Impact of New Scatter Correction Strategies on High-Resolution Research Tomograph Brain PET Studies (original) (raw)
Related papers
NeuroImage, 2003
It is recognized that scatter correction can supply more accurate absolute quantification, and that iterative reconstruction results in better noise properties and significantly reduces streak artefacts; however, it is not entirely clear whether they produce significant changes in [ 18 F]-FDG distribution of reconstructed 3D brain PET images relative to not scatter corrected images and analytic reconstruction procedures. The current study assesses the effect of model-based scatter correction using the single-scatter simulation algorithm and iterative reconstruction in 3D brain PET studies, using statistical parametric mapping (SPM) analysis. The study population consisted of 14 healthy volunteers (6 males, 8 females; age 63-80 years). PET images were reconstructed using an analytic 3DRP reprojection algorithm with (SC) and without explicit scatter correction (NSC), as well as using an iterative ordered subset-expectation maximization (OSEM) algorithm. Calculated attenuation correction was performed assuming uniform attenuation ( ϭ 0.096 cm Ϫ1 ) for brain tissues when data are precorrected for scatter. The broad-beam attenuation coefficient ( ϭ 0.06 cm Ϫ1 ) determined from phantom studies was applied to NSC images. The images were coregistered and normalized using the default [ 15 O]-H 2 O template supplied with SPM99 and an [ 18 F]-FDG template. A t statistic image for the contrast condition effect was then constructed. The contrast comparing SC to NSC images suggest that regional brain metabolic activity decreases significantly in the frontal gyri, in addition to the middle temporal and postcentral gyri. On the other hand, activity increases in the cerebellum, thalamus, insula, brainstem, temporal lobe, and the frontal cortex. No significant changes were detected when comparing images reconstructed using analytic and iterative algorithms. It is concluded that, for some cerebral areas, significant differences in [ 18 F]-FDG distribution arise when images are reconstructed with and without explicit SC. This needs to be considered when interpreting [ 18 F]-FDG 3D brain PET images after applying SC.
Journal of Nuclear Medicine, 2017
In PET, corrections for photon scatter and attenuation are essential for visual and quantitative consistency. MR attenuation correction (MRAC) is generally conducted by image segmentation and assignment of discrete attenuation coefficients, which offer limited accuracy compared with CT attenuation correction. Potential inaccuracies in MRAC may affect scatter correction, because the attenuation image (m-map) is used in single scatter simulation (SSS) to calculate the scatter estimate. We assessed the impact of MRAC to scatter correction using 2 scatter-correction techniques and 3 m-maps for MRAC. Methods: The tail-fitted SSS (TF-SSS) and a Monte Carlo-based single scatter simulation (MC-SSS) algorithm implementations on the Philips Ingenuity TF PET/MR were used with 1 CT-based and 2 MR-based m-maps. Data from 7 subjects were used in the clinical evaluation, and a phantom study using an anatomic brain phantom was conducted. Scatter-correction sinograms were evaluated for each scatter correction method and m-map. Absolute image quantification was investigated with the phantom data. Quantitative assessment of PET images was performed by volume-of-interest and ratio image analysis. Results: MRAC did not result in large differences in scatter algorithm performance, especially with TF-SSS. Scatter sinograms and scatter fractions did not reveal large differences regardless of the m-map used. TF-SSS showed slightly higher absolute quantification. The differences in volume-of-interest analysis between TF-SSS and MC-SSS were 3% at maximum in the phantom and 4% in the patient study. Both algorithms showed excellent correlation with each other with no visual differences between PET images. MC-SSS showed a slight dependency on the m-map used, with a difference of 2% on average and 4% at maximum when a m-map without bone was used. Conclusion: The effect of different MR-based m-maps on the performance of scatter correction was minimal in non-time-of-flight 18 F-FDG PET/MR brain imaging. The SSS algorithm was not affected significantly by MRAC. The performance of the MC-SSS algorithm is comparable but not superior to TF-SSS, warranting further investigations of algorithm optimization and performance with different radiotracers and time-of-flight imaging.
Scatter correction techniques in 3D PET: a Monte Carlo evaluation
IEEE Transactions on Nuclear Science, 1999
In this work, a Monte Carlo software package, PET-EGS, designed to simulate realistic PET clinical studies, was used to assess three different approaches to scatter correction in 3D PET: analytical (gaussian fitting technique), experimental (dual energy window technique) and probabilistic (Monte Carlo technique). Phantom'and clinical studies were carried out by 3D PET and simulated by PET-EGS. A clinical study (I8F-FDG brain study) was simulated assuming PET emission/transmission multiple-volume images as a voxelised source object describing the distribution of both the radioactivity and attenuation coefficients and accounting for out-of-field activity and media. The accuracy of PET-EGS in modelling the physical response of a 3D PET scanner was assessed by statistical comparison between measured and total (scatter + unscatter) simulated distributions (probability for the two distributions to be the same distribution: p > 0.95). The accuracy of the scatter models, for each scatter correction technique, was evaluated on sinograms by statistical comparison between the estimated and the simulated scatter distributions (agreement < 1 a). The accuracy of scatter correction was evaluated on sinograms by comparison between scatter corrected and simulated unscatter distributions, proving a comparable accuracy of all the considered scatter correction techniques for brainlike distributed sources.
