3 ± 6.2% at SBR2 and -42.7 ± 36.7% to 8.6 ± 3.1 at SBR4. Dice similarity coefficient significantly increased by increasing SBR from 2 to 4, ranging from 25.7 to 83.4% between reconstruction methods. Mean ΔTLG was -12.0 ± 1.7 for diameters > 17 mm and -17.8 ± 7.8 for diameters ≤ 17 mm at SBR4. It was -31.7 ± 4.3 for diameters > 17 mm and -14.2 ± 5.8 for diameters ≤ 17 mm at SBR2. Textural features were prone to variations by reconstruction methods (p < 0.05).

CONCLUSIONS

Inter-reconstruction variability was significantly affected by the target size, SBR, and cut-off threshold value. In small tumors, inter-reconstruction variability was noteworthy, and quantitative parameters were strongly affected. TOFPSF reconstruction with small filter size produced greater improvements in performance and accuracy in quantitative PET/CT imaging.

KEY POINTS

• Quantitative volumetric PET evaluation is critical for the analysis of tumors. • However, volumetric and textural evaluation is prone to important variations according to different image reconstruction settings. • TOFPSF reconstruction with small filter size improves quantitative analysis.

Partial volume correction for improved PET quantification in 18F-NaF imaging of atherosclerotic plaques

BACKGROUND

Accurate quantification of plaque imaging using 18F-NaF PET requires partial volume correction (PVC).

METHODS

PVC of PET data was implemented by the use of a local projection (LP) method. LP-based PVC was evaluated with an image quality (NEMA) and with a thorax phantom with "plaque-type" lesions of 18-36 mL. The validated PVC method was then applied to a cohort of 17 patients, each with at least one plaque in the carotid or ascending aortic arteries. In total, 51 calcified (HU > 110) and 16 non-calcified plaque lesions (HU < 110) were analyzed. The lesion-to-background ratio (LBR) and the relative change of LBR (ΔLBR) were measured on PET.

RESULTS

Following PVC, LBR of the spheres (NEMA phantom) was within 10% of the original values. LBR of the thoracic lesions increased by 155% to 440% when the LP-PVC method was applied to the PET images. In patients, PVC increased the LBR in both calcified [mean = 78% (-8% to 227%)] and non-calcified plaques [mean = 41%, (-9%-104%)].

CONCLUSIONS

PVC helps to improve LBR of plaque-type lesions in both phantom studies and clinical patients. Better results were obtained when the PVC method was applied to images reconstructed with point spread function modeling.

Comparison of PET/CT and PET/MR imaging and dosimetry of yttrium-90 (90Y) in patients with unresectable hepatic tumors who have received intra-arterial radioembolization therapy with 90Y microspheres

BACKGROUND

The aim of our study was to compare 90Y dosimetry obtained from PET/MRI versus PET/CT post-therapy imaging among patients with primary or metastatic hepatic tumors. First, a water-filled Jaszczak phantom containing fillable sphere with 90Y-chloride was acquired on both the PET/CT and PET/MRI systems, in order to check the cross-calibration of the modalities. Following selective internal radiation therapy (SIRT) with 90Y microspheres, 32 patients were imaged on a PET/CT system, immediately followed by a PET/MRI study. Reconstructed images were transferred to a common platform and used to calculate 90Y dosimetry. A Passing-Bablok regression scatter diagram and the Bland and Altman method were used to analyze the difference between the dosimetry values.

RESULTS

The phantom study showed that both modalities were calibrated with less than 1% error. The mean liver doses for the 32 subjects calculated from PET/CT and PET/MRI were 51.6 ± 24.7 Gy and 46.5 ± 22.7 Gy, respectively, with a mean difference of 5.1 ± 5.0 Gy. The repeatability coefficient was 9.0 (18.5% of the mean). The Spearman rank correlation coefficient was very high, ρ = 0.97. Although the maximum dose to the liver can be significantly different (up to 40%), mean liver doses from each modalities were relatively close, with a difference of 18.5% or less.

CONCLUSIONS

The two main contributors to the difference in 90Y dosimetry calculations using PET/CT versus PET/MRI can be attributed to the differences in regions of interest (ROIs) and differences attributed to attenuation correction. Due to the superior soft-tissue contrast of MRI, liver contours are usually better seen than in CT images. However, PET/CT provides better quantification of PET images, due to better attenuation correction. In spite of these differences, our results demonstrate that the dosimetry values obtained from PET/MRI and PET/CT in post-therapy 90Y studies were similar.

Hybrid PET/MRI Methodology

The hybrid PET/MR scanner represents the first implementation of the effective integration of two modalities allowing truly synchronous/simultaneous acquisition of their imaging signals. This integration, resulting from the innovation and development of specific hardware components has paved the way for new approaches in the study of neurodegenerative diseases. This chapter will describe the hardware development that has led to the availability of different clinical solutions for PET/MR imaging as well as the still-open technological challenges and opportunities related to the processing and exploitation of the simultaneous acquisition in neurological studies.

