Ordered Subsets Expectation Maximization Algorithm Research Articles

Refining penalty parameter selection in whole-body PET image reconstruction for lung cancer patients using the cross-validation log-likelihood method

Objective.Penalty parameters in penalized likelihood positron emission tomography (PET) reconstruction are typically determined empirically. The cross-validation log-likelihood (CVLL) method has been introduced to optimize these parameters by maximizing a CVLL function, which assesses the likelihood of reconstructed images using one subset of a list-mode dataset based on another subset. This study aims to validate the efficacy of the CVLL method in whole-body imaging for cancer patients using a conventional clinical PET scanner.Approach.Fifteen lung cancer patients were injected with 243.7 ± 23.8 MBq of [18F]FDG and underwent a 22 min PET scan on a Biograph mCT PET/CT scanner, starting at 60 ± 5 min post-injection. The PET list-mode data were partitioned by subsampling without replacement, with 20 minutes of data for image reconstruction using an in-house ordered subset expectation maximization algorithm and the remaining 2 minutes of data for cross-validation. Two penalty parameters, penalty strengthβand Fair penalty function parameterδ, were subjected to optimization. Whole-body images were reconstructed, and CVLL values were computed across various penalty parameter combinations. The optimal image corresponding to the maximum CVLL value was selected by a grid search for each patient.Main results.Theδvalue required to maximize the CVLL value was notably small (⩽10-6in this study). The influences of voxel size and scan duration on image optimization were investigated. A correlation analysis revealed a significant inverse relationship between optimalβand scan count level, with a correlation coefficient of -0.68 (p-value = 3.5 × 10-5). The optimal images selected by the CVLL method were compared with those chosen by two radiologists based on their diagnostic preferences. Differences were observed in the selection of optimal images.Significance.This study demonstrates the feasibility of incorporating the CVLL method into routine imaging protocols, potentially allowing for a wide range of combinations of injected radioactivity amounts and scan durations in modern PET imaging.

The effect of reconstruction algorithms on semi-quantitative measurements in 18F-FDG PET/CT imaging.

This study was carried out to understand whether Q.Clear and ordered subset expectation maximization (OSEM), reconstruction algorithms used in fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) applications, and parameters such as time of flight (TOF) and point spread function (PSF) cause different results in semi-quantitative measurements. Raw PET data of 264 patients who were referred to 18F-FDG PET/CT imaging with the purpose of evaluation of known or suspicious malignant disease were reconstructed separately with Q.Clear (GE Healthcare), a BPL, an OSEM algorithm, PSF (SharpIR®) and TOF (VUE Point FX®) methods. Each patient's liver, mediastinal blood pool, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and standardized uptake values (SUV) (SUVmax, SUVmean, and SUVpeak) of a total of 264 lesions selected from the patients were performed. β350+ToF yielded higher measurement results than all other variables for all of the lesion SUVmax, lesion SUVmean, L/AP SUVmax, and L/AP SUVmean parameters. OSEM+ToF and OSEM+TOF+PSF algorithms yielded higher mean and median SUVmax values for the reference structures (liver and mediastinum) and for lesions SUVmax and SUVmean values were statistically significantly lower than the β350+ToF method. The method with the lowest mean value for the L/Liver SUVmax variable was OSEM+ToF 4iter16ss (mean=1.76), while the method with the highest mean value was β350+ToF (mean=2.26). β350+ToF was the reconstruction method with the highest ratios for L/AP SUVmax and SUVmean for both lesions below and above 1 cm. β350+ToF algorithm had also statistically significantly higher results for these variables compared to all other parameters in malignant lesions. When comparing 18F-FDG PET/CT images, the use of different reconstruction algorithms may lead to misleading results, especially in the evaluation of response to treatment of malignancies.

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.

Quantitative 177Lu SPECT/CT imaging for personalized dosimetry using a ring-shaped CZT-based camera

