Ordered Subset Expectation Maximization Research Articles

Comparison of quantitative whole body PET parameters on [68Ga]Ga-PSMA-11 PET/CT using ordered Subset Expectation Maximization (OSEM) vs. bayesian penalized likelihood (BPL) reconstruction algorithms in men with metastatic castration-resistant prostate cancer

BackgroundPSMA PET/CT is a predictive and prognostic biomarker for determining response to [177Lu]Lu-PSMA-617 in patients with metastatic castration resistant prostate cancer (mCRPC). Thresholds defined to date may not be generalizable to newer image reconstruction algorithms. Bayesian penalized likelihood (BPL) reconstruction algorithm is a novel reconstruction algorithm that may improve contrast whilst preventing introduction of image noise. The aim of this study is to compare the quantitative parameters obtained using BPL and the Ordered Subset Expectation Maximization (OSEM) reconstruction algorithms.MethodsFifty consecutive patients with mCRPC who underwent [68Ga]Ga-PSMA-11 PET/CT using OSEM reconstruction to assess suitability for [177Lu]Lu-PSMA-617 therapy were selected. BPL algorithm was then used retrospectively to reconstruct the same PET raw data. Quantitative and volumetric measurements such as tumour standardised uptake value (SUV)max, SUVmean and Molecular Tumour Volume (MTV-PSMA) were calculated on both reconstruction methods. Results were compared (Bland-Altman, Pearson correlation coefficient) including subgroups with low and high-volume disease burdens (MTV-PSMA cut-off 40 mL).ResultsThe SUVmax and SUVmean were higher, and MTV-PSMA was lower in the BPL reconstructed images compared to the OSEM group, with a mean difference of 8.4 (17.5%), 0.7 (8.2%) and − 21.5 mL (-3.4%), respectively. There was a strong correlation between the calculated SUVmax, SUVmean, and MTV-PSMA values in the OSEM and BPL reconstructed images (Pearson r values of 0.98, 0.99, and 1.0, respectively). No patients were reclassified from low to high volume disease or vice versa when switching from OSEM to BPL reconstruction.Conclusions[68Ga]Ga-PSMA-11 PET/CT quantitative and volumetric parameters produced by BPL and OSEM reconstruction methods are strongly correlated. Differences are proportional and small for SUVmean, which is used as a predictive biomarker. Our study suggests that both reconstruction methods are acceptable without clinical impact on quantitative or volumetric findings. For longitudinal comparison, committing to the same reconstruction method would be preferred to ensure consistency.

Novel Detector Configurations in Cone-Beam CT Systems: A Simulation Study

Cone-beam computed tomography (CBCT) has emerged in recent years as an adequate alternative to mammography and tomosynthesis due to the several advantages over traditional mammography, including its ability to provide 3D images, its reduced radiation dose, and its ability to image dense breasts more effectively and conduct more effective breast compressions, etc. Furthermore, CBCT is capable of providing images with high sensitivity and specificity, allowing a more accurate evaluation, even of dense breasts, where mammography and tomosynthesis may lead to a false diagnosis. Clinical and experimental CBCT systems rely on cesium iodine (CsI:Tl) scintillators for X-ray energy conversion. This study comprises an investigation among different novel CBCT detector technologies, consisting either of scintillators (BGO, LSO:Ce, LYSO:Ce, LuAG:Ce, CaF2:Eu, LaBr3:Ce) or semiconductors (Silicon, CZT) in order to define the optimum detector design for a future experimental setup, dedicated to breast imaging. For this purpose, a micro-CBCT system was adapted, using GATE v9.2.1, consisting of the aforementioned various detection schemes. Two phantom configurations were selected: (a) an aluminum capillary positioned at the center of the field of view in order to calculate the system’s spatial resolution and (b) a breast phantom consisting of spheres of different materials, such that their characteristics are close to the breast composition. Breast phantom contrast-to-noise ratios (CNRs) were extracted from the phantom’s tomographic images. The images were reconstructed with filtered back projection (FBP) and ordered subsets expectation-maximization (OSEM) algorithms. The semiconductors acted satisfactorily in low-density matter, while LYSO:Ce, LaBr3:Ce, and LuAG:Ce presented adequate CNRs for all the different spheres’ densities. The energy converters that are presented in this study were evaluated for their performance against the standard CsI:Tl crystal.

Development of Solutions Based on Computer Simulation for Quantitative SPECT/CT

Purpose: In modern nuclear medicine, an ordered subset expectation maximization (OSEM) iterative algorithm is used to obtain images by single photon emission computed tomography (SPECT) method. At the same time, the problem of choosing the stopping iteration number at which the solution will be as close as possible to the exact value has not been solved. The purpose of this work is to study the problem of stopping the OSEM algorithm. Material and methods: The studies were carried out using the method of mathematical modeling based on the software package “Virtual Platform for Simulation Testing of the SPECT/CT Method”. Computer experiments simulated SPECT/CT with 99mTc phosphotech of a patient with metastatic lesion of the posterior segment of the third rib. The stopping criterion of the iterative OSEM algorithm was studied to obtain a solution that is quantitatively closest to the exact value of the accumulated activity at the tumor. Results: In computer modeling experiments, the tumor dependent Pearson chi-square test was shown to provide a solution that should give correct values for the SUVmean score. However, further research is needed on this important problem to determine how strongly the number of iterations depends on the size of the tumor and the amount of activity accumulated in it. Conclusion: Based on the results obtained, we can conclude that in the SPECT method, in order to move to accurate quantitative estimates of the accumulated activity in the tumor, it is necessary to develop a tumor-oriented stopping criterion for iterative algorithm. If there are several tumors, the stopping iteration numbers for them may differ. Further research on this important issue is planned.