An Efficient Approach to Perform MR-assisted PET Data Optimization in Simultaneous PET/MR Neuroimaging Studies

A main advantage of PET is that it provides quantitative measures of the radiotracer concentration, but its accuracy is confounded by several factors, including attenuation, subject motion, and limited spatial resolution. Using the information from one simultaneously acquired morphological MR sequence with embedded navigators, we propose an efficient method called MR-assisted PET data optimization (MaPET) to perform attenuation correction (AC), motion correction, and anatomy-aided reconstruction. Methods: For attenuation correction, voxel-wise linear attenuation coefficient maps were generated using an SPM8-based approach method on the MR volume. The embedded navigators were used to derive head motion estimates for event-based PET motion correction. The anatomy provided by the MR volume was incorporated into the PET image reconstruction using a kernel-based method. Region-based analyses were carried out to assess the quality of images generated through various stages of PET data optimization. Results: The optimized PET images reconstructed with MaPET was superior in image quality compared to images reconstructed using only attenuation correction, with high SNR and low coefficient of variation (5.08 and 0.229 in a composite cortical region compared to 3.12 and 0.570). The optimized images were also shown using the Cohen's d metric to achieve a greater effect size in distinguishing cortical regions with hypometabolism from regions of preserved metabolism in each individual for different diagnosis groups. Conclusion: We have shown the spatiotemporally correlated data acquired using a single MR sequence can be used for PET attenuation, motion and partial volume effects corrections and the MaPET method may enable more accurate assessment of pathological changes in dementia and other brain disorders.

Using CT Data to Improve the Quantitative Analysis of 18F-FBB PET Neuroimages

¹⁸F-FBB PET is a neuroimaging modality that is been increasingly used to assess brain amyloid deposits in potential patients with Alzheimer's disease (AD). In this work, we analyze the usefulness of these data to distinguish between AD and non-AD patients. A dataset with ¹⁸F-FBB PET brain images from 94 subjects diagnosed with AD and other disorders was evaluated by means of multiple analyses based on t-test, ANOVA, Fisher Discriminant Analysis and Support Vector Machine (SVM) classification. In addition, we propose to calculate amyloid standardized uptake values (SUVs) using only gray-matter voxels, which can be estimated using Computed Tomography (CT) images. This approach allows assessing potential brain amyloid deposits along with the gray matter loss and takes advantage of the structural information provided by most of the scanners used for PET examination, which allow simultaneous PET and CT data acquisition. The results obtained in this work suggest that SUVs calculated according to the proposed method allow AD and non-AD subjects to be more accurately differentiated than using SUVs calculated with standard approaches.

Noninvasive method for measurement of cerebral blood flow using O-15 water PET/MRI with ASL correlation

PURPOSE

A noninvasive image derived input function (IDIF) method was applied to estimate arterial input function from brain H₂¹⁵O-PET/MRI images for the measurement of cerebral blood flow (CBF) because of difficulty in arterial blood sampling during PET/MRI scans. To evaluate accuracy and reproducibility of radioactivity in the internal carotid arteries (ICA) for the IDIF method, a new phantom using a skull bone was applied in the cross-calibration process between the scanner and a gamma-well counter.

METHODS

Eleven healthy volunteers (9 males, 43.9 ± 10.9y) underwent PET/MRI studies with a 3-min H₂¹⁵O-PET and several MRI scans including arterial spin labeling (ASL) perfusion MRI. PET images were reconstructed as dynamic data using two sets of reconstruction parameters, which were determined by basic assessment of radioactivity concentration reproducibility in the tubes of the phantom. The IDIF method extracted the time-activity curves of the ICA from several image slices in the PET data. CBF images were calculated using the autoradiographic (ARG) method and a one-tissue compartment model (1-TCM).

RESULTS

The global means of CBF from the ARG, 1-TCM, and ASL-MRI were 44.8 ± 4.3, 47.9 ± 5.9 and 57.9 ± 8.6 (mL/min/100 g), respectively. CBF from ASL-MRI was significantly greater compared with CBF from H₂¹⁵O-PET (P < 0.001). However, these CBF values were significantly correlated with each other in the scatter plots (P < 0.05).

CONCLUSIONS

Noninvasive measurement of CBF using H₂¹⁵O-PET/MRI and IDIF with the cross-calibration method with a skull phantom experiment provided reasonable quantitative values. The IDIF method allowed reliable estimation of arterial radioactivity concentration, which is useful for clinical application. The ASL-MRI perfusion image from the simultaneous acquisition tended to overestimate CBF.

Determination of gamma camera calibration factors for quantitation of therapeutic radioisotopes

Background

Camera calibration, which translates reconstructed count map into absolute activity map, is a prerequisite procedure for quantitative SPECT imaging. Both planar and tomographic scans using different phantom geometries have been proposed for the determination of the camera calibration factor (CF). However, there is no consensus on which approach is the best. The aim of this study is to evaluate all these calibration methods, compare their performance, and propose a practical and accurate calibration method for SPECT quantitation of therapeutic radioisotopes. Twenty-one phantom experiments (Siemens Symbia SPECT/CT) and 12 Monte Carlo simulations (GATE v6.1) using three therapy isotopes (¹³¹I, ¹⁷⁷Lu, and ¹⁸⁸Re) have been performed. The following phantom geometries were used: (1) planar scans of point source in air (PS), (2) tomographic scans of insert(s) filled with activity placed in non-radioactive water (HS + CB), (3) tomographic scans of hot insert(s) in radioactive water (HS + WB), and (4) tomographic scans of cylinders uniformly filled with activity (HC). Tomographic data were reconstructed using OSEM with CT-based attenuation correction and triple energy window (TEW) scatter correction, and CF was determined using total counts in the reconstructed image, while for planar scans, the photopeak counts, corrected for scatter and background with TEW, were used. Additionally, for simulated data, CF obtained from primary photons only was analyzed.

