Relevance of accurate Monte Carlo modeling in nuclear medical imaging

Radiation Detectors and Sensors in Medical Imaging

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory.

Cloud-based serverless computing enables accelerated monte carlo simulations for nuclear medicine imaging

Objective.This study investigates the potential of cloud-based serverless computing to accelerate Monte Carlo (MC) simulations for nuclear medicine imaging tasks. MC simulations can pose a high computational burden-even when executed on modern multi-core computing servers. Cloud computing allows simulation tasks to be highly parallelized and considerably accelerated.Approach.We investigate the computational performance of a cloud-based serverless MC simulation of radioactive decays for positron emission tomography imaging using Amazon Web Service (AWS) Lambda serverless computing platform for the first time in scientific literature. We provide a comparison of the computational performance of AWS to a modern on-premises multi-thread reconstruction server by measuring the execution times of the processes using between105and2·1010simulated decays. We deployed two popular MC simulation frameworks-SimSET and GATE-within the AWS computing environment. Containerized application images were used as a basis for an AWS Lambda function, and local (non-cloud) scripts were used to orchestrate the deployment of simulations. The task was broken down into smaller parallel runs, and launched on concurrently running AWS Lambda instances, and the results were postprocessed and downloaded via the Simple Storage Service.Main results.Our implementation of cloud-based MC simulations with SimSET outperforms local server-based computations by more than an order of magnitude. However, the GATE implementation creates more and larger output file sizes and reveals that the internet connection speed can become the primary bottleneck for data transfers. Simulating 109decays using SimSET is possible within 5 min and accrues computation costs of about $10 on AWS, whereas GATE would have to run in batches for more than 100 min at considerably higher costs.Significance.Adopting cloud-based serverless computing architecture in medical imaging research facilities can considerably improve processing times and overall workflow efficiency, with future research exploring additional enhancements through optimized configurations and computational methods.

Dose, dose, dose, but where is the patient dose?

The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed. Technological developments in recent years involving AI-based automatic organ segmentation and 'near real-time' Monte Carlo dose calculations suggest the feasibility and advantage of obtaining patient-specific organ doses. It appears that the time for ICRP and other international organizations to embrace 'patient-specific' dose quantity representing risk may have finally come. While the existing dose metrices meet specific demands, emphasis needs to be also placed on making radiation units understandable to the medical community.

MCGPU-PET: An Open-Source Real-Time Monte Carlo PET Simulator

Monte Carlo (MC) simulations are commonly used to model the emission, transmission, and/or detection of radiation in Positron Emission Tomography (PET). In this work, we introduce a new open-source MC software for PET simulation, MCGPU-PET, which has been designed to fully exploit the computing capabilities of modern GPUs to simulate the acquisition of more than 100 million coincidences per second from voxelized sources and material distributions. The new simulator is an extension of the PENELOPE-based MCGPU code previously used in cone-beam CT and mammography applications. We validated the accuracy of the accelerated code by comparing it to GATE and PeneloPET simulations achieving an agreement within 10 percent approximately. As an example application of the code for fast estimation of PET coincidences, a scan of the NEMA IQ phantom was simulated. A fully 3D sinogram with 6382 million true coincidences and 731 million scatter coincidences was generated in 54 seconds in one GPU. MCGPU-PET provides an estimation of true and scatter coincidences and spurious background (for positron-gamma emitters such as 124I) at a rate 3 orders of magnitude faster than CPU-based MC simulators. This significant speed-up enables the use of the code for accurate scatter and prompt-gamma background estimations within an iterative image reconstruction process.

Validation of a discovery MI 4-ring model according to the NEMA NU 2-2018 standards: from Monte Carlo simulations to clinical-like reconstructions

BACKGROUND

We propose a comprehensive evaluation of a Discovery MI 4-ring (DMI) model, using a Monte Carlo simulator (GATE) and a clinical reconstruction software package (PET toolbox). The following performance characteristics were compared with actual measurements according to NEMA NU 2-2018 guidelines: system sensitivity, count losses and scatter fraction (SF), coincidence time resolution (CTR), spatial resolution (SR), and image quality (IQ). For SR and IQ tests, reconstruction of time-of-flight (TOF) simulated data was performed using the manufacturer's reconstruction software.

RESULTS

Simulated prompt, random, true, scatter and noise equivalent count rates closely matched the experimental rates with maximum relative differences of 1.6%, 5.3%, 7.8%, 6.6%, and 16.5%, respectively, in a clinical range of less than 10 kBq/mL. A 3.6% maximum relative difference was found between experimental and simulated sensitivities. The simulated spatial resolution was better than the experimental one. Simulated image quality metrics were relatively close to the experimental results.

CONCLUSIONS

The current model is able to reproduce the behaviour of the DMI count rates in the clinical range and generate clinical-like images with a reasonable match in terms of contrast and noise.

Investigation and optimization of PET-guided SPECT reconstructions for improved radionuclide therapy dosimetry estimates

Introduction

To investigate and optimize the SPECTRE (Single Photon Emission Computed Theranostic REconstruction) reconstruction approach, using the hybrid kernelised expectation maximization (HKEM) algorithm implemented in the software for tomographic image reconstruction (STIR) software library, and to demonstrate the feasibility of performing algorithm exploration and optimization in 2D. Optimal SPECTRE parameters were investigated for the purpose of improving SPECT-based radionuclide therapy (RNT) dosimetry estimates.

Materials and Methods

Using the NEMA IEC body phantom as the test object, SPECT data were simulated to model an early and late imaging time point following a typical therapeutic dose of 8 GBq of 177Lu. A theranostic 68Ga PET-prior was simulated for the SPECTRE reconstructions. The HKEM algorithm parameter space was investigated for SPECT-unique and PET-SPECT mutual features to characterize optimal SPECTRE parameters for the simulated data. Mean and maximum bias, coefficient of variation (COV %), recovery, SNR and root-mean-square error (RMSE) were used to facilitate comparisons between SPECTRE reconstructions and OSEM reconstructions with resolution modelling (OSEM_RM). 2D reconstructions were compared to those performed in 3D in order to evaluate the utility of accelerated algorithm optimization in 2D. Segmentation accuracy was evaluated using a 42% fixed threshold (FT) on the 3D reconstructed data.

Results

SPECTRE parameters that demonstrated improved image quality and quantitative accuracy were determined through investigation of the HKEM algorithm parameter space. OSEM_RM and SPECTRE reconstructions performed in 2D and 3D were qualitatively and quantitatively similar, with SPECTRE showing an average reduction in background COV % by a factor of 2.7 and 3.3 for the 2D case and 3D case respectively. The 42% FT analysis produced an average % volume difference from ground truth of 158% and 26%, for the OSEM_RM and SPECTRE reconstructions, respectively.

