Model-based scatter correction for fully 3D PET

Added Value of [18F]PSMA-1007 PET/CT and PET/MRI in Patients With Biochemically Recurrent Prostate Cancer: Impact on Detection Rates and Clinical Management

BACKGROUND

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) can change management in a large fraction of patients with biochemically recurrent prostate cancer (BCR).

PURPOSE

To investigate the added value of PET to MRI and CT for this patient group, and to explore whether the choice of the PET paired modality (PET/MRI vs. PET/CT) impacts detection rates and clinical management.

STUDY TYPE

Retrospective.

SUBJECTS

41 patients with BCR (median age [range]: 68 [55-78]).

FIELD STRENGTH/SEQUENCE

3T, including T1-weighted gradient echo (GRE), T2-weighted turbo spin echo (TSE) and dynamic contrast-enhanced GRE sequences, diffusion-weighted echo-planar imaging, and a T1-weighted TSE spine sequence. In addition to MRI, [18F]PSMA-1007 PET and low-dose CT were acquired on the same day.

ASSESSMENT

Images were reported using a five-point Likert scale by two teams each consisting of a radiologist and a nuclear medicine physician. The radiologist performed a reading using CT and MRI data and a joint reading between radiologist and nuclear medicine physician was performed using MRI, CT, and PET from either PET/MRI or PET/CT. Findings were presented to an oncologist to create intended treatment plans. Intrareader and interreader agreement analysis was performed.

STATISTICAL TESTS

McNemar test, Cohen's κ, and intraclass correlation coefficients. A P-value <0.05 was considered significant.

RESULTS

7 patients had positive findings on MRI and CT, 22 patients on joint reading with PET/CT, and 18 patients joint reading with PET/MRI. For overall positivity, interreader agreement was poor for MR and CT (κ = 0.36) and almost perfect with addition of PET (PET/CT κ = 0.85, PET/MRI κ = 0.85). The addition of PET from PET/CT and PET/MRI changed intended treatment in 20 and 18 patients, respectively. Between joint readings, intended treatment was different for eight patients.

DATA CONCLUSION

The addition of [18F]PSMA-1007 PET/MRI or PET/CT to MRI and CT may increase detection rates, could reduce interreader variability, and may change intended treatment in half of patients with BCR.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 3.

Deep learning-based PET image denoising and reconstruction: a review

This review focuses on positron emission tomography (PET) imaging algorithms and traces the evolution of PET image reconstruction methods. First, we provide an overview of conventional PET image reconstruction methods from filtered backprojection through to recent iterative PET image reconstruction algorithms, and then review deep learning methods for PET data up to the latest innovations within three main categories. The first category involves post-processing methods for PET image denoising. The second category comprises direct image reconstruction methods that learn mappings from sinograms to the reconstructed images in an end-to-end manner. The third category comprises iterative reconstruction methods that combine conventional iterative image reconstruction with neural-network enhancement. We discuss future perspectives on PET imaging and deep learning technology.

Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner

Objective.This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner.Approach.Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode and time-of-flight-based image reconstruction framework. We also introduced a unique scatter scaling technique at the detector block-level for optimal estimation of the scatter contribution in each line of response. First image evaluations were derived from phantom data spanning the entire axial FOV along with image data from a human subject with a large body mass index. Data was evaluated based on qualitative inspections, and contrast recovery, background variability, residual scatter removal from cold regions, biases and axial uniformity were quantified and compared to non-scatter-corrected images.Main results.All reconstructed images demonstrated qualitative and quantitative improvements compared to non-scatter-corrected images: contrast recovery coefficients improved by up to 17.2% and background variability was reduced by up to 34.3%, and the residual lung error was between 1.26% and 2.08%. Low biases throughout the axial FOV indicate high quantitative accuracy and axial uniformity of the corrections. Up to 99% of residual activity in cold areas in the human subject was removed, and the reliability of the method was demonstrated in challenging body regions like in the proximity of a highly attenuating knee prosthesis.Significance.The MC SC method employed was demonstrated to be accurate and robust in TB-PET. The results of this study can serve as a benchmark for optimizing the quantitative performance of future SC techniques.

Energy-based scatter estimation in clinical PET

BACKGROUND

Scatter correction (SC) is essential in PET for accurate quantitative imaging. The state-of-the-art SC method is single-scatter simulation (SSS). Although this method is usually robust and accurate, it can fail in some situations, for example when there is motion between the CT and PET scans in PET/CT. Therefore, it is of interest to consider other SC methods.

PURPOSE

In this work, an energy-based scatter estimation (EBS) method is described in detail, tested in phantoms and patients, and compared to SSS.

METHODS

This version of EBS was developed for list-mode data from Biograph Vision-600 PET/CT scanner. EBS is based on digitized 2D energy histograms in each bin of a coarsely sampled PET sinogram, either with or without time of flight (TOF). The histograms are modeled as a noisy realization of a linear combination of nine basis functions whose parameters were derived from a measurement of the 511-keV photopeak spectrum as well as Monte-Carlo simulations of the scattering process. EBS uses an iterative expectation maximization approach to determine the coefficients in the linear combination, and from this estimates the scatter. The investigation was restricted to 18 F-based PET data in which the acquired number of counts was similar to the levels seen in oncological whole-body PET/CT scans. To evaluate the performance, phantom scans were used that involved the NEMA NU2-2018 protocol, a slab phantom, an NU 2-1994 phantom, a cardiac phantom in an anthropomorphic chest phantom, and a uniformly-filled torso phantom with a bladder phantom slightly outside the axial field of view. Contrast recovery (CR) and other parameters were evaluated in images reconstructed with SSS and EBS. Furthermore, FDG PET scans of seven lung cancer patients were used in the evaluation. Standardized uptake values (SUV) based on SSS and EBS were compared in 27 lesions.

RESULTS

EBS and SSS images were visually similar in all cases except the torso + bladder phantom, where the EBS was much closer to the expected uniform image. The NU2-2018 analysis indicated a 2% scatter residual in EBS images compared to 3% with SSS, and 10% higher background variability, which is a surrogate for image noise. The cardiac phantom scan showed that CR was 98.2% with EBS and 99.6% with SSS, and that the SSS sinogram had values greater than the net-true emission sinogram, indicating a slight overcorrection in the case of SSS. In the lesion SUV comparison in patient scans, EBS correlated strongly (R2  = 0.9973) with SSS, and SUV based on EBS were systematically 0.1 SUV lower. In the case of the torso + bladder phantom portion, the SSS image of the torso + bladder phantom was 299% times hotter than expected in one area, due to scatter estimation error, compared to 16% colder with EBS.

CONCLUSIONS

In evaluating clinically relevant parameters such as SUV in focal lesions, EBS and SSS give almost the same results. In phantoms, some scatter figures of merit were slightly improved by use of EBS, though an image variability figure of merit was slightly degraded. In typical oncological whole-body PET/CT, EBS may be a suitable replacement for SSS, especially when SSS fails due to technical problems during the scan.