Phantom and clinical evaluation of the Bayesian penalised likelihood reconstruction algorithm Q.Clear without PSF correction in amyloid PET images

PurposeBayesian penalised likelihood (BPL) reconstruction, which incorporates point-spread-function (PSF) correction, provides higher signal-to-noise ratios and more accurate quantitation than conventional ordered subset expectation maximization (OSEM) reconstruction. However, applying PSF correction to brain PET imaging is controversial due to Gibbs artefacts that manifest as unpredicted cortical uptake enhancement. The present study aimed to validate whether BPL without PSF would be useful for amyloid PET imaging.MethodsImages were acquired from Hoffman 3D brain and cylindrical phantoms for phantom study and 71 patients administered with [18F]flutemetamol in clinical study using a Discovery MI. All images were reconstructed using OSEM, BPL with PSF correction, and BPL without PSF correction. Count profile, %contrast, recovery coefficients (RCs), and image noise were calculated from the images acquired from the phantoms. Amyloid β deposition in patients was visually assessed by two physicians and quantified based on the standardised uptake value ratio (SUVR).ResultsThe overestimated radioactivity in profile curves was eliminated using BPL without PSF correction. The %contrast and image noise decreased with increasing β values in phantom images. Image quality and RCs were better using BPL with, than without PSF correction or OSEM. An optimal β value of 600 was determined for BPL without PSF correction. Visual evaluation almost agreed perfectly (κ = 0.91–0.97), without depending on reconstruction methods. Composite SUVRs did not significantly differ between reconstruction methods.ConclusionGibbs artefacts disappeared from phantom images using the BPL without PSF correction. Visual and quantitative evaluation of [18F]flutemetamol imaging was independent of the reconstruction method. The BPL without PSF correction could be the standard reconstruction method for amyloid PET imaging, despite being qualitatively inferior to BPL with PSF correction for [18F]flutemetamol amyloid PET imaging.

Stability of radiomic features from positron emission tomography images: a phantom study comparing advanced reconstruction algorithms and ordered subset expectation maximization.

In this study, we compared the repeatability and reproducibility of radiomic features obtained from positron emission tomography (PET) images according to the reconstruction algorithm used-advanced reconstruction algorithms, such as HYPER iterative (IT), HYPER deep learning reconstruction (DLR), and HYPER deep progressive reconstruction (DPR), or traditional Ordered Subset Expectation Maximization (OSEM)-to understand the potential variations and implications of using advanced reconstruction techniques in PET-based radiomics. We used a heterogeneous phantom with acrylic spherical beads (4- or 8-mm diameter) filled with 18F. PET images were acquired and reconstructed using OSEM, IT, DLR, and DPR. Original and wavelet radiomic features were calculated using SlicerRadiomics. Radiomic feature repeatability was assessed using the Coefficient of Variance (COV) and intraclass correlation coefficient (ICC), and inter-acquisition time reproducibility was assessed using the concordance correlation coefficient (CCC). For the 4- and 8-mm diameter beads phantom, the proportion of radiomic features with a COV < 10% was equivocal or higher for the advanced reconstruction algorithm than for OSEM. ICC indicated that advanced methods generally outperformed OSEM in repeatability, except for the original features of the 8-mm beads phantom. In the inter-acquisition time reproducibility analysis, the combinations of 3 and 5min exhibited the highest reproducibility in both phantoms, with IT and DPR showing the highest proportion of radiomic features with CCC > 0.8. Advanced reconstruction methods provided enhanced stability of radiomic features compared with OSEM, suggesting their potential for optimal image reconstruction in PET-based radiomics, offering potential benefits in clinical diagnostics and prognostics.

Optimizing scan time and bayesian penalized likelihood reconstruction algorithm in copper-64 PET/CT imaging: a phantom study.

