Monte Carlo simulation of the system performance of a long axial field-of-view PET based on monolithic LYSO detectors
Maya Abi Akl, Meysam Dadgar, Yassine Toufique, Othmane Bouhali and Stefaan Vandenberghe
13 Jun 2023
In light of the milestones achieved in PET design so far, further sensitivity improvements aim to optimise factors such as the dose, throughput, and detection of small lesions. While several longer axial field-of-view (aFOV) PET systems based on pixelated detectors have been installed, continuous monolithic scintillation detectors recently gained increased attention due to their depth of interaction capability and superior intrinsic resolution. As a result, the aim of this work is to present and evaluate the performance of two long aFOV, monolithic LYSO-based PET scanner designs.
Geant4 Application for Tomographic Emission (GATE) v9.1 was used to perform the simulations. Scanner designs A and B have an aFOV of 36.2 cm (7 rings) and 72.6 cm (14 rings), respectively, with 40 detector modules per ring each and a bore diameter of 70 cm. Each module is a 50 x 50 x 16 mm(3) monolithic LYSO crystal. Sensitivity, noise equivalent count rate (NECR), scatter fraction, spatial resolution, and image quality tests were performed based on NEMA NU-2018 standards.
The sensitivity of design A was calculated to be 29.2 kcps/MBq at the centre and 27 kcps/MBq at 10 cm radial offset; similarly, the sensitivity of design B was found to be 106.8 kcps/MBq and 98.3 kcps/MBq at 10 cm radial offset. NECR peaks were reached at activity concentrations beyond the range of activities used for clinical studies. In terms of spatial resolution, the values for the point sources were below 2 mm for the radial, tangential, and axial full width half maximum. The contrast recovery coefficient ranged from 53% for design B and 4:1 contrast ratio to 90% for design A and 8:1 ratio, with a reasonably low background variability.
Longer aFOV PET designs using monolithic LYSO have superior spatial resolution compared to current pixelated total-body PET (TB-PET) scanners. These systems combine high sensitivity with improved contrast recovery.
Walk-through flat panel total-body PET: a patient-centered design for high throughput imaging at lower cost using DOI-capable high-resolution monolithic detectors
Stefaan Vandenberghe, Florence M. Muller, Nadia Withofs, Meysam Dadgar, Jens Maebe, Boris Vervenne, Maya Abi Akl, Song Xue, Kuangyu Shi, Giancarlo Sportelli, Nicola Belcari, Roland Hustinx, Christian Vanhove and Joel S. Karp
19 July 2023
Long axial field-of-view (LAFOV) systems have a much higher sensitivity than standard axial field-of-view (SAFOV) PET systems for imaging the torso or full body, which allows faster and/or lower dose imaging. Despite its very high sensitivity, current total-body PET (TB-PET) throughput is limited by patient handling (positioning on the bed) and often a shortage of available personnel. This factor, combined with high system costs, makes it hard to justify the implementation of these systems for many academic and nearly all routine nuclear medicine departments. We, therefore, propose a novel, cost-effective, dual flat panel TB-PET system for patients in upright standing positions to avoid the time-consuming positioning on a PET-CT table; the walk-through (WT) TB-PET. We describe a patient-centered, flat panel PET design that offers very efficient patient throughput and uses monolithic detectors (with BGO or LYSO) with depth-of-interaction (DOI) capabilities and high intrinsic spatial resolution. We compare system sensitivity, component costs, and patient throughput of the proposed WT-TB-PET to a SAFOV (= 26 cm) and a LAFOV (= 106 cm) LSO PET systems.
Patient width, height (= top head to start of thighs) and depth (= distance from the bed to front of patient) were derived from 40 randomly selected PET-CT scans to define the design dimensions of the WT-TB-PET. We compare this new PET system to the commercially available Siemens Biograph Vision 600 (SAFOV) and Siemens Quadra (LAFOV) PET-CT in terms of component costs, system sensitivity, and patient throughput. System cost comparison was based on estimating the cost of the two main components in the PET system (Silicon Photomultipliers (SiPMs) and scintillators). Sensitivity values were determined using Gate Monte Carlo simulations. Patient throughput times (including CT and scout scan, patient positioning on bed and transfer) were recorded for 1 day on a Siemens Vision 600 PET. These timing values were then used to estimate the expected patient throughput (assuming an equal patient radiotracer injected activity to patients and considering differences in system sensitivity and time-of-flight information) for WT-TB-PET, SAFOV and LAFOV PET.
