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

[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.

SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans

Purpose

SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT).

Methods

The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included.

Results

The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation.

Conclusions

The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.

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.

Quantification of brain oxygen extraction and metabolism with [15O]-gas PET: A technical review in the era of PET/MRI

Oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO₂) are key cerebral physiological parameters to identify at-risk cerebrovascular patients and understand brain health and function. PET imaging with [¹⁵O]-oxygen tracers, either through continuous or bolus inhalation, provides non-invasive assessment of OEF and CMRO₂. Numerous tracer delivery, PET acquisition, and kinetic modeling approaches have been adopted to map brain oxygenation. The purpose of this technical review is to critically evaluate different methods for [¹⁵O]-gas PET and its impact on the accuracy and reproducibility of OEF and CMRO₂ measurements. We perform a meta-analysis of brain oxygenation PET studies in healthy volunteers and compare between continuous and bolus inhalation techniques. We also describe OEF metrics that have been used to detect hemodynamic impairment in cerebrovascular disease. For these patients, advanced techniques to accelerate the PET scans and potential synthesis with MRI to avoid arterial blood sampling would facilitate broader use of [¹⁵O]-oxygen PET for brain physiological assessment.

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.

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.