Objectives: The aim of this study was to evaluate Cu-64 PET phantom image quality using Bayesian Penalized Likelihood (BPL) and Ordered Subset Expectation Maximum with point-spread function modeling (OSEM-PSF) reconstruction algorithms. In the BPL, the regularization parameterβwas varied to identify the optimum value for image quality. In the OSEM-PSF, the effect of acquisition time was evaluated to assess the feasibility of shortened scan duration.Methods: A NEMA IEC PET body phantom was filled with known activities of water soluble Cu-64. The phantom was imaged on a PET/CT scanner and was reconstructed using BPL and OSEM-PSF algorithms. For the BPL reconstruction, variousβvalues (150, 250, 350, 450, and 550) were evaluated. For the OSEM-PSF algorithm, reconstructions were performed using list-mode data intervals ranging from 7.5 to 240 s. Image quality was assessed by evaluating the signal to noise ratio (SNR), contrast to noise ratio (CNR), and background variability (BV).Results: The SNR and CNR were higher in images reconstructed with BPL compared to OSEM-PSF. Both the SNR and CNR increased with increasingβ, peaking atβ= 550. The CNR for allβ, sphere sizes and tumor-to-background ratios (TBRs) satisfied the Rose criterion for image detectability (CNR > 5). BPL reconstructed images withβ= 550 demonstrated the highest improvement in image quality. For OSEM-PSF reconstructed images with list-mode data duration ≥ 120 s, the noise level and CNR were not significantly different from the baseline 240 s list-mode data duration.Conclusions: BPL reconstruction improved Cu-64 PET phantom image quality by increasing SNR and CNR relative to OSEM-PSF reconstruction. Additionally, this study demonstrated scan time can be reduced from 240 to 120 s when using OSEM-PSF reconstruction while maintaining similar image quality. This study provides baseline data that may guide future studies aimed to improve clinical Cu-64 imaging.

Iterative Reconstruction of Micro Computed Tomography Scans Using Multiple Heterogeneous GPUs.

Graphics processing units (GPUs) facilitate massive parallelism and high-capacity storage, and thus are suitable for the iterative reconstruction of ultrahigh-resolution micro computed tomography (CT) scans by on-the-fly system matrix (OTFSM) calculation using ordered subsets expectation maximization (OSEM). We propose a finite state automaton (FSA) method that facilitates iterative reconstruction using a heterogeneous multi-GPU platform through parallelizing the matrix calculations derived from a ray tracing system of ordered subsets. The FSAs perform flow control for parallel threading of the heterogeneous GPUs, which minimizes the latency of launching ordered-subsets tasks, reduces the data transfer between the main system memory and local GPU memory, and solves the memory-bound of a single GPU. In the experiments, we compared the operation efficiency of OS-MLTR for three reconstruction environments. The heterogeneous multiple GPUs with job queues for high throughput calculation speed is up to five times faster than the single GPU environment, and that speed up is nine times faster than the heterogeneous multiple GPUs with the FIFO queues of the device scheduling control. Eventually, we proposed an event-triggered FSA method for iterative reconstruction using multiple heterogeneous GPUs that solves the memory-bound issue of a single GPU at ultrahigh resolutions, and the routines of the proposed method were successfully executed on each GPU simultaneously.

Impact of [11C]methionine PET with Bayesian penalized likelihood reconstruction on glioma grades based on new WHO 2021 classification.

The uptake of [11C]methionine in positron emission tomography (PET) imaging overlapped in earlier images of tumors. Bayesian penalized likelihood (BPL) reconstruction increases the quantitative values of tumors compared with conventional ordered subset-expectation maximization (OSEM). The present study aimed to grade glioma malignancy based on the new WHO 2021 classification using [11C]methionine PET images reconstructed using BPL. We categorized 32 gliomas in 28 patients as grades 2/3 (n = 15) and 4 (n = 17) based on the WHO 2021 classification. All [11C]methionine images were reconstructed using OSEM + time-of-flight (TOF) and BPL + TOF (β = 200). Maximum standardized uptake value (SUVmax) and tumor-to-normal tissue ratio (T/Nmax) were measured at each lesion. The mean SUVmax was 4.65 and 4.93 in grade 2/3 and 6.38 and 7.11 in grade 4, and the mean T/Nmax was 7.08 and 7.22 in grade 2/3 and 9.30 and 10.19 in grade 4 for OSEM and BPL, respectively. The BPL significantly increased these values in grade 4 gliomas. The area under the receiver operator characteristic (ROC) curve (AUC) for SUVmax was the highest (0.792) using BPL. The BPL increased mean SUVmax and mean T/Nmax in lesions with higher contrast such as grade 4 glioma. The discrimination power between grades 2/3 and 4 in SUVmax was also increased using [11C]methionine PET images reconstructed with BPL.

Feasibility of noise-reduction reconstruction technology based on non-local-mean principle in SiPM-PET/CT

Quantitative values of positron emission tomography (PET) images using non-local-mean in a silicon photomultiplier (SiPM)-PET/computed tomography (CT) system with phantom and clinical images.The evaluation was conducted on a National Electrical Manufacturers Association body phantom with micro-spheres (4, 5, 6, 8, 10, 13 mm) and clinical images using the SiPM-PET/CT system.The signal-to-background ratio of the phantom was set to 4, and all PET image data was obtained and reconstructed using three-dimensional ordered subset expectation maximization, time-of-flight, point-spread function, and a 4-mm Gaussian filter (GF) and clear adaptive low-noise method (CaLM) in mild, standard, and strong intensities.The evaluation included the standardized uptake value (SUV), percent contrast (QH), coefficient of variation of the background area (CVbackground) clinical imaging for SUV of lung nodules, liver signal-to-noise ratio (SNR), and visual evaluation.SUVmax for 8-mm sphere in phantom images at 2 min for GF and CaLM (mild, standard, strong) were 2.11, 2.32, 2.02, and 1.72; the QH, 8 mm was 27.33 %, 27.47 %, 21.81 %, and 16.09 %; and CVbackground was 12.78, 11.35, 7.86, and 4.71, respectively.CaLM demonstrated higher SUVmax in clinical images than GF for all lung nodule sizes. The average SUVmax for nodules with a diameter of ≤ 1 cm were 5.9 ± 2.4, 9.9 ± 4.9, 9.9 ± 5.0, and 9.9 ± 5.0 for GF and CaLM-mild, standard, and strong intensities, respectively.Liver SNRs were higher for CaLM (mild, standard, strong) compared to GF, with increasing CaLM intensity causing higher liver SNR. CaLM-mild and standard demonstrated suitability for diagnosis in visual evaluation.

Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning

ObjectiveTo improve the PET image quality by a deep progressive learning (DPL) reconstruction algorithm and evaluate the DPL performance in lesion quantification.MethodsWe reconstructed PET images from 48 oncological patients using ordered subset expectation maximization (OSEM) and deep progressive learning (DPL) methods. The patients were enrolled into three overlapped studies: 11 patients for image quality assessment (study 1), 34 patients for sub-centimeter lesion quantification (study 2), and 28 patients for imaging of overweight or obese individuals (study 3). In study 1, we evaluated the image quality visually based on four criteria: overall score, image sharpness, image noise, and diagnostic confidence. We also measured the image quality quantitatively using the signal-to-background ratio (SBR), signal-to-noise ratio (SNR), contrast-to-background ratio (CBR), and contrast-to-noise ratio (CNR). To evaluate the performance of the DPL algorithm in quantifying lesions, we compared the maximum standardized uptake values (SUVmax), SBR, CBR, SNR and CNR of 63 sub-centimeter lesions in study 2 and 44 lesions in study 3.ResultsDPL produced better PET image quality than OSEM did based on the visual evaluation methods when the acquisition time was 0.5, 1.0 and 1.5 min/bed. However, no discernible differences were found between the two methods when the acquisition time was 2.0, 2.5 and 3.0 min/bed. Quantitative results showed that DPL had significantly higher values of SBR, CBR, SNR, and CNR than OSEM did for each acquisition time. For sub-centimeter lesion quantification, the SUVmax, SBR, CBR, SNR, and CNR of DPL were significantly enhanced, compared with OSEM. Similarly, for lesion quantification in overweight and obese patients, DPL significantly increased these parameters compared with OSEM.ConclusionThe DPL algorithm dramatically enhanced the quality of PET images and enabled more accurate quantification of sub-centimeters lesions in patients and lesions in overweight or obese patients. This is particularly beneficial for overweight or obese patients who usually have lower image quality due to the increased attenuation.

The determination of the optimal threshold on measurement of thyroid volume using quantitative SPECT/CT for Graves' hyperthyroidism

PurposeTo investigate the optimal threshold for measuring thyroid volume in patients with Grave's hyperthyroidism (GH) by SPECT/CT.Materials and methodsA 53 mL butterfly-shaped hollow container made of two 45-degree transparent elbows was put into a NEMA IEC phantom tank. The butterfly-shaped container and the tank were then filled with Na99mTcO4 of different radioactive concentrations, respectively, which could simulate thyroid gland with GH by different target-to-background ratios (T/B) (200:1, 600:1, 1000:1). The different T/B of planar imaging and SPECT/CT were acquired by a Discovery NM/CT 670 Pro SPECT/CT. With Thyroid software (Version 4.0) of GE-Xeleris workstation, the region of the thyroid gland in planar imaging was delineated. The thyroid area and average long diameter of both lobes were substituted into the Allen formula to calculate the thyroid volume. The calculation error was compared with the actual volume. Q-Metrix software was used to perform CT-based attenuation correction, scatter correction, resolution recovery. Ordered-subsets expectation maximization was used to reconstruct SPECT data. 20%, 25%, 30%, 40%, 50%, 60% thresholds were selected to automatically delineate the volume of interest and compared with the real volume, which determinated the optimal threshold. We measured the thyroid volume of 40 GH patients using the threshold and compared the volumes obtained by planar imaging and ultrasound three-dimensional. The differences of the volumes with different T/B and thresholds were compared by the ANOVA and least significant difference t test. The volumes delineated by SPECT/CT were evaluated using ANOVA, least significant difference t test, correlation analysis and, linear regression and Bland–Altman concordance test plot. The differences and consistency of thyroid volume were compared among the above three methods.ResultsThere was no significant difference in the results between different T/B models (P > 0.05). The thyroid volume calculated by the planar imaging formula method was higher than the real volume, with an average overestimation of 22.81%. The volumes delineated by SPECT/CT threshold automatically decreased while the threshold increased. There were significant differences between groups with different thresholds (P < 0.001). With an average error of 3.73%, the thyroid volume analyzed by the threshold of 25% was close to the results of ultrasound measurement (P > 0.05). Thyroid volume measured by planar imaging method was significantly higher than ultrasound and SPECT/CT threshold automatic delineation method (P < 0.05). The agreement between the SPECT/CT 25% threshold and ultrasound (r = 0.956, b = 0.961) was better than that between the planar imaging and ultrasound (r = 0.590, b = 0.574). The Bland–Altman plot also showed that the thyroid volume measured by the 25% threshold automatic delineation method was in good agreement with the ultrasound measurement.ConclusionsThe T/B has no effect on the measurement of thyroid volume in GH patients; planar imaging method can significantly overestimate thyroid volume in GH patients, and 25% threshold automatic delineation method can obtain more accurate thyroid volume in GH patients.