Conclusions

The SPECTRE reconstruction approach demonstrates significant potential for improved SPECT image quality, leading to more accurate RNT dosimetry estimates when conventional segmentation methods are used. Exploration and optimization of SPECTRE benefited from both fast reconstruction times afforded by first considering the 2D case. This is the first in-depth exploration of the SPECTRE reconstruction approach, and as such, it reveals several insights for reconstructing SPECT data using PET side information.

Validation of a Monte Carlo simulated cardiac phantom for planar and SPECT studies

PURPOSE

This work aimed to validate Monte Carlo (MC) simulated cardiac phantoms for the evaluation of planar- and SPECT-gated-blood-pool (GBP-P and GBP-S) studies.

METHODS

A comparison of gamma camera system performance criteria measurements (energy resolution, spatial resolution, sensitivity) with MC simulations was conducted. Furthermore, the accuracy of measured and simulated volumes of two stereolithography-printed cardiac phantoms (based on 4D-XCAT phantoms) was assessed. Finally, the simulated GBP-P and GBP-S XCAT studies were validated by comparing calculated left ventricular ejection fraction (LVEF) and ventricle volume values with known parameters.

RESULTS

The simulated performance criteria compared well with measured values (energy resolution difference: 0.1 ± 0.10%; spatial resolution (full width at half maximum) difference ≤ 0.5 ± 0.8 mm and system sensitivity difference ≤ 6.2 ± 0.62cps/MBq). The measured and simulated cardiac phantoms were in good agreement; the left anterior oblique views compared well. This is supported by line profiles through these phantoms and on average, simulated counts were 5.8% lower than measured counts. The LVEF values calculated from the GBP-P and GBP-S simulated data differ from known values (2.8 ± 0.64% and 0.8 ± 0.52%). The differences between the known XCAT LV volumes and simulated GBP-S calculated volumes were -1.2 ± 1.91 ml and -1.5 ± 0.96 ml for the end-diastolic and end-systolic volumes.

CONCLUSION

The MC-simulated cardiac phantom has been validated successfully. Stereolithography-printing allows researchers to create clinically realistic organ phantoms and is a valuable tool for validating MC simulations and clinical software. By conducting GBP simulation studies with various XCAT models, the user will be able to generate GBP-P and GBP-S databases for future software evaluation.

Validation of [Formula: see text]Tc and [Formula: see text]Lu quantification parameters for a Monte Carlo modelled gamma camera

PURPOSE

Monte Carlo (MC) simulation in Nuclear Medicine is a powerful tool for modeling many physical phenomena which are difficult to track or measure directly. MC simulation in SPECT/CT imaging is particularly suitable for optimizing the quantification of activity in a patient, and, consequently, the absorbed dose to each organ. To do so, validating MC results with real data acquired with gamma camera is mandatory. The aim of this study was the validation of the calibration factor (CF) and the recovery coefficient (RC) obtained with SIMIND Monte Carlo code for modeling a Siemens Symbia Intevo Excel SPECT-CT gamma camera to ensure optimal [Formula: see text]Tc and [Formula: see text]Lu SPECT quantification.

METHODS

Phantom experiments using [Formula: see text]Tc and [Formula: see text]Lu have been performed to measure spatial resolution and sensitivity, as well as to evaluate the CF and RC from acquired data. The geometries used for 2D planar imaging were (1) Petri dish and (2) capillary source while for 3D volumetric imaging were (3) a uniform filled cylinder phantom and (4) a Jaszczack phantom with spheres of different volumes. The experimental results have been compared with the results obtained from Monte Carlo simulations performed in the same geometries.

RESULTS

Comparison shows good accordance between simulated and experimental data. The measured planar spatial resolution was 8.3[Formula: see text] mm for [Formula: see text]Tc and 11.8±0.6 mm for [Formula: see text]Lu. The corresponding data obtained by SIMIND for [Formula: see text]Tc was 7.8±0.1 mm, while for [Formula: see text]Lu was 12.4±0.4 mm. The CF was 110.1±5.5 cps/MBq for Technetium and 18.3±1.0 cps/MBq for Lutetium. The corresponding CF obtained by SIMIND for [Formula: see text]Tc was 107.3±0.3 cps/MBq, while for [Formula: see text]Lu 20.4±0.7 cps/MBq. Moreover, a complete curve RCs vs Volume (ml) both for Technetium and Lutetium was determined to correct the PVE for all volumes of clinical interest. In none of the cases, a RC coefficient equal to 100 was found.

CONCLUSIONS

The validation of quantification parameters shows that SIMIND can be used for simulating both gamma camera planar and SPECT images of Siemens Symbia Intevo using [Formula: see text]Tc and [Formula: see text]Lu radionuclides for different medical purposes and treatments.

Dosimetry Effects Due to the Presence of Fe Nanoparticles for Potential Combination of Hyperthermic Cancer Treatment with MRI-Based Image-Guided Radiotherapy

Nanoparticles have proven to be biocompatible and suitable for many biomedical applications. Currently, hyperthermia cancer treatments based on Fe nanoparticle infusion excited by alternating magnetic fields are commonly used. In addition to this, MRI-based image-guided radiotherapy represents, nowadays, one of the most promising accurate radiotherapy modalities. Hence, assessing the feasibility of combining both techniques requires preliminary characterization of the corresponding dosimetry effects. The present work reports on a theoretical and numerical simulation feasibility study aimed at pointing out preliminary dosimetry issues. Spatial dose distributions incorporating magnetic nanoparticles in MRI-based image-guided radiotherapy have been obtained by Monte Carlo simulation approaches accounting for all relevant radiation interaction properties as well as charged particles coupling with strong external magnetic fields, which are representative of typical MRI-LINAC devices. Two main effects have been evidenced: local dose enhancement (up to 60% at local level) within the infused volume, and non-negligible changes in the dose distribution at the interfaces between different tissues, developing to over 70% for low-density anatomical cavities. Moreover, cellular uptakes up to 10% have been modeled by means of considering different Fe nanoparticle concentrations. A theoretical temperature-dependent model for the thermal enhancement ratio (TER) has been used to account for radiosensitization due to hyperthermia. The outcomes demonstrated the reliability of the Monte Carlo approach in accounting for strong magnetic fields and mass distributions from patient-specific anatomy CT scans to assess dose distributions in MRI-based image-guided radiotherapy combined with magnetic nanoparticles, while the hyperthermic radiosensitization provides further and synergic contributions.