BackgroundDosimetry after radiopharmaceutical therapy with 177Lu (177Lu-RPT) relies on quantitative SPECT/CT imaging, for which suitable reconstruction protocols are required. In this study, we characterized for the first time the quantitative performance of a ring-shaped CZT-based camera using two different reconstruction algorithms: an ordered subset expectation maximization (OSEM) and a block sequential regularized expectation maximization (BSREM) combined with noise reduction regularization. This study lays the foundations for the definition of a reconstruction protocol enabling accurate dosimetry for patients treated with 177Lu-RPT.MethodsA series of 177Lu-filled phantoms were acquired on a StarGuide™ (GE HealthCare), with energy and scatter windows centred at 208 (± 6%) keV and 185 (± 5%) keV, respectively. Images were reconstructed with the manufacturer implementations of OSEM (GE-OSEM) and BSREM (Q.Clear) algorithms, and various combinations of iterations and subsets. Additionally, the manufacturer-recommended Q.Clear-based reconstruction protocol was evaluated. Quantification accuracy, measured as the difference between the SPECT-based and the radionuclide calibrator-based activity, and noise were evaluated in a large cylinder. Recovery coefficients (RCs) and spatial resolution were assessed in a NEMA IEC phantom with sphere inserts. The reconstruction protocols considered suitable for clinical applications were tested on a cohort of patients treated with [177Lu]Lu-PSMA-I&T.ResultsThe accuracy of the activity from the cylinder, although affected by septal penetration, was < 10% for all reconstructions. Both algorithms featured improved spatial resolution and higher RCs with increasing updates at the cost of noise build-up, but Q.Clear outperformed GE-OSEM in reducing noise accumulation. When the reconstruction parameters were carefully selected, similar values for noise (~0.15), spatial resolution (~1 cm) and RCs were found, irrespective of the reconstruction algorithm. Analogue results were found in patients.ConclusionsAccurate activity quantification is possible when imaging 177Lu with StarGuide™. However, the impact of septal penetration requires further investigations. GE-OSEM is a valid alternative to the recommended Q.Clear reconstruction algorithm, featuring comparable performances assessed on phantoms and patients.

Variaciones en los parámetros cuantitativos y en la puntuación de la escala de Deauville aplicando diferentes algoritmos de reconstrucción en las imágenes PET/TC con [18F]FDG de pacientes con linfoma

Introduction and Objectives18F-FDG PET with the Deauville score (DS) is a unique semiquantitative method for lymphoma. However, type of standard uptake values (max, mean, and peak) reconstruction algorithms could affect DS. We compared the Bayesian Penalized Likelihood reconstruction algorithm (BPL) with Ordered Subsets Expectation Maximization (OSEM) on quantitative parameters and DS in lymphoma. We investigated the effect of the size of the lymph node on quantitative variation. Patients and MethodsRaw PET data of 255 lymphoma patients were reconstructed separately with Q.Clear (GE Healthcare), a BPL, and SharpIR (GE Healthcare), an OSEM algorithm. In both images, each patient's liver, mediastinal blood pool, and SUVs (SUVmax, SUVmean, and SUVpeak) of a total of 487 lesions selected from the patients were performed. DSmax, DSmean, and DSpeak were compared. ResultsIn our study, DS increased significantly with BPL (p<0.001), and the DS increased to 4-5 in 30 patients evaluated as 1-2-3 with OSEM. It was found that the quantitative values of the lymph nodes increased statistically with BPL (p<0.001), and the liver from the reference regions were significantly decreased (p<0.001). In addition, difference in lymph node was independently associated with size of lesion and was significantly more pronounced in small lesions (p<0.001). The effects of BPL algorithm were more pronounced in SUVmax than in SUVmean and SUVpeak. DS-mean and DS-peak scores were less changed by BPL than DS-max. ConclusionDifferent reconstruction algorithms in FDG PET/CT affect the quantitative evaluation. That variation may affect the change in DS in lymphoma patients, thus affecting patient management.