Impact of Attenuation Correction, Collimator, and Iterative Reconstruction Protocols on 67Ga SPECT/CT Quantification

Purpose: The main goal of this study was to determine the optimal collimator in the absence of medium energy collimators along with the impact of Attenuation Correction (AC) and different iterative reconstruction protocols on the quantitative evaluation of Gallium-67 (67Ga) SPECT/CT imaging.&#x0D; Materials and Methods: A GE Discovery 670 dual-head SPECT/CT scanner and a NEMA phantom filled with 67Ga solution were used to scan the patients. The projections were acquired with both Low Energy High Resolution (LEHR) and High Energy General Purpose (HEGP) collimators, and CT images were acquired to evaluate the effect of attenuation correction. SPECT data were reconstructed using the ordered subset expectation maximization (OSEM) method with various combinations of iterations and subsets. The performance was quantified, and a clinical study validated the phantom study.&#x0D; Results: Acquired images by the HEGP collimator yielded higher Contrast Recovery (CR) and Contrast to Noise Ratio (CNR) in images with AC than those without non-AC (41.6% and 74.2%, respectively). The CNR in all spheres after AC was increased by 80.4% (82.1%) for the HEGP collimator against the LEHR collimator. Also, an increase in iterations × subsets from 16 to 48 led to the Coefficient of Variation (COV) increasing by 17.2%, 16.67%, 15.50%, 14.4%, 14.2%, and 14.1% for 10 mm to 37 mm sphere diameter, respectively.&#x0D; Conclusion: CT-based AC and HEGP collimators can yield improved 67Ga SPECT quantification compared to Non-AC and LEHR collimators. The choice of the optimal collimator with the reconstruction protocol led to changes in the image quality and quantitative accuracy, emphasizing the need to carefully select the appropriate combination of data acquisition factors.&#x0D;  

РАЗРАБОТКА ПРОГРАММНЫХ СРЕДСТВ МАТЕМАТИЧЕСКОГО ИМИТАЦИОННОГО МОДЕЛИРОВАНИЯ НА ОСНОВЕ КЛИНИЧЕСКИХ ДАННЫХ И ФАНТОМНЫХ ИССЛЕДОВАНИЙ ДЛЯ ОЦЕНКИ ПЕРФУЗИИ ГОЛОВНОГО МОЗГА И ПОВЫШЕНИЯ КАЧЕСТВА ИЗОБРАЖЕНИЙ ПРИ ОФЭКТ/КТ С 99MTC-ГМПАО

Purpose: To develop a software package Virtual examination of brain perfusion by the method of SPECT/CT with 99mTc-HMPAO (Teoxime) and its practical application to study the conditions for achieving the best image quality in clinical studies of patients. Material and methods: The studies were performed using clinical data and the method of computer simulation. Clinical data of single-photon emission computed tomography combined with X-ray computed tomography (SPECT/CT) with 99mTc-hexamethylpropyleneamine oxime (99mTc-Teoxime, produced by DIAMED LLC) of a patient with an ischemic stroke of the right frontal cortex were obtained on a two-detector gamma-camera NM/CT 670 DR GE Discovery (USA) using high-resolution low-energy collimators (LEHR). The measured data were processed using specialized software Q.Brain and Q.Volumetrix MI on a Xeleris 4.0 DR workstation from GE Healthcare (USA) to obtain reconstructed axial tomographic slices. To carry out simulation computer simulation of the procedure of examination of perfusion of GM by the method of SPECT/CT has developed a software package that includes a mathematical Hoffman phantom with the ability to simulate clinical cases of hypoperfusion of different localization and size (Virtual Patient), modeling the collection of “raw” projection data and an image reconstruction program based on the OSEM algorithm (Ordered Subset Expectation Maximization). An important advantage of the mathematical modeling method is the ability to assess the quality of the reconstructed image by calculating the root-mean-square error when compared with a given phantom. In numerical experiments, the dependence of the reconstruction error on the parameters of the OSEM algorithm (on the number of subgroups – subsets, and on the number of iterations) was investigated in order to determine the conditions for achieving the best image quality. A statistical stop criterion was developed and tested. Results: For the first time, a software package was developed and tested that allows us to investigate errors in the reconstruction algorithm, which is a great difficulty when using clinical research methods. A criterion for stopping iterations is proposed when using the OSEM reconstruction algorithm – minimizing the functional deviation of the chi-square function from the target value, while the detector pixels with non-zero values are combined into blocks according to the 2×2 scheme. There is a reliable good correlation between the proposed stop criterion and the minimum of the root-mean-square error of image reconstruction. This makes it possible to introduce this criterion into the clinical practice of using computational tools for reconstructing sections of the SPECT to obtain the best image. The simulation results demonstrated the possibility of reducing the time of data recording, during which the patient must remain motionless, at least twice. Conclusion: The method of computer simulation developed in this work is a practically useful technology that helps optimize the use of SPECT to achieve the best possible results of brain imaging in patients.