Development of scalable lymphatic system in the 4D XCAT phantom: Application to quantitative evaluation of lymphoma PET segmentations

BACKGROUND

Digital anthropomorphic phantoms, such as the 4D extended cardiac-torso (XCAT) phantom, are actively used to develop, optimize, and evaluate a variety of imaging applications, allowing for realistic patient modeling and knowledge of ground truth. The XCAT phantom defines the activity and attenuation for a simulated patient, which includes a complete set of organs, muscle, bone, and soft tissue, while also accounting for cardiac and respiratory motion. However, the XCAT phantom does not currently include the lymphatic system, critical for evaluating medical imaging tasks such as sentinel node detection, node density measurement, and radiation dosimetry.

PURPOSE

In this study, we aimed to develop a scalable lymphatic system in the XCAT phantom, to facilitate improved research of the lymphatic system in medical imaging. Using this scalable lymphatic system, we modeled the lymph node conglomerate pathology that is characteristically observed in primary mediastinal B-cell lymphoma (PMBCL). As an extended application, we evaluated positron emission tomography (PET) image quantification of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of these simulated lymphomas, though the phantoms may be applied to other imaging modalities and study design paradigms (e.g., image quality, detection).

METHODS

A template model for the lymphatic system was developed based on anatomical data from the Visible Human Project of the National Library of Medicine. The segmented nodes and vessels were fit with non-uniform rational basis spline surfaces, and multichannel large deformation diffeomorphic metric mapping was used to propagate the template to different XCAT anatomies. To model conglomerates observed in PMBCL, lymph nodes were enlarged, converged within the mediastinum, and tracer concentration was increased. We used the phantoms as inputs to a PET simulation tool, which generated images using ordered subsets expectation maximization reconstruction with 2-8 mm Gaussian filters. Fixed thresholding (FT) and gradient segmentation were used to determine MTV and TLG. Percent bias (%Bias) and coefficient of variation (COV) were computed as measures of accuracy and precision, respectively, for each MTV and TLG measurement.

RESULTS

Using the methodology described above, we introduced a scalable lymphatic system in the XCAT phantom, which allows for the radioactivity and attenuation ground truth to be generated in 116 ± 2.5 s using a 2.3 GHz processor. Within the Rhinoceros interface, lymph node anatomy and function were modified to create a cohort of 10 phantoms with lymph node conglomerates. Using the lymphoma phantoms to evaluate PET quantification of MTV, mean %Bias values were -9.3%, -41.3%, and 20.9%, while COV values were 4.08%, 7.6%, and 3.4% using 25% FT, 40% FT, and gradient segmentations, respectively. Comparatively for TLG, mean %Bias values were -27.4%, -45.8%, and -16.0%, while COV values were 1.9%, 5.7%, and 1.4%, for the 25% FT, 40% FT, and gradient segmentations, respectively.

CONCLUSIONS

In this work, we upgraded the XCAT phantom to include a lymphatic system, comprised of a network of 276 scalable lymph nodes and corresponding vessels. As an application, we created a cohort of phantoms with lymph node conglomerates to evaluate lymphoma quantification in PET imaging, which highlights an important application of this work.

Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure

Objective. This paper describes the development and validation of a GPU-accelerated Monte Carlo (MC) dose computing module dedicated to organ dose calculations of individual patients undergoing nuclear medicine (NM) internal radiation exposures involving PET/CT examination. Approach. This new module extends the more-than-10-years-long ARCHER project that developed a GPU-accelerated MC dose engine by adding dedicated NM source-definition features. To validate the code, we compared dose distributions from the point ion source, including 18F, 11C, 15O, and 68Ga, calculated for a water phantom against a well-tested MC code, GATE. To demonstrate the clinical utility and advantage of ARCHER-NM, one set of 18F-FDG PET/CT data for an adult male NM patient is calculated using the new code. Radiosensitive organs in the CT dataset are segmented using a CNN-based tool called DeepViewer. The PET image intensity maps are converted to radioactivity distributions to allow for MC radiation transport dose calculations at the voxel level. The dose rate maps and corresponding statistical uncertainties were calculated at the acquisition time of PET image. Main results. The water-phantom results show excellent agreement, suggesting that the radiation physics module in the new NM code is adequate. The dose rate results of the 18F-FDG PET imaging patient show that ARCHER-NM’s results agree very well with those of the GATE within −2.45% to 2.58% (for a total of 28 organs considered in this study). Most impressively, ARCHER-NM obtains such results in 22 s while it takes GATE about 180 min for the same number of 5 × 108 simulated decay events. Significance. This is the first study presenting GPU-accelerated patient-specific MC internal radiation dose rate calculations for clinically realistic 18F-FDG PET/CT imaging case involving autosegmentation of whole-body PET/CT images. This study suggests that the proposed computing tools—ARCHER-NM— are accurate and fast enough for routine internal dosimetry in NM clinics.

Evaluation of Iodine-123 and Iodine-131 SPECT activity quantification: a Monte Carlo study

Purpose

The quantitative accuracy of Nuclear Medicine images, acquired for both planar and SPECT studies, is influenced by the isotope-collimator combination as well as image corrections incorporated in the iterative reconstruction process. These factors can be investigated and optimised using Monte Carlo simulations. This study aimed to evaluate SPECT quantification accuracy for ¹²³I with both the low-energy high resolution (LEHR) and medium-energy (ME) collimators and ¹³¹I with the high-energy (HE) collimator.

Methods

Simulated SPECT projection images were reconstructed using the OS-EM iterative algorithm, which was optimised for the number of updates, with appropriate corrections for scatter, attenuation and collimator detector response (CDR), including septal scatter and penetration compensation. An appropriate calibration factor (CF) was determined from four different source geometries (activity-filled: water-filled cylindrical phantom, sphere in water-filled (cold) cylindrical phantom, sphere in air and point-like source), investigated with different volume of interest (VOI) diameters. Recovery curves were constructed from recovery coefficients to correct for partial volume effects (PVEs). The quantitative method was evaluated for spheres in voxel-based digital cylindrical and patient phantoms.

Results

The optimal number of OS-EM updates was 60 for all isotope-collimator combinations. The CF_point with a VOI diameter equal to the physical size plus a 3.0-cm margin was selected, for all isotope-collimator geometries. The spheres’ quantification errors in the voxel-based digital cylindrical and patient phantoms were less than 3.2% and 5.4%, respectively, for all isotope-collimator combinations.