A proper protocol for routine 18F-FDG uEXPLORER total-body PET/CT scans

BackgroundConventional clinical PET scanners typically have an axial field of view (AFOV) of 15–30 cm, resulting in limited coverage and relatively low photon detection efficiency. Taking advantage of the development of long-axial PET/CT, the uEXPLORER PET/CT scanner with an axial coverage of 194 cm increases the effective count rate by approximately 40 times compared to that of conventional PET scanners. Ordered subset expectation maximization (OSEM) is the most widely used iterative algorithm in PET. The major drawback of OSEM is that the iteration process must be stopped before convergence to avoid image degradation due to excessive noise. A new Bayesian penalized-likelihood iterative PET reconstruction, named HYPER iterative, was developed and is now available on the uEXPLORER total-body PET/CT, which incorporates a noise control component by using a penalty function in each iteration and finds the maximum likelihood solution through repeated iterations. To date, its impact on lesion visibility in patients with a full injected dose or half injected dose is unclear. The goal of this study was to determine a proper protocol for routine 18F-FDG uEXPLORER total-body PET/CT scans.ResultsThe uEXPLORER total-body PET/CT images reconstructed using both OSEM and HYPER iterative algorithms of 20 tumour patients were retrospectively reviewed. The quality of the 5 min PET image was excellent (score 5) for all of the dose and reconstruction methods. Using the HYPER iterative method, the PET images reached excellent quality at 1 min with full-dose PET and at 2 min with half-dose PET. The PET image reached a similar excellent quality at 2 min with a full dose and at 3 min with a half dose using OSEM. The noise in the OSEM reconstruction was higher than that in the HYPER iterative. Compared to OSEM, the HYPER iterative had a slightly higher SUVmax and TBR of the lesions for large positive lesions (≥ 2 cm) (SUVmax: up to 9.03% higher in full dose and up to 12.52% higher in half dose; TBR: up to 8.69% higher in full dose and up to 23.39% higher in half dose). For small positive lesions (≤ 10 mm), the HYPER iterative had an obviously higher SUVmax and TBR of the lesions (SUVmax: up to 45.21% higher in full dose and up to 74.96% higher in half dose; TBR: up to 44.91% higher in full dose and up to 93.73% higher in half dose).ConclusionsA 1 min scan with a full dose and a 2 min scan with a half dose are optimal for clinical diagnosis using the HYPER iterative and 2 min and 3 min for OSEM. For quantification of the small lesions, HYPER iterative reconstruction is preferred.

Feasibility of acquisitions using total-body PET/CT with a half-dose [68Ga]Ga-FAPI-04 activity in oncology patients.

[68Ga]Ga-FAPI-04 (gallium-68-labeled fibroblast activation protein inhibitor-04) PET/CT has been widely used in diagnosing malignant tumors. Total-body PET/CT has a long axial field of view and provides higher sensitivity compared to traditional PET/CT. However, whether the reduced injected dose of [68Ga]Ga-FAPI-04 could obtain qualified imaging has not been evaluated. To explore the effect of half-dose [68Ga]Ga-FAPI-04 on image quality and tumor detectability in oncology patients. A total of twenty-seven patients with tumors or clinically suspected tumors were included, and all patients were scanned with total-body PET/CT after an injected dose of 0.84-1.14 MBq/kg [68Ga]Ga-FAPI-04. All patients obtained superior image quality with 300 s original acquisition time. Images were reconstructed using 180 s, 120 s, 60 s, 40 s, 30 s, 20 s scanning duration by ordered subset expectation maximization algorithm. The subjective image quality of all patients in each time group was scored using 5-point Likert scale. Mediastinal blood pool, liver, spleen, and muscle were analyzed as background using semi-quantitative parameters maximum standardized uptake values (SUVmax), mean standardized uptake values (SUVmean), standard deviation (SD), and signal to noise ratio (SNR). The lesion detection rate, SUVmax, and tumor-to-background ratio (TBR) were calculated for tumors confirmed by pathology. The subjective image quality score decreased with the shortening of scanning time; however, both 180 s and 120 s images met the diagnostic requirements in terms of overall quality, lesion conspicuity, and image noise. The SUVmax of background increased with the reduction of scanning time, while the SUVmean was relatively stable. With the shortening of scanning time, the SD gradually increased, and the SNR gradually decreased, which was consistent with subjective image quality scores. In 180 s and 120 s images, all 11 primary lesions and 79 metastatic lesions were detected. The SUVmax of tumor focus showed an increasing trend as same as the background. Compared with 300 s, the TBR muscle had no statistical difference in 180 s and 120 s. Half-dose [68Ga]Ga-FAPI-04 in total-body PET/CT imaging can shorten the acquisition time to 120 s with acceptable subjective image quality and 100% tumor detection rate. Total-body PET/CT imaging with a half-dose [68Ga]Ga-FAPI-04 and reduced acquisition time can be used in radiation-sensitive and poor tolerant to prolong horizontal positioning and waiting time populations such as children and gravidas.