Advancements in Positron Emission Tomography Detectors: From Silicon Photomultiplier Technology to Artificial Intelligence Applications

This review article focuses on PET detector technology, which is the most crucial factor in determining PET image quality. The article highlights the desired properties of PET detectors, including high detection efficiency, spatial resolution, energy resolution, and timing resolution. Recent advancements in PET detectors to improve these properties are also discussed, including the use of silicon photomultiplier technology, advancements in depth-of-interaction and time-of-flight PET detectors, and the use of artificial intelligence for detector development. The article provides an overview of PET detector technology and its recent advancements, which can significantly enhance PET image quality.

3D-OSEM versus FORE + OSEM: Optimal Reconstruction Algorithm for FDG PET with a Short Acquisition Time

Objective  In this study, we investigated the optimal reconstruction algorithm in fluorodeoxyglucose (FDG) positron emission tomography (PET) with a short acquisition time. Materials and Methods  In the phantom study, six spheres filled with FDG solution (sphere size: 6.23-37 mm; radioactivity ratio of spheres to background = 8:1) and placed in a National Electrical Manufacturers Association phantom were evaluated. Image acquisition time was 15 to 180 seconds, and the obtained image data were reconstructed using each of the Fourier rebinning (FORE) + ordered subsets expectation-maximization (OSEM) and 3D-OSEM algorithms. In the clinical study, mid-abdominal images of 19 patients were evaluated using regions of interest placed on areas of low, intermediate, and high radioactivity. All obtained images were investigated visually, and quantitatively using maximum standardized uptake value (SUV) and coefficient of variation (CV). Results  In the phantom study, FORE + OSEM images with a short acquisition time had large CVs (poor image quality) but comparatively constant maximum SUVs. 3D-OSEM images showed comparatively constant CVs (good image quality) but significantly low maximum SUVs. The results of visual evaluation were well correlated with those of quantitative evaluation. Small spheres were obscured on 3D-OSEM images with short acquisition time, but image quality was not greatly deteriorated. The clinical and phantom studies yielded similar results. Conclusion  FDG PET images with a short acquisition time reconstructed by FORE + OSEM showed poorer image quality than by 3D-OSEM. However, images obtained with a short acquisition time and reconstructed with FORE + OSEM showed clearer FDG uptake and more useful than 3D-OSEM in the light of the detection of lesions.

Pelvic PET/MR attenuation correction in the image space using deep learning

Introduction

The five-class Dixon-based PET/MR attenuation correction (AC) model, which adds bone information to the four-class model by registering major bones from a bone atlas, has been shown to be error-prone. In this study, we introduce a novel method of accounting for bone in pelvic PET/MR AC by directly predicting the errors in the PET image space caused by the lack of bone in four-class Dixon-based attenuation correction.

Methods

A convolutional neural network was trained to predict the four-class AC error map relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation correction µ-map were used as input to the models. CT and PET/MR examinations for 22 patients ([18F]FDG) were used for training and validation, and 17 patients were used for testing (6 [18F]PSMA-1007 and 11 [68Ga]Ga-PSMA-11). A quantitative analysis of PSMA uptake using voxel- and lesion-based error metrics was used to assess performance.

Results

In the voxel-based analysis, the proposed model reduced the median root mean squared percentage error from 12.1% and 8.6% for the four- and five-class Dixon-based AC methods, respectively, to 6.2%. The median absolute percentage error in the maximum standardized uptake value (SUVmax) in bone lesions improved from 20.0% and 7.0% for four- and five-class Dixon-based AC methods to 3.8%.

Conclusion

The proposed method reduces the voxel-based error and SUVmax errors in bone lesions when compared to the four- and five-class Dixon-based AC models.

A list-mode multi-energy window low-count SPECT reconstruction method for isotopes with multiple emission peaks

BACKGROUND

Single-photon emission computed tomography (SPECT) provides a mechanism to perform absorbed-dose quantification tasks for [Formula: see text]-particle radiopharmaceutical therapies ([Formula: see text]-RPTs). However, quantitative SPECT for [Formula: see text]-RPT is challenging due to the low number of detected counts, the complex emission spectrum, and other image-degrading artifacts. Towards addressing these challenges, we propose a low-count quantitative SPECT reconstruction method for isotopes with multiple emission peaks.

METHODS

Given the low-count setting, it is important that the reconstruction method extracts the maximal possible information from each detected photon. Processing data over multiple energy windows and in list-mode (LM) format provide mechanisms to achieve that objective. Towards this goal, we propose a list-mode multi energy window (LM-MEW) ordered-subsets expectation-maximization-based SPECT reconstruction method that uses data from multiple energy windows in LM format and include the energy attribute of each detected photon. For computational efficiency, we developed a multi-GPU-based implementation of this method. The method was evaluated using 2-D SPECT simulation studies in a single-scatter setting conducted in the context of imaging [[Formula: see text]Ra]RaCl[Formula: see text], an FDA-approved RPT for metastatic prostate cancer.

RESULTS

The proposed method yielded improved performance on the task of estimating activity uptake within known regions of interest in comparison to approaches that use a single energy window or use binned data. The improved performance was observed in terms of both accuracy and precision and for different sizes of the region of interest.

CONCLUSIONS

Results of our studies show that the use of multiple energy windows and processing data in LM format with the proposed LM-MEW method led to improved quantification performance in low-count SPECT of isotopes with multiple emission peaks. These results motivate further development and validation of the LM-MEW method for such imaging applications, including for [Formula: see text]-RPT SPECT.

PET scatter estimation using deep learning U-Net architecture

Objective.Positron emission tomography (PET) image reconstruction needs to be corrected for scatter in order to produce quantitatively accurate images. Scatter correction is traditionally achieved by incorporating an estimated scatter sinogram into the forward model during image reconstruction. Existing scatter estimated methods compromise between accuracy and computing time. Nowadays scatter estimation is routinely performed using single scatter simulation (SSS), which does not accurately model multiple scatter and scatter from outside the field-of-view, leading to reduced qualitative and quantitative PET reconstructed image accuracy. On the other side, Monte-Carlo (MC) methods provide a high precision, but are computationally expensive and time-consuming, even with recent progress in MC acceleration.Approach.In this work we explore the potential of deep learning (DL) for accurate scatter correction in PET imaging, accounting for all scatter coincidences. We propose a network based on a U-Net convolutional neural network architecture with 5 convolutional layers. The network takes as input the emission and computed tomography (CT)-derived attenuation factor (AF) sinograms and returns the estimated scatter sinogram. The network training was performed using MC simulated PET datasets. Multiple anthropomorphic extended cardiac-torso phantoms of two different regions (lung and pelvis) were created, considering three different body sizes and different levels of statistics. In addition, two patient datasets were used to assess the performance of the method in clinical practice.Main results.Our experiments showed that the accuracy of our method, namely DL-based scatter estimation (DLSE), was independent of the anatomical region (lungs or pelvis). They also showed that the DLSE-corrected images were similar to that reconstructed from scatter-free data and more accurate than SSS-corrected images.Significance.The proposed method is able to estimate scatter sinograms from emission and attenuation data. It has shown a better accuracy than the SSS, while being faster than MC scatter estimation methods.