Conclusion

The study showed that quantification errors of less than 6.0% could be attained, for all isotope-collimator combinations, if corrections for; scatter, attenuation, CDR (including septal scatter and penetration) and PVEs are performed. ¹²³I LEHR and ¹²³I ME quantification accuracies compared well when appropriate corrections for septal scatter and penetration were applied. This can be useful in departments that perform ¹²³I studies and may not have access to ME collimators.

Verification of phantom accuracy using a Monte Carlo simulation: bone scintigraphy chest phantom

We aimed to compare the measurement and simulation data of bone scintigraphy of a chest phantom using a Monte Carlo simulation to verify the accuracy of the simulated data. The SIM² bone phantom was enclosed using 300 kBq/mL of technetium-99 m (^99mTc) to represent the bone tumor and 50 kBq/mL of ^99mTc to represent normal bone. Projection data were obtained using single-photon emission computed tomography (SPECT). Simulated projection data were constructed based on CT data. The contrast ratio, recovery coefficient (RC), % coefficient variation (CV), and power spectrum density (PSD) of each part were calculated from the reconstructed data. The contrast ratio and RC were equal between the actual and simulated data. Higher % CV values were noted for soft tissue than for normal bone. The PSD was equal for all frequency band ranges. Our results prove the utility of the Monte Carlo simulation for verifying various data using phantoms.

Applications of artificial intelligence in nuclear medicine image generation

Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging have focused on the diagnosis, treatment monitoring, and correlation analyses with pathology or specific gene mutation. It can also be used for image generation to shorten the time of image acquisition, reduce the dose of injected tracer, and enhance image quality. This work provides an overview of the application of AI in image generation for single-photon emission computed tomography (SPECT) and positron emission tomography (PET) either without or with anatomical information [CT or magnetic resonance imaging (MRI)]. This review focused on four aspects, including imaging physics, image reconstruction, image postprocessing, and internal dosimetry. AI application in generating attenuation map, estimating scatter events, boosting image quality, and predicting internal dose map is summarized and discussed.

Validation of a SIMIND Monte Carlo modelled gamma camera for Iodine-123 and Iodine-131 imaging

Purpose

Monte Carlo (MC) modelling techniques can assess the quantitative accuracy of both planar and SPECT Nuclear Medicine images. It is essential to validate the MC code's capabilities in modelling a specific clinical gamma camera, for radionuclides of interest, before its use as a clinical image simulator. This study aimed to determine if the SIMIND MC code accurately simulates emission images measured with a Siemens Symbia™ T16 SPECT/CT system for I-123 with a LEHR and a ME collimator and for I-131 with a HE collimator.

Methods

The static and WB planar validation tests included extrinsic system energy pulse-height distributions (EPHDs), system sensitivity and system spatial resolution in air as well as a scatter medium. The SPECT validation test comprised the sensitivity from a simple geometry of a sphere in a cylindrical water-filled phantom.

Results

The system EPHDs compared well, with differences between measured and simulated primary photopeak FWHM values not exceeding 4.6 keV. Measured and simulated planar system sensitivity values displayed percentage differences less than 6.9% and 6.3% for static and WB planar images, respectively. Measured and simulated planar system spatial resolution values in air showed percentage differences not exceeding 6.4% (FWHM) and 10.0% (FWTM), and 5.1% (FWHM) and 5.4% (FWTM) for static and WB planar images, respectively. For static planar system spatial resolution measured and simulated in a scatter medium, percentage differences of FWHM and FWTM values were less than 5.8% and 12.6%, respectively. The maximum percentage difference between the measured and simulated SPECT validation results was 3.6%.

Conclusion

The measured and simulated validation results compared well for all isotope-collimator combinations and showed that the SIMIND MC code could be used to accurately simulate static and WB planar and SPECT projection images of the Siemens Symbia™ T16 SPECT/CT for both I-123 and I-131 with their respective collimators.

Monte Carlo simulation and performance assessment of GE Discovery 690 VCT positron emission tomography/computed tomography scanner

The aim of this study is to simulate GE Discovery 690 VCT positron emission tomography/computed tomography (PET/CT) scanner using Geant4 Application for Tomographic Emission (GATE) simulation package (version 8). Then, we assess the performance of scanner by comparing measured and simulated parameter results. Detection system and geometry of PET scanner that consists of 13,824 LYSO crystals designed in 256 blocks and 24 ring detectors were modeled. In order to achieve a precise model, we verified scanner model. Validation was based on a comparison between simulation data and experimental results obtained with this scanner in the same situation. Parameters used for validation were sensitivity, spatial resolution, and contrast. Image quality assessment was done based on comparing the contrast recovery coefficient (CRC) of simulated and measured images. The findings demonstrate that the mean difference between simulated and measured sensitivity is <7%. The simulated spatial resolution agreed to within <5.5% of the measured values. Contrast results had a slight divergence within the range below 4%. The image quality validation study demonstrated an acceptable agreement in CRC for 8:1 and 2:1 source-to-background activity ratio. Validated performance parameters showed good agreement between experimental data and simulated results and demonstrated that GATE is a valid simulation tool for simulating this scanner model. The simulated model of this scanner can be used for future studies regarding optimization of image reconstruction algorithms and emission acquisition protocols.

A Monte Carlo simulation study of scatter fraction and the impact of patient BMI on scatter in long axial field-of-view PET scanners

The NEMA NU-2 standard describes a protocol for measurement of scatter fraction (SF) using an axially-aligned line source, offset at 45mm from the central axis, in a cylindrical polyethylene phantom. In this work, which is an extension of our preliminary results previuosly published in the Proceedings of IEEE NSS/MIC 2018 [1], we aim to evaluate the performance of the NEMA NU-2 SF protocol in a Siemens Biograph mCT PET/CT whole-body scanner and a long axial field-of-view (LAFOV) total-body PET scanner to determine whether modifications to the NEMA NU-2 SF protocol are needed for the characterisation of scatter in such scanners. In addition, we evaluate the impact of patient body mass index (BMI) on SF in a LAFOV scanner. The Siemens Biograph mCT and a typical LAFOV PET scanner were modelled in GATE. Monte Carlo simulations were performed to validate the mCT scanner model against published experimental results. SF was estimated using a modified NEMA NU-2 protocol with variable radial offsets on both scanners and compared to ground truth SF measurements obtained with a uniform-activity cylindrical phantom. Correlation between BMI and SF in the LAFOV scanner was evaluated by simulating anthropomorphic phantoms with different BMIs and realistic ¹⁸F-FDG distributions, together with uniformly-filled 200cm long cylindrical phantoms with equivalent effective diameters. The optimal offset was found to be either 60mm or 80mm, depending on the chosen optimality metric. We conclude that modifications to NEMA NU-2 are required for accurate SF characterisation in whole-body and LAFOV scanners. Finally, SF in anthropomorphic phantoms with realistic tissue concentrations of ¹⁸F-FDG was found to be strongly correlated with SF in an equivalent-volume cylindrical phantom for the LAFOV PET scanner; BMI was also found to strongly positively correlate with the SF.