The variation of quantitative parameters and Deauville scores with different reconstruction algorithms in FDG PET/CT imaging of lymphoma patients

Introduction and objectives18F-FDG PET with the Deauville score (DS) is a unique semiquantitative method for lymphoma. However, type of standard uptake values (max, mean, and peak) reconstruction algorithms could affect DS. We compared the Bayesian Penalized Likelihood reconstruction algorithm (BPL) with Ordered Subsets Expectation Maximization (OSEM) on quantitative parameters and DS in lymphoma. We investigated the effect of the size of the lymph node on quantitative variation. Patients and methodsRaw PET data of 255 lymphoma patients were reconstructed separately with Q.Clear (GE Healthcare), a BPL, and SharpIR (GE Healthcare), an OSEM algorithm. In both images, each patient's liver, mediastinal blood pool, and SUVs (SUVmax, SUVmean, and SUVpeak) of a total of 487 lesions selected from the patients were performed. DSmax, DSmean, and DSpeak were compared. ResultsIn our study, DS increased significantly with BPL (p < 0.001), and the DS increased to 4–5 in thirty patients evaluated as 1−2–3 with OSEM. It was found that the quantitative values of the lymph nodes increased statistically with BPL (p < 0.001), and the liver from the reference regions were significantly decreased (p < 0.001). In addition, difference in lymph node was independently associated with size of lesion and was significantly more pronounced in small lesions (p < 0.001). The effects of BPL algorithm were more pronounced in SUVmax than in SUVmean and SUVpeak. DS-mean and DS-peak scores were less changed by BPL than DS-max. ConclusionDifferent reconstruction algorithms in FDG PET/CT affect the quantitative evaluation. That variation may affect the change in DS in lymphoma patients, thus affecting patient management.

Evaluation of a method based on synthetic data inserted into raw data prior to reconstruction for the assessment of PET scanners

BackgroundPerformance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. Even though clinical data are the final target, their use to characterize systems response is constrained by the lack of ground truth. Phantom tests overcome this limitation by controlling the object of study, but remain simple and are not representative of patient complexity. The objective of this study is to evaluate the accuracy of a simulation method using synthetic spheres inserted into acquired raw data prior to reconstruction, simulating multiple scenarios in comparison with equivalent physical experiments.MethodsWe defined our experimental framework using the National Electrical Manufacturers Association NU-2 2018 Image Quality standard, but replaced the standard sphere set with more appropriate sizes (4, 5, 6, 8, 10 and 13 mm) better suited to current PET scanner performance. Four experiments, with different spheres-to-background ratios (2:1, 4:1, 6:1 and 8:1), were performed. An additional dataset was acquired with a radioactive background but no activity within the spheres (water only) to establish a baseline. Then, we artificially simulated radioactive spheres to reproduce other experiments using synthetic data inserted into the original sinogram. Images were reconstructed following standard guidelines using ordered subset expectation maximization algorithm along with a Bayesian penalized likelihood algorithm. We first visually compared experimental and simulated images. Afterward, we measured the activity concentration values into the spheres to calculate the mean and maximum recovery coefficients (RCmean and RCmax) which we used in a quantitative analysis.ResultsNo significant visual differences were identified between experimental and simulated series. Mann–Whitney U tests comparing simulated and experimental distributions showed no statistical differences for both RCmean (P value = 0.611) and RCmax (P value = 0.720). Spearman tests revealed high correlation for RCmean (ρ = 0.974, P value < 0.001) and RCmax (ρ = 0.974, P value < 0.001) between both datasets. From Bland–Altman plots, we highlighted slight shifts in RCmean and RCmax of, respectively, 2.1 ± 16.9% and 3.3 ± 22.3%.ConclusionsWe evaluated the efficiency of our hybrid method in faithfully mimicking practical situations producing satisfactory results compared to equivalent experimental data.

Feasibility of Imaging Small Animals on a 360° Whole-Body Cadmium Zinc Telluride SPECT Camera: a Phantom Study.

Single-photon emission computed tomography has found an important place in preclinical cancer research. Nevertheless, the cameras dedicated to small animals are not widely available. The present study aimed to assess the feasibility of imaging small animals by a newly released 360° cadmium zinc telluride camera (VERITON, Spectrum Dynamics, Israel) dedicated to human patients. A cylindrical phantom containing hot spheres was used to evaluate the intrinsic performance of the camera first without the presence of background activity and then with two contrasts between background and hot spheres (1/4 and 1/10). Acquisitions were repeated with different scan durations (10 and 20min), two tested radioisotopes (Tc-99m and I-123), and a set of reconstruction parameters (10 iterations [i] 8 subsets [s], 10i16s, 10i32s). A 3D-printed phantom mimicking a rat with four subcutaneous tumours was then used to test the camera under preclinical conditions. The results obtained from the micro-hollow sphere phantom showed that it was possible to visualize spheres with an inner diameter of 3.95mm without background activity. Moreover, spheres with diameters of 4.95mm can be seen in the condition of high contrast between background and spheres (1/10) and 7.86mm with lower contrast (1/4). The rat-sized phantom acquisitions showed that 10- and 8-mm subcutaneous tumours were visible with a good contrast obtained for the two radioisotopes tested in this study. Both Tc-99m and I-123 measurements demonstrated that a 10-min acquisition reconstructed with an ordered subset expectation maximization algorithm applying 10i32s was optimal to obtain sufficient image quality in terms of noise, resolution, and contrast. Phantom results showed the ability of the system to detect sub-centimetre lesions for various radioisotopes. It seemed feasible to image small animals using a 360° cadmium zinc telluride gamma camera for preclinical cancer research purposes.

