Optimization of penalization function in Bayesian penalized likelihood reconstruction algorithm for [18F]flutemetamol amyloid PET images.

Point-spread-function (PSF) correction is not recommended for amyloid PET images due to Gibbs artifacts. Q.Clear™, a Bayesian Penalized Likelihood (BPL) reconstruction method without incorporating PSF correction reduces these artifacts but degrades image contrast by our previous findings. The present study aimed to recover lost contrast by optimizing reconstruction parameters in time-of-flight (TOF) BPL reconstruction of amyloid PET images without PSF correction. We selected candidate conditions based on a phantom study and then determined which were optimal in a clinical study. Phantom images were reconstructed under conditions of 1‒9 iterations, ß 300-1000 and γ factors from 2 to 10 in TOF-BPL without PSF correction. We evaluated the %contrast and the coefficients of variation (CV, %). Standardized uptake value ratios (SUVr) and Centiloid scales (CL) were calculated from PET images acquired from 71 participants after an [18F]flutemetamol injection. Both %contrast and CV were independent of iterations, whereas a trade-off was found between γ factors and ß. We selected a γ factors of 5 without PSF correction (iterations, 1; ß, 500) and of 10 without PSF correction (iterations, 1; ß, 800) as candidates for clinical investigation. The SUVr and CL remained stable across various conditions, and CL scales effectively discriminated amyloid PET using measured values. The optimal reconstruction parameters of TOF-BPL for [18F]flutemetamol PET images were γ factor 10, iterations 1 and ß 800, without PSF correction.

Phantom test procedures for a new neuro-oncological amino acid PET tracer: [18F]fluciclovine.

OBJECTIVE: Amino acid positron emission tomography (PET) examinations using anti-1-amino-3-[18F]-fluorocyclobutane-1-carboxylic acid ([18F]FACBC) were allowed for routine clinical use in July 2024. However, phantom test procedures for [18F]FACBC reconstruction parameters have not yet been established. The present study aimed to establish new phantom test procedures for [18F]FACBC brain PET imaging to determine optimal reconstruction parameters. METHODS: Background (BG) activity as well as hot sphere and target-to-background ratios (TBRs) of [18F]FACBC were estimated based on brain activity and tumor-to-normal tissue ratios (TNR) in a Japanese clinical trial of [18F]FACBC. Phantom experiments proceeded under [18F]FACBC or L-[methyl-11C]-methionine ([11C]MET) conditions. The number of iterations and the Gaussian filter parameters were determined from the reconstruction parameters %contrastmean and coefficients of variation (CVs) in ordered subset expectation maximization (OSEM) and time-of-flight (TOF) with or without point-spread-function (PSF) correction. RESULTS: The amounts of activity in the hot spheres and BG were 1.1 and 5.5 kBq/mL, respectively, and the TBR was 5.0 at the start of acquisition. The %contrastmean of all hot spheres was higher with [18F]FACBC than [11C]MET, and %contrastmean converged between 4 and 6 iterations in hot spheres with diameters < 10 mm. We used four iterations for OSEM + TOF and five for OSEM + TOF + PSF correction for [18F]FACBC and [11C]MET images. The CV was higher for [18F]FACBC than [11C]MET. The optimal sizes of Gaussian filters for OSEM + TOF and OSEM + TOF + PSF correction of image reconstruction were 5 mm for [18F]FACBC, and 4 and 3 mm, respectively, for [11C]MET images. CONCLUSIONS: We estimated phantom activity and TBR based on brain activity in a Japanese clinical trial and established new phantom test procedures for [18F]FACBC. We recommend that the optimal reconstruction parameters for [18F]FACBC should be set to the same number of iterations as [11C]MET and that the FWHM of Gaussian filter should have a few mm higher than [11C]MET to reduce image noise from brain normal tissue.

Development of a novel phantom for tau PET imaging.