Small-angle Compton Scatter Artifact in Tc-99m-IDA Hepatobiliary Scintigraphy Resulting in the Breast Overlying the Liver in Planar Dynamic Imaging

Compton scatter photons are generally considered problematic in nuclear medicine imaging. Therefore, efforts are being made to minimize the involvement of these photons by employing some special strategies in daily practice. Basically, photons scattering at a small angle and traveling in the proper direction stand a chance of getting recorded and thereby participate in the image formation. These photons may create artifactual hot spots in the vicinity of a region with high concentration of radioactivity. The present study focuses on the negative impact of such photons during routine imaging in clinical setting, through an artifact detected in technetium-99m-IDA hepatobiliary scintigraphy, with the purpose of highlighting this issue to the nuclear medicine practitioners.

Whole-body voxel-based internal dosimetry using deep learning

Purpose

In the era of precision medicine, patient-specific dose calculation using Monte Carlo (MC) simulations is deemed the gold standard technique for risk-benefit analysis of radiation hazards and correlation with patient outcome. Hence, we propose a novel method to perform whole-body personalized organ-level dosimetry taking into account the heterogeneity of activity distribution, non-uniformity of surrounding medium, and patient-specific anatomy using deep learning algorithms.

Methods

We extended the voxel-scale MIRD approach from single S-value kernel to specific S-value kernels corresponding to patient-specific anatomy to construct 3D dose maps using hybrid emission/transmission image sets. In this context, we employed a Deep Neural Network (DNN) to predict the distribution of deposited energy, representing specific S-values, from a single source in the center of a 3D kernel composed of human body geometry. The training dataset consists of density maps obtained from CT images and the reference voxelwise S-values generated using Monte Carlo simulations. Accordingly, specific S-value kernels are inferred from the trained model and whole-body dose maps constructed in a manner analogous to the voxel-based MIRD formalism, i.e., convolving specific voxel S-values with the activity map. The dose map predicted using the DNN was compared with the reference generated using MC simulations and two MIRD-based methods, including Single and Multiple S-Values (SSV and MSV) and Olinda/EXM software package.

Results

The predicted specific voxel S-value kernels exhibited good agreement with the MC-based kernels serving as reference with a mean relative absolute error (MRAE) of 4.5 ± 1.8 (%). Bland and Altman analysis showed the lowest dose bias (2.6%) and smallest variance (CI: − 6.6, + 1.3) for DNN. The MRAE of estimated absorbed dose between DNN, MSV, and SSV with respect to the MC simulation reference were 2.6%, 3%, and 49%, respectively. In organ-level dosimetry, the MRAE between the proposed method and MSV, SSV, and Olinda/EXM were 5.1%, 21.8%, and 23.5%, respectively.

Conclusion

The proposed DNN-based WB internal dosimetry exhibited comparable performance to the direct Monte Carlo approach while overcoming the limitations of conventional dosimetry techniques in nuclear medicine.

Validation of a Monte Carlo modelled gamma camera for Lutetium-177 imaging

This study validated a model of the Siemens Symbia T16 dual-head SPECT/CT gamma camera created using the Monte Carlo program SIMIND for ¹⁷⁷Lu. The validation was done by comparing experimental and simulated gamma camera performance criteria tests for the ¹⁷⁷Lu 208 keV photopeak with a medium-energy collimator. Results showed good agreement between the experimental and simulated values. These results illustrated that SIMIND could emulate the Symbia T16 successfully and therefore, can be used with confidence to model ¹⁷⁷Lu images.

Preclinical Voxel-Based Dosimetry in Theranostics: a Review

Due to the increasing use of preclinical targeted radionuclide therapy (TRT) studies for the development of novel theranostic agents, several studies have been performed to accurately estimate absorbed doses to mice at the voxel level using reference mouse phantoms and Monte Carlo (MC) simulations. Accurate dosimetry is important in preclinical theranostics to interpret radiobiological dose-response relationships and to translate results for clinical use. Direct MC (DMC) simulation is believed to produce more realistic voxel-level dose distribution with high precision because tissue heterogeneities and nonuniform source distributions in patients or animals are considered. Although MC simulation is considered to be an accurate method for voxel-based absorbed dose calculations, it is time-consuming, computationally demanding, and often impractical in daily practice. In this review, we focus on the current status of voxel-based dosimetry methods applied in preclinical theranostics and discuss the need for accurate and fast voxel-based dosimetry methods for pretherapy absorbed dose calculations to optimize the dose computation time in preclinical TRT.

Deep-dose: a voxel dose estimation method using deep convolutional neural network for personalized internal dosimetry

Personalized dosimetry with high accuracy is crucial owing to the growing interests in personalized medicine. The direct Monte Carlo simulation is considered as a state-of-art voxel-based dosimetry technique; however, it incurs an excessive computational cost and time. To overcome the limitations of the direct Monte Carlo approach, we propose using a deep convolutional neural network (CNN) for the voxel dose prediction. PET and CT image patches were used as inputs for the CNN with the given ground truth from direct Monte Carlo. The predicted voxel dose rate maps from the CNN were compared with the ground truth and dose rate maps generated voxel S-value (VSV) kernel convolution method, which is one of the common voxel-based dosimetry techniques. The CNN-based dose rate map agreed well with the ground truth with voxel dose rate errors of 2.54% ± 2.09%. The VSV kernel approach showed a voxel error of 9.97% ± 1.79%. In the whole-body dosimetry study, the average organ absorbed dose errors were 1.07%, 9.43%, and 34.22% for the CNN, VSV, and OLINDA/EXM dosimetry software, respectively. The proposed CNN-based dosimetry method showed improvements compared to the conventional dosimetry approaches and showed results comparable with that of the direct Monte Carlo simulation with significantly lower calculation time.

Proposition of a practical protocol for obtaining a valid radiology image using radiography tally of MCNPX Monte Carlo Code

BACKGROUND AND OBJECTIVE

Over the past years, Monte Carlo codes have widespread use in the radiation research field. Radiography tally of MCNPX Monte Carlo code can be a popular and applicable tool for simulation of radiography images. However, validation is the most important prerequisite before using its results.

