Impact of New Scatter Correction Strategies on High-Resolution Research Tomograph Brain PET Studies (original) (raw)
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.
Assessment of Scatter Components in High- Resolution PET: Correction by Nonstationary
1995
This paper describes a new approach to determine individual scatter kernels and to use them for scatter correction by integral transformation of the projections. Methods: Individual scatter components are fitted on the projections of a line source by monoexponentials. The position-dependent scatter parameters of each scatter component are then used to design non-station ary scatter correction kernels for each point in the projection. These kernels are used in a convolution-subtraction method which consecutively removes object, collimator and detector scatter from projections. This method is based on a model which assumes that image degradation results exclusively from Compton interactions of annihilation photons, thus neglecting further Compton interactions of object scatters with collimator and de tector. Results: Subtraction of the object scatter component improved contrast typical of what is obtained with standard con volution-subtraction methods. The collimator scatter component is so weak that it can be safely combined with object scatter for correction. Subtraction of detector scatter from images did not improve contrast because statistical accuracy is degraded by removing counts from hot regions while cold regions (back ground) remain unchanged. Conclusion: Subtraction of object and collimator scatter improves contrast only. The slight gain in image sharpness resulting from the subtraction of detector scat ter does not justify removal of this component at the expense of sensitivity.
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.
Practical issues and limitations of brain attenuation correction on a simultaneous PET-MR scanner
EJNMMI Physics, 2020
Background Despite the advent of clinical PET-MR imaging for routine use in 2011 and the development of several methods to address the problem of attenuation correction, some challenges remain. We have identified and investigated several issues that might affect the reliability and accuracy of current attenuation correction methods when these are implemented for clinical and research studies of the brain. These are (1) the accuracy of converting CT Hounsfield units, obtained from an independently acquired CT scan, to 511 keV linear attenuation coefficients; (2) the effect of padding used in the MR head coil; (3) the presence of close-packed hair; (4) the effect of headphones. For each of these, we have examined the effect on reconstructed PET images and evaluated practical mitigating measures. Results Our major findings were (1) for both Siemens and GE PET-MR systems, CT data from either a Siemens or a GE PET-CT scanner may be used, provided the conversion to 511 keV μ-map is perfor...
Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data
NeuroImage, 2014
Exploratory (i.e., voxelwise) spatial methods are commonly used in neuroimaging to identify areas that show an effect when a region-of-interest (ROI) analysis cannot be performed because no strong a priori anatomical hypothesis exists. However, noise at a single voxel is much higher than noise in a ROI making noise management critical to successful exploratory analysis. This work explores how preprocessing choices affect the bias and variability of voxelwise kinetic modeling analysis of brain positron emission tomography (PET) data. These choices include the use of volume- or cortical surface-based smoothing, level of smoothing, use of voxelwise partial volume correction (PVC), and PVC masking threshold. PVC was implemented using the Muller-Gartner method with the masking out of voxels with low gray matter (GM) partial volume fraction. Dynamic PET scans of an antagonist serotonin-4 receptor radioligand ([(11)C]SB207145) were collected on sixteen healthy subjects using a Siemens HRRT PET scanner. Kinetic modeling was used to compute maps of non-displaceable binding potential (BPND) after preprocessing. The results showed a complicated interaction between smoothing, PVC, and masking on BPND estimates. Volume-based smoothing resulted in large bias and intersubject variance because it smears signal across tissue types. In some cases, PVC with volume smoothing paradoxically caused the estimated BPND to be less than when no PVC was used at all. When applied in the absence of PVC, cortical surface-based smoothing resulted in dramatically less bias and the least variance of the methods tested for smoothing levels 5mm and higher. When used in combination with PVC, surface-based smoothing minimized the bias without significantly increasing the variance. Surface-based smoothing resulted in 2-4 times less intersubject variance than when volume smoothing was used. This translates into more than 4 times fewer subjects needed in a group analysis to achieve similarly powered statistical tests. Surface-based smoothing has less bias and variance because it respects cortical geometry by smoothing the PET data only along the cortical ribbon and so does not contaminate the GM signal with that of white matter and cerebrospinal fluid. The use of surface-based analysis in PET should result in substantial improvements in the reliability and detectability of effects in exploratory PET analysis, with or without PVC.