PURPOSE: The cortical uptake of tau positron emission tomography (PET) tracers corresponds to the Braak stage and reflects the distribution and progression of tau neurofibrillary tangles. The present study aimed to develop and validate the basic performance of a novel tau PET phantom, as well as to establish standard test procedures and analytical methods. METHODS: The tau PET phantom consisted of a brain simulation section simulated medial temporal lobe region and resolution and uniformity sections. The brain simulation section and hot rods and uniformity section contained 4 and 2 kBq/mL of 18F, respectively and images were acquired three times for 20 min with a PET/CT scanner. The resolution section was visually assessed with two sets of hot and cold rods. Recovery coefficients (RCs) as a quantitative value and coefficient of variation (CV) as image noise were determined based on the brain simulation and the uniformity section, respectively. RESULTS: Preparation of activity in the phantom was repeatable among three measurements. The quality of images in the brain simulation and uniformity section with the rods was good. The 5- or 6-mm rods were detected separately. The mean RCs calculated based on the VOI template were between 0.75 and 0.83. The CV at the center slice of uniformity section was 5.54%. CONCLUSIONS: We developed a novel tau PET phantom to assess quantitative value, image noise, and detectability and resolution from brain simulation section, uniformity section, and rods, respectively. This phantom will contribute to the standardization and harmonization of tau PET imaging.

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

PURPOSE: Bayesian 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. METHODS: Images 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 ß deposition in patients was visually assessed by two physicians and quantified based on the standardised uptake value ratio (SUVR). RESULTS: The overestimated radioactivity in profile curves was eliminated using BPL without PSF correction. The %contrast and image noise decreased with increasing ß values in phantom images. Image quality and RCs were better using BPL with, than without PSF correction or OSEM. An optimal ß 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. CONCLUSION: Gibbs 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.

Deep Learning-Driven Estimation of Centiloid Scales from Amyloid PET Images with 11C-PiB and 18F-Labeled Tracers in Alzheimer's Disease.

BACKGROUND: Standard methods for deriving Centiloid scales from amyloid PET images are time-consuming and require considerable expert knowledge. We aimed to develop a deep learning method of automating Centiloid scale calculations from amyloid PET images with 11C-Pittsburgh Compound-B (PiB) tracer and assess its applicability to 18F-labeled tracers without retraining. METHODS: We trained models on 231 11C-PiB amyloid PET images using a 50-layer 3D ResNet architecture. The models predicted the Centiloid scale, and accuracy was assessed using mean absolute error (MAE), linear regression analysis, and Bland-Altman plots. RESULTS: The MAEs for Alzheimer's disease (AD) and young controls (YC) were 8.54 and 2.61, respectively, using 11C-PiB, and 8.66 and 3.56, respectively, using 18F-NAV4694. The MAEs for AD and YC were higher with 18F-florbetaben (39.8 and 7.13, respectively) and 18F-florbetapir (40.5 and 12.4, respectively), and the error rate was moderate for 18F-flutemetamol (21.3 and 4.03, respectively). Linear regression yielded a slope of 1.00, intercept of 1.26, and R2 of 0.956, with a mean bias of -1.31 in the Centiloid scale prediction. CONCLUSIONS: We propose a deep learning means of directly predicting the Centiloid scale from amyloid PET images in a native space. Transferring the model trained on 11C-PiB directly to 18F-NAV4694 without retraining was feasible.

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

OBJECTIVE: 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. METHODS: 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 (ß = 200). Maximum standardized uptake value (SUVmax) and tumor-to-normal tissue ratio (T/Nmax) were measured at each lesion. RESULTS: 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. CONCLUSIONS: 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.

Impact of irregular waveforms on data-driven respiratory gated PET/CT images processed using MotionFree algorithm.