PET/CT Reconstruction and Its Impact on [Measures of] Metabolic Tumor Volume

In oncological imaging, the use of metabolic tumor volume (MTV) for further prognostic differentiation and the development of risk adapted strategies appears promising. The aim of this analysis was to evaluate ultra-high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on different methods of MTV measurement. We analyzed positron emission tomography combined with computed tomography (PET/CT) scans of 40 Hodgkin lymphoma patients before first-line treatment who had undergone fluorodeoxyglucose (FDG) PET/CT. The MTVs were determined taking an SUV of 4.0 (MTV4.0) as a fixed threshold or 41% of the single hottest voxel (MTV41%) as an adaptive threshold for automated lymphoma delineation in both UHD and OSEM reconstructions. We then compared the absolute and relative differences between MTV4.0 and MTV41% in UHD and OSEM reconstructions. The relative distribution of MTV4.0 and MTV41% in relation to the reconstruction method applied was recorded and respective differences were tested for statistical significance using the paired sample t-test. A comparison of MTV4.0 and MTV41% showed smaller relative and absolute differences in MTV between different reconstruction settings for the MTV4.0 method. Conversely, the absolute as well as the relative differences between MTVs obtained from different reconstructions settings were significantly greater when the MTV41% method was applied (p<0001). MTV4.0 brings higher robustness between different reconstruction settings, while with MTV41% the deviation between volumes obtained with different reconstruction settings is greater. For clinical routine and for multicenter settings, the MTV4.0 therefore appears most promising.

Study of 68Ga Labelled PET/CT Scan Parameters Optimization

Purpose: Gallium-68 (68Ga) is increasingly used in nuclear medicine imaging for various conditions such as lymphoma and neuroendocrine tumors by labeling tracers like Prostate Specific Membrane Antigen (PSMA) and DOTA-TOC. However, compared to Fluorine-18 (18F) used in conventional nuclear medicine imaging, 68Ga has lower spatial resolution and relatively higher Signal to Background Ratio (SBR). Therefore, this study aimed to investigate the optimized parameters and reconstruction methods for PET/CT imaging using the 68Ga radiotracer through model-based image evaluation. Materials and Methods: Based on clinical images of 68Ga-PSMA PET/CT, a NEMA/IEC 2008 PET phantom model was prepared with a Hot vs Background (H/B) ratio of 10:1. Images were acquired for 9 minutes in list mode using DMIDR (GE, Milwaukee WI, USA). Subsequently, reconstructions were performed for 1 to 8 minutes using OS-EM (Ordered Subset Expectation Maximization) + TOF (Time of Flight) + Sharp IR (VPFX-S), and BSREM (Block Sequential Regularized Expectation Maximization) + TOF + Sharp IR (QCFX-S-400), followed by comparative evaluation. Based on the previous experimental results, images were reconstructed for BSREM + TOF + Sharp IR / 2 minutes (QCFX-S–2min) with varying β-strength values from 100 to 700. The image quality was evaluated using AMIDE (freeware, Ver.1.0.1) and Advanced Workstation (GE, USA). Results: Images reconstructed with QCFX-S-400 showed relatively higher values for SNR (Signal to Noise Ratio), CNR (Contrast to Noise Ratio), count, RC (Recovery Coefficient), and SUV (Standardized Uptake Value) compared to VPFX-S. SNR, CNR, and SUV exhibited the highest values at 2 minutes/bed acquisition time. RC showed the highest values for a 10 mm sphere at 2 minutes/bed acquisition time. For small spheres of 10 mm and 13 mm, an inverse relationship between β-strength increase and count was observed. SNR and CNR peaked at β-strength 400 and then decreased, while SUV and RC exhibited a normal distribution based on sphere size for β-strength values of 400 and above. Conclusion: Based on the experiments, PET/CT imaging using the 68Ga radiotracer yielded the most favorable quantitative and qualitative results with a 2 minutes/bed acquisition time and BSREM reconstruction, particularly when applying β-strength 400. The application of BSREM can enhance accurate quantification and image quality in 68Ga PET/CT imaging, and an optimization process tailored to each institution's imaging objectives appears necessary.

An extended bore length solid-state digital-BGO PET/CT system: design, preliminary experience, and performance characteristics.