A dedicated breast-PET/CT scanner: Numerical observer study of lesion detection

BACKGROUND

Dedicated, breast-specific positron emission tomography (BPET)-cone-beam computed tomography (BPET/CT) systems have been developed to improve detection and diagnosis of cancer in women with indeterminate mammograms caused by radiodense breasts. The absorption of X-rays that often vexes mammography in this subset of women does not affect the detection of the high energy annihilation photons used in PET. PET imaging of the breast, however, is subject to limitations caused by their comparatively low spatial resolution (∼2 mm) and often moderate radiotracer uptake in lesions.

PURPOSE

The purpose of this investigation is to explore the PET-based lesion detection capabilities of a BPET/CT scanner developed by the Department of Radiology Instrumentation group at West Virginia University.

METHODS

The PET component of the system consists of a rotating pair of 96 × 72 arrays of 2 × 2 × 15 mm3 LYSO scintillator elements. The cone-beam-CT component utilized a pulsed X-ray source and flat panel detector operated in portrait orientation. The density maps created by the CT scanner were used to correct the BPET data for photon attenuation and Compton scattering. The nonuniform uptake of 18 F-fluorodeoxyglucose (FDG) in normal breast tissue was emulated in a specially designed phantom consisting of an acrylic cylinder filled with a mixture of acrylic beads and liquid containing FDG. FDG-avid lesions were simulated with agar spheres (3, 4, 6, 8, and 10 mm diameters) containing vary amounts of FDG to produce target-to-background ratios (TBR) of 6:1, 8:1, and 10:1. The spheres also contained X-ray contrast agent to make even the smallest ones readily visible in CT images. Positions of all the lesions were identified in the CT images. These positions were used to extract signal present and signal absent sub-images from the PET images. The sub-images were then input to software that calculated areas-under-the-curve for two numerical model observers (Laguerre-Gauss channelized Hotelling observer and non-prewhitening matched filter).

RESULTS

The results showed that the smallest detectable lesion with this system is no smaller than ∼3 mm in diameter with a TBR of 6:1. Simulated lesions with diameters of 4 mm and greater were calculated to have good to excellent likelihood of detection for all TBRs tested.

CONCLUSION

The results from this investigation identified the detectability capabilities and limitations for a dedicated breast-PET/CT scanner. Its ability to detect relatively small simulated FDG-avid breast lesions for a range of TBRs indicates its potential for clinical application. Finally, the study used methodologies that could be applied to a detectability assessment of other PET/CT scanners.

Assessment of a digital and an analog PET/CT system for accurate myocardial perfusion imaging with a flow phantom

In Myocardial Perfusion Imaging (MPI) with Positron Emission Tomography/Computed Tomography (PET/CT) systems, accurate quantification is essential. We assessed flow quantification accuracy over various injected activities using a flow phantom.

METHODS

The study was performed on the digital 4-ring Discovery MI (DMI-20) and analog Discovery 690 (D690) PET/CT systems, using 325-1257 MBq of [15O]H2O. PET performance and flow quantification accuracy were assessed in terms of count-rates, dead-time factors (DTF), scatter fractions (SF), time-activity curves (TACs), areas-under-the-curves (AUCs) and flow values.

RESULTS

On DMI-20, prompts of 12.8 Mcps, DTF of 2.06 and SF of 46.1% were measured with 1257 MBq of activity. On the D690, prompts of 6.85 Mcps, DTF of 1.57 and SF of 32.5% were measured with 1230 MBq of activity. AUC values were linear over all activities. Mean wash-in flow error was - 9% for both systems whereas wash-out flow error was - 5% and - 6% for DMI-20 and D690. With the highest activity, wash-out flow error was - 12% and - 7% for the DMI-20 and D690.

CONCLUSION

DMI-20 and D690 preserved accurate flow quantification over all injected activities, with maximum error of - 12%. In the future, flow quantification accuracy over the activities and count-rates evaluated in this study should be assessed.

Data-driven, energy-based method for estimation of scattered events in positron emission tomography

Objective. Scattered events add bias in the reconstructed positron emission tomography (PET) images. Our objective is the accurate estimation of the scatter distribution, required for an effective scatter correction. Approach. In this paper, we propose a practical energy-based (EB) scatter estimation method that uses the marked difference between the energy distribution of the non-scattered and scattered events in the presence of randoms. In contrast to previous EB methods, we model the unscattered events using data obtained from measured point sources. Main results. We demonstrate feasibility using Monte Carlo simulated as well as experimental data acquired on the long axial field-of-view (FOV) PennPET EXPLORER scanner. Simulations show that the EB scatter estimated sinograms, for all phantoms, are in excellent agreement with the ground truth scatter distribution, known from the simulated data. Using the standard NEMA image quality (IQ) phantom we find that both the EB and single scatter simulation (SSS) provide good contrast recovery values. However, the EB correction gives better lung residuals. Significance. Application of the EB method on measured data showed, that the proposed method can be successfully translated to real-world PET scanners. When applied to a 20 cm diameter ×20 cm long cylindrical phantom the EB and SSS algorithms demonstrated very similar performance. However, on a larger 35 cm × 30 cm long cylinder the EB can better account for increased multiple scattering and out-of-FOV activity, providing more uniform images with 12%–36% reduced background variability. In typical PET ring sizes, the EB estimation can be performed in a matter of a few seconds compared to the several minutes needed for SSS, leading to efficiency advantages over the SSS implementation. as well.

Validation of a computational chain from PET Monte Carlo simulations to reconstructed images

The study aimed to create a pipeline from Monte Carlo simulated projections of a Gate PET system to reconstructed images. The PET system was modelled after the GE Discovery MI (DMI) PET/CT, and the simulated projections were reconstructed with the stand-alone reconstruction software CASToR. Attenuation correction, normalisation calibration, random estimation, and scatter estimation for the simulations were computed with in-house programs. The pipeline was compared in both projection and image space with data acquired on a clinical DMI and reconstructed with GE's off-line PET reconstruction software (PET Toolbox) and CASToR. The simulated and measured data were compared for the number of prompt coincidences, scatter fraction, contrast recovery coefficient (CRC), signal-to-noise ratio (SNR), background variability, residual lung error, and image profiles. A slight discrepancy was noted in the projection space, but good agreements were generally achieved in image space between simulated and measured data. The CRC was found to be 81 % for Gate – CASToR, 84 % for GE – CASToR, and 84 % for GE - PET Toolbox for the largest sphere of the NEMA image quality (IQ) phantom, and the SNR was found to be 98 for Gate – CASToR, 91 for GE – CASToR, and 93 for GE – PET Toolbox. Profiles drawn over the spheres for the NEMA IQ phantom and the Data Spectrum (DS) phantom show a good match between measurement and simulation. The results indicate feasibility to utilise the pipeline as a tool for off-line simulation-based studies. A complete pipeline introduces possibilities to study the impact of single parameters in the whole chain from simulation to reconstructed images.

Precision dosimetry in yttrium-90 radioembolization through CT imaging of radiopaque microspheres in a rabbit liver model

PURPOSE

To perform precision dosimetry in yttrium-90 radioembolization through CT imaging of radiopaque microspheres in a rabbit liver model and to compare extracted dose metrics to those produced from conventional PET-based dosimetry.

