Quantitative validation of Monte Carlo SPECT simulation: application to a Mediso AnyScan GATE simulation.

BACKGROUND: Monte Carlo (MC) simulations are used in nuclear medicine imaging as they provide unparalleled insight into processes that are not directly experimentally measurable, such as scatter and attenuation in an acquisition. Whilst MC is often used to provide a 'ground-truth', this is only the case if the simulation is fully validated against experimental data. This work presents a quantitative validation for a MC simulation of a single-photon emission computed tomography (SPECT) system. METHODS: An MC simulation model of the Mediso AnyScan SCP SPECT system installed at the UK National Physical Laboratory was developed in the GATE (Geant4 Application for Tomographic Emission) toolkit. Components of the detector head and two collimator configurations were modelled according to technical specifications and physical measurements. Experimental detection efficiency measurements were collected for a range of energies, permitting an energy-dependent intrinsic camera efficiency correction function to be determined and applied to the simulation on an event-by-event basis. Experimental data were collected in a range of geometries with [Formula: see text]Tc for comparison to simulation. The procedure was then repeated with [Formula: see text]Lu to determine how the validation extended to another isotope and set of collimators. RESULTS: The simulation's spatial resolution, sensitivity, energy spectra and the projection images were compared with experimental measurements. The simulation and experimental uncertainties were determined and propagated to all calculations, permitting the quantitative agreement between simulated and experimental SPECT acquisitions to be determined. Statistical agreement was seen in sinograms and projection images of both [Formula: see text]Tc and [Formula: see text]Lu data. Average simulated and experimental sensitivity ratios of ([Formula: see text]) were seen for emission and scatter windows of [Formula: see text]Tc, and ([Formula: see text]) and ([Formula: see text]) for the 113 and 208 keV emissions of [Formula: see text]Lu, respectively. CONCLUSIONS: MC simulations will always be an approximation of a physical system and the level of agreement should be assessed. A validation method is presented to quantify the level of agreement between a simulation model and a physical SPECT system.

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT.

Initial clinical experience with dedicated multi-pinhole (MPH) collimator for 99mTc-HMPAO brain perfusion SPECT.

OBJECTIVE: Dedicated multi-pinhole (MPH) collimators have been successfully tested in selected clinical investigations. The aim of our work was to report initial experiences with an MPH collimator set designed for brain perfusion single photon emission tomography (SPECT). SUBJECTS AND METHODS: Ten patients underwent sequential technetium-99m-hexamethylpropyleneamineoxime (99mTc-HMPAO) SPECT with a dual-head SPECT camera equipped with conventional low-energy parallel hole collimators (LEHR), and with a triple-head system equipped with MPH collimators. Low-energy parallel hole collimators data were reconstructed by filtered back projection (FBP), ordered subset expectation maximization (OSEM), software for tomographic image reconstruction (STIR). In addition, both the parallel hole data and MPH data were reconstructed by Tera-TomoTM 3D iterative reconstruction denoted LEHR_TT3D and MPH_TT3D, respectively. Five medical experts visually compared the reconstructed images of the five data sets and defined a ranking sequence from the lowest (1) to the highest (5) image quality. Results were compared using the Friedman test. P values below 0.05 were considered significant. RESULTS: Low-energy parallel hole collimators acquisition resulted in 5 million, while MPH acquisition in 13 million total counts with 30 and 34 minutes of acquisition time, respectively. Mean rank coefficients of the reconstruction methods were 1.96±0.52, 2.66±0.46, 2.86±0.60, 3.62±0.55, 3.9±0.68 for FBP, STIR, LEHR_TT3D, LEHR_OSEM, MPH_TT3D respectively. The differences between MPH_TT3D-FBP (P<0.01); MPH_TT3D-STIR (P<0.05); LEHR_OSEM-FBP (P<0.01) were significant. CONCLUSION: Image quality provided by MPH collimator is comparable to that provided by conventional LEHR imaging. Higher sensitivity has the potential to shorten acquisition time or to reduce the amount of administered activity.

Hybrid kernelised expectation maximisation for Bremsstrahlung SPECT reconstruction in SIRT with 90Y micro-spheres.

BACKGROUND: Selective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial. METHODS: In this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method. RESULTS: The results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals. CONCLUSIONS: Such quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver.

Attenuation Correction Using Template PET Registration for Brain PET: A Proof-of-Concept Study.

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient's head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm.