Results

For phantom experiments, CF obtained from PS and HS + WB agreed to within 6% (below 3% if experiments performed on the same day are considered). However, CF from HS + CB exceeded those from PS by 4–12%. Similar trend was found in simulation studies. Analysis of CFs from primary photons helped us to understand this discrepancy. It was due to underestimation of scatter by the TEW method, further enhanced by attenuation correction. This effect becomes less important when the source is distributed over the entire phantom volume (HS + WB and HC).

Conclusions

Camera CF could be determined using planar scans of a point source, provided that the scatter and background contributions are removed, for example using the clinically available TEW method. This approach is simple and yet provides CF with sufficient accuracy (~ 5%) to be used in clinics for radiotracer quantification.

Joint solution for PET image segmentation, denoising, and partial volume correction

Segmentation, denoising, and partial volume correction (PVC) are three major processes in the quantification of uptake regions in post-reconstruction PET images. These problems are conventionally addressed by independent steps. In this study, we hypothesize that these three processes are dependent; therefore, jointly solving them can provide optimal support for quantification of the PET images. To achieve this, we utilize interactions among these processes when designing solutions for each challenge. We also demonstrate that segmentation can help in denoising and PVC by locally constraining the smoothness and correction criteria. For denoising, we adapt generalized Anscombe transformation to Gaussianize the multiplicative noise followed by a new adaptive smoothing algorithm called regional mean denoising. For PVC, we propose a volume consistency-based iterative voxel-based correction algorithm in which denoised and delineated PET images guide the correction process during each iteration precisely. For PET image segmentation, we use affinity propagation (AP)-based iterative clustering method that helps the integration of PVC and denoising algorithms into the delineation process. Qualitative and quantitative results, obtained from phantoms, clinical, and pre-clinical data, show that the proposed framework provides an improved and joint solution for segmentation, denoising, and partial volume correction.

PET/MRI Hybrid Systems

Over the last decade, the combination of PET and MRI in one system has proven to be highly successful in basic preclinical research, as well as in clinical research. Nowadays, PET/MRI systems are well established in preclinical imaging and are progressing into clinical applications to provide further insights into specific diseases, therapeutic assessments, and biological pathways. Certain challenges in terms of hardware had to be resolved concurrently with the development of new techniques to be able to reach the full potential of both combined techniques. This review provides an overview of these challenges and describes the opportunities that simultaneous PET/MRI systems can exploit in comparison with stand-alone or other combined hybrid systems. New approaches were developed for simultaneous PET/MRI systems to correct for attenuation of 511 keV photons because MRI does not provide direct information on gamma photon attenuation properties. Furthermore, new algorithms to correct for motion were developed, because MRI can accurately detect motion with high temporal resolution. The additional information gained by the MRI can be employed to correct for partial volume effects as well. The development of new detector designs in combination with fast-decaying scintillator crystal materials enabled time-of-flight detection and incorporation in the reconstruction algorithms. Furthermore, this review lists the currently commercially available systems both for preclinical and clinical imaging and provides an overview of applications in both fields. In this regard, special emphasis has been placed on data analysis and the potential for both modalities to evolve with advanced image analysis tools, such as cluster analysis and machine learning.

Evaluation of Parallel Level Sets and Bowsher's Method as Segmentation-Free Anatomical Priors for Time-of-Flight PET Reconstruction

In this article, we evaluate Parallel Level Sets (PLS) and Bowsher's method as segmentation-free anatomical priors for regularized brain positron emission tomography (PET) reconstruction. We derive the proximity operators for two PLS priors and use the EM-TV algorithm in combination with the first order primal-dual algorithm by Chambolle and Pock to solve the non-smooth optimization problem for PET reconstruction with PLS regularization. In addition, we compare the performance of two PLS versions against the symmetric and asymmetric Bowsher priors with quadratic and relative difference penalty function. For this aim, we first evaluate reconstructions of 30 noise realizations of simulated PET data derived from a real hybrid positron emission tomography/magnetic resonance imaging (PET/MR) acquisition in terms of regional bias and noise. Second, we evaluate reconstructions of a real brain PET/MR data set acquired on a GE Signa time-of-flight PET/MR in a similar way. The reconstructions of simulated and real 3D PET/MR data show that all priors were superior to post-smoothed maximum likelihood expectation maximization with ordered subsets (OSEM) in terms of bias-noise characteristics in different regions of interest where the PET uptake follows anatomical boundaries. Our implementation of the asymmetric Bowsher prior showed slightly superior performance compared with the two versions of PLS and the symmetric Bowsher prior. At very high regularization weights, all investigated anatomical priors suffer from the transfer of non-shared gradients.

Impact of tissue kinetic heterogeneity on PET quantification: case study with the L-[1-11C]leucine PET method for cerebral protein synthesis rates

Functional quantification with PET is generally based on modeling that assumes tissue regions are kinetically homogeneous. Even in regions sufficiently small to approach homogeneity, spillover due to resolution limitations of PET scanners may introduce heterogeneous kinetics into measured data. Herein we consider effects of kinetic heterogeneity at the smallest volume accessible, the single image voxel. We used L-[1-¹¹C]leucine PET and compared rates of cerebral protein synthesis (rCPS) estimated voxelwise with methods that do (Spectral Analysis Iterative Filter, SAIF) and do not (Basis Function Method, BFM) allow for kinetic heterogeneity. In high resolution PET data with good counting statistics BFM produced estimates of rCPS comparable to SAIF, but at lower computational cost; thus the simpler, less costly method can be applied. With poorer counting statistics (lower injected radiotracer doses), BFM estimates were more biased. In data smoothed to simulate lower resolution PET, BFM produced estimates of rCPS 9-14% higher than SAIF, overestimation consistent with applying a homogeneous tissue model to kinetically heterogeneous data. Hence with lower resolution data it is necessary to account for kinetic heterogeneity in the analysis. Kinetic heterogeneity may impact analyses of other tracers and scanning protocols differently; assessments should be made on a case by case basis.