MATERIALS AND METHODS

A CT calibration phantom was designed containing posts with nominal microsphere concentrations of 0.5 mg/mL, 5.0 mg/mL, and 25.0 mg/mL. The mean Hounsfield unit was extracted from the post volumes to generate a calibration curve to relate Hounsfield units to microsphere concentration. A nominal bolus of 40 mg of microspheres was administered to the livers of eight rabbits, followed by PET/CT imaging. A CT-based activity distribution was calculated through the application of the calibration curve to the CT liver volume. Post-treatment dosimetry was performed through the convolution of yttrium-90 dose-voxel kernels and the PET- and CT-based cumulated activity distributions. The mean dose to the liver in PET- and CT-based dose distributions was compared through linear regression, ANOVA, and Bland-Altman analysis.

RESULTS

A linear least-squares fit to the average Hounsfield unit and microsphere concentration data from the calibration phantom confirmed a strong correlation (r2 > 0.999) with a slope of 14.13 HU/mg/mL. A poor correlation was found between the mean dose derived from CT and PET (r2 = 0.374), while the ANOVA analysis revealed statistically significant differences (p < 10-12) between the MIRD-derived mean dose and the PET- and CT-derived mean dose. Bland-Altman analysis predicted an offset of 15.0 Gy between the mean dose in CT and PET. The dose within the liver was shown to be more heterogeneous in CT than in PET with an average coefficient of variation equal to 1.99 and 1.02, respectively.

CONCLUSION

The benefits of a CT-based approach to post-treatment dosimetry in yttrium-90 radioembolization include improved visualization of the dose distribution, reduced partial volume effects, a better representation of dose heterogeneity, and the mitigation of respiratory motion effects. Post-treatment CT imaging of radiopaque microspheres in yttrium-90 radioembolization provides the means to perform precision dosimetry and extract accurate dose metrics used to refine the understanding of the dose-response relationship, which could ultimately improve future patient outcomes.

Comparison of deep learning-based emission-only attenuation correction methods for positron emission tomography

PURPOSE

This study aims to compare two approaches using only emission PET data and a convolution neural network (CNN) to correct the attenuation (μ) of the annihilation photons in PET.

METHODS

One of the approaches uses a CNN to generate μ-maps from the non-attenuation-corrected (NAC) PET images (μ-CNN_NAC). In the other method, CNN is used to improve the accuracy of μ-maps generated using maximum likelihood estimation of activity and attenuation (MLAA) reconstruction (μ-CNN_MLAA). We investigated the improvement in the CNN performance by combining the two methods (μ-CNN_MLAA+NAC) and the suitability of μ-CNN_NAC for providing the scatter distribution required for MLAA reconstruction. Image data from ¹⁸F-FDG (n = 100) or ⁶⁸ Ga-DOTATOC (n = 50) PET/CT scans were used for neural network training and testing.

RESULTS

The error of the attenuation correction factors estimated using μ-CT and μ-CNN_NAC was over 7%, but that of scatter estimates was only 2.5%, indicating the validity of the scatter estimation from μ-CNN_NAC. However, CNN_NAC provided less accurate bone structures in the μ-maps, while the best results in recovering the fine bone structures were obtained by applying CNN_MLAA+NAC. Additionally, the μ-values in the lungs were overestimated by CNN_NAC. Activity images (λ) corrected for attenuation using μ-CNN_MLAA and μ-CNN_MLAA+NAC were superior to those corrected using μ-CNN_NAC, in terms of their similarity to λ-CT. However, the improvement in the similarity with λ-CT by combining the CNN_NAC and CNN_MLAA approaches was insignificant (percent error for lung cancer lesions, λ-CNN_NAC = 5.45% ± 7.88%; λ-CNN_MLAA = 1.21% ± 5.74%; λ-CNN_MLAA+NAC = 1.91% ± 4.78%; percent error for bone cancer lesions, λ-CNN_NAC = 1.37% ± 5.16%; λ-CNN_MLAA = 0.23% ± 3.81%; λ-CNN_MLAA+NAC = 0.05% ± 3.49%).

CONCLUSION

The use of CNN_NAC was feasible for scatter estimation to address the chicken-egg dilemma in MLAA reconstruction, but CNN_MLAA outperformed CNN_NAC.

[Improvement of Cold Artifacts in Body Trunk 18F-FDG PET/CT by Absolute-single scatter simulation: Validation in an Out-of-body High-accumulation Phantom]

PURPOSE

This study aimed to verify whether cold artifacts caused by the gap state between attenuation correction computed tomography (ACCT) and positron emission tomography (PET) data (so-called hot-in-air (HIA) state) in body trunk PET/computer tomography (CT) examinations can be improved by the Absolute-single scatter simulation (SSS), which is a scatter correction method in a phantom experiment using the high-accumulation syringe of out-of-body phantom.

METHOD

PET imaging profile curves in the HIA state were evaluated using a high-accumulation syringe that simulated a urinary tract pouch encapsulated with ¹⁸F-FDG solution. The hot syringe-to-background ratio (HBR) of the syringe was changed to 5, 7, and 10. Moreover, PET image quality evaluation of the HIA state was performed with a syringe placed on the top of a NEMA IEC body phantom. Six spheres (10-37 mm in diameter) were placed inside the phantom and filled with ¹⁸F-FDG solution with a sphere-to-background ratio of 4. The evaluation items of image quality were N_{10 mm}, Q_{H, 10 mm} / N_{10 mm}, and recovery coefficient (RC).

RESULT

The image quality tended to deteriorate as the HBR of the syringe increased in the relative-SSS, while the effect was small in the Absolute-SSS and the lowest at HBR 10. The RC_{10 mm} of HBR 5 was 0.33 for the Relative-SSS, which was below the criterion for the Relative-SSS, but was 0.5 for the Absolute-SSS, which met the criterion.

CONCLUSION

Absolute-SSS significantly improved cold artifacts caused by HIA states on body trunk PET/CT examinations, suggesting that it is highly useful both visually and quantitatively.

Halo artifacts of indwelling urinary catheter by inaccurate scatter correction in 18F-FDG PET/CT imaging: incidence, mechanism, and solutions

BACKGROUND

Halo artifacts from urinary catheters can occur due to inaccurate scatter correction, and the artifacts affect the tumor visibility in ¹⁸F-FDG PET/CT images. We investigated the incidence rate and the mechanisms of halo-artifact generation and explored several scatter correction techniques to prevent artifacts.

METHODS

We conducted patient and phantom studies. (1) We retrospectively reviewed the cases of patients who had undergone ¹⁸F-FDG PET/CT scans. To determine the frequency of halo-artifact generation, we used the patients' PET images with a standard scatter correction based on a tail-fitted single-scatter simulation (TF-SSS) using 4-mm voxel μ-maps (TFS 4-mm). (2) We performed phantom studies to evaluate the effects of a urine catheter and two scatter correction techniques, i.e., TF-SSS with 2-mm voxel μ-maps (TFS 2-mm) and a Monte Carlo-based single-scatter simulation (MC-SSS) using 4-mm voxel μ-maps (MCS 4-mm). The average standardized uptake values (SUVs) were measured for axial PET images. (3) Using the patients' data, we investigated whether TFS 2-mm and MCS 4-mm can eliminate the artifacts in the clinical images.