OBJECTIVES: MotionFree® (AMF) is a data-driven respiratory gating (DDG) algorithm for image processing that has recently been introduced into clinical practice. The present study aimed to verify the accuracy of respiratory waveform and the effects of normal and irregular respiratory motions using AMF with the DDG algorithm. METHODS: We used a NEMA IEC body phantom comprising six spheres (37-, 28-, 22-, 17-, 13-, and 10 mm diameter) containing 18F. The sphere-to-background ratio was 4:1 (21.2 and 5.3 kBq/mL). We acquired PET/CT images from a stationary or moving phantom placed on a custom-designed motion platform. Respiratory motions were reproduced based on normal (sinusoidal or expiratory-paused waveforms) and irregular (changed amplitude or shifted baseline waveforms) movements. The "width" parameters in AMF were set at 10-60% and extracted data during the expiratory phases of each waveform. We verified the accuracy of the derived waveforms by comparing those input from the motion platform and output determined using AMF. Quantitative accuracy was evaluated as recovery coefficients (RCs), improvement rate, and %change that were calculated based on sphere diameter or width. We evaluated statistical differences in activity concentrations of each sphere between normal and irregular waveforms. RESULTS: Respiratory waveforms derived from AMF were almost identical to the input waveforms on the motion platform. Although the RCs in each sphere for expiratory-paused and ideal stationary waveforms were almost identical, RCs except the expiratory-paused waveform were lower than those for the stationary waveform. The improvement rate decreased more for the irregular, than the normal waveforms with AMF in smaller spheres. The %change was improved by decreasing the width of waveforms with a shifted baseline. Activity concentrations significantly differed between normal waveforms and those with a shifted baseline in spheres < 28 mm. CONCLUSIONS: The PET images using AMF with the DDG algorithm provided the precise waveform of respiratory motions and the improvement of quantitative accuracy in the four types of respiratory waveforms. The improvement rate was the most obvious in expiratory-paused waveforms, and the most subtle in those with a shifted baseline. Optimizing the width parameter in irregular waveform will benefit patients who breathe like the waveform with the shifted baseline.

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 (ß-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.

[The Questionnaire Survey of Japanese Practice and Environment for Targeted Radionuclide Therapy in 2021].

PURPOSE: Recently, the targeted radionuclide therapy (TRT) was urgently required to adapt the practice and environment because of the implementation of novel therapeutic radiopharmaceuticals such as alpha- and beta- radionuclides therapy. The present study aimed to clarify the questionnaire survey with the current situation (safety controls for workers and patients) at Japanese TRT facilities. METHODS: The massive questionnaire survey, 2 months from October to November 2021, was conducted among nationwide 251 facilities that have performed TRT in the past two years. The alpha- and beta- therapeutic radiopharmaceuticals were categorized and answered by one representative of the facility under anonymity. We analyzed the actual situation of each facility related to occupational exposure, radiation protection, contamination inspection, patient release criteria, and dosimetry for TRT. RESULTS: The survey response rate was 69.1% (174 facilities). About 75% of these facilities reported that they either follow the guidelines or take their own measures to reduce occupational exposure. The confirmed means of patient release criteria were 68.0% with the administered radioactivity and 87.2% with the ambient dose rate. The cold run was not performed for the first time at 15.0% and 10.0% of the facilities for ß- and α-emitting radionuclides, respectively. The facilities without attachment syringe shields were 39.2% for alpha-radionuclides therapy and 20.3% for beta-radionuclides therapy. CONCLUSION: We clarified the Japanese problem for TRT practice and environment by the questionnaire survey. Our findings indicated that the Japanese guidelines and manuals for TRT were not partly followed in the nationwide facilities.

Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images.

BACKGROUND: The Bayesian penalized likelihood PET reconstruction (BPL) algorithm, Q.Clear (GE Healthcare), has recently been clinically applied to clinical image reconstruction. The BPL includes a relative difference penalty (RDP) as a penalty function. The ß value that controls the behavior of RDP determines the global strength of noise suppression, whereas the γ factor in RDP controls the degree of edge preservation. The present study aimed to assess the effects of various γ factors in RDP on the ability to detect sub-centimeter lesions. METHODS: All PET data were acquired for 10 min using a Discovery MI PET/CT system (GE Healthcare). We used a NEMA IEC body phantom containing spheres with inner diameters of 10, 13, 17, 22, 28 and 37 mm and 4.0, 5.0, 6.2, 7.9, 10 and 13 mm. The target-to-background ratio of the phantom was 4:1, and the background activity concentration was 5.3 kBq/mL. We also evaluated cold spheres containing only non-radioactive water with the same background activity concentration. All images were reconstructed using BPL + time of flight (TOF). The ranges of ß values and γ factors in BPL were 50-600 and 2-20, respectively. We reconstructed PET images using the Duetto toolbox for MATLAB software. We calculated the % hot contrast recovery coefficient (CRChot) of each hot sphere, the cold CRC (CRCcold) of each cold sphere, the background variability (BV) and residual lung error (LE). We measured the full width at half maximum (FWHM) of the micro hollow hot spheres ≤ 13 mm to assess spatial resolution on the reconstructed PET images. RESULTS: The CRChot and CRCcold for different ß values and γ factors depended on the size of the small spheres. The CRChot, CRCcold and BV increased along with the γ factor. A 6.2-mm hot sphere was obvious in BPL as lower ß values and higher γ factors, whereas γ factors ≥ 10 resulted in images with increased background noise. The FWHM became smaller when the γ factor increased. CONCLUSION: High and low γ factors, respectively, preserved the edges of reconstructed PET images and promoted image smoothing. The BPL with a γ factor above the default value in Q.Clear (γ factor = 2) generated high-resolution PET images, although image noise slightly diverged. Optimizing the ß value and the γ factor in BPL enabled the detection of lesions ≤ 6.2 mm.