SPECT/CT: an update on technological developments and clinical applications

Functional nuclear medicine imaging with single-photon emission CT (SPECT) in combination with anatomical CT has been commercially available since the beginning of this century. The combination of the two modalities has improved both the sensitivity and specificity of many clinical applications and CT in conjunction with SPECT that allows for spatial overlay of the SPECT data on good anatomy images. Introduction of diagnostic CT units as part of the SPECT/CT system has also potentially allowed for a more cost-efficient use of the equipment. Most of the SPECT systems available are based on the well-known Anger camera principle with NaI(Tl) as a scintillation material, parallel-hole collimators and multiple photomultiplier tubes, which, from the centroid of the scintillation light, determine the position of an event. Recently, solid-state detectors using cadmium-zinc-telluride became available and clinical SPECT cameras employing multiple pinhole collimators have been developed and introduced in the market. However, even if new systems become available with better hardware, the SPECT reconstruction will still be affected by photon attenuation and scatter and collimator response. Compensation for these effects is needed even for qualitative studies to avoid artefacts leading to false positives. This review highlights the recent progress for both new SPECT cameras systems as well as for various data-processing and compensation methods.

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Test-Retest Reproducibility for the Tau PET Imaging Agent Flortaucipir F 18

Alzheimer disease (AD) is characterized by β-amyloid (Aβ) plaques and tau neurofibrillary tangles. There are several PET imaging biomarkers for Aβ including ¹¹C-PiB and ¹⁸F-florbetapir. Recently, PET tracers for tau neurofibrillary tangles have become available and have shown utility in detection and monitoring of neurofibrillary pathology over time. Flortaucipir F 18 is one such tracer. Initial clinical studies indicated greater tau binding in AD and mild cognitive impairment patients than in controls in a pattern consistent with tau pathology observed at autopsy. However, little is known about the reproducibility of such findings. To our knowledge, this study reports the first data regarding test-retest reproducibility of flortaucipir F 18 PET. Methods: Twenty-one subjects who completed the study (5 healthy controls, 6 mild cognitive impairment, and 10 AD) received 370 MBq of flortaucipir F 18 and were imaged for 20 min beginning 80 min after injection and again at 110 min after injection. Follow-up (retest) imaging occurred between 48 h and 4 wk after initial imaging. Images were spatially normalized to Montreal Neurological Institute template space. SUVRs were calculated using AAL (Automated Anatomical Labeling atlas) volumes of interest (VOIs) for parietal, temporal, occipital, anterior, and posterior hippocampal, parahippocampal, and fusiform regions, as well as a posterior neocortical VOI composed of average values from parietal, temporal, and occipital areas. Further, a VOI derived by discriminant analysis that maximally separated diagnostic groups (multiblock barycentric discriminant analysis [MUBADA]) was used. All VOIs were referenced to a subsection of cerebellar gray matter (cere-crus) as well as a parametrically derived white matter-based reference region (parametric estimate of reference signal intensity [PERSI]). t test, correlation analyses, and intraclass correlation coefficient were used to explore test-retest performance. Results: Test-retest analyses demonstrated low variability in flortaucipir F 18 SUVR. The SD of mean percentage change between test and retest using the PERSI reference region was 2.22% for a large posterior neocortical VOI, 1.84% for MUBADA, 1.46% for frontal, 1.98% for temporal, 2.28% for parietal, and 3.27% for occipital VOIs. Further, significant correlations (R² > 0.85; P < 0.001) were observed for all regions, and intraclass correlation coefficient values (test-retest consistency) were greater than 0.92 for all regions. Conclusion: Significant test-retest reproducibility for flortaucipir F 18 was found across neocortical and mesial temporal lobe structures. These preliminary data suggest that flortaucipir F 18 tau imaging could be used to examine changes in tau burden over time.

Monte Carlo-based quantitative pinhole SPECT reconstruction using a ray-tracing back-projector

Background

Monte Carlo simulations provide accurate models of nuclear medicine imaging systems as they can properly account for the full physics of photon transport. The accuracy of the model included in the maximum-likelihood–expectation-maximization (ML-EM) reconstruction limits the overall accuracy of the reconstruction results. In this paper, we present a Monte Carlo-based ML-EM reconstruction method for pinhole single-photon emission computed tomography (SPECT) that has been incorporated into the SIMIND Monte Carlo program. The Monte Carlo-based model, which accounts for all of the physical and geometrical characteristics of the camera system, is used in the forward-projection step of the reconstruction, while a simpler model based on ray-tracing is used for back-projection. The aim of this work was to investigate the quantitative accuracy of this combination of forward- and back-projectors in the clinical pinhole camera GE Discovery NM 530c.

Results

The total activity was estimated in ^99mTc-filled spheres with volumes between 0.5 and 16 mL. The total sphere activity was generally overestimated but remained within 10% of the reference activity defined by the phantom preparation. The recovered activity converged towards the reference activity as the number of iterations increased. Furthermore, the recovery of the activity concentrations within the physical boundaries of the spheres increased with increasing sphere volume. Additionally, the Monte Carlo-based reconstruction enabled recovery of the true activity concentration in the myocardium of a cardiac phantom mounted in a torso phantom regardless of whether the torso was empty or water-filled. A qualitative comparison to data reconstructed using the clinical reconstruction algorithm showed that the two methods performed similarly, although the images reconstructed using the clinical software were more uniform due to the incorporation of noise regularization and post-filtration in that reconstruction technique.