RESULTS

(1) There were 61 patients with urinary catheters; in five (8.2%), halo artifacts were observed in the TFS 4-mm PET images. (2) The phantom study clearly reproduced the halo artifacts in the TFS 4-mm PET images. The halo artifacts were generated when urine moved in the interval between the CT and PET imaging, and when the urinary catheter was placed in a circular shape. The SUVs for the TFS 4-mm and TFS-2mm PET images were underestimated at the halo-artifact regions, whereas the SUVs for the MCS 4-mm PET images were close to the true values. (3) The halo artifacts disappeared in the TFS 2-mm PET images in 4/5 patients but not 1/5 patient, whereas the halo artifacts were completely absent in the MCS 4-mm PET images in 5/5 patients.

CONCLUSIONS

These data suggest that halo artifacts are caused if the PET images do not correspond to the physical material in the μ-maps, which induces the scatter correction error. With the MC-SSS, it was possible to accurately estimate the scatter without generating halo artifacts.

A filtering approach for PET and PG predictions in a proton treatment planning system

Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved PG distributions for arbitrary tissues. The method estimates PG yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against PET monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.9 mm, with maximum standard deviation of 0.9 mm and 1.1 mm, for positron-emitters and PG shifts, respectively. Normalized mean absolute errors were within 1.2 and 5.3%. When comparing measured and predicted PET data, the same more complex case yielded an average shift of 3 mm, while all other cases were below absolute average shifts of 1.1 mm. Normalized mean absolute errors were below 7.2% for all cases. A novel solution to predict positron-emitter and PG distributions in a treatment planning system is proposed, enabling calculation times of only a few seconds to minutes for entire patient cases, which is suitable for integration in daily clinical routine.

Effect of attenuation mismatches in time of flight PET reconstruction

While the pursuit of better time resolution in positron emission tomography (PET) is rapidly evolving, little work has been performed on time of flight (TOF) image quality at high time resolution in the presence of modelling inconsistencies. This works focuses on the effect of using the wrong attenuation map in the system model, causing perturbations in the reconstructed radioactivity image. Previous work has usually considered the effects to be local to the area where there is attenuation mismatch, and has shown that the quantification errors in this area tend to reduce with improved time resolution. This publication shows however that errors in the PET image at a distance from the mismatch increase with time resolution. The errors depend on the reconstruction algorithm used. We quantify the errors in the hypothetical case of perfect time resolution for maximum likelihood reconstructions. In addition, we perform reconstructions on simulated and patient data. In particular, for respiratory-gated reconstructions from a wrong attenuation map, increased errors are observed with improved time resolutions in areas close to the lungs (e.g. from 13.3% in non-TOF to up to 20.9% at 200 ps in the left ventricle).

Scatter Correction Based on GPU-Accelerated Full Monte Carlo Simulation for Brain PET/MRI

Accurate scatter correction is essential for qualitative and quantitative PET imaging. Until now, scatter correction based on Monte Carlo simulation (MCS) has been recognized as the most accurate method of scatter correction for PET. However, the major disadvantage of MCS is its long computational time, which makes it unfeasible for clinical usage. Meanwhile, single scatter simulation (SSS) is the most widely used method for scatter correction. Nevertheless, SSS has the disadvantage of limited robustness for dynamic measurements and for the measurement of large objects. In this work, a newly developed implementation of MCS using graphics processing unit (GPU) acceleration is employed, allowing full MCS-based scatter correction in clinical 3D brain PET imaging. Starting from the generation of annihilation photons to their detection in the simulated PET scanner, all relevant physical interactions and transport phenomena of the photons were simulated on GPUs. This resulted in an expected distribution of scattered events, which was subsequently used to correct the measured emission data. The accuracy of the approach was validated with simulations using GATE (Geant4 Application for Tomography Emission), and its performance was compared to SSS. The comparison of the computation time between a GPU and a single-threaded CPU showed an acceleration factor of 776 for a voxelized brain phantom study. The speedup of the MCS implemented on the GPU represents a major step toward the application of the more accurate MCS-based scatter correction for PET imaging in clinical routine.

System evaluation of automated production and inhalation of 15O-labeled gaseous radiopharmaceuticals for the rapid 15O-oxygen PET examinations

BACKGROUND

¹⁵O-oxygen inhalation PET is unique in its ability to provide fundamental information regarding cerebral hemodynamics and energy metabolism in man. However, the use of ¹⁵O-oxygen has been limited in a clinical environment largely attributed to logistical complexity, in relation to a long study period, and the need to produce and inhale three sets of radiopharmaceuticals. Despite the recent works that enabled shortening of the PET examination period, radiopharmaceutical production has still been a limiting factor. This study was aimed to evaluate a recently developed radiosynthesis/inhalation system that automatically supplies a series of ¹⁵O-labeled gaseous radiopharmaceuticals of C¹⁵O, ¹⁵O₂, and C¹⁵O₂ at short intervals.

METHODS

The system consists of a radiosynthesizer which produces C¹⁵O, ¹⁵O₂, and C¹⁵O₂; an inhalation controller; and an inhalation/scavenging unit. All three parts are controlled by a common sequencer, enabling automated production and inhalation at intervals less than 4.5 min. The gas inhalation/scavenging unit controls to sequentially supply of qualified radiopharmaceuticals at given radioactivity for given periods at given intervals. The unit also scavenges effectively the non-inhaled radioactive gases. Performance and reproducibility are evaluated.

RESULTS

Using an ¹⁵O-dedicated cyclotron with deuteron of 3.5 MeV at 40 μA, C¹⁵O, ¹⁵O₂, and C¹⁵O₂ were sequentially produced at a constant rate of 1400, 2400, and 2000 MBq/min, respectively. Each of radiopharmaceuticals were stably inhaled at < 4.5 min intervals with negligible contamination from the previous supply. The two-hole two-layered face mask with scavenging device minimized the gaseous radioactivity surrounding subject's face, while maintaining the normocapnia during examination periods. Quantitative assessment of net administration doses could be assessed using a pair of radio-detectors at inlet and scavenging tubes, as 541 ± 149, 320 ± 103, 523 ± 137 MBq corresponding to 2-min supply of 2574 ± 255 MBq for C¹⁵O, and 1-min supply of 2220 ± 766 and 1763 ± 174 for ¹⁵O₂ and C¹⁵O₂, respectively.

CONCLUSIONS

The present system allowed for automated production and inhalation of series of ¹⁵O-labeled radiopharmaceuticals as required in the rapid ¹⁵O-Oxygen PET protocol. The production and inhalation were reproducible and improved logistical complexity, and thus the use of ¹⁵O-oxygen might have become practically applicable in clinical environments.

Validation of scatter limitation correction to eliminate scatter correction error in oxygen-15 gas-inhalation positron emission tomography images

OBJECTIVE

High levels of radioactivity inside a facemask cause scatter correction (SC) errors that appear as photopenic artifacts on quantitative oxygen-15 (O) gas-inhalation positron emission tomography (PET) images. The present study aimed to validate the ability of scatter limitation correction (SLC) to eliminate SC errors in O gas-inhalation PET images acquired from patients and a phantom.