The WT-TB-PET is composed of two flat panels; each is 70 cm wide and 106 cm high, with a 50-cm gap between both panels. These design dimensions were justified by the patient sizes measured from the 40 random PET-CT scans. Each panel consists of 14 × 20 monolithic BGO detector blocks that are 50 × 50 × 16 mm in size and are coupled to a readout with 6 × 6 mm SiPMs arrays. For the WT-TB-PET, the detector surface is reduced by a factor of 1.9 and the scintillator volume by a factor of 2.2 compared to LAFOV PET systems, while demonstrating comparable sensitivity and much better uniform spatial resolution (< 2 mm in all directions over the FOV). The estimated component cost for the WT-TB-PET is 3.3 × lower than that of a 106 cm LAFOV system and only 20% higher than the PET component costs of a SAFOV. The estimated maximum number of patients scanned on a standard 8-h working day increases from 28 (for SAFOV) to 53–60 (for LAFOV in limited/full acceptance) to 87 (for the WT-TB-PET). By scanning faster (more patients), the amount of ordered activity per patient can be reduced drastically: the WT-TB-PET requires 66% less ordered activity per patient than a SAFOV.
We propose a monolithic BGO or LYSO-based WT-TB-PET system with DOI measurements that departs from the classical patient positioning on a table and allows patients to stand upright between two flat panels. The WT-TB-PET system provides a solution to achieve a much lower cost TB-PET approaching the cost of a SAFOV system. High patient throughput is increased by fast patient positioning between two vertical flat panel detectors of high sensitivity. High spatial resolution (< 2 mm) uniform over the FOV is obtained by using DOI-capable monolithic scintillators.
Effect of detector geometry and surface finish on Cerenkov based time estimation in monolithic BGO detectors
Jens Maebe and Stefaan Vandenberghe
5 January 2023
Objective. Time-of-flight positron emission tomography based on bismuth germanate (BGO) detectors is made possible due to fast emission of Cerenkov light. Only around 17 Cerenkov photons are produced per 511 keV photoelectric event, making high photon collection efficiency crucial for obtaining good time-of-flight capabilities. In this study, we investigate how different lateral and back surface finishes affect the photon collection efficiency and Cerenkov based timing performance in monolithic BGO. Approach. The study is performed using GATE for gamma and optical photon modeling, with surface reflections of photons simulated by the LUT Davis model. We compare for different detector configurations (regarding size and surface finishes) the photon collection efficiency, detection delays of the first few optical photons and coincidence time resolution estimations obtained by modeling the SiPM signals and performing leading edge discrimination. An additional comparison is made to LYSO scintillators and pixelated detectors. Main results. Although Cerenkov photon emission is directional, many high incidence angle Cerenkov photons are emitted due to electron scattering in the crystal. Substituting a polished back (photodetector side) surface for a rough surface increases the collection efficiency of these high angle of incidence photons. Results show that for a monolithic 50 × 50 × 12 mm3 BGO detector with reflective side surfaces, this leads to an overall increase in photon collection efficiency of 34%. Cerenkov photon collection efficiency is also improved, resulting in a reduction of the photon detection delays (and the variation therein) of the first few optical photons. This leads to a better coincidence time resolution, primarily achieved by a shortening of the tails in the time-of-flight kernel, with an 18% reduction in full width at tenth maximum. Significance. This study shows the importance of the photon collection efficiency for timing performance in Cerenkov based monolithic detectors, and how it can be improved with different surface finishes.