METHODS

Herein, validation of MCNPX radiography tally with experimental results based on the output image parameters has been investigated. Three cubic phantoms with different thicknesses and aluminum, water, and acrylic inserts were studied. The effects of uniformity correction, the detector efficiency of X-ray in different energies, as well as noise caused by a high statistical error in the simulation were also evaluated.

RESULTS

Based on the proposed protocol to correct the error and uniformity of simulated images versus experimental ones, the maximum difference of less than 5% was achieved.

CONCLUSIONS

Consequently, using the presented method with fewer steps than previous similar works, the MCNPX radiography tally of Monte Carlo code is a useful and validated tool for medical investigation of radiology images.

Innovations in Computer Technologies Have Impacted Radiation Dosimetry Through Anatomically Realistic Phantoms and Fast Monte Carlo Simulations

Radiological physics principles have not changed in the past 60 y when computer technologies advanced exponentially. The research field of anatomical modeling for the purpose of radiation dose calculations has experienced an explosion in activity in the past two decades. Such an exciting advancement is due to the feasibility of creating three-dimensional geometric details of the human anatomy from tomographic imaging and of performing Monte Carlo radiation transport simulations on increasingly fast and cheap personal computers. The advent of a new type of high-performance computing hardware in recent years-graphics processing units-has made it feasible to carry out time-consuming Monte Carlo calculations at near real-time speeds. This paper introduces the history of three generations of computational human phantoms (the stylized medical internal radiation dosimetry-type phantoms, the voxelized tomographic phantoms, and the boundary representation deformable phantoms) and new development of the graphics processing unit-based Monte Carlo radiation dose calculations. Examples are given for research projects performed by my students in applying computational phantoms and a new Monte Carlo code, ARCHER, to problems in radiation protection, imaging, and radiotherapy. Finally, the paper discusses challenges and future opportunities for research.

Benchmarking of Siemens Linac in Electron Modes: 8-14 MeV Electron Beams

BACKGROUND

Radiation therapy using electron beams is a promising method due to its physical dose distribution. Monte Carlo (MC) code is the best and most accurate technique for forespeaking the distribution of dose in radiation treatment of patients.

MATERIAL AND METHODS

We report an MC simulation of a linac head and depth dose on central axis, along with profile calculations. The purpose of the present research is to carefully analyze the application of MC methods for the calculation of dosimetric parameters for electron beams with energies of 8-14 MeV at a Siemens Primus linac. The principal components of the linac head were simulated using MCNPX code for different applicators.

RESULTS

The consequences of measurements and simulations revealed a good agreement. Gamma index values were below 1 for most points, for all energy values and all applicators in percent depth dose and dose profile computations. A number of states exhibited rather large gamma indices; these points were located at the tail of the percent depth dose graph; these points were less used in in radiotherapy. In the dose profile graph, gamma indices of most parts were below 1. The discrepancies between the simulation results and measurements in terms of Z_max, R₉₀, R₈₀ and R₅₀ were insignificant. The results of Monte Carlo simulations showed a good agreement with the measurements.

CONCLUSION

The software can be used for simulating electron modes of a Siemens Primus linac when direct experimental measurements are not feasible.

Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies.

Effects of body habitus on internal radiation dose calculations using the 5-year-old anthropomorphic male models

Computational phantoms are commonly used in internal radiation dosimetry to assess the amount and distribution pattern of energy deposited in various parts of the human body from different internal radiation sources. Radiation dose assessments are commonly performed on predetermined reference computational phantoms while the argument for individualized patient-specific radiation dosimetry exists. This study aims to evaluate the influence of body habitus on internal dosimetry and to quantify the uncertainties in dose estimation correlated with the use of fixed reference models. The 5-year-old IT'IS male phantom was modified to match target anthropometric parameters, including body weight, body height and sitting height/stature ratio (SSR), determined from reference databases, thus enabling the creation of 125 5-year-old habitus-dependent male phantoms with 10th, 25th, 50th, 75th and 90th percentile body morphometries. We evaluated the absorbed fractions and the mean absorbed dose to the target region per unit cumulative activity in the source region (S-values) of F-18 in 46 source regions for the generated 125 anthropomorphic 5-year-old hybrid male phantoms using the Monte Carlo N-Particle eXtended general purpose Monte Carlo transport code and calculated the absorbed dose and effective dose of five ¹⁸F-labelled radiotracers for children of various habitus. For most organs, the S-value of F-18 presents stronger statistical correlations with body weight, standing height and sitting height than BMI and SSR. The self-absorbed fraction and self-absorbed S-values of F-18 and the absorbed dose and effective dose of ¹⁸F-labelled radiotracers present with the strongest statistical correlations with body weight. For ¹⁸F-Amino acids, ¹⁸F-Brain receptor substances, ¹⁸F-FDG, ¹⁸F-L-DOPA and ¹⁸F-FBPA, the mean absolute effective dose differences between phantoms of different habitus and fixed reference models are 11.4%, 11.3%, 10.8%, 13.3% and 11.4%, respectively. Total body weight, standing height and sitting height have considerable effects on human internal dosimetry. Radiation dose calculations for individual subjects using the most closely matched habitus-dependent computational phantom should be considered as an alternative to improve the accuracy of the estimates.

Electromagnetic computation and modeling in MRI

Electromagnetic (EM) computational modeling is used extensively during the development of a Magnetic Resonance Imaging (MRI) scanner, its installation, and use. MRI, which relies on interactions between nuclear magnetic moments and the applied magnetic fields, uses a range of EM tools to optimize all of the magnetic fields required to produce the image. The main field magnet is designed to exacting specifications but challenges in manufacturing, installation, and use require additional tools to maintain target operational performance. The gradient magnetic fields, which provide the primary signal localization mechanism, are designed under another set of complex design trade-offs which include conflicting imaging performance specifications and patient physiology. Gradients are largely impervious to external influences, but are also used to enhance main field operational performance. The radiofrequency (RF) magnetic fields, which are used to elicit the signals fundamental to the MR image, are a challenge to optimize for a host of reasons that include patient safety, image quality, cost optimization, and secondary signal localization capabilities. This review outlines these issues and the EM modeling used to optimize MRI system performance.

Flexible radioluminescence imaging for FDG-guided surgery

PURPOSE

Flexible radioluminescence imaging (Flex-RLI) is an optical method for imaging ¹⁸F-fluorodeoxyglucose (FDG)-avid tumors. The authors hypothesize that a gadolinium oxysulfide: terbium (GOS:Tb) flexible scintillator, which loosely conforms to the body contour, can enhance tumor signal-to-background ratio (SBR) compared with RLI, which utilizes a flat scintillator. The purpose of this paper is to characterize flex-RLI with respect to alternative modalities including RLI, beta-RLI (RLI with gamma rejection), and Cerenkov luminescence imaging (CLI).