MATERIALS AND METHODS

We analyzed the SC errors in phantom images and calculated parametric images of the cerebral blood flow (CBF), cerebral blood volume, oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen (CMRO2). Phantoms comprised a cylinder and paper with radioactivity to simulate a facemask during (O)O2 gas inhalation. Parametric images were calculated from O gas-inhalation PET images of ten participants. All PET data were reconstructed using conventional SC as model-based SC and SLC. Images acquired from the phantoms and parametric images were assessed visually and quantitatively in the presence and absence of SC error.

RESULTS

SC error was evident in images derived from the paper phantom and at the slice level of the cerebellum in CBF, OEF, and CMRO2 images. The radioactivity concentration in the cylindrical phantom with the paper phantom significantly improved with SLC. The SLC also increased the quantitative indices of CBF, OEF, and CMRO2 by 23.8, 42.2, and 44.4%, respectively.

CONCLUSION

SLC visually eliminated the SC error and increased the quantitative parameters on O gas-inhalation images derived from a phantom and from patients.

Reconstruction/segmentation of attenuation map in TOF-PET based on mixture models

Attenuation correction is known as a necessary step in positron emission tomography (PET) system to have accurate and quantitative activity images. Emission-based method is known as a promising approach for attenuation map estimation on TOF-PET scanners. The proposed method in this study imposes additional histogram-based information as a mixture model prior on the emission-based approach using maximum a posteriori (MAP) framework to improve its performance and make such a nearly segmented attenuation map. To eliminate misclassification of histogram modeling, a Median root prior is incorporated on the proposed approach to reduce the noise between neighbor voxels and encourage spatial smoothness in the reconstructed attenuation map. The joint-MAP optimization is carried out as an iterative approach wherein an alteration of the activity and attenuation updates is followed by a mixture decomposition of the attenuation map histogram. Also, the proposed method can segment attenuation map during the reconstruction. The evaluation of the proposed method on the numerical, simulation and real contexts indicate that the presented method has the potential to be used as a stand-alone method or even combined with other methods for attenuation correction on PET/MR systems.

Clinical Evaluation of 68Ga-PSMA-II and 68Ga-RM2 PET Images Reconstructed With an Improved Scatter Correction Algorithm

OBJECTIVE

Gallium-68-labeled radiopharmaceuticals pose a challenge for scatter estimation because their targeted nature can produce high contrast in these regions of the kidneys and bladder. Even small errors in the scatter estimate can result in washout artifacts. Administration of diuretics can reduce these artifacts, but they may result in adverse events. Here, we investigated the ability of algorithmic modifications to mitigate washout artifacts and eliminate the need for diuretics or other interventions.

MATERIALS AND METHODS

The model-based scatter algorithm was modified to account for PET/MRI scanner geometry and challenges of non-FDG tracers. Fifty-three clinical ⁶⁸Ga-RM2 and ⁶⁸Ga-PSMA-11 whole-body images were reconstructed using the baseline scatter algorithm. For comparison, reconstruction was also processed with modified sampling in the single-scatter estimation and with an offset in the scatter tail-scaling process. None of the patients received furosemide to attempt to decrease the accumulation of radiopharmaceuticals in the bladder. The images were scored independently by three blinded reviewers using the 5-point Likert scale.

RESULTS

The scatter algorithm improvements significantly decreased or completely eliminated the washout artifacts. When comparing the baseline and most improved algorithm, the image quality increased and image artifacts were reduced for both ⁶⁸Ga-RM2 and for ⁶⁸Ga-PSMA-11 in the kidneys and bladder regions.

CONCLUSION

Image reconstruction with the improved scatter correction algorithm mitigated washout artifacts and recovered diagnostic image quality in ⁶⁸Ga PET, indicating that the use of diuretics may be avoided.

A dedicated breast-PET/CT scanner: Evaluation of basic performance characteristics

PURPOSE

Application of advanced imaging techniques, such as PET and x ray CT, can potentially improve detection of breast cancer. Unfortunately, both modalities have challenges in the detection of some lesions. The combination of the two techniques, however, could potentially lead to an overall improvement in diagnostic breast imaging. The purpose of this investigation is to test the basic performance of a new dedicated breast-PET/CT.

METHODS

The PET component consists of a rotating pair of detectors. Its performance was evaluated using the NEMA NU4-2008 protocols. The CT component utilizes a pulsed x ray source and flat panel detector mounted on the same gantry as the PET scanner. Its performance was assessed using specialized phantoms. The radiation dose to a breast during CT imaging was explored by the measurement of free-in-air kerma and air kerma measured at the center of a 16 cm-diameter PMMA cylinder. Finally, the combined capabilities of the system were demonstrated by imaging of a micro-hot-rod phantom.

RESULTS

Overall, performance of the PET component is comparable to many pre-clinical and other dedicated breast-PET scanners. Its spatial resolution is 2.2 mm, 5 mm from the center of the scanner using images created with the single-sliced-filtered-backprojection algorithm. Peak NECR is 24.6 kcps; peak sensitivity is 1.36%; the scatter fraction is 27%. Spatial resolution of the CT scanner is 1.1 lp/mm at 10% MTF. The free-in-air kerma is 2.33 mGy, while the PMMA-air kerma is 1.24 mGy. Finally, combined imaging of a micro-hot-rod phantom illustrated the potential utility of the dual-modality images produced by the system.

CONCLUSION

The basic performance characteristics of a new dedicated breast-PET/CT scanner are good, demonstrating that its performance is similar to current dedicated PET and CT scanners. The potential value of this system is the capability to produce combined duality-modality images that could improve detection of breast disease. The next stage in development of this system is testing with more advanced phantoms and human subjects.

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Anatomical accuracy of abdominal lesion localization

Software-based image registration can improve the diagnostic value of imaging procedures and is an alternative to hybrid scanners. The aim of this study was to evaluate the anatomical accuracy of automatic rigid image registration of independently acquired datasets of positron emission tomography with 18F-deoxyglucose and abdominal magnetic resonance imaging. Patients, methods: Analyses were performed on 28 abdominal lesions from 20 patients. The PET data were obtained using a stand-alone PET camera in 14 cases and a hybrid PET/CT scanner in 9 cases. The abdominal T1- and T2-weighted MRI scans were acquired on 1.5 T MRI scanners. The mean time interval between MRI and PET was 7.3 days (0–28 days). Automatic rigid registration was carried out using a self-developed registration tool integrated into commercial available software (InSpace for Siemens Syngo). Distances between the centres of gravity of 28 manually delineated neoplastic lesions represented in PET and MRI were measured in X-, Y-, and Z-direction. The intra- (intraclass correlation 0.94) and inter- (intraclass correlation 0.86) observer repeatability were high. Results: The average distance in all MRI sequences was 5.2 ± 7.6 mm in X-direction, 4.0 ± 3.7 mm in Y-direction and 6.1 ± 5.1 mm in Z-direction. There was a significantly higher misalignment in Z-direction (p < 0.05). The misalignment was not significantly different for the registration of T1- and T2- weighted sequences (p = 0.7). Conclusion: The misalignment between FDG-PET and abdominal MRI registered using an automated rigid registration tool was comparable to data reported for software-based fusion between PET and CT. Although this imprecision may not affect diagnostic accuracy, it is not sufficient to allow for pixel-wise integration of MRI and PET information.