Assessment of different quantification metrics of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm

BackgroundWe aim to assess the spill-in effect and the benefit in quantitative accuracy for [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) using the background correction (BC) technique. MethodsSeventy-two datasets of patients diagnosed with AAA were reconstructed with ordered subset expectation maximization algorithm incorporating point spread function (PSF). Spill-in effect was investigated for the entire aneurysm (AAA), and part of the aneurysm excluding the region close to the bone (AAAexc). Quantifications of PSF and PSF+BC images using different thresholds (% of max. SUV in target regions-of-interest) to derive target-to-background (TBR) values (TBRmax, TBR90, TBR70 and TBR50) were compared at 3 and 10 iterations. ResultsTBR differences were observed between AAA and AAAexc due to spill-in effect from the bone into the aneurysm. TBRmax showed the highest sensitivity to the spill-in effect while TBR50 showed the least. The spill-in effect was reduced at 10 iterations compared to 3 iterations, but at the expense of reduced contrast-to-noise ratio (CNR). TBR50 yielded the best trade-off between increased CNR and reduced spill-in effect. PSF+BC method reduced TBR sensitivity to spill-in effect, especially at 3 iterations, compared to PSF (P-value ≤ 0.05). ConclusionTBR50 is robust metric for reduced spill-in and increased CNR.

Optimization of 99m Tc whole-body SPECT/CT image quality: A phantom study.

PurposeInvestigate the impact of acquisition time and reconstruction parameters on single‐photon emission computed tomography/computed tomography (SPECT/CT) image quality with the ultimate aim of finding the shortest possible acquisition time for clinical whole‐body SPECT/CT (WB‐SPECT/CT) while maintaining image qualityMethodsThe National Electrical Manufacturers Association (NEMA) image quality measurements were performed on a SPECT/CT imaging system using a NEMA International Electrotechnical Commission (IEC) phantom with spherical inserts of varying diameter (10–37 mm), filled with 99mTc in activity sphere‐to‐background concentration ratio of 8.5:1. A gated acquisition was acquired and binned data were summed to simulate acquisitions of 15, 8, and 3 s per projection angle. Images were reconstructed on a Hermes (HERMES Medical Solutions AB, Stockholm, Sweden) workstation using eight subsets and between 4 and 24 iterations of the three‐dimensional (3D) ordered subset expectation maximization (OSEM) algorithm. Reconstructed images were post‐smoothed with 3D Gaussian filter ranging from 0 to 12 mm full‐width at half maximum (FWHM). Contrast recovery, background variability, and contrast‐to‐noise ratio were evaluatedResultsAs expected, the spheres were more clearly defined as acquisition time and count statistics improved. The optimal iteration number and Gaussian filter were determined from the contrast recovery convergence and level of noise. Convergence of contrast recovery was observed at eight iterations while 12 iterations yielded stabilized values at all acquisition times. In addition, it was observed that applying 3D Gaussian filter of 8–12 mm FWHM suppressed the noise and mitigated Gibbs artifacts. Background variability was larger for small spheres than larger spheres and the noise decreased when acquisition time became longer. A contrast‐to‐noise ratio >5 was reached for the two smallest spheres of 10 and 13 mm at acquisition times of 8 sConclusionOptimized reconstruction parameters preserved image quality with reduce acquisition time in present study. This study suggests an optimal protocol for clinical 99mTc SPECT/CT can be reached at 8 s per projection angle, with data reconstructed using 12 iterations and eight subset of the 3D OSEM algorithm and 8 mm Gaussian post‐filter.