Evaluation of data-driven respiratory gating for subcentimeter lesions using digital PET/CT system and three-axis motion phantom.

Introduction.The application of data-driven respiratory gating (DDG) for subcentimeter lesions with respiratory movement remains poorly understood. Hence, this study aimed to clarify DDG application for subcentimeter lesions and the ability of digital Positron emission tomography/computed tomography (PET/CT) system combined with DDG to detect these lesions under three-axis respiration.Methods.Discovery MI PET/CT system and National Electrical Manufacturers Association (NEMA) body phantom with Micro Hollow Sphere (4, 5, 6, 8, 10, and 13 mm) were used. The NEMA phantom was filled with18F-FDG solutions of 42.4 and 5.3 kBq/ml for each hot sphere and background region. The 3.6 s cycles of three-axis respiratory motion were reproduced using the motion platform UniTraQ. The PET data acquisition was performed in stationary and respiratory-moving states. The data were reconstructed in three PET groups: stationary (NM-PET), no gating with respiratory movement (NG-PET), and DDG gating with respiratory movement (DDG-PET) groups. For image quality, percent contrast (QH); maximum, peak, and mean standardized uptake value (SUV); background region; and detectability index (DI) were evaluated in each PET group. Visual assessment was also conducted.Results.The groups with respiratory movement had deteriorated QHand SUVs compared with NM-PET. Compared with NG-PET, DDG-PET has significantly improved QHand SUVs in spheres above 6 mm. The background region showed no significant difference between groups. The SUVmax, SUVpeak, and QHvalues of 8 mm sphere were highest in NM-PET, followed by DDG-PET and NG-PET. In visual assessment, the spheres above 6 mm were detected in all PET groups. DDG application did not detect new lesions, but it increased DI and visual score.Conclusions. The application of principal component analysis (PCA)-based DDG algorithm improves both image quality and quantitative SUVs in subcentimeter lesions measuring above 6 mm. Although DDG application cannot detect new subcentimeter lesions, it increases the visual indices.

Development of a new quantification method using partial volume effect correction for individual energy peaks in 111In-pentetreotide SPECT/CT.

Objectives: Somatostatin receptor scintigraphy (SRS) using 111In-pentetreotide has no established quantification method. The purpose of this study was to develop a new quantitative method to correct the partial volume effect (PVE) for individual energy peaks in 111In-pentetreotide single-photon emission computed tomography (SPECT). Methods: Phantom experiments were performed to construct a new quantitative method. In the phantom experiments, a NEMA IEC body phantom was used. Acquisition was performed using two energy peaks (171 keV and 245 keV) on the SPECT/CT system. The volume of interest was set at each hot sphere and lung insert in the SPECT images of each energy peak, and the recovery coefficient (RC) was calculated to understand the PVE. A new quantitative index, the indium uptake index (IUI), was calculated using the RC to correct the PVE. The quantitative accuracy of the IUI in the hot sphere was confirmed. Case studies were performed to clarify the quantitative accuracy. In a case study, the relationship between the IUI and the Krenning score, which is used as a visual assessment, was evaluated for each lesion. Results: The obtained RCs showed that the energy peak at 171 keV was faster in recovering the effect of PVE than that at 245 keV. The IUI in the 17-mm-diameter hot sphere was overestimated by 4.8% and 8.3% at 171 keV and 245 keV, respectively, compared to the actual IUIs. The relationship between IUI and Krenning score was rs=0.773 (p<0.005) at sum, rs=0.739 (p<0.005) at 171 keV, and rs=0.773 (p<0.005) at 245 keV. Conclusion: We have developed a new quantification method for 111In-pentetreotide SPECT/CT using RC-based PVE correction for an individual energy peak of 171 keV. The quantitative accuracy of this method was high even for accumulations of less than 20 mm, and it showed a good relationship with the Krenning score; therefore, the clinical usefulness of IUI was demonstrated.