METHODS

The photon sensitivity, spatial resolution, and signal linearity of flex-RLI were characterized with in vitro phantoms. In vivo experiments utilizing 13 nude mice inoculated with the head and neck (UMSCC1-Luc) cell line were then conducted in accordance with the institutional Administrative Panel on Laboratory Animal Care. After intravenous injection of ¹⁸F-FDG, the tumor SBR values for flex-RLI were compared to those for RLI, beta-RLI, and CLI using the Wilcoxon signed rank test.

RESULTS

With respect to photon sensitivity, RLI, beta-RLI, and flex-RLI produced 1216.2, 407.0, and 98.6 times more radiance per second than CLI. Respective full-width half maximum values across a 0.5 mm capillary tube were 6.9, 6.4, 2.2, and 1.5 mm, respectively. Flex-RLI demonstrated a near perfect correlation with ¹⁸F activity (r = 0.99). Signal uniformity for flex-RLI improved after more aggressive homogenization of the GOS powder with the silicone elastomer during formulation. In vivo, the SBR value for flex-RLI (median 1.29; interquartile range 1.18-1.36) was statistically greater than that for RLI (1.08; 1.02-1.14; p < 0.01) by 26%. However, there was no statistically significant difference in SBR values between flex-RLI and beta-RLI (p = 0.92). Furthermore, there was no statistically significant difference in SBR values between flex-RLI and CLI (p = 0.11) in a more limited dataset.

CONCLUSIONS

Flex-RLI provides high quality images with SBRs comparable to those from CLI and beta-RLI in a single 10 s acquisition.

A Monte Carlo study on (223)Ra imaging for unsealed radionuclide therapy

PURPOSE

Radium-223 ((223)Ra), an α-emitting radionuclide, is used in unsealed radionuclide therapy for metastatic bone tumors. The demand for qualitative (223)Ra imaging is growing to optimize dosimetry. The authors simulated (223)Ra imaging using an in-house Monte Carlo simulation code and investigated the feasibility and utility of (223)Ra imaging.

METHODS

The Monte Carlo code comprises two modules, hexagon and nai. The hexagon code simulates the photon and electron interactions in the tissues and collimator, and the nai code simulates the response of the NaI detector system. A 3D numeric phantom created using computed tomography images of a chest phantom was installed in the hexagon code. (223)Ra accumulated in a part of the spine, and three x-rays and 19 γ rays between 80 and 450 keV were selected as the emitted photons. To evaluate the quality of the (223)Ra imaging, the authors also simulated technetium-99m ((99m)Tc) imaging under the same conditions and compared the results.

RESULTS

The sensitivities of the three photopeaks were 147 counts per unit of source activity (cps MBq(-1); photopeak: 84 keV, full width of energy window: 20%), 166 cps MBq(-1) (154 keV, 15%), and 158 cps MBq(-1) (270 keV, 10%) for a low-energy general-purpose (LEGP) collimator, and those for the medium-energy general-purpose (MEGP) collimator were 33, 13, and 8.0 cps MBq(-1), respectively. In the case of (99m)Tc, the sensitivity was 55 cps MBq(-1) (141 keV, 20%) for LEGP and 52 cps MBq(-1) for MEGP. The fractions of unscattered photons of the total photons reflecting the image quality were 0.09 (84 keV), 0.03 (154 keV), and 0.02 (270 keV) for the LEGP collimator and 0.41, 0.25, and 0.50 for the MEGP collimator, respectively. Conversely, this fraction was approximately 0.65 for the simulated (99m)Tc imaging. The sensitivity with the LEGP collimator appeared very high. However, almost all of the counts were because of photons that penetrated or were scattered in the collimator; therefore, the proportions of unscattered photons were small.

CONCLUSIONS

Their simulation study revealed that the most promising scheme for (223)Ra imaging is an 84-keV window using an MEGP collimator. The sensitivity of the photopeaks above 100 keV is too low for (223)Ra imaging. A comparison of the fractions of unscattered photons reveals that the sensitivity and image quality are approximately two-thirds of those for (99m)Tc imaging.

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

Effective dose reduction in spine radiographic imaging by choosing the less radiation-sensitive side of the body

BACKGROUND CONTEXT

X-ray absorption is highest in the organs and tissues located closest to the radiation source. The photon flux that crosses the body decreases from the entry surface toward the image receptor. The internal organs absorb x-rays and shield each other during irradiation. Therefore, changing the x-ray projection angle relative to the patient for specific spine procedures changes the radiation dose that each organ receives. Every organ has different radiation sensitivity, so irradiation from different sides of the body changes the biological influence and radiation risk potential on the total body, that is the effective dose (ED).

PURPOSE

The study aimed to determine the less radiation-sensitive sides of the body during lateral and anterior-posterior (AP) or posterior anterior (PA) directions.

STUDY DESIGN

The study used exposure of patient phantoms and Monte Carlo simulation of the effective doses.

PATIENT SAMPLE

Calculations for adults and 10-year-old children were included because the pediatric population has a greater lifetime radiation risk than adults.

OUTCOME MEASURES

Pediatric and adult tissue and organ doses and ED from cervical, thoracic, and lumbar x-ray spine examinations were performed from different projections.

METHODS

Standard mathematical phantoms for adults and 10-year-old children, using PCXMC 2.0 software based on Monte Carlo simulations, were used to calculate pediatric and adult tissue and organ doses and ED. The study was not funded. The authors have no conflicts of interest to declare.

RESULTS

Spine x-ray exposure from various right (RT) LAT projection angles was associated with lower ED compared with the same left (LT) LAT projections (up to 28% and 27% less for children aged 10 and adults, respectively). The PA spine projections showed up to 64% lower ED for children aged 10 and 65% for adults than AP projections. The AP projection at the thoracic spine causes an excess breast dose of 543.3% and 597.0% for children aged 10 and adults, respectively.

CONCLUSIONS

Radiation ED in spine procedures can be significantly reduced by performing x-ray exposures through the less radiation-sensitive sides of the body, which are PA in the frontal position and right lateral in the lateral position.

Monte Carlo simulation of PET and SPECT imaging of 90Y

PURPOSE

Yittrium-90 ((90)Y) is traditionally thought of as a pure beta emitter, and is used in targeted radionuclide therapy, with imaging performed using bremsstrahlung single-photon emission computed tomography (SPECT). However, because (90)Y also emits positrons through internal pair production with a very small branching ratio, positron emission tomography (PET) imaging is also available. Because of the insufficient image quality of (90)Y bremsstrahlung SPECT, PET imaging has been suggested as an alternative. In this paper, the authors present the Monte Carlo-based simulation-reconstruction framework for (90)Y to comprehensively analyze the PET and SPECT imaging techniques and to quantitatively consider the disadvantages associated with them.