A solid-state PET/CT system uses bismuth germanium oxide (BGO) scintillating crystals coupled to silicon photomultipliers over an extended 32 cm axial field-of-view (FOV) to provide high spatial resolution and very high sensitivity. Performance characteristics were determined for this digital-BGO system, including NEMA and EARL standards. Spatial resolution, scatter fraction (SF), noise equivalent count rate (NECR), sensitivity, count rate accuracy, and image quality (IQ) were evaluated for the digital-BGO system as per NEMA NU 2-2018, at 2 sites of first clinical install. System energy resolution was measured. Bayesian penalized-likelihood reconstruction (BPL) was used for IQ. EARL Standards 2 studies were reconstructed by BPL combined with a contrast-enhancing deep learning algorithm. An Esser PET phantom was evaluated. Three patient examples were obtained with low-dose radiotracer activity: 2 MBq/kg of [18F]FDG ([18F]-2-fluoro-2-deoxy-D-glucose), 2.3 MBq/kg [68Ga]Ga-DOTA-TATE ([dodecane tetra-acetic acid,Tyr3]-octreotate), and 14.5 MBq/kg [82Rb]RbCl ([82Rb]-rubidium-chloride). Total scan times were ≤ 8 min. NEMA sensitivity was 47.6 cps/kBq at the axial center. Spatial resolution at 1 cm from the center axis was ≤4.5 mm (filtered back projection) and ≤3.8 mm (ordered subset expectation maximization). SF was 35.6%, count rate accuracy was 2.16%, and peak NECR was 485.2 kcps at 16.9 kBq/mL. Contrast for IQ was 61.1 to 90.7% (smallest to largest sphere) with background variations from 7.6 to 2.1%, and a "lung" error of 4.7%. The average detector energy resolution was 9.67%. Image quality for patient scans was good. EARL Standards 2 criteria were robustly met and Esser phantom features ≥4.8 mm were resolved at 2 min per bed position. A solid-state 32 cm axial FOV digital-BGO PET/CT system provides good spatial and energy resolution, high count rates, and superior NEMA sensitivity in its class, enabling fast clinical acquisitions with low-dose radiotracer activity.

Visualization of small brain nuclei with a high-spatial resolution, clinically available whole-body PET scanner

ObjectiveTo verify the visibility of physiological 18F-fluorodeoxyglucose (18F-FDG) uptake in nuclei in and around the brainstem by a whole-body (WB) silicon photomultiplier positron emission tomography (SiPM-PET) scanner with point-spread function (PSF) reconstruction using various iteration numbers.MethodsTen healthy subjects (5 men, 5 women; mean age, 56.0 ± 5.0 years) who underwent 18F-FDG PET/CT using a WB SiPM-PET scanner and magnetic resonance imaging (MRI) of the brain including a spin-echo three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions fluid-attenuated inversion recovery (3D-FLAIR) and a 3D-T1 magnetization-prepared rapid gradient-echo (T1-MPRAGE) images were enrolled. Each acquired PET image was reconstructed using ordered-subset expectation maximization (OSEM) with iteration numbers of 4, 16, 64, and 256 (subset 5 fixed) + time-of-flight (TOF) + PSF. The reconstructed PET images and 3D-FLAIR images for each subject were registered to individual T1-MPRAGE volumes using normalized mutual information criteria. For each MR-coregistered individual PET image, the pattern of FDG uptake in the inferior olivary nuclei (ION), dentate nuclei (DN), midbrain raphe nuclei (MRN), inferior colliculi (IC), mammillary bodies (MB), red nuclei (RN), subthalamic nuclei (STN), lateral geniculate nuclei (LGN), medial geniculate nuclei (MGN), and superior colliculi (SC) was visually classified into the following three categories: good, clearly distinguishable FDG accumulation; fair, obscure contour of FDG accumulation; poor, FDG accumulation indistinguishable from surrounding uptake.ResultsAmong individual 18F-FDG PET images with OSEM iterations of 4, 16, 64, and 256 + TOF + PSF, the iteration numbers that showed the best visibility in each structure were as follows: ION, MRN, LGN, MGN, and SC, iteration 64; DN, iteration 16; IC, iterations 16, 64, and 256; MB, iterations 64 and 256; and RN and STN, iterations 16 and 64, respectively. Of the four iterations, the 18F-FDG PET image of iteration 64 visualized FDG accumulation in small structures in and around the brainstem most clearly (good, 98 structures; fair, 2 structures).ConclusionsA clinically available WB SiPM-PET scanner is useful for visualizing physiological FDG uptake in small brain nuclei, using a sufficiently high number of iterations for OSEM with TOF and PSF reconstructions.

Reduced count pediatric whole-body 18F-FDG PET imaging reconstruction with a Bayesian penalized likelihood algorithm.