Conclusions

We developed a Monte Carlo-based reconstruction method for pinhole SPECT and evaluated it using phantom measurements. The combination of a Monte Carlo-based forward-projector and a simplified analytical ray-tracing back-projector produced quantitative images of acceptable image quality. No explicit calibration is necessary in this method since the forward-projector model maintains a relationship between the number of counts and activity.

Impact of motion compensation and partial volume correction for 18F-NaF PET/CT imaging of coronary plaque

Recent studies have suggested that ¹⁸F-NaF-PET enables visualization and quantification of plaque micro-calcification in the coronary tree. However, PET imaging of plaque calcification in the coronary arteries is challenging because of the respiratory and cardiac motion as well as partial volume effects. The objective of this work is to implement an image reconstruction framework, which incorporates compensation for respiratory as well as cardiac motion (MoCo) and partial volume correction (PVC), for cardiac ¹⁸F-NaF PET imaging in PET/CT. We evaluated the effect of MoCo and PVC on the quantification of vulnerable plaques in the coronary arteries. Realistic simulations (Biograph TPTV, Biograph mCT) and phantom acquisitions (Biograph mCT) were used for these evaluations. Different uptake values in the calcified plaques were evaluated in the simulations, while three 'plaque-type' lesions of 36, 31 and 18 mm³ were included in the phantom experiments. After validation, the MoCo and PVC methods were applied in four pilot NaF-PET patient studies. In all cases, the MoCo-based image reconstruction was performed using the STIR software. The PVC was obtained from a local projection (LP) method, previously evaluated in preclinical and clinical PET. The results obtained show a significant increase of the measured lesion-to-background ratios (LBR) in the MoCo  +  PVC images. These ratios were further enhanced when using directly the tissue-activities from the LP method, making this approach more suitable for the quantitative evaluation of coronary plaques. When using the LP method on the MoCo images, LBR increased between 200% and 1119% in the simulated data, between 212% and 614% in the phantom experiments and between 46% and 373% in the plaques with positive uptake observed in the pilot patients. In conclusion, we have built and validated a STIR framework incorporating MoCo and PVC for ¹⁸F-NaF PET imaging of coronary plaques. First results indicate an improved quantification of plaque-type lesions.

Flortaucipir F 18 Quantitation Using Parametric Estimation of Reference Signal Intensity

PET imaging of tau pathology in Alzheimer disease may benefit from the use of white matter reference regions. These regions have shown reduced variability compared with conventional cerebellar regions in amyloid imaging. However, they are susceptible to contamination from partial-volume blurring of tracer uptake in the cortex. We present a new technique, PERSI (Parametric Estimation of Reference Signal Intensity), for flortaucipir F 18 count normalization that leverages the advantages of white matter reference regions while mitigating potential partial-volume effects. Methods: Subjects with a clinical diagnosis of Alzheimer disease, mild cognitive impairment, or normal cognition underwent T1-weighted MRI and florbetapir imaging (to determine amyloid [Aβ] status) at screening and flortaucipir F 18 imaging at single or multiple time points. Flortaucipir F 18 images, acquired as 4 × 5 min frames 80 min after a 370-MBq injection, were motion-corrected, averaged, and transformed to Montreal Neurological Institute (MNI) space. The PERSI reference region was calculated for each scan by fitting a bimodal gaussian distribution to the voxel-intensity histogram within an atlas-based white matter region and using the center and width of the lower-intensity peak to identify the voxel intensities to be included. Four conventional reference regions were also evaluated: whole cerebellum, cerebellar gray matter, atlas-based white matter, and subject-specific white matter. SUVr (standardized uptake value ratio) was calculated for a statistically defined neocortical volume of interest. Performance was evaluated with respect to test-retest variability in a phase 2 study of 21 subjects (5-34 d between scans). Baseline variability in controls (SD of SUVr and ΔSUVr) and effect sizes for group differences (Cohen d; Aβ-positive impaired vs. Aβ-negative normal) were evaluated in another phase 2 study with cross-sectional data (n = 215) and longitudinal data (n = 142/215; 18 ± 2 mo between scans). Results: PERSI showed superior test-retest reproducibility (1.84%) and group separation ability (cross-sectional Cohen d = 9.45; longitudinal Cohen d = 2.34) compared with other reference regions. Baseline SUVr variability and ΔSUVr were minimal in Aβ control subjects with no specific flortaucipir F 18 uptake (SUVr, 1.0 ± 0.04; ΔSUVr, 0.0 ± 0.02). Conclusion: PERSI reduced variability while enhancing discrimination between diagnostic cohorts. Such improvements could lead to more accurate disease staging and robust measurements of changes in tau burden over time for the evaluation of putative therapies.