NeuroImage, 2014
Aim: Combined PET/MR systems have now become available for clinical use. Given the lack of integrated standard transmission (TX) sources in these systems, attenuation and scatter correction (AC) must be performed using the available MR-images. Since bone tissue cannot easily be accounted for during MR-AC, PET quantification can be biased, in particular, in the vicinity of the skull. Here, we assess PET quantification in PET/MR imaging of patients using phantoms and patient data. Materials and methods: Nineteen patients referred to our clinic for a PET/CT exam as part of the diagnostic evaluation of suspected dementia were included in our study. The patients were injected with 200 MBq [ 18 F]FDG and imaged with PET/CT and PET/MR in random sequence within 1 h. Both, PET/CT and PET/MR were performed as single-bed acquisitions without contrast administration. PET/CT and PET/MR data were reconstructed following CT-based and MR-based AC, respectively. MR-AC was performed based on: (A) standard Dixon-Water-Fat segmentation (DWFS), (B) DWFS with co-registered and segmented CT bone values superimposed, and (C) with co-registered full CT-based attenuation image. All PET images were reconstructed using AW-OSEM, with neither resolution recovery nor time-of-flight option employed. PET/CT (D) or PET/MR (A-C) images were decay-corrected to the start time of the first examination. PET images following AC were evaluated visually and quantitatively using 10 homeomorphic regions of interest drawn on a transaxial T1w-MR image traversing the central basal ganglia. We report the relative difference (%) of the mean ROI values for (A)-(C) in reference to PET/CT (D). In a separate phantom experiment a 2 L plastic bottle was layered with approximately 12 mm of Gypsum plaster to mimic skull bone. The phantom was imaged on PET/CT only and standard MR-AC was performed by replacing hyperdense CT attenuation values corresponding to bone (plaster) with attenuation values of water. PET image reconstruction was performed with CT-AC (D) and CT-AC using the modified CT images corresponding to MR-AC using DWFS (A). Results: PET activity values in patients following MR-AC (A) showed a substantial radial dependency when compared to PET/CT. In all patients cortical PET activity was lower than the activity in the central region of the brain (10-15%). When adding bone attenuation values to standard MR-AC (B and C) the radial gradient of PET activity values was removed. Further evaluation of PET/MR activity following MR-AC (A) relative to MR-AC (C) using the full CT for attenuation correction showed an underestimation of 25% in the cortical regions and 5-10% in the central regions of the brain. Observations in patients were replicated by observations from the phantom study. Conclusion: Our phantom and patient data demonstrate a spatially varying bias of the PET activity in PET/MR images of the brain when bone tissue is not accounted for during attenuation correction. This has immediate implications for PET/MR imaging of the brain. Therefore, refinements to existing MR-AC methods or alternative strategies need to be found prior to adopting PET/MR imaging of the brain in clinical routine and research.
NeuroImage, 2008
It is imperative that users of voxel-based morphometry (VBM) be aware of its reproducibility and the factors which influence results. We assessed the reproducibility of a VBM software package (SPM5) in measuring gray matter (GM) and white matter (WM) volumes from at least two consecutive 3D T1-weighted studies in 64 subjects. Factors investigated were the inter-study interval (ISI: 2.2 h to 124 days), signal-to-noise ratio (SNR: number of image averages (NA) = 1 or 2), scanner software version and idle time. SNR was measured by direct estimation of tissue noise (SNR TN) and mean intensity in noise-only voxels (SNR NO). After the scanner software upgrade, voxel intensity increased 5-fold and WM mean SNR TN by 24% (p b 0.001). Mean WM and GM volume changes in consecutive studies were near 0% (absolute SD of 7 ml and 10 ml respectively). Studies acquired with original scanner software showed a small (1.6%) mean GM volume increase attributed to SNR TN increases in five subjects due to scanner maintenance. GM volumes increased with SNR TN across the software upgrade (up to 4.3%; p b 0.01) and NA = 2 acquisitions (up to 4.1%; p b 0.001). GM and WM volumes were independent of ISI when ISI did not encompass the software change. Scanner idle times of N6 h decreased SNR by 7% (p b 0.001). SPM5 failed to include visible peripheral GM in only 2 subjects. SNR TN increases were greater than SNR NO increases across the software upgrade. It was concluded that SNR changes significantly influence SPM5-derived GM volumes. SNR may be influenced by scanner software upgrades and hardware condition and should be routinely assessed in studies of brain volume.
Correction for partial volume effects in PET: principle and validation
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 1998
The accuracy of PET for measuring regional radiotracer concentrations in the human brain is limited by the finite resolution capability of the scanner and the resulting partial volume effects (PVEs). We designed a new algorithm to correct for PVEs by characterizing the geometric interaction between the PET system and the brain activity distribution. The partial volume correction (PVC) algorithm uses high-resolution volumetric MR images correlated with the PET volume. We used a PET simulator to calculate recovery and cross-contamination factors of identified tissue components in the brain model. These geometry-dependent transfer coefficients form a matrix representing the fraction of true activity from each distinct brain region observed in any given set of regions of interest. This matrix can be inverted to correct for PVEs, independent of the tracer concentrations in each tissue component. A sphere phantom was used to validate the simulated point-spread function of the PET scanner....
