Positron emission tomography (PET) images are degraded by a phenomenon known as the partial volume effect (PVE). Approaches have been developed to reduce PVEs, typically through the utilisation of ...structural information provided by other imaging modalities such as MRI or CT. These methods, known as partial volume correction (PVC) techniques, reduce PVEs by compensating for the effects of the scanner resolution, thereby improving the quantitative accuracy. The PETPVC toolbox described in this paper comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data. Eight core PVC techniques are available. These core methods can be combined to create a total of 22 different PVC techniques. Simulated brain PET data are used to demonstrate the utility of toolbox in idealised conditions, the effects of applying PVC with mismatched point-spread function (PSF) estimates and the potential of novel hybrid PVC methods to improve the quantification of lesions. All anatomy-based PVC techniques achieve complete recovery of the PET signal in cortical grey matter (GM) when performed in idealised conditions. Applying deconvolution-based approaches results in incomplete recovery due to premature termination of the iterative process. PVC techniques are sensitive to PSF mismatch, causing a bias of up to 16.7% in GM recovery when over-estimating the PSF by 3 mm. The recovery of both GM and a simulated lesion was improved by combining two PVC techniques together. The PETPVC toolbox has been written in C++, supports Windows, Mac and Linux operating systems, is open-source and publicly available.
Purpose
Alzheimer’s disease (AD) is the most common form of dementia. Clinically, it is characterized by progressive cognitive and functional impairment with structural hallmarks of cortical atrophy ...and ventricular expansion. Amyloid plaque aggregation is also known to occur in AD subjects. In-vivo imaging of amyloid plaques is now possible with positron emission tomography (PET) radioligands. PET imaging suffers from a degrading phenomenon known as the partial volume effect (PVE). The quantitative accuracy of PET images is reduced by PVEs primarily due to the limited spatial resolution of the scanner. The degree of PVE is influenced by structure size, with smaller structures tending to suffer from more severe PVEs such as atrophied grey matter regions. The aims of this paper were to investigate the effect of partial volume correction (PVC) on the quantification of amyloid PET and to highlight the importance of selecting an appropriate PVC technique.
Methods
An improved PVC technique, region-based voxel-wise (RBV) correction, was compared against existing Van-Cittert (VC) and Müller-Gärtner (MG) methods using amyloid PET imaging data. Digital phantom data were produced using segmented MRI scans from a control subject and an AD subject. Typical tracer distributions were generated for each of the phantom anatomies. Also examined were 70 clinical PET scans acquired using
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Fflutemetamol. Volume of interest (VOI) analysis was performed for corrected and uncorrected images.
Results
PVC was shown to improve the quantitative accuracy of regional analysis performed on amyloid PET images. Of the corrections applied, VC deconvolution demonstrated the worst recovery of grey matter values. MG PVC was shown to induce biases in some grey matter regions due to grey matter variability. In addition, white matter variability was shown to influence the accuracy of MG PVC in cortical grey matter and also cerebellar grey matter, a typical reference region for amyloid PET normalization in sporadic AD. RBV was shown to be more accurate than MG in terms of grey matter and white matter uptake. An increase in within-group variability after PVC was observed and is believed to be a genuine, more accurate representation of the data rather than a correction-induced error. The standardized uptake value ratio (SUVR) threshold for classifying subjects as either amyloid-positive or amyloid-negative was found to be 1.64 in the uncorrected dataset, rising to 2.25 after PVC.
Conclusion
Care should be taken when applying PVC to amyloid PET images. Assumptions made in existing PVC strategies can induce biases that could lead to erroneous inferences about uptake in certain regions. The proposed RBV PVC technique accounts for within-compartment variability, with the potential to reduce errors of this kind.