Abdominal aortic aneurysm (AAA) monitoring and risk of rupture is currently assumed to be correlated with the aneurysm diameter. Aneurysm growth, however, has been demonstrated to be unpredictable. Using PET to measure uptake of [18F]-NaF in calcified lesions of the abdominal aorta has been shown to be useful for identifying AAA and to predict its growth. The PET low spatial resolution, however, can affect the accuracy of the diagnosis. Advanced edge-preserving reconstruction algorithms can overcome this issue. The kernel method has been demonstrated to provide noise suppression while retaining emission and edge information. Nevertheless, these findings were obtained using simulations, phantoms and a limited amount of patient data. In this study, the authors aim to investigate the usefulness of the anatomically guided kernelized expectation maximization (KEM) and the hybrid KEM (HKEM) methods and to judge the statistical significance of the related improvements. Sixty-one datasets of patients with AAA and 11 from control patients were reconstructed with ordered subsets expectation maximization (OSEM), HKEM and KEM and the analysis was carried out using the target-to-blood-pool ratio, and a series of statistical tests. The results show that all algorithms have similar diagnostic power, but HKEM and KEM can significantly recover uptake of lesions and improve the accuracy of the diagnosis by up to 22% compared to OSEM. The same improvements are likely to be obtained in clinical applications based on the quantification of small lesions, like for example cancer. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

PET image reconstruction using physical and mathematical modelling for time of flight PET-MR scanners in the STIR library.

This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

Comparison of Correction Techniques for the Spill in Effect in Emission Tomography.

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this study evaluates and compares the performance of various recently developed spill-in correction techniques, namely: background correction (BC), local projection (LP), and hybrid kernelized (HKEM) methods. We used a simulated digital phantom and [18F]-NaF PET data of three patients with abdominal aortic aneurysms (AAA) acquired with Siemens Biograph mMR™ and mCT™ scanners respectively. Region of Interest (ROI) analysis was performed and the extracted SUV mean , SUV max and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUV mean , SUV max and TBR max scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies.

Hybrid PET/MR Kernelised Expectation Maximisation Reconstruction for Improved Image-Derived Estimation of the Input Function from the Aorta of Rabbits.

Positron emission tomography (PET) provides simple noninvasive imaging biomarkers for multiple human diseases which can be used to produce quantitative information from single static images or to monitor dynamic processes. Such kinetic studies often require the tracer input function (IF) to be measured but, in contrast to direct blood sampling, the image-derived input function (IDIF) provides a noninvasive alternative technique to estimate the IF. Accurate estimation can, in general, be challenging due to the partial volume effect (PVE), which is particularly important in preclinical work on small animals. The recently proposed hybrid kernelised ordered subsets expectation maximisation (HKEM) method has been shown to improve accuracy and contrast across a range of different datasets and count levels and can be used on PET/MR or PET/CT data. In this work, we apply the method with the purpose of providing accurate estimates of the aorta IDIF for rabbit PET studies. In addition, we proposed a method for the extraction of the aorta region of interest (ROI) using the MR and the HKEM image, to minimise the PVE within the rabbit aortic region-a method which can be directly transferred to the clinical setting. A realistic simulation study was performed with ten independent noise realisations while two, real data, rabbit datasets, acquired with the Biograph Siemens mMR PET/MR scanner, were also considered. For reference and comparison, the data were reconstructed using OSEM, OSEM with Gaussian postfilter and KEM, as well as HKEM. The results across the simulated datasets and different time frames show reduced PVE and accurate IDIF values for the proposed method, with 5% average bias (0.8% minimum and 16% maximum bias). Consistent results were obtained with the real datasets. The results of this study demonstrate that HKEM can be used to accurately estimate the IDIF in preclinical PET/MR studies, such as rabbit mMR data, as well as in clinical human studies. The proposed algorithm is made available as part of an open software library, and it can be used equally successfully on human or animal data acquired from a variety of PET/MR or PET/CT scanners.

Effect of PET-MR Inconsistency in the Kernel Image Reconstruction Method.

Anatomically-driven image reconstruction algorithms have become very popular in positron emission tomography (PET) where they have demonstrated improved image resolution and quantification. This work, consider the effect of spatial inconsistency between MR and PET images in hot and cold regions of the PET image. We investigate these effects on the kernel method from machine learning, in particular, the hybrid kernelized expectation maximization (HKEM). These were applied to Jaszczak phantom and patient data acquired with the Biograph Siemens mMR. The results show that even a small shift can cause a significant change in activity concentration. In general, the PET-MR inconsistencies can induce the partial volume effect, more specifically the 'spill-in' of the affected cold regions and the 'spill-out' from the hot regions. The maximum change was about 100% for the cold region and 10% for the hot lesion using KEM, against the 37% and 8% obtained with HKEM. The findings of this work suggest that including PET information in the kernel enhances the flexibility of the reconstruction in case of spatial inconsistency. Nevertheless, accurate registration and choice of the appropriate MR image for the creation of the kernel is essential to avoid artifacts, blurring, and bias.