Determination of a reliable assessment for occupational eye lens dose in nuclear medicine.

The most recent statement published by the International Commission on Radiological Protection describes a reduction in the maximum allowable occupational eye lens dose from 150 to 20 mSv/year (averaged over 5-year periods). Exposing the eye lens to radiation is a concern for nuclear medicine staff who handle radionuclide tracers with various levels of photon energy. This study aimed to define the optimal dosimeter and means of measuring the amount of exposure to which the eye lens is exposed during a routine nuclear medicine practice. A RANDO human phantom attached to Glass Badge and Luminess Badge for body or neck, DOSIRIS and VISION for eyes, and nanoDot for body, neck, and eyes was exposed to 99m Tc, 123 I, and 18 F radionuclides. Sealed syringe sources of each radionuclide were positioned 30 cm from the abdomen of the phantom. Estimated exposure based on measurement conditions (i.e., air kerma rate constants, conversion coefficient, distance, activity, and exposure time) was compared measured dose equivalent of each dosimeter. Differences in body, neck, and eye lens dosimeters were statistically analyzed. The 10-mm dose equivalent significantly differed between the Glass Badge and Luminess Badge for the neck, but these were almost equivalent at the body. The 0.07-mm dose equivalent for the nanoDot dosimeters was greatly overestimated compared to the estimated exposure of 99m Tc and 123 I radionuclides. Measured dose equivalents of exposure significantly differed between the body and eye lens dosimeters with respect to 18 F. Although accurately measuring radiation exposure to the eye lenses of nuclear medicine staff is conventionally monitored using dosimeters worn on the chest or abdomen, eye lens dosimeters that provide a 3-mm dose equivalent near the eye would be a more reliable means of assessing radiation doses in the mixed radiation environment of nuclear medicine.

Evaluation of quantitative accuracy among different scatter corrections for quantitative bone SPECT/CT imaging.

Although scatter correction improves SPECT image contrast and thus image quality, the effects of quantitation accuracy under various conditions remain unclear. The present study aimed to empirically define the conditions for the optimal scatter correction of quantitative bone SPECT/CT images. Scatter correction was performed by applying dual and triple energy windows (DEW and TEW) with different sub-energy window widths, and effective scatter source estimation (ESSE) to CT-based scatter correction. Scattered radiation was corrected on images acquired using a triple line source (TLSP) phantom and an uniform cylinder phantom. The TLSP consisted of a line source containing 74.0 MBq of 99mTc in the middle, and a background component containing air, water or a K2HPO4 solution with a density equivalent to that of bone. The sum of all pixels in air, water and the K2HPO4 solution was measured on SPECT images. Scatter fraction (SF) and normalized mean square error (NMSE) based on counts from the air background as a reference were then calculated to assess quantitative errors due to scatter correction. The uniform cylinder phantom contained the same K2HPO4 solution and 222.0 MBq of 99mTc. The coefficient of variation (CV) was calculated from the count profile of this phantom to assess the uniformity of SPECT images across scatter correction under various conditions. Both SF and NMSE in SPECT images of phantoms containing water in the background were lower at a TEW sub-window of 3% (TEW3%), than in other scatter corrections, whereas those in K2HPO4 were lower at a DEW sub-window of 20% (DEW20%). Larger DEW and smaller TEW sub-energy windows allowed more effective correction. The CV of the uniform cylinder phantom, DEW20%, was inferior to all other tested scatter corrections. The quantitative accuracy of bone SPECT images substantially differed according to the method of scatter correction. The optimal scatter correction for quantitative bone SPECT was DEW20% (k = 1), but at the cost of slightly decreased image uniformity.

Comparison of skeletal segmentation by deep learning-based and atlas-based segmentation in prostate cancer patients.