A method for attenuation and scatter correction of brain SPECT based on computed tomography images
Nuclear Medicine Communications, 2003
A method for attenuation and scatter correction of brain single photon emission computed tomography (SPECT) is described where computed tomography (CT) images of the brain are used for the calculation of attenuation maps. The method is evaluated for the substance 99m Tc hexamethylpropylene amine oxime. A transmission dependent scatter correction is utilized and is based on ray sums calculated through the attenuation map. A method based on external markers is used to align the SPECT and CT image volumes. The markers need only to be present during the SPECT acquisition since the corresponding landmarks can be found without markers on the CT images. The mismatching has been investigated for five patients who have undergone both a CT examination and a SPECT examination with markers. Twelve individuals from the staff have pointed out the landmarks on the CT images, with an average standard deviation of 3.4 mm. Reconstructions with an attenuation map shifted the corresponding 95% confidence interval have been performed to obtain an estimation of the quantitative uncertainty caused by the mismatching, and quantitative errors of up to 6.3% have been measured. At present the method is probably most useful when groups of patients are studied. (# 2003 Lippincott Williams & Wilkins)
Advances in scatter correction for 3D PET/CT
IEEE Symposium Conference Record Nuclear Science 2004., 2004
We report on several significant improvements to the implementation of image-based scatter correction for 3D PET and PET/CT. Among these advances are: a new algorithm to scale the estimated scatter sinogram to the measured data, thereby largely compensating for external scatter; the ability to handle CT image truncation during this scaling; the option to iterate the scatter calculation for improved accuracy; the use of ordered subset estimation maximization (OSEM) reconstruction for the estimated emission images from which the scatter contributions are simulated; reporting of data quality parameters such as scatter and randoms fractions, and noise equivalent count rate (NECR), for each patient bed position; and extensive quality control output. Scatter correction (2 iterations, OSEM) typically requires 15-45 sec per bed. Very good agreement between the estimated scatter and measured emission data for several typical clinical scans is reported for CPS Pico-3D and HiRez LSO PET/CT systems.
A hybrid method of attenuation correction for positron emission tomography brain studies
European Journal of Nuclear Medicine, 1994
A hybrid method for attenuation correction (HAC) in positron emission tomography (PET) brain studies is proposed. The technique requires the acquisition of two short (1 min) transmission scans immediately before or after the emission study, with the patient and the head fixation system in place and after removing the patient from the scanner with the head fixation system alone. The method combines a uniform map of attenuation coefficients for the patient's head with measured attenuation coefficients for the head fixation system to generate a hybrid attenuation map. The HAC method was calibrated on 30 PET cerebral studies for comparison with the conventional measured attenuation correction method by ROI analysis. Average differences of less than 3% were found for cortical and subcortical regions. The HAC technique is particularly suitable in a PET clinical environment, allowing a reduction of the total study time, greater comfort for patients and an increase in patient throughput.
Medical Physics, 2003
Reliable attenuation correction represents an essential component of the long chain of modules required for the reconstruction of artifact-free, quantitative brain positron emission tomography ͑PET͒ images. In this work we demonstrate the proof of principle of segmented magnetic resonance imaging ͑MRI͒-guided attenuation and scatter corrections in three-dimensional ͑3D͒ brain PET. We have developed a method for attenuation correction based on registered T1-weighted MRI, eliminating the need of an additional transmission ͑TX͒ scan. The MR images were realigned to preliminary reconstructions of PET data using an automatic algorithm and then segmented by means of a fuzzy clustering technique which identifies tissues of significantly different density and composition. The voxels belonging to different regions were classified into air, skull, brain tissue and nasal sinuses. These voxels were then assigned theoretical tissue-dependent attenuation coefficients as reported in the ICRU 44 report followed by Gaussian smoothing and addition of a good statistics bed image. The MRI-derived attenuation map was then forward projected to generate attenuation correction factors ͑ACFs͒ to be used for correcting the emission ͑EM͒ data. The method was evaluated and validated on 10 patient data where TX and MRI brain images were available. Qualitative and quantitative assessment of differences between TX-guided and segmented MRIguided 3D reconstructions were performed by visual assessment and by estimating parameters of clinical interest. The results indicated a small but noticeable improvement in image quality as a consequence of the reduction of noise propagation from TX into EM data. Considering the difficulties associated with preinjection TX-based attenuation correction and the limitations of current calculated attenuation correction, MRI-based attenuation correction in 3D brain PET would likely be the method of choice for the foreseeable future as a second best approach in a busy nuclear medicine center and could be applied to other functional brain imaging modalities such as SPECT.