Towards enhanced PET quantification in clinical oncology

Positron emission tomography (PET) has, since its inception, established itself as the imaging modality of choice for the in vivo quantitative assessment of molecular targets in a wide range of biochemical processes underlying tumour physiology. PET image quantification enables to ascertain a direct link between the time-varying activity concentration in organs/tissues and the fundamental parameters portraying the biological processes at the cellular level being assessed. However, the quantitative potential of PET may be affected by a number of factors related to physical effects, hardware and software system specifications, tracer kinetics, motion, scan protocol design and limitations in current image-derived PET metrics. Given the relatively large number of PET metrics reported in the literature, the selection of the best metric for fulfilling a specific task in a particular application is still a matter of debate. Quantitative PET has advanced elegantly during the last two decades and is now reaching the maturity required for clinical exploitation, particularly in oncology where it has the capability to open many avenues for clinical diagnosis, assessment of response to treatment and therapy planning. Therefore, the preservation and further enhancement of the quantitative features of PET imaging is crucial to ensure that the full clinical value of PET imaging modality is utilized in clinical oncology. Recent advancements in PET technology and methodology have paved the way for faster PET acquisitions of enhanced sensitivity to support the clinical translation of highly quantitative four-dimensional (4D) parametric imaging methods in clinical oncology. In this report, we provide an overview of recent advances and future trends in quantitative PET imaging in the context of clinical oncology. The pros/cons of the various image-derived PET metrics will be discussed and the promise of novel methodologies will be highlighted.

Population Pharmacokinetics of Tracers: A New Tool for Medical Imaging?

Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.

Optimizing Image Quantification for 177Lu SPECT/CT Based on a 3D Printed 2-Compartment Kidney Phantom

The aim of this work was to find an optimal setup for activity determination of ¹⁷⁷Lu-based SPECT/CT imaging reconstructed with 2 commercially available methods (xSPECT Quant and Flash3D). For this purpose, 3-dimensional (3D)-printed phantoms of different geometries were manufactured, different partial-volume correction (PVC) methods were applied, and the accuracy of the activity determination was evaluated. Methods: A 2-compartment kidney phantom (70% cortical and 30% medullary compartment), a sphere, and an ellipsoid of equal volumes were 3D printed, filled with ¹⁷⁷Lu, and scanned with a SPECT/CT system. Reconstructions were performed with xSPECT and Flash3D. Different PVC methods were applied to find an optimal quantification setup: method 1 was a geometry-specific recovery coefficient based on the 3D printing model, method 2 was a geometry-specific recovery coefficient based on the low-dose CT scan, method 3 was an enlarged volume of interest including spilled-out counts, method 4 was activity concentration in the peak milliliter applied to the entire CT-based volume, and method 5 was a fixed threshold of 42% of the maximum in a large volume containing the object of interest. Additionally, the influence of postreconstruction gaussian filtering was investigated. Results: Although the recovery coefficients of sphere and ellipsoid differed by only 0.7%, a difference of 31.7% was observed between the sphere and the renal cortex phantoms. Without postfiltering, the model-based recovery coefficients (methods 1 and 2) resulted in the best accuracies (xSPECT, 1.5%; Flash3D, 10.3%), followed by the enlarged volume (method 3) (xSPECT, 8.5%; Flash3D, 13.0%). The peak-milliliter method (method 4) showed large errors only for sphere and ellipsoid (xSPECT, 23.4%; Flash3D, 21.6%). Applying a 42% threshold (method 5) led to the largest quantification errors (xSPECT, 32.3%; Flash3D, 46.7%). After postfiltering, a general increase in the errors was observed. Conclusion: In this work, 3D printing was used as a prototyping technique for a geometry-specific investigation of SPECT/CT reconstruction parameters and PVC methods. The optimal setup for activity determination was found to be an unsmoothed SPECT/CT reconstruction in combination with a recovery coefficient based on the low-dose CT. The difference between spheric and renal recovery coefficients suggests that the typically applied volume-dependent but only sphere-based recovery coefficient lookup tables should be replaced by a more geometry-specific alternative.

Voxel-based multimodel fitting method for modeling time activity curves in SPECT images

PURPOSE

Estimating the biodistribution and the pharmacokinetics from time-sequence SPECT images on a per-voxel basis is useful for studying activity nonuniformity or computing absorbed dose distributions by convolution of voxel kernels or Monte-Carlo radiation transport. Current approaches are either region-based, thus assuming uniform activity within the region, or voxel-based but using the same fitting model for all voxels.

METHODS

We propose a voxel-based multimodel fitting method (VoMM) that estimates a fitting function for each voxel by automatically selecting the most appropriate model among a predetermined set with Akaike criteria. This approach can be used to compute the time integrated activity (TIA) for all voxels in the image. To control fitting optimization that may fail due to excessive image noise, an approximated version based on trapezoid integration, named restricted method, is also studied. From this comparison, the number of failed fittings within images was estimated and analyzed. Numerical experiments were used to quantify uncertainties and feasibility was demonstrated with real patient data.

RESULTS

Regarding numerical experiments, root mean square errors of TIA obtained with VoMM were similar to those obtained with bi-exponential fitting functions, and were lower (< 5% vs.  > 10%) than with single model approaches that consider the same fitting function for all voxels. Failure rates were lower with VoMM and restricted approaches than with single-model methods. On real clinical data, VoMM was able to fit 90% of the voxels and led to less failed fits than single-model approaches. On regions of interest (ROI) analysis, the difference between ROI-based and voxel-based TIA estimations was low, less than 4%. However, the computation of the mean residence time exhibited larger differences, up to 25%.

CONCLUSIONS

The proposed voxel-based multimodel fitting method, VoMM, is feasible on patient data. VoMM leads organ-based TIA estimations similar to conventional ROI-based method. However, for pharmacokinetics analysis, studies of spatial heterogeneity or voxel-based absorbed dose assessment, VoMM could be used preferentially as it prevents model overfitting.