Initial results of a mouse brain PET insert with a staggered 3-layer DOI detector

Objective. Small animal positron emission tomography (PET) requires a submillimeter resolution for better quantification of radiopharmaceuticals. On the other hand, depth-of-interaction (DOI) information is essential to preserve the spatial resolution while maintaining the sensitivity. Recently, we developed a staggered 3-layer DOI detector with 1 mm crystal pitch and 15 mm total crystal thickness, but we did not demonstrate the imaging performance of the DOI detector with full ring geometry. In this study we present initial imaging results obtained for a mouse brain PET prototype developed with the staggered 3-layer DOI detector. Approach. The prototype had 53 mm inner diameter and 11 mm axial field-of-view. The PET scanner consisted of 16 DOI detectors each of which had a staggered 3-layer LYSO crystal array (4/4/7 mm) coupled to a 4 × 4 silicon photomultiplier array. The physical performance was evaluated in terms of the NEMA NU 4 2008 protocol. Main Results. The measured spatial resolutions at the center and 15 mm radial offset were 0.67 mm and 1.56 mm for filtered-back-projection, respectively. The peak absolute sensitivity of 0.74% was obtained with an energy window of 400–600 keV. The resolution phantom imaging results show the clear identification of a submillimetric rod pattern with the ordered-subset expectation maximization algorithm. The inter-crystal scatter rejection using a narrow energy window could enhance the resolvability of a 0.75 mm rod significantly. Significance. In an animal imaging experiment, the detailed mouse brain structures such as cortex and thalamus were clearly identified with high contrast. In conclusion, we successfully developed the mouse brain PET insert prototype with a staggered 3-layer DOI detector.

Effects of New Bayesian Penalized Likelihood Reconstruction Algorithm on Visualization and Quantification of Upper Abdominal Malignant Tumors in Clinical FDG PET/CT Examinations.

PurposeThis study evaluated the effects of new Bayesian penalized likelihood (BPL) reconstruction algorithm on visualization and quantification of upper abdominal malignant tumors in clinical FDG PET/CT examinations, comparing the results to those obtained by an ordered subset expectation maximization (OSEM) reconstruction algorithm. Metabolic tumor volume (MTV) and texture features (TFs), as well as SUV-related metrics, were evaluated to clarify the BPL effects on quantification.Materials and MethodsA total of 153 upper abdominal lesions (82 liver metastatic and 71 pancreatic cancers) were included in this study. FDG PET/CT images were acquired with a GE Discovery 710 scanner equipped with a time-of-flight system. Images were reconstructed using OSEM and BPL (beta 700) algorithms. In 58 lesions <1.5 cm in greatest diameter (small-lesion group), visual image quality of each lesion was evaluated using a four-point scale. SUVmax was obtained for quantitative metrics. Visual scores and SUVmax were compared between OSEM and BPL images. In 95 lesions >2.0 cm in greatest diameter (larger-lesion group), SUVmax, SUVpeak, MTV, and six TFs were compared between OSEM and BPL images. In addition to the size-based analyses, an increase of SUVmax with BPL was evaluated according to the original SUVmax in OSEM images.ResultsIn the small-lesion group, both visual score and SUVmax were significantly higher in the BPL than OSEM images. The increase in visual score was observed in 20 (34%) of all 58 lesions. In the larger-lesion group, no statistical difference was observed in SUVmax, SUVpeak, or MTV between OSEM and BPL images. BPL increased high gray-level zone emphasis and decreased low gray-level zone emphasis among six TFs compared to OSEM with statistical significance. No statistical differences were observed in other TFs. SUVmax-based analysis demonstrated that BPL increased and decreased SUVmax in lesions with low (<5) and high (>10) SUVmax in original OSEM images, respectively.ConclusionThis study demonstrated that BPL improved conspicuity of small or low-count upper abdominal malignant lesions in clinical FDG PET/CT examinations. Only two TFs represented significant differences between OSEM and BPL images of all quantitative metrics in larger lesions.

Optimizing reconstruction parameters for quantitative 124I-PET in the presence of therapeutic doses of 131I

BackgroundThe goal of this work was to determine the quantitative accuracy and optimal reconstruction parameters for 124I-PET imaging in the presence of therapeutic levels of 131I. In this effort, images were acquired on a GE D710 PET/CT scanner using a NEMA IEC phantom with spheres containing 124I and increasing amounts of 131I activity in the background. At each activity level, two scans were acquired, one with the phantom centered in the field of view (FOV) and one 11.2 cm off-center. Reconstructions used an ordered subset expectation maximization algorithm with up to 100 iterations of 16 subsets, with and without time-of-flight (TOF) information. Results were evaluated visually and by comparing the 124I activity relative to the scan performed in the absence of 131I.Results131I within the FOV added to the randoms rate, to dead time, and to pile-up within the detectors. Using our standard clinical reconstruction parameters, the image quality and quantitative accuracy suffered at 131I activities above 1.4 GBq. Convergence rates slowed progressively in the presence of increasing amounts of 131I for both TOF and nonTOF reconstructions. TOF reconstructions converged more quickly than nonTOF but often towards erroneous concentrations. Iterating nonTOF reconstructions to convergence produced quantitatively accurate images except for the off-center phantom at the very highest level of background 131I tested.ConclusionsThis study shows that quantitative PET is feasible in the presence of large amounts of 131I. The high randoms fractions resulted in slow reconstruction convergence and negatively impacted TOF corrections and/or the accuracy of TOF information. Therefore, increased iterations and nonTOF reconstructions are recommended.