METHODS

Our PET and SPECT simulation modules were developed using Monte Carlo simulation of Electrons and Photons (MCEP), developed by Dr. S. Uehara. PET code (MCEP-PET) generates a sinogram, and reconstructs the tomography image using a time-of-flight ordered subset expectation maximization (TOF-OSEM) algorithm with attenuation compensation. To evaluate MCEP-PET, simulated results of (18)F PET imaging were compared with the experimental results. The results confirmed that MCEP-PET can simulate the experimental results very well. The SPECT code (MCEP-SPECT) models the collimator and NaI detector system, and generates the projection images and projection data. To save the computational time, the authors adopt the prerecorded (90)Y bremsstrahlung photon data calculated by MCEP. The projection data are also reconstructed using the OSEM algorithm. The authors simulated PET and SPECT images of a water phantom containing six hot spheres filled with different concentrations of (90)Y without background activity. The amount of activity was 163 MBq, with an acquisition time of 40 min.

RESULTS

The simulated (90)Y-PET image accurately simulated the experimental results. PET image is visually superior to SPECT image because of the low background noise. The simulation reveals that the detected photon number in SPECT is comparable to that of PET, but the large fraction (approximately 75%) of scattered and penetration photons contaminates SPECT image. The lower limit of (90)Y detection in SPECT image was approximately 200 kBq/ml, while that in PET image was approximately 100 kBq/ml.

CONCLUSIONS

By comparing the background noise level and the image concentration profile of both the techniques, PET image quality was determined to be superior to that of bremsstrahlung SPECT. The developed simulation codes will be very useful in the future investigations of PET and bremsstrahlung SPECT imaging of (90)Y.

Evaluation of various energy windows at different radionuclides for scatter and attenuation correction in nuclear medicine

OBJECTIVE

Improving signal to noise ratio (SNR) and qualified images by the various methods is very important for detecting the abnormalities at the body organs. Scatter and attenuation of photons by the organs lead to errors in radiopharmaceutical estimation as well as degradation of images. The choice of suitable energy window and the radionuclide have a key role in nuclear medicine which appearing the lowest scatter fraction as well as having a nearly constant linear attenuation coefficient as a function of phantom thickness.

METHODS

The energy windows of symmetrical window (SW), asymmetric window (ASW), high window (WH) and low window (WL) using Tc-99m and Sm-153 radionuclide with solid water slab phantom (RW3) and Teflon bone phantoms have been compared, and Matlab software and Monte Carlo N-Particle (MCNP4C) code were modified to simulate these methods and obtaining the amounts of FWHM and full width at tenth maximum (FWTM) using line spread functions (LSFs). The experimental data were obtained from the Orbiter Scintron gamma camera.

RESULTS

Based on the results of the simulation as well as experimental work, the performance of WH and ASW display of the results, lowest scatter fraction as well as constant linear attenuation coefficient as a function of phantom thickness. WH and ASW were optimal windows in nuclear medicine imaging for Tc-99m in RW3 phantom and Sm-153 in Teflon bone phantom. Attenuation correction was done for WH and ASW optimal windows and for these radionuclides using filtered back projection algorithm. Results of simulation and experimental show that very good agreement between the set of experimental with simulation as well as theoretical values with simulation data were obtained which was nominally less than 7.07 % for Tc-99m and less than 8.00 % for Sm-153. Corrected counts were not affected by the thickness of scattering material. The Simulated results of Line Spread Function (LSF) for Sm-153 and Tc-99m in phantom based on four windows and TEW method were indicated that the FWHM and FWTM values were approximately the same in TEW method and WH and ASW, but the sensitivity at the optimal window was more than that of the other one.

CONCLUSIONS

The suitable determination of energy window width on the energy spectra can be useful in optimal design to improve efficiency and contrast. It is found that the WH is preferred to the ASW and the ASW is preferred to the SW.

Scatter characterization and correction for simultaneous multiple small-animal PET imaging

PURPOSE

The rapid growth and usage of small-animal positron emission tomography (PET) in molecular imaging research has led to increased demand on PET scanner's time. One potential solution to increase throughput is to scan multiple rodents simultaneously. However, this is achieved at the expense of deterioration of image quality and loss of quantitative accuracy owing to enhanced effects of photon attenuation and Compton scattering. The purpose of this work is, first, to characterize the magnitude and spatial distribution of the scatter component in small-animal PET imaging when scanning single and multiple rodents simultaneously and, second, to assess the relevance and evaluate the performance of scatter correction under similar conditions.

METHODS

The LabPET™-8 scanner was modelled as realistically as possible using Geant4 Application for Tomographic Emission Monte Carlo simulation platform. Monte Carlo simulations allow the separation of unscattered and scattered coincidences and as such enable detailed assessment of the scatter component and its origin. Simple shape-based and more realistic voxel-based phantoms were used to simulate single and multiple PET imaging studies. The modelled scatter component using the single-scatter simulation technique was compared to Monte Carlo simulation results. PET images were also corrected for attenuation and the combined effect of attenuation and scatter on single and multiple small-animal PET imaging evaluated in terms of image quality and quantitative accuracy.

RESULTS

A good agreement was observed between calculated and Monte Carlo simulated scatter profiles for single- and multiple-subject imaging. In the LabPET™-8 scanner, the detector covering material (kovar) contributed the maximum amount of scatter events while the scatter contribution due to lead shielding is negligible. The out-of field-of-view (FOV) scatter fraction (SF) is 1.70, 0.76, and 0.11% for lower energy thresholds of 250, 350, and 400 keV, respectively. The increase in SF ranged between 25 and 64% when imaging multiple subjects (three to five) of different size simultaneously in comparison to imaging a single subject. The spill-over ratio (SOR) increases with increasing the number of subjects in the FOV. Scatter correction improved the SOR for both water and air cold compartments of single and multiple imaging studies. The recovery coefficients for different body parts of the mouse whole-body and rat whole-body anatomical models were improved for multiple imaging studies following scatter correction.

CONCLUSIONS

The magnitude and spatial distribution of the scatter component in small-animal PET imaging of single and multiple subjects simultaneously were characterized, and its impact was evaluated in different situations. Scatter correction improves PET image quality and quantitative accuracy for single rat and simultaneous multiple mice and rat imaging studies, whereas its impact is insignificant in single mouse imaging.