Effect of scatter correction when comparing attenuation maps: Application to brain PET/MR
2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2014
In PET imaging, attenuation and scatter corrections are an essential requirement to accurately quantify the radionuclide uptake. In the context of PET/MR scanners, obtaining the attenuation information can be challenging. Various authors have quantified the effect of an imprecise attenuation map on the reconstructed PET image but its influence on scatter correction has usually been ignored. In this paper, we investigate the effects of imperfect attenuation maps (µmaps) on the scatter correction in a simulation setting. We focused our study on three µmaps: the reference µmap derived from a CT image, and two MR-based methods. Two scatter estimation strategies were implemented: a µmap-specific scatter estimation and an ideal scatter estimation relying only on the reference CT µmap. The scatter estimation used the Single Scatter Simulation algorithm with tail-fitting. The results show that, for FDG brain PET, regardless of the µmap used in the reconstruction, the difference on PET images between µmap-specific and ideal scatter estimations is small (less than 1%). More importantly, the relative error between attenuation correction methods does not change depending on the scatter estimation method included in the simulation and reconstruction process. This means that the effect of errors in the µmap on the PET image is dominated by the attenuation correction, while the scatter estimate is relatively unaffected. Therefore, while scatter correction improves reconstruction accuracy, it is unnecessary to include scatter in the simulation when comparing different attenuation correction methods for brain PET/MR.
The Development, Past Achievements, and Future Directions of Brain PET
Journal of Cerebral Blood Flow & Metabolism, 2012
The early developments of brain positron emission tomography (PET), including the methodological advances that have driven progress, are outlined. The considerable past achievements of brain PET have been summarized in collaboration with contributing experts in specific clinical applications including cerebrovascular disease, movement disorders, dementia, epilepsy, schizophrenia, addiction, depression and anxiety, brain tumors, drug development, and the normal healthy brain. Despite a history of improving methodology and considerable achievements, brain PET research activity is not growing and appears to have diminished. Assessments of the reasons for decline are presented and strategies proposed for reinvigorating brain PET research. Central to this is widening the access to advanced PET procedures through the introduction of lower cost cyclotron and radiochemistry technologies. The support and expertize of the existing major PET centers, and the recruitment of new biologists, bio-...
Investigation of motion induced errors in scatter correction for the HRRT brain scanner
IEEE Nuclear Science Symposuim & Medical Imaging Conference, 2010
Patient motion during PET scans introduces errors in the attenuation correction and image blurring leading to false changes in regional radioactivity concentrations. However, the potential effect that motion has on simulation-based scatter correction is not fully appreciated. Specifically for tracers with high uptake close to the edge of head (e.g. scalp and nose) as observed with [ 11 C]Verapamil, mismatches between transmission and emission data can lead to significant quantification errors and image artefacts due to over scatter correction. These errors are linked with unusually high values in the scatter scaling factors (SSF) returned during the single scatter simulation process implemented in the HRRT image reconstruction.
Limitations of dual-photopeak window scatter correction for brain imaging
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 1997
A method for performing scatter corrections that would directly use the photopeak information and would be straightforward for use in clinical practice would be attractive in SPECT imaging. The dual-photopeak window method may be such a method. It relates the scatter fraction to the ratio of the lower to the total parts of a split-photopeak window. We investigated the use of this scatter correction method on a dedicated brain camera. Calibration curves for the Ceraspect, a dedicated brain imaging camera, were obtained for four split-window combinations using point sources in air and water. Simulations of the Ceraspect calibration curves at several energy resolution values were obtained using a Monte Carlo simulation of the instrument. The calibration curves, experimental and simulated, revealed an ambiguous and unstable relationship between lower-to-total ratio and scatter fraction. The unsatisfactory calibration curves can be attributed to the limited scatter produced in a brain-si...
Scatter degrades the contrast and quantitative accuracy of positron emission tomography (PET) images, and most methods for estimating and correcting scattered coincidences in PET subtract scattered events from the measured data. Compton scattering kinematics can be used to map out the locus of possible scattering locations. These curved lines (2D) or surfaces (3D), which connect the coincidence detectors, encompass the surface (2D) or volume (3D) where the decay occurs. In the limiting case where the scattering angle approaches zero, the scattered coincidence approaches the true coincidence. Therefore, both true and scattered coincidences can be considered similarly in a generalized scatter maximum-likelihood expectation-maximization reconstruction algorithm. The proposed method was tested using list-mode data obtained from a GATE simulation of a Jaszczak-type phantom. For scatter fractions from 10% to 60%, this approach reduces noise and improves the contrast recovery coefficients by 0.5-3.0% compared with reconstructions using true coincidences and by 3.0-24.5% with conventional reconstruction methods. The results demonstrate that this algorithm is capable of producing images entirely from scattered photons, eliminates the need for scatter corrections, increases image contrast, and reduces noise. This could be used to improve diagnostic quality and/or to reduce patient dose and radiopharmaceutical cost.