Simulation study on 3D convolutional neural networks for time-of-flight prediction in monolithic PET detectors using digitized waveforms
Jens Maebe and Stefaan Vandenberghe
15 June 2022
Objective. We investigate the use of 3D convolutional neural networks for gamma arrival time estimation in monolithic scintillation detectors. Approach. The required data is obtained by Monte Carlo simulation in GATE v8.2, based on a 50 × 50 × 16 mm3 monolithic LYSO crystal coupled to an 8 × 8 readout array of silicon photomultipliers (SiPMs). The electronic signals are simulated as a sum of bi-exponentional functions centered around the scintillation photon detection times. We include various effects of statistical fluctuations present in non-ideal SiPMs, such as dark counts and limited photon detection efficiency. The data was simulated for two distinct overvoltages of the SensL J-Series 60 035 SiPMs, in order to test the effects of different SiPM parameters. The neural network uses the array of detector waveforms, digitized at 10 GS s−1, to predict the time at which the gamma arrived at the crystal. Main results. Best results were achieved for an overvoltage of +6 V, at which point the SiPM reaches its optimal photon detection efficiency, resulting in a coincidence time resolution (CTR) of 141 ps full width at half maximum (FWHM). It is a 26% improvement compared to a simple averaging of the first few SiPM timestamps obtained by leading edge discrimination, which in comparison produced a CTR of 177 ps FWHM. In addition, better detector uniformity was achieved, although some degradation near the corners did remain. Significance. These improvements in time resolution can lead to higher signal-to-noise ratios in time-of-flight positron emission tomography, ultimately resulting in better diagnostic capabilities.
Performance evaluation of a micro-CT system for laboratory animal imaging with iterative reconstruction capabilities
Florence Marie Muller, Christian Vanhove, Bert Vandeghinste and Stefaan Vandenberghe
Background: In recent years, there has been a rapid proliferation in micro-computed tomography (micro-CT) systems becoming more available for routine preclinical research, with applications in many areas, including bone, lung, cancer, and cardiac imaging. Micro-CT provides the means to non-invasively acquire detailed anatomical information, but high-resolution imaging comes at the cost of longer scan times and higher doses, which is not desirable given the potential risks related to x-ray radiation. To achieve dose reduction and higher throughputs without compromising image quality, fewer projections can be acquired. This is where iterative reconstruction methods can have the potential to reduce noise since these algorithms can better handle sparse projection data, compared to filtered backprojection PURPOSE: We evaluate the performance characteristics of a compact benchtop micro-CT scanner that provides iterative reconstruction capabilities with GPU-based acceleration. We thereby investigate the potential benefit of iterative reconstruction for dose reduction.
Methods: Based on a series of phantom experiments, the benchtop micro-CT system was characterized in terms of image uniformity, noise, low contrast detectability, linearity, and spatial resolution. Whole-body images of a plasticized ex vivo mouse phantom were also acquired. Different acquisition protocols (general-purpose versus high-resolution, including low dose scans) and different reconstruction strategies (analytic versus iterative algorithms: FDK, ISRA, ISRA-TV) were compared.
Results: Signal uniformity was maintained across the radial and axial field-of-view (no cupping effect) with an average difference in Hounsfield units (HU) between peripheral and central regions below 50. For low contrast detectability, regions with at least ∆HU of 40 to surrounding material could be discriminated (for rods of 2.5 mm diameter). A high linear correlation (R2 = 0.997) was found between measured CT values and iodine concentrations (0-40 mg/ml). Modulation transfer function (MTF) calculations on a wire phantom evaluated a resolution of 10.2 lp/mm at 10% MTF that was consistent with the 8.3% MTF measured on the 50 µm bars (10 lp/mm) of a bar-pattern phantom. Noteworthy changes in signal-to-noise and contrast-to-noise values were found for different acquisition and reconstruction protocols. Our results further showed the potential of iterative reconstruction to deliver images with less noise and artefacts.
Conclusions: In summary, the micro-CT system that was evaluated in the present work was shown to provide a good combination of performance characteristics between image uniformity, low contrast detectability, and resolution in short scan times. With the iterative reconstruction capabilities of this micro-CT system in mind (ISRA and ISRA-TV), the adoption of such algorithms by GPU-based acceleration enables the integration of noise reduction methods which here demonstrated potential for high-quality imaging at reduced doses.