D-SPECT (Spectrum Dynamics, Israel) is a novel SPECT system for cardiac perfusion studies. Based on CZT detectors, region-centric scanning, high-sensitivity collimators and resolution recovery, it ...offers potential advantages over conventional systems. A series of measurements were made on a beta-version D-SPECT system in order to evaluate its performance in terms of energy resolution, scatter fraction, sensitivity, count rate capability and resolution. Corresponding measurements were also done on a conventional SPECT system (CS) for comparison. The energy resolution of the D-SPECT system at 140 keV was 5.5% (CS: 9.25%), the scatter fraction 30% (CS: 34%), the planar sensitivity 398 s(-1) MBq(-1) per head ((99m)Tc, 10 cm) (CS: 72 s(-1) MBq(-1)), and the tomographic sensitivity in the heart region was in the range 647-1107 s(-1) MBq(-1) (CS: 141 s(-1) MBq(-1)). The count rate increased linearly with increasing activity up to 1.44 M s(-1). The intrinsic resolution was equal to the pixel size, 2.46 mm (CS: 3.8 mm). The average reconstructed resolution using the standard clinical filter was 12.5 mm (CS: 13.7 mm). The D-SPECT has superior sensitivity to that of a conventional system with similar spatial resolution. It also has excellent energy resolution and count rate characteristics, which should prove useful in dynamic and dual radionuclide studies.
Myocardial perfusion imaging (MPI) is well established in the diagnosis and workup of patients with known or suspected coronary artery disease (CAD); however, it can underestimate the extent of ...obstructive CAD. Quantification of myocardial perfusion reserve with PET can assist in the diagnosis of multivessel CAD. We evaluated the feasibility of dynamic tomographic SPECT imaging and quantification of a retention index to describe global and regional myocardial perfusion reserve using a dedicated solid-state cardiac camera.
Ninety-five consecutive patients (64 men and 31 women; median age, 67 y) underwent dynamic SPECT imaging with (99m)Tc-sestamibi at rest and at peak vasodilator stress, followed by standard gated MPI. The dynamic images were reconstructed into 60-70 frames, 3-6 s/frame, using ordered-subsets expectation maximization with 4 iterations and 32 subsets. Factor analysis was used to estimate blood-pool time-activity curves, used as input functions in a 2-compartment kinetic model. K1 values ((99m)Tc-sestamibi uptake) were calculated for the stress and rest images, and K2 values ((99m)Tc-sestamibi washout) were set to zero. Myocardial perfusion reserve (MPR) index was calculated as the ratio of the stress and rest K1 values. Standard MPI was evaluated semiquantitatively, and total perfusion deficit (TPD) of at least 5% was defined as abnormal.
Global MPR index was higher in patients with normal MPI (n = 51) than in patients with abnormal MPI (1.61 interquartile range (IQR), 1.33-2.03 vs. 1.27 IQR, 1.12-1.61, P = 0.0002). By multivariable regression analysis, global MPR index was associated with global stress TPD, age, and smoking. Regional MPR index was associated with the same variables and with regional stress TPD. Sixteen patients undergoing invasive coronary angiography had 20 vessels with stenosis of at least 50%. The MPR index was 1.11 (IQR, 1.01-1.21) versus 1.30 (IQR, 1.12-1.67) in territories supplied by obstructed and nonobstructed arteries, respectively (P = 0.02). MPR index showed a stepwise reduction with increasing extent of obstructive CAD (P = 0.02).
Dynamic tomographic imaging and quantification of a retention index describing global and regional perfusion reserve are feasible using a solid-state camera. Preliminary results show that the MPR index is lower in patients with perfusion defects and in regions supplied by obstructed coronary arteries. Further studies are needed to establish the clinical role of this technique as an aid to semiquantitative analysis of MPI.
Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived ...input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing 18FGE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p<0.001), PWB ratio (r = 0.93, p<0.001), and the PIF (r = 0.92, p<0.001) as well as total distribution volume (VT) in 11 regions across the brain (r = 0.95, p<0.001). IDIF+venous VT had a mean bias of −1.7% and a comparable regional coefficient of variation (arterial: 21.3 ± 2.5%, IDIF+venous: 21.5 ± 2.0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate VT estimates (mean bias 9.9%; r = 0.71, p<0.001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias −20.9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0.45, p<0.001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0.92, p = 0.003) and PWB ratio (r = 0.93, p = 0.003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of 18FGE-179 VT.