Plane-dependent ML scatter scaling: 3D extension of the 2D simulated single scatter (SSS) estimate

Scatter correction is typically done using a simulation of the single scatter, which is then scaled to account for multiple scatters and other possible model mismatches. This scaling factor is determined by fitting the simulated scatter sinogram to the measured sinogram, using only counts measured along LORs that do not intersect the patient body, i.e. 'scatter-tails'. Extending previous work, we propose to scale the scatter with a plane dependent factor, which is determined as an additional unknown in the maximum likelihood (ML) reconstructions, using counts in the entire sinogram rather than only the 'scatter-tails'. The ML-scaled scatter estimates are validated using a Monte-Carlo simulation of a NEMA-like phantom, a phantom scan with typical contrast ratios of a ⁶⁸Ga-PSMA scan, and 23 whole-body ¹⁸F-FDG patient scans. On average, we observe a 12.2% change in the total amount of tracer activity of the MLEM reconstructions of our whole-body patient database when the proposed ML scatter scales are used. Furthermore, reconstructions using the ML-scaled scatter estimates are found to eliminate the typical 'halo' artifacts that are often observed in the vicinity of high focal uptake regions.

Scatter Correction with Combined Single-Scatter Simulation and Monte Carlo Simulation Scaling Improved the Visual Artifacts and Quantification in 3-Dimensional Brain PET/CT Imaging with 15O-Gas Inhalation

In 3-dimensional PET/CT imaging of the brain with ¹⁵O-gas inhalation, high radioactivity in the face mask creates cold artifacts and affects the quantitative accuracy when scatter is corrected by conventional methods (e.g., single-scatter simulation [SSS] with tail-fitting scaling [TFS-SSS]). Here we examined the validity of a newly developed scatter-correction method that combines SSS with a scaling factor calculated by Monte Carlo simulation (MCS-SSS). Methods: We performed phantom experiments and patient studies. In the phantom experiments, a plastic bottle simulating a face mask was attached to a cylindric phantom simulating the brain. The cylindric phantom was filled with ¹⁸F-FDG solution (3.8-7.0 kBq/mL). The bottle was filled with nonradioactive air or various levels of ¹⁸F-FDG (0-170 kBq/mL). Images were corrected either by TFS-SSS or MCS-SSS using the CT data of the bottle filled with nonradioactive air. We compared the image activity concentration in the cylindric phantom with the true activity concentration. We also performed ¹⁵O-gas brain PET based on the steady-state method on patients with cerebrovascular disease to obtain quantitative images of cerebral blood flow and oxygen metabolism. Results: In the phantom experiments, a cold artifact was observed immediately next to the bottle on TFS-SSS images, where the image activity concentrations in the cylindric phantom were underestimated by 18%, 36%, and 70% at the bottle radioactivity levels of 2.4, 5.1, and 9.7 kBq/mL, respectively. At higher bottle radioactivity, the image activity concentrations in the cylindric phantom were greater than 98% underestimated. For the MCS-SSS, in contrast, the error was within 5% at each bottle radioactivity level, although the image generated slight high-activity artifacts around the bottle when the bottle contained significantly high radioactivity. In the patient imaging with ¹⁵O₂ and C¹⁵O₂ inhalation, cold artifacts were observed on TFS-SSS images, whereas no artifacts were observed on any of the MCS-SSS images. Conclusion: MCS-SSS accurately corrected the scatters in ¹⁵O-gas brain PET when the 3-dimensional acquisition mode was used, preventing the generation of cold artifacts, which were observed immediately next to a face mask on TFS-SSS images. The MCS-SSS method will contribute to accurate quantitative assessments.

History and future technical innovation in positron emission tomography

Instrumentation for positron emission tomography (PET) imaging has experienced tremendous improvements in performance over the past 60 years since it was first conceived as a medical imaging modality. Spatial resolution has improved by a factor of 10 and sensitivity by a factor of 40 from the early designs in the 1970s to the high-performance scanners of today. Multimodality configurations have emerged that combine PET with computed tomography (CT) and, more recently, with MR. Whole-body scans for clinical purposes can now be acquired in under 10 min on a state-of-the-art PET/CT. This paper will review the history of these technical developments over 40 years and summarize the important clinical research and healthcare applications that have been made possible by these technical advances. Some perspectives for the future of this technology will also be presented that promise to bring about new applications of this imaging modality in clinical research and healthcare.

Impact of Region-of-Interest Delineation Methods, Reconstruction Algorithms, and Intra- and Inter-Operator Variability on Internal Dosimetry Estimates Using PET

PURPOSE

Human dosimetry studies play a central role in radioligand development for positron emission tomography (PET). Drawing regions of interest (ROIs) on the PET images is used to measure the dose in each organ. In the study aspects related to ROI delineation methods were evaluated for two radioligands of different biodistribution (intestinal vs urinary).

PROCEDURES

PET images were simulated from a human voxel-based phantom. Several ROI delineation methods were tested: antero-posterior projections (AP), 3D sub-samples of the organs (S), and a 3D volume covering the whole-organ (W). Inter- and intra-operator variability ROI drawing was evaluated by using human data.

RESULTS

The effective dose estimates using S and W methods were comparable to the true values. AP methods overestimated (49 %) the dose for the radioligand with intestinal biodistribution. Moreover, the AP method showed the highest inter-operator variability: 11 ± 1 %.

CONCLUSIONS

The sub-sampled organ method showed the best balance between quantitative accuracy and inter- and intra-operator variability.

Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems

Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positron-emitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.

Validation of a simplified scatter correction method for 3D brain PET with 15O

Objective

Positron emission tomography (PET) enables quantitative measurements of various biological functions. Accuracy in data acquisition and processing schemes is a prerequisite for this. The correction of scatter is especially important when a 3D PET scanner is used. The aim of this study was to validate the use of a simplified calculation-based scatter correction method for ¹⁵O studies in the brain.

Methods

We applied two scatter correction methods to the same ¹⁵O PET data acquired from patients with cerebrovascular disease (n = 10): a hybrid dual-energy-window scatter correction (reference method), and a deconvolution scatter correction (simplified method). The PET study included three sequential scans for ¹⁵O-CO, ¹⁵O-O₂, and ¹⁵O-H₂O, from which the following quantitative parameters were calculated, cerebral blood flow, cerebral blood volume, cerebral metabolic rate of oxygen, and oxygen extraction fraction.

Results

Both scatter correction methods provided similar reconstruction images with almost identical image noise, although there were slightly greater differences in white-matter regions compared with gray matter regions. These differences were also greater for ¹⁵O-CO than for ¹⁵O-H₂O and ¹⁵O-O₂. Region of interest analysis of the quantitative parameters demonstrated that the differences were less than 10 % (except for cerebral blood volume in white-matter regions), and the agreement between the methods was excellent, with intraclass correlation coefficients above 0.95 for all the parameters.

Conclusions

The deconvolution scatter correction despite its simplified implementation provided similar results to the hybrid dual-energy-window scatter correction. We consider it suitable for application in a clinical ¹⁵O brain study using a 3D PET scanner.