Artificial intelligence with deep learning in nuclear medicine and radiology
Milan Decuyper, Jens Maebe, Roel Van Holen and Stefaan Vandenberghe
The use of deep learning in medical imaging has increased rapidly over the past few years, finding applications throughout the entire radiology pipeline, from improved scanner performance to automatic disease detection and diagnosis. These advancements have resulted in a wide variety of deep learning approaches being developed, solving unique challenges for various imaging modalities. This paper provides a review on these developments from a technical point of view, categorizing the different methodologies and summarizing their implementation. We provide an introduction to the design of neural networks and their training procedure, after which we take an extended look at their uses in medical imaging. We cover the different sections of the radiology pipeline, highlighting some influential works and discussing the merits and limitations of deep learning approaches compared to other traditional methods. As such, this review is intended to provide a broad yet concise overview for the interested reader, facilitating adoption and interdisciplinary research of deep learning in the field of medical imaging.
High-resolution monolithic LYSO detector with 6-layer depth-of-interaction for clinical PET
Mariele Stockhoff, Milan Decuyper, Roel Van Holen and Stefaan Vandenberghe
Abstract:The system spatial resolution of whole-body positron emission tomography (PET) is limited to around 2 mm due to positron physics and the large diameter of the bore. To stay below this 'physics'-limit a scintillation detector with an intrinsic spatial resolution of around 1.3 mm is needed. Currently used detector technology consists of arrays of 2.6-5 mm segmented scintillator pixels which are the dominant factor contributing to the system resolution. Pixelated detectors using smaller pixels exist but face major drawbacks in sensitivity, timing, energy resolution and cost. Monolithic continuous detectors, where the spatial resolution is determined by the shape of the light distribution on the photodetector array, are a promising alternative. Without having the drawbacks of pixelated detectors, monolithic ones can also provide depth-of-interaction (DOI) information. In this work we present a monolithic detector design aiming to serve high-resolution clinical PET systems while maintaining high sensitivity. A 50 × 50 × 16 mm3Lutetium-Yttrium oxyorthosilicate scintillation crystal with silicon photomultiplier (SiPM) backside readout is calibrated in singles mode by a collimated beam obtaining a reference dataset for the event positioning. A mean nearest neighbour (MNN) algorithm and an artificial neural network for positioning are compared. The targeted intrinsic detector resolution of 1.3 mm needed to reach a 2 mm resolution on system level was accomplished with both algorithms. The neural network achieved a mean spatial resolution of 1.14 mm FWHM for the whole detector and 1.02 mm in the centre (30 × 30 mm2). The MNN algorithm performed slightly worse with 1.17 mm for the whole detector and 1.13 mm in the centre. The intrinsic DOI information will also result in uniform system spatial resolution over the full field of view.
Optical simulation study on the spatial resolution of a thick monolithic PET detector
Mariele Stockhoff , Roel Van Holen and Stefaan Vandenberghe
23 Sep 2019
The intrinsic spatial resolution of clinical positron emission tomography (PET) detectors is ~3-4 mm. A further improvement of the resolution using pixelated detectors will not only result in a prohibitive cost, but is also inevitably accompanied by a strong degradation of important performance parameters like timing, energy resolution and sensitivity. Therefore, it is likely that future generation high resolution PET detectors will be based on continuous monolithic scintillation detectors. Monolithic detectors have attractive properties to reach superior 3D spatial resolution while outperforming pixelated detectors in timing, energy resolution and sensitivity. In this work, optical simulations including an advanced surface reflection model, allow us to investigate the influence of three parameters on the spatial resolution: silicon photomultiplier (SiPM) pixel size, photon detection efficiency (PDE) and the number of channels used to read out the SiPM array. A lutetium-yttrium oxyorthosilicate (LYSO) crystal with dimensions 50 × 50 × 16 mm3 coupled to an SiPM array is calibrated and a nearest neighbor (NN) algorithm is used to position events. Findings show that the tested parameters affect the spatial resolution resulting in 0.40-0.66 mm full width at half maximum (FWHM). Best resolution could be obtained with smaller SiPM pixels, higher PDE, and an individual channel readout. However, it was shown that combining channels by adding their signals can significantly reduce the amount of readout channels while having small or no significant impact on the resolution. The mean depth of interaction (DOI) estimation error is 1.6 mm. This study demonstrates the ultimate spatial resolution that can be obtained with this detector without being constrained by practical limitations of experimental setups. In the future these optical simulations may be used as a more precise and fast method to obtain calibration data for real monolithic detectors.