Cortical β-amyloid burden, gray matter, and memory in adults at varying APOE ε4 risk for Alzheimer's disease

Models of preclinical Alzheimer's disease (AD) propose that cerebral amyloidosis leads to neurodegeneration and subsequent cognitive decline. This study investigated whether APOE genotype is related to β-amyloid (Aβ) burden in brain regions preferentially affected by AD and whether Aβ burden is associated with gray-matter (GM) fraction (as a marker of neurodegeneration) and episodic memory performance in cognitively normal middle-aged individuals at varying genetic risk for AD. Three groups of cognitively normal participants aged 50-65 years with a first-degree family history of AD (APOE genotype ε4ε4 [n = 15], ε3ε4 [n = 15], and ε3ε3 [n = 15]) underwent [¹¹C]PiB positron emission tomography scans to quantify cortical Aβ, brain magnetic resonance imaging, and neuropsychological testing. APOE ε4ε4 participants demonstrated significantly higher cortical Aβ burden than APOE ε3ε3 (p < 0.001). Furthermore, cortical Aβ burden was inversely associated with cortical GM fraction (p = 0.017) but not episodic memory performance. In cognitively normal, middle-aged individuals, Aβ burden is significantly associated with GM fraction but not episodic memory performance. These findings are consistent with models of preclinical AD in which neurodegeneration occurs before manifest cognitive decline.

Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis

Purpose

Positron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2–3× the PET system’s spatial resolution, and the clinical impact of this is not evident. This systematic review provides an up-to-date overview of studies investigating the impact of partial-volume correction (PVC) in oncological PET studies.

Methods

We searched in PubMed and Embase databases according to the PRISMA statement, including studies from inception till May 9, 2016. Two reviewers independently screened all abstracts and eligible full-text articles and performed quality assessment according to QUADAS-2 and QUIPS criteria. For a set of similar diagnostic studies, we statistically pooled the results using bivariate meta-regression.

Results

Thirty-one studies were eligible for inclusion. Overall, study quality was good. For diagnosis and nodal staging, PVC yielded a strong trend of increased sensitivity at expense of specificity. Meta-analysis of six studies investigating diagnosis of pulmonary nodules (679 lesions) showed no significant change in diagnostic accuracy after PVC (p = 0.222). Prognostication was not improved for non-small cell lung cancer and esophageal cancer, whereas it did improve for head and neck cancer. Response assessment was not improved by PVC for (locally advanced) breast cancer or rectal cancer, and it worsened in metastatic colorectal cancer.

Conclusions

The accumulated evidence to date does not support routine application of PVC in standard clinical PET practice. Consensus on the preferred PVC methodology in oncological PET should be reached. Partial-volume-corrected data should be used as adjuncts to, but not yet replacement for, uncorrected data.

Electronic supplementary material

The online version of this article (doi:10.1007/s00259-017-3775-4) contains supplementary material, which is available to authorized users.

Radiomanganese PET Detects Changes in Functional β-Cell Mass in Mouse Models of Diabetes

The noninvasive measurement of functional β-cell mass would be clinically valuable for monitoring the progression of type 1 and type 2 diabetes as well as the viability of transplanted insulin-producing cells. Although previous work using MRI has shown promise for functional β-cell mass determination through voltage-dependent Ca²⁺ channel (VDCC)-mediated internalization of Mn²⁺, the clinical utility of this technique is limited by the cytotoxic levels of the Mn²⁺ contrast agent. Here, we show that positron emission tomography (PET) is advantageous for determining functional β-cell mass using ⁵²Mn²⁺ (t_1/2: 5.6 days). We investigated the whole-body distribution of ⁵²Mn²⁺ in healthy adult mice by dynamic and static PET imaging. Pancreatic VDCC uptake of ⁵²Mn²⁺ was successfully manipulated pharmacologically in vitro and in vivo using glucose, nifedipine (VDCC blocker), the sulfonylureas tolbutamide and glibenclamide (K_ATP channel blockers), and diazoxide (K_ATP channel opener). In a mouse model of streptozotocin-induced type 1 diabetes, ⁵²Mn²⁺ uptake in the pancreas was distinguished from healthy controls in parallel with classic histological quantification of β-cell mass from pancreatic sections. ⁵²Mn²⁺-PET also reported the expected increase in functional β-cell mass in the ob/ob model of pretype 2 diabetes, a result corroborated by histological β-cell mass measurements and live-cell imaging of β-cell Ca²⁺ oscillations. These results indicate that ⁵²Mn²⁺-PET is a sensitive new tool for the noninvasive assessment of functional β-cell mass.

Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial

PURPOSE

In recent years, multiple studies have demonstrated the value of volumetric FDG-PET/CT parameters as independent prognostic factors in patients with non-small cell lung cancer (NSCLC). We aimed to determine the optimal cut-off points of pretreatment volumetric FDG-PET/CT parameters in predicting overall survival (OS) in patients with locally advanced NSCLC and to recommend imaging biomarkers appropriate for routine clinical applications.

METHODS

Patients with inoperable stage IIB/III NSCLC enrolled in ACRIN 6668/RTOG 0235 were included. Pretreatment FDG-PET scans were quantified using semiautomatic adaptive contrast-oriented thresholding and local-background partial-volume-effect-correction algorithms. For each patient, the following indices were measured: metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, SUVmean, partial-volume-corrected TLG (pvcTLG), and pvcSUVmean for the whole-body, primary tumor, and regional lymph nodes. The association between each index and patient outcome was assessed using Cox proportional hazards regression. Optimal cut-off points were estimated using recursive binary partitioning in a conditional inference framework and used in Kaplan-Meier curves with log-rank testing. The discriminatory ability of each index was examined using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC(t)).

