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.

Toward standardization of tau PET imaging corresponding to various tau PET tracers: a multicenter phantom study.

OBJECTIVE: Tau positron emission tomography (PET) imaging is a recently developed non-invasive tool that can detect the density and extension of tau neurofibrillary tangles. Tau PET tracers have been validated to harmonize and accelerate their development and implementation in clinical practice. Whereas standard protocols including injected dose, uptake time, and duration have been determined for tau PET tracers, reconstruction parameters have not been standardized. The present study conducted phantom experiments based on tau pathology to standardize quantitative tau PET imaging parameters and optimize reconstruction conditions of PET scanners at four Japanese sites according to the results of phantom experiments. METHODS: The activity of 4.0 and 2.0 kBq/mL for Hoffman 3D brain and cylindrical phantoms, respectively, was estimated from published studies of brain activity using [18F]flortaucipir, [18F]THK5351, and [18F]MK6240. We developed an original tau-specific volume of interest template for the brain based on pathophysiological tau distribution in the brain defined as Braak stages. We acquired brain and cylindrical phantom images using four PET scanners. Iteration numbers were determined as contrast and recover coefficients (RCs) in gray (GM) and white (WM) matter, and the magnitude of the Gaussian filter was determined from image noise. RESULTS: Contrast and RC converged at ≥ 4 iterations, the error rates of RC for GM and WM were < 15% and 1%, respectively, and noise was < 10% in Gaussian filters of 2-4 mm in images acquired using the four scanners. Optimizing the reconstruction conditions for phantom tau PET images acquired by each scanner improved contrast and image noise. CONCLUSIONS: The phantom activity was comprehensive for first- and second-generation tau PET tracers. The mid-range activity that we determined could be applied to later tau PET tracers. We propose an analytical tau-specific VOI template based on tau pathophysiological changes in patients with AD to standardize tau PET imaging. Phantom images reconstructed under the optimized conditions for tau PET imaging achieved excellent image quality and quantitative accuracy.

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.

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.

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.

Decreased imaging time of amyloid PET using [18F]florbetapir can maintain quantitative accuracy.

Shortening the amount of time required to acquire amyloid positron emission tomography (PET) brain images while maintaining the accuracy of quantitative evaluation would help to overcome motion artifacts associated with Alzheimer's disease patients. The present study aimed to validate the quantitative accuracy of [18F]florbetapir ([18F]FBP) imaging over a shorter acquisition duration. Forty participants were injected with [18F]FBP, and PET images were acquired for 50-55, 50-60, and 50-70 min after injection. Three physicians visually assessed the reprocessed [18F]FBP images using a binary scale to classify them as amyloid ß (Aß) negative or positive. A mean composite standard uptake value ratio (cSUVR) > 1.075 was defined as Aß-positive based on receiver operating characteristic curves. Inter-reader and inter-acquisition duration agreements with visual assessment were evaluated using Cohen's kappa (κ). Binary visual discrimination of 102 for the 120 [18F]FBP images, was consistent among the three readers. Sixteen, sixteen, and fourteen of the 40 [18F]FBP images acquired for 50-55, 50-60, and 50-70 min after injection, respectively, were deemed Aß-positive by visual assessment. The inter-rater agreement was high, and the inter-acquisition duration agreement was almost perfect. The cSUVR did not change significantly among the acquisition durations, and the acquisition duration did not affect the outcome of discrimination based on the cSUVR cutoff. A shorter acquisition duration changed the visual assessment outcomes. Stable quantitative values were derived from [18F]FBP images acquired within 5 min. cSUVR helped to improve the performance and confidence in the outcomes of visual assessment.