OBJECTIVE: We aimed to compare the deep learning-based (VSBONE BSI) and atlas-based (BONENAVI) segmentation accuracy that have been developed to measure the bone scan index based on skeletal segmentation. METHODS: We retrospectively conducted bone scans for 383 patients with prostate cancer. These patients were divided into two groups: 208 patients were injected with 99mTc-hydroxymethylene diphosphonate processed by VSBONE BSI, and 175 patients were injected with 99mTc-methylene diphosphonate processed by BONENAVI. Three observers classified the skeletal segmentations as either a "Match" or "Mismatch" in the following regions: the skull, cervical vertebrae, thoracic vertebrae, lumbar vertebrae, pelvis, sacrum, humerus, rib, sternum, clavicle, scapula, and femur. Segmentation error was defined if two or more observers selected "Mismatch" in the same region. We calculated the segmentation error rate according to each administration group and evaluated the presence of hot spots suspected bone metastases in "Mismatch" regions. Multivariate logistic regression analysis was used to determine the association between segmentation error and variables like age, uptake time, total counts, extent of disease, and gamma cameras. RESULTS: The regions of "Mismatch" were more common in the long tube bones for VSBONE BSI and in the pelvis and axial skeletons for BONENAVI. Segmentation error was observed in 49 cases (23.6%) with VSBONE BSI and 58 cases (33.1%) with BONENAVI. VSBONE BSI tended that "Mismatch" regions contained hot spots suspected of bone metastases in patients with multiple bone metastases and showed that patients with higher extent of disease (odds ratio = 8.34) were associated with segmentation error in multivariate logistic regression analysis. CONCLUSIONS: VSBONE BSI has a potential to be higher segmentation accuracy compared with BONENAVI. However, the segmentation error in VSBONE BSI occurred dependent on bone metastases burden. We need to be careful when evaluating multiple bone metastases using VSBONE BSI.

Impact of patient body habitus on image quality and quantitative value in bone SPECT/CT.

OBJECTIVE: The first edition of guidelines for standardization of bone single photon emission computed tomography (SPECT) imaging was published in 2017, and the optimization and standardization are widely promoted. To the purpose, clarification of the factors related to image quality and quantitative values and their influence are required. The present study aimed to clarify and optimize the influence of patient body habitus on image quality and quantitative values in bone SPECT/CT. METHODS: National Electrical Manufacturers Association body phantom (S-size) and custom-made large body phantoms (M-size and L-size) that simulate the abdomens of Japanese patients weighing 60, 80, and 100 kg, were used. Each phantom was filled with 99mTc-solutions of 108 and 18 kBq/mL for the hot spheres and background, respectively. Dynamic SPECT acquisition was performed for 6000 s (150 s /rotation × 40 rotation). The data were divided into six projection data and reconstructed each acquisition time (150, 300, 450, 600, 750, 900 s, and single projection 6000 s). Image quality was evaluated for contrast (QH, 17 mm), background noise (NB, 17 mm), contrast-to-noise ratio (CNR), maximum standardized uptake value (SUVmax, 17 mm), and visual assessment for a 17 mm hot sphere. RESULTS: Image quality in the 300 s acquisition showed that values of QH, 17 mm, CNR, and SUVmax, 17 mm decreased (-16.7%, -11.8%, and -11.3%) for M-size and (-28.2%, -30.1%, and -21.7%) for L-size compared with S-size, respectively. No significant difference was observed in NB, 17 mm values. M-size and L-size required 1.2 and 2.3 times longer acquisition, to achieve same CNR as S-size. In visual assessment, 17 mm hot sphere could not be detected only in the L-size. When the Japanese bone SPECT guidelines criteria were applied in 600 s, the sphere could be detected between all phantoms. CONCLUSIONS: Patient body habitus significantly affects image quality and decreases the quantitative value in bone SPECT/CT. For the optimization, extend acquisition time according to the patient body habitus is effective for image quality. And for the standardization, it is important to achieve imaging conditions that meet the Japanese bone SPECT guidelines criteria to ensure adequate detectability.

Determination of optimal regularization factor in Bayesian penalized likelihood reconstruction of brain PET images using [18 F]FDG and [11 C]PiB.

PURPOSE: The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (ß) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal ß value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]PiB). METHODS: Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM + time-of-flight (TOF) under clinical conditions and BPL + TOF (ß = 20-1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The ß values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal ß values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). RESULTS: The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of ß = 20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when ß = 150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of ß values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of ß values. Visual evaluation confirmed that the optimal ß values were 200 and 450 for [18 F]FDG and [11 C]PiB, respectively. CONCLUSIONS: The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal ß values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal ß values in BPL for brain PET imaging.