Effect of different examination conditions on image quality and quantitative value of amyloid positron emission tomography using 18F-flutemetamol.

The recommended start time for 18F-flutemetamol amyloid positron emission tomography (PET) examination is 60-120min after 18F-flutemetamol injection, while an acquisition time of 10-30min is generally recommended. We aimed to elucidate the effects of different examination conditions on image quality, diagnostic ability, and quantitative value of amyloid PET using 18F-flutemetamol. We acquired data on a Discovery PET/computed tomography 710 scanner using Hoffman brain and pillar phantoms with 20MBq of 18F for 30min. The images were reconstructed into 10-, 20-, and 30-min periods. The ordered subset-expectation maximization algorithm was used for image reconstruction, which uses a 2- or 4-mm Gaussian filter and a combination of iteration and subset numbers. The percentage contrast and coefficient of variation (CV; as the image noise) were used as physical evaluation indices for reconstructed images, and images with superior contrast and low image noise were selected for clinical evaluation. The imaging data of 15 symptomatic patients (n = 7 and n = 8 for positive and negative diagnoses of Alzheimer's disease, respectively) were reconstructed under the phantom study conditions. Radiographers visually evaluated and ranked the clinical images based on the overall contrast and image noise, and nuclear medicine specialists diagnosed Alzheimer's disease. We compared the standardized uptake value ratio (SUVR) obtained with different acquisition conditions. The basic study using the phantom revealed high convergence of contrast and image noise in five patterns of acquisition time and filter strengths. Regarding visual evaluation, the use of a 2-mm Gaussian filter caused difficulties in diagnosis because the brain parenchymal accumulation was mottled with high image noise. Differences in image quality and diagnostic ability due to different examination times were not significant. Differences in the SUVR were not significant in patients with a negative Alzheimer's disease diagnosis; in patients with a positive diagnosis, the SUVR showed significant fluctuation depending on the acquisition conditions. The differences in image quality and diagnostic performance due to the differences in 10-min acquisition time were not significant; however, of note, SUVR showed significant fluctuation depending on the acquisition conditions in patients diagnosed with Alzheimer's disease.

Comparison of Regularized Reconstruction and Ordered Subset Expectation Maximization Reconstruction in the Diagnostics of Prostate Cancer Using Digital Time-of-Flight 68Ga-PSMA-11 PET/CT Imaging.

In prostate cancer, the early detection of distant spread has been shown to be of importance. Prostate-specific membrane antigen (PSMA)-binding radionuclides in positron emission tomography (PET) is a promising method for precise disease staging. PET diagnostics depend on image reconstruction techniques, and ordered subset expectation maximization (OSEM) is the established standard. Block sequential regularized expectation maximization (BSREM) is a more recent reconstruction algorithm and may produce fewer equivocal findings and better lesion detection. Methods: 68Ga PSMA-11 PET/CT scans of patients with de novo or suspected recurrent prostate cancer were retrospectively reformatted using both the OSEM and BSREM algorithms. The lesions were counted and categorized by three radiologists. The intra-class correlation (ICC) and Cohen’s kappa for the inter-rater reliability were calculated. Results: Sixty-one patients were reviewed. BSREM identified slightly fewer lesions overall and fewer equivocal findings. ICC was excellent with regards to definitive lymph nodes and bone metastasis identification and poor with regards to equivocal metastasis irrespective of the reconstruction algorithm. The median Cohen’s kappa were 0.66, 0.74, 0.61 and 0.43 for OSEM and 0.61, 0.63, 0.66 and 0.53 for BSREM, with respect to the tumor, local lymph nodes, metastatic lymph nodes and bone metastasis detection, respectively. Conclusions: BSREM in the setting of 68Ga PMSA PET staging or restaging is comparable to OSEM.