Single-photon emission computed tomography (SPECT) systems with pinhole collimators are becoming increasingly important in clinical and preclinical nuclear medicine investigations as they can provide ...a superior resolution-sensitivity trade-off compared to conventional parallel-hole and fanbeam collimators. Previously, open-source software did not exist for reconstructing tomographic images from pinhole-SPECT datasets. A 3D SPECT system matrix modelling library specific for pinhole collimators has recently been integrated into STIR, an open-source software package for tomographic image reconstruction. The pinhole-SPECT library enables corrections for attenuation and the spatially variant collimator–detector response by incorporating their effects into the system matrix. Attenuation correction can be calculated with a simple single line of response or a full model. The spatially variant collimator–detector response can be modelled with a point spread function and depth of interaction corrections for increased system matrix accuracy. In addition, improvements to computational speed and memory requirements can be made with image masking. This work demonstrates the flexibility and accuracy of STIR’s support for pinhole-SPECT datasets using measured and simulated single-pinhole SPECT data from which reconstructed images were analysed quantitatively and qualitatively. The extension of the open-source STIR project with advanced pinhole-SPECT modelling will enable the research community to study the impact of pinhole collimators in several SPECT imaging scenarios and with different scanners.
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.
INTRODUCTION
The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized ...tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI).
METHODS
We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian‐mixture‐modelling–derived cutpoints for Aβ PET positivity were converted.
RESULTS
The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM‐based Centiloids. Linear adjustment produced a WM‐based cutpoint of 18.1.
DISCUSSION
Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed.
HIGHLIGHTS
Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results.
Centiloid values can be influenced by differences in acquisition.
We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort.
Whole cerebellum referenced values could be reliably transformed to Centiloids.
White matter referenced values may be less generalizable between datasets.
Purpose
It has recently been recognized that PET/CT may play a role in diffuse parenchymal lung disease. However, interpretation can be confounded due to the variability in lung density both within ...and between individuals. To address this issue a novel correction method is proposed.
Methods
A CT scan acquired during shallow breathing is registered to a PET study and smoothed so as to match the PET resolution. This is used to derive voxel-based tissue fraction correction factors for the individual. The method was evaluated in a lung phantom study in which the lung was simulated by a Styrofoam/water mixture. The method was further evaluated using
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F-FDG in 12 subjects free from pulmonary disease where ranges before and after correction were considered.
Results
Correction resulted in similar activity concentrations for the lung and background regions, consistent with the experimental phantom set-up. Correction resulted in reduced inter- and intrasubject variability in the estimated SUV. The possible application of the method was further demonstrated in five subjects with interstitial lung changes where increased SUV was demonstrated. Single study pre- and post-treatment studies were also analysed to further illustrate the utility of the method.
Conclusion
The proposed tissue fraction correction method is a promising technique to account for variability of density in interpreting lung PET studies.
In this study, we aim to reconstruct single-photon emission computed tomography images using anatomical information from magnetic resonance imaging as a priori knowledge about the activity ...distribution. The trade-off between anatomical and emission data is one of the main concerns for such studies. In this work, we propose an anatomically driven anisotropic diffusion filter (ADADF) as a penalized maximum likelihood expectation maximization optimization framework. The ADADF method has improved edge-preserving denoising characteristics compared to other smoothing penalty terms based on quadratic and non-quadratic functions. The proposed method has an important ability to retain information which is absent in the anatomy. To make our approach more stable to the noise-edge classification problem, robust statistics have been employed. Comparison of the ADADF method is performed with a successful anatomically driven technique, namely, the Bowsher prior (BP). Quantitative assessment using simulated and clinical neuroreceptor volumetric data show the advantage of the ADADF over the BP. For the modelled data, the overall image resolution, the contrast, the signal-to-noise ratio and the ability to preserve important features in the data are all improved by using the proposed method. For clinical data, the contrast in the region of interest is significantly improved using the ADADF compared to the BP, while successfully eliminating noise.
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