RESULTS

The study included 196 patients. Pretreatment whole-body and primary tumor MTV, TLG, and pvcTLG were independently prognostic of OS. Optimal cut-off points were 175.0, 270.9, and 35.5 cm³ for whole-body TLG, pvcTLG, and MTV, and were 168.2, 239.8, and 17.4 cm³ for primary tumor TLG, pvcTLG, and MTV, respectively. In time-dependent ROC analysis, AUC(t) for MTV and TLG were uniformly higher than that of SUV measures over all time points. Primary tumor and whole-body parameters demonstrated similar patterns of separation for those patients above versus below the optimal cut-off points in Kaplan-Meier curves and in time-dependent ROC analysis.

CONCLUSION

We demonstrated that pretreatment whole-body and primary tumor volumetric FDG-PET/CT parameters, including MTV, TLG, and pvcTLG, are strongly prognostic for OS in patients with locally advanced NSCLC, and have similar discriminatory ability. Therefore, we believe that, after validation in future trials, the derived optimal cut-off points for primary tumor volumetric FDG-PET/CT parameters, or their more refined versions, could be incorporated into routine clinical practice, and may provide more accurate prognostication and staging based on tumor metabolic features.

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.

Implementation of absolute quantification in small-animal SPECT imaging: Phantom and animal studies

PURPOSE

Presence of photon attenuation severely challenges quantitative accuracy in single-photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small-animal SPECT imaging.

METHODS

Images were reconstructed using an iterative reconstruction method based on the maximum-likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first-order Chang's method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method.

RESULTS

The phantom experiments showed that the error of -15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of -22.8 ± 6.3% (ranging from -31.2% to -14.8%) in the uncorrected images was reduced to +3.5 ± 6.7% (ranging from -6.7 to +9.8%) after applying attenuation correction.

CONCLUSION

The results indicate that the proposed attenuation correction algorithm based on the first-order Chang's method, as implemented in our dedicated small-animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification.

A comparison of five partial volume correction methods for Tau and Amyloid PET imaging with [18F]THK5351 and [11C]PIB

PURPOSE

To suppress partial volume effect (PVE) in brain PET, there have been many algorithms proposed. However, each methodology has different property due to its assumption and algorithms. Our aim of this study was to investigate the difference among partial volume correction (PVC) method for tau and amyloid PET study.

METHODS

We investigated two of the most commonly used PVC methods, Müller-Gärtner (MG) and geometric transfer matrix (GTM) and also other three methods for clinical tau and amyloid PET imaging. One healthy control (HC) and one Alzheimer's disease (AD) PET studies of both [¹⁸F]THK5351 and [¹¹C]PIB were performed using a Eminence STARGATE scanner (Shimadzu Inc., Kyoto, Japan). All PET images were corrected for PVE by MG, GTM, Labbé (LABBE), Regional voxel-based (RBV), and Iterative Yang (IY) methods, with segmented or parcellated anatomical information processed by FreeSurfer, derived from individual MR images. PVC results of 5 algorithms were compared with the uncorrected data.

RESULTS

In regions of high uptake of [¹⁸F]THK5351 and [¹¹C]PIB, different PVCs demonstrated different SUVRs. The degree of difference between PVE uncorrected and corrected depends on not only PVC algorithm but also type of tracer and subject condition.

CONCLUSION

Presented PVC methods are straight-forward to implement but the corrected images require careful interpretation as different methods result in different levels of recovery.

Comparative analysis of iterative reconstruction algorithms with resolution recovery and time of flight modeling for 18F-FDG cardiac PET: A multi-center phantom study

BACKGROUND

The purpose of this study was to evaluate the image quality in cardiac 18F-FDG PET using the time of flight (TOF) and/or point spread function (PSF) modeling in the iterative reconstruction (IR).

METHODS

Three scanners and an anthropomorphic cardiac phantom with an insert simulating a transmural defect (TD) were used. Two sets of scans (with/without TD) were acquired, and four reconstruction schemes were considered: (1) IR; (2) IR + PSF, (3) IR + TOF, and (4) IR + TOF + PSF. LV wall thickness (FWHM), contrast between LV wall and inner chamber (C IC), and TD contrast in LV wall (C TD) were evaluated.

RESULTS

Tests of the reconstruction protocols showed a decrease in FWHM from IR (13 mm) to IR + PSF (11 mm); an increase in the C IC from IR (65%) to IR + PSF (71%) and from IR + TOF (72%) to IR + TOF + PSF (77%); and an increase in the C TD from IR + PSF (72%) to IR + TOF (75%) and to IR + TOF + PSF (77%). Tests of the scanner/software combinations showed a decrease in FWHM from Gemini_TF (13 mm) to Biograph_mCT (12 mm) and to Discovery_690 (11 mm); an increase in the C IC from Gemini_TF (65%) to Biograph_mCT (73%) and to Discovery_690 (75%); and an increase in the C TD from Gemini_TF/Biograph_mCT (72%) to Discovery_690 (77%).

CONCLUSION

The introduction of TOF and PSF increases image quality in cardiac 18F-FDG PET. The scanner/software combinations exhibit different performances, which should be taken into consideration when making cross comparisons.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine ^99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of [Formula: see text], the tracer transport rate (ml · min-1 · ml-1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced [Formula: see text] maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced [Formula: see text] estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.