Improved detection of in-transit metastases of malignant melanoma with BSREM reconstruction in digital [18F]FDG PET/CT

ObjectivesTo compare block sequential regularized expectation maximization (BSREM) and ordered subset expectation maximization (OSEM) for the detection of in-transit metastasis (ITM) of malignant melanoma in digital [18F]FDG PET/CT.MethodsWe retrospectively analyzed a cohort of 100 [18F]FDG PET/CT scans of melanoma patients with ITM, performed between May 2017 and January 2020. PET images were reconstructed with both OSEM and BSREM algorithms. SUVmax, target-to-background ratio (TBR), and metabolic tumor volume (MTV) were recorded for each ITM. Differences in PET parameters were analyzed with the Wilcoxon signed-rank test. Differences in image quality for different reconstructions were tested using the Man-Whitney U test.ResultsBSREM reconstruction led to the detection of 287 ITM (39% more than OSEM). PET parameters of ITM were significantly different between BSREM and OSEM reconstructions (p < 0.001). SUVmax and TBR were higher (76.5% and 77.7%, respectively) and MTV lower (49.5%) on BSREM. ITM missed with OSEM had significantly lower SUVmax (mean 2.03 vs. 3.84) and TBR (mean 1.18 vs. 2.22) and higher MTV (mean 2.92 vs. 1.01) on OSEM compared to BSREM (all p < 0.001).ConclusionsBSREM detects significantly more ITM than OSEM, owing to higher SUVmax, higher TBR, and less blurring. BSREM is particularly helpful in small and less avid lesions, which are more often missed with OSEM.Key Points• In melanoma patients, [18F]FDG PET/CT helps to detect in-transit metastases (ITM), and their detection is improved by using BSREM instead of OSEM reconstruction.• BSREM is particularly useful in small lesions.

Comparison of ordered-subset expectation maximization and filtered back projection reconstruction based on quantitative outcome from dynamic [18F]NaF PET images.

[18F]NaF PET imaging is a useful tool for measuring regional bone metabolism. However, due to tracer in urine, [18F]NaF PET images of the hip reconstructed using filtered back projection (FBP) frequently show streaking artifacts in slices through the bladder leading to noisy time-activity curves unsuitable for quantification. This study compares differences between quantitative outcomes at the hip derived from images reconstructed using the FBP and ordered-subset expectation maximization (OSEM) methods. Dynamic [18F]NaF PET data at the hip for four postmenopausal women were reconstructed using FBP and nine variations of the OSEM algorithm (all combinations of 1, 5, 15 iterations and 10, 15, 21 subsets). Seven volumes of interest were placed in the hip. Bone metabolism was measured using standardized uptake values, Patlak analysis (Ki-PAT) and Hawkins model Ki-4k. Percentage differences between the standardized uptake values and Ki values from FBP and OSEM images were assessed. OSEM images appeared visually smoother and without the streaking artifacts seen with FBP. However, due to loss of counts, they failed to recover the quantitative values in VOIs close to the bladder, including the femoral head and femoral neck. This was consistent for all quantification methods. Volumes of interest farther from the bladder or larger and receiving greater counts showed good convergence with 5 iterations and 21 subsets. For VOIs close to the bladder, including the femoral neck and femoral head, 15 iterations and 10, 15 or 21 subsets were not enough to obtain OSEM images suitable for measuring bone metabolism and showed no improvement compared to FBP.

Task-based assessment of binned and list-mode SPECT systems.

In SPECT, list-mode (LM) format allows storing data at higher precision compared to binned data. There is significant interest in investigating whether this higher precision translates to improved performance on clinical tasks. Towards this goal, in this study, we quantitatively investigated whether processing data in LM format, and in particular, the energy attribute of the detected photon, provides improved performance on the task of absolute quantification of region-of-interest (ROI) uptake in comparison to processing the data in binned format. We conducted this evaluation study using a DaTscan brain SPECT acquisition protocol, conducted in the context of imaging patients with Parkinson's disease. This study was conducted with a synthetic phantom. A signal-known exactly/background-known-statistically (SKE/BKS) setup was considered. An ordered-subset expectation-maximization algorithm was used to reconstruct images from data acquired in LM format, including the scatter-window data, and including the energy attribute of each LM event. Using a realistic 2-D SPECT system simulation, quantification tasks were performed on the reconstructed images. The results demonstrated improved quantification performance when LM data was used compared to binning the attributes in all the conducted evaluation studies. Overall, we observed that LM data, including the energy attribute, yielded improved performance on absolute quantification tasks compared to binned data.