Advanced positron emission tomography (PET) image reconstruction methods promise to allow optimized PET/CT protocols with improved image quality,decreased administered activity and/or acquisition times. To evaluate the impact of reducing counts(simulating reduced acquisition time) in block sequential regularized expectation maximization (BSREM) reconstructed pediatric whole-body 18F-fluorodeoxyglucose (FDG) PET images, and to compare BSERM with ordered-subset expectation maximization (OSEM) reconstructed reduced-count images. Twenty children (16 male) underwent clinical whole-body 18F-FDG PET/CT examinations using a 25-cm axial field-of-view (FOV) digital PET/CT system at 90s per bed (s/bed) with BSREM reconstruction (β=700). Reduced count simulations with varied BSREM β levels were generated from list-mode data: 60s/bed, β=800; 50s/bed, β=900; 40s/bed, β=1000; and 30s/bed, β=1300. In addition, a single OSEM reconstruction was created at 60s/bed based on prior literature. Qualitative (Likert scores) and quantitative (standardized uptake value [SUV]) analyses were performed to evaluate image quality and quantitation across simulated reconstructions. The mean patient age was 9.0 ± 5.5 (SD) years, mean weight was 38.5 ± 24.5kg, and mean administered 18F-FDG activity was 4.5 ± 0.7 (SD) MBq/kg. Between BSREM reconstructions, no qualitative measure showed a significant difference versus the 90s/bed β=700 standard (all P>0.05). SUVmax values for lesions were significantly lower from 90s/bed, β=700 only at a simulated acquisition time of 30s/bed, β=1300 (P=0.001). In a side-by-side comparison of BSREM versus OSEM reconstructions, 40s/bed, β=1000 images were generally preferred over 60s/bed TOF OSEM images. In children who undergo whole-body 18F-FDG PET/CT on a 25-cm FOV digital PET/CT scanner, reductions in acquisition time or, by corollary, administered radiopharmaceutical activity of >50% from a clinical standard of 90s/bed may be possible while maintaining diagnostic quality when a BSREM reconstruction algorithm is used.

Influence of different time framings, reconstruction algorithms and post-processing methods on the quantification of myocardial blood flow from 13 N-NH3 PET images.

The aim was to investigate to what extent the quantification of myocardial blood flow (MBF) from dynamic 13 N-NH3 positron emission tomography(PET) images is affected by time frame schemes, time-of-flight (ToF), reconstruction algorithms, blood pool volume of interest (VOI) locations and compartment models in patients with suspected chronic coronary syndrome. A standard MBF value was determined from 25 patients' rest/stress 13 N-NH3 PET/CT images reconstructed with ordered subset expectation maximization (OSEM), 5 s time frame for the first frames without ToF, subsequently analyzed using a basal VOI and the deGrado compartment model. MBFs calculated using 2or 10 s for the first frames, ToF, block-sequential regularized expectation maximization (BSREM), apical or large VOI, Hutchins or Krivokapich compartment models were compared to MBFstandard in Bland-Altman plots (bias ± SD). Good agreement in global rest/stress MBF (mL/min/g) was found when changing the time frame scheme or reconstruction algorithm (MBFstandard vs. MBF2s : -0.02 ± 0.06; MBF10s : 0.01 ± 0.07; MBFBSREM : 0.01 ± 0.07), while a lower level of agreement was found when altering the other factors (MBFstandard vs.MBFToF : -0.07 ± 0.10; MBFapical VOI : -0.27 ± 0.25; MBFlarge VOI : -0.11 ± 0.10; MBFHutchins : -0.08 ± 0.10; MBFKrivokapich : -0.47 ± 0.50). Quantification of MBF from 13 N-NH3 PET images is more affected by choice of compartment models, ToF and blood pool VOIs than by different time frame schemes and reconstruction algorithms.

Performance Characteristics of a New-Generation Digital Bismuth Germanium Oxide PET/CT System, Omni Legend 32, According to NEMA NU 2-2018 Standards.

The Omni Legend 32 PET/CT system features silicon photomultiplier (SiPM)-based detectors with bismuth germanium oxide crystals and a 32-cm axial field of view (FOV). The present study aimed to determine the performance characteristics of the Omni Legend 32 PET/CT system according to National Electrical Manufacturers Association (NEMA) NU 2-2018 standards. Methods: The PET component of this system comprises 22 detector modules; each module contains 24 detector blocks with 72 bismuth germanium oxide crystals with a volume of 4.1 × 4.1 × 30 mm coupled to 18 SiPM devices with a 6 × 6 mm area, resulting in an axial FOV of 32 cm. The spatial resolution, sensitivity, count rate performance, and image quality delivered by PET were evaluated using the NEMA NU 2-2018 standard. PET images of 2 patients were evaluated to get a visual first impression of the Omni Legend 32 PET/CT system together with Precision DL. Results: The average spatial resolution at 1, 10, and 20 cm from the central axis was 4.3, 5.3, and 6.2 mm, respectively, for filtered backprojection and 3.7, 4.3, and 5.1 mm, respectively, for ordered-subset expectation maximization. The NEMA sensitivity was 47.30 and 47.05 cps/kBq at the axial center of the FOV and at a 10-cm radial offset, respectively. The scatter fraction, count rate accuracy, and peak noise-equivalent count rates were 35.4%, 1.7%, and 501.7 kcps, respectively, at 15.7 kBq/mL. Contrast recovery for the NEMA body phantom from the smallest to the largest sphere ranged from 61.3% to 93.0%, with a background variability of 5.4%-11.7% and a lung error of 5.1% for Q.Clear (β-value, 50). Good patient image quality was obtained with the Omni Legend 32. Conclusion: The Omni Legend 32 has class-leading sensitivity and count rates within the category of whole-body PET systems while maintaining spatial resolution broadly comparable to that of other current SiPM-based PET/CT systems. This combination of properties results in a very good image quality.