Attenuation Correction for Magnetic Resonance Coils in Combined PET/MR Imaging: A Review

With the introduction of clinical PET/magnetic resonance (MR) systems, novel attenuation correction methods are needed, as there are no direct MR methods to measure the attenuation of the objects in the field of view (FOV). A unique challenge for PET/MR attenuation correction is that coils for MR data acquisition are located in the FOV of the PET camera and could induce significant quantitative errors. In this review, current methods and techniques to correct for the attenuation of a variety of coils are summarized and evaluated.

The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction

PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples.

[Usefulness of Determining Acquisition Time by True Count Rate Measurement Method for Delivery 18F-FDG PET/CT]

A stable quality of delivery 18F-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) requires suitable acquisition time, which can be obtained from an accurate true count of 18F-FDG. However, the true count is influenced by body mass index (BMI) and attenuation of 18F-FDG. In order to remove these influences, we have developed a new method (actual measurement method) to measure the actual true count rate based on sub-pubic thigh, which allows us to calculate a suitable acquisition time. In this study, we aimed to verify the acquisition count through our new method in terms of two categories: (1) the accuracy of acquisition count and (2) evaluation of clinical images using physical index. Our actual measurement method was designed to obtain suitable acquisition time through the following procedure. A true count rate of sub-pubic thigh was measured through detector of PET, and used as a standard true count rate. Finally, the obtained standard count rate was processed to acquisition time. This method was retrospectively applied to 150 patients, receiving 18F-FDG administration from 109.7 to 336.8 MBq, and whose body weight ranged from 37 to 95.4 kg. The accuracy of true count was evaluated by comparing relationships of true count, relative to BMI or to administered dose of 18F-FDG. The PET/CT images obtained by our actual measurement method were assessed using physical index. Our new method resulted in accurate true count, which was not influenced by either BMI or administered dose of 18F-FDG, as well as satisfied PET/CT images with recommended criteria of physical index in all patients.

18-Month Performance Assessment of Gemini TF 16 PET/CT System in a High-Volume Department

Acceptance testing is a set of quality control tests performed to verify various manufacturer-specified parameters before a newly installed PET/CT system can be accepted for clinical use. A new PET/CT system, Gemini TF 16, installed in our department in September 2012 has a PET component capable of time-of-flight imaging using lutetium-yttrium-oxyorthosilicate crystals and operates in 3-dimensional mode. Our aim was to evaluate the system before acceptance and observe the consistency of its performance during high-volume work for 18 mo after installation (we perform an average of 30 PET/CT scans daily).

METHODS

We performed NEMA (National Electrical Manufacturers Association) NU-2 2007 acceptance testing on the Gemini TF 16; continuously evaluated its gain calibration, timing resolution, and energy resolution during the subsequent 18 mo; and analyzed the results.

RESULTS

The system passed the acceptance testing and showed few fluctuations in energy and timing resolutions during the observation period.

CONCLUSION

The Gemini TF 16 whole-body PET/CT system performed excellently during the 18-mo study period despite the high volume of work.

Acquisition time optimization of positron emission tomography studies by use of a regression function derived from torso cross-sections and noise-equivalent counts

In this study, we aimed to optimize the positron emission tomography (PET) acquisition time for individual patients by employing a regression function derived from torso cross-sections by using computed tomography (CT) attenuation corrections and the noise-equivalent counts (NECs). We initially determined the standard image quality or the standard NEC at our institution by visually assessing the images acquired from 61 patients. We measured the NECs of the livers and the torso cross-sections of 165 patients who were evaluated with PET/CT with (18)F-2-fluoro-2-deoxy-D-glucose on the basis of our standard protocol of 120 s/bed position. The optimal acquisition time (OPT) was calculated as the product of the ratio of the standard NEC to the estimated NEC multiplied by 120 s. The estimated NEC was derived from the oval cross-section of each patient by use of the regression function. We evaluated the validity of the OPT equation in 59 additional patients. We determined 5.83 Mcounts as the standard NEC at our institution. The mean OPTs in a group of 59 patients of whom 20, 19, and 20 were underweight, normal-weight, and overweight, respectively, were 106.3 ± 18.0, 137.1 ± 4.6, and 172.1 ± 24.3 s, respectively. After optimization, the NECs for normal-weight and overweight patients increased by 14 and 43 %, respectively, compared with the NECs attained with use of the conventional acquisition time (120 s). Using the regression function based on the torso cross-sections and the NECs enabled optimizations of the PET acquisition times for individual patients.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition.We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality.With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images.Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Evaluation of scatter limitation correction: a new method of correcting photopenic artifacts caused by patient motion during whole-body PET/CT imaging

OBJECTIVE

Overcorrection of scatter caused by patient motion during whole-body PET/computed tomography (CT) imaging can induce the appearance of photopenic artifacts in the PET images. The present study aimed to quantify the accuracy of scatter limitation correction (SLC) for eliminating photopenic artifacts.

METHODS

This study analyzed photopenic artifacts in (18)F-fluorodeoxyglucose ((18)F-FDG) PET/CT images acquired from 12 patients and from a National Electrical Manufacturers Association phantom with two peripheral plastic bottles that simulated the human body and arms, respectively. The phantom comprised a sphere (diameter, 10 or 37 mm) containing fluorine-18 solutions with target-to-background ratios of 2, 4, and 8. The plastic bottles were moved 10 cm posteriorly between CT and PET acquisitions. All PET data were reconstructed using model-based scatter correction (SC), no scatter correction (NSC), and SLC, and the presence or absence of artifacts on the PET images was visually evaluated. The SC and SLC images were also semiquantitatively evaluated using standardized uptake values (SUVs).

RESULTS

Photopenic artifacts were not recognizable in any NSC and SLC image from all 12 patients in the clinical study. The SUVmax of mismatched SLC PET/CT images were almost equal to those of matched SC and SLC PET/CT images. Applying NSC and SLC substantially eliminated the photopenic artifacts on SC PET images in the phantom study. SLC improved the activity concentration of the sphere for all target-to-background ratios. The highest %errors of the 10 and 37-mm spheres were 93.3 and 58.3%, respectively, for mismatched SC, and 73.2 and 22.0%, respectively, for mismatched SLC.

CONCLUSION

Photopenic artifacts caused by SC error induced by CT and PET image misalignment were corrected using SLC, indicating that this method is useful and practical for clinical qualitative and quantitative PET/CT assessment.

Patient-dependent count-rate adaptive normalization for PET detector efficiency with delayed-window coincidence events

Quantitative PET imaging is widely used in clinical diagnosis in oncology and neuroimaging. Accurate normalization correction for the efficiency of each line-of- response is essential for accurate quantitative PET image reconstruction. In this paper, we propose a normalization calibration method by using the delayed-window coincidence events from the scanning phantom or patient. The proposed method could dramatically reduce the 'ring' artifacts caused by mismatched system count-rates between the calibration and phantom/patient datasets. Moreover, a modified algorithm for mean detector efficiency estimation is proposed, which could generate crystal efficiency maps with more uniform variance. Both phantom and real patient datasets are used for evaluation. The results show that the proposed method could lead to better uniformity in reconstructed images by removing ring artifacts, and more uniform axial variance profiles, especially around the axial edge slices of the scanner. The proposed method also has the potential benefit to simplify the normalization calibration procedure, since the calibration can be performed using the on-the-fly acquired delayed-window dataset.