Triple energy window scatter correction technique in PET

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.

Simultaneous Imaging of Ga-DOTA-TATE and Lu-DOTA-TATE in Murine Models of Neuroblastoma

68Ga-DOTA-TATE and 177Lu-DOTA-TATE are radiolabeled somatostatin analogs used to detect or treat neuroendocrine tumors. They are administered separately for either diagnostic or therapeutic purposes but little experimental data for their biokinetics are measured simultaneously in the same biological model. By co-administering 68Ga-DOTA-TATE and 177Lu-DOTA-TATE in three laboratory mice bearing two IMR32 tumor xenografts expressing different levels of somatostatin receptors (SSTRs) on their shoulders and imaging both 68Ga and 177Lu simultaneously, we investigated the relationship between the uptake of 68Ga-DOTA-TATE and 177Lu-DOTA-TATE in organs and tumors. In addition, using the percent of injected activity (%IA) values of 68Ga-DOTA-TATE at 0 hr and 4 hr, we investigated the correlation between 68Ga-DOTA-TATE %IA and the time-integrated activity coefficients (TIACs) of 177Lu-DOTA-TATE to estimate the organ-based and tumor-based doses of 177Lu-DOTA-TATE. The results showed that the extrapolated clearance time of 68Ga-DOTA-TATE linearly correlated with the TIACs of 177Lu-DOTA-TATE in the IMR32-SSTR2 tumor, kidneys, brain, heart, liver, stomach and remainder body. The extrapolated %IA value at 0 hr of 68Ga-DOTA-TATE linearly correlated with the TIACs of 177Lu-DOTA-TATE in the IMR32 tumor and lungs. In our murine study, both kidneys and lungs were organs that showed high absorbed doses of 177Lu-DOTA-TATE.

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.

Fast Energy Dependent Scatter Correction for List-Mode PET Data

Improvements in energy resolution of modern positron emission tomography (PET) detectors have created opportunities to implement energy-based scatter correction algorithms. Here, we use the energy information of auxiliary windows to estimate the scatter component. Our method is directly implemented in an iterative reconstruction algorithm, generating a scatter-corrected image without the need for sinograms. The purpose was to implement a fast energy-based scatter correction method on list-mode PET data, when it was not possible to use an attenuation map as a practical approach for the scatter degradation. The proposed method was evaluated using Monte Carlo simulations of various digital phantoms. It accurately estimated the scatter fraction distribution, and improved the image contrast in the simulated studied cases. We conclude that the proposed scatter correction method could effectively correct the scattered events, including multiple scatters and those originated in sources outside the field of view.

Applications of artificial intelligence in nuclear medicine image generation

Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging have focused on the diagnosis, treatment monitoring, and correlation analyses with pathology or specific gene mutation. It can also be used for image generation to shorten the time of image acquisition, reduce the dose of injected tracer, and enhance image quality. This work provides an overview of the application of AI in image generation for single-photon emission computed tomography (SPECT) and positron emission tomography (PET) either without or with anatomical information [CT or magnetic resonance imaging (MRI)]. This review focused on four aspects, including imaging physics, image reconstruction, image postprocessing, and internal dosimetry. AI application in generating attenuation map, estimating scatter events, boosting image quality, and predicting internal dose map is summarized and discussed.

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.

Evaluation of the Feasibility and Quantitative Accuracy of a Generalized Scatter 2D PET Reconstruction Method

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.

Simultaneous attenuation and scatter corrections from the projections in small animal PET imaging

Attenuation and scatter corrections are important in quantitative positron emission tomography (PET) imaging even in small animals such as mice and rats. In this work we describe a simple and efficient model to correct for both scatter and attenuation in a single operation. The model aims to solve the equation M=(A+F) P for the primaries P, corrected for attenuation and scatter, based on the measured coincidences M, the matrix of compensation for attenuation A and on the scatter fractions F issued from all emitting sources and contributing to M. The scatter functions are analytically calculated using Klein-Nishina formula, the scanner geometry and the detection efficiencies. This method was applied in measured data of line sources and hot spots phantoms as well as in rat heart and tumors and compared to Monte Carlo based simulations and to the single scatter simulation model developed by Watson et al. The corrected data showed a quantitative contrast and signal to noise ratio enhancement with respect to the uncorrected data. In terms of results, our method is comparable to that of Watson et al. The Monte Carlo simulations, where the primaries and the scattered events were separately registered, confirmed the accuracy of the new approach.

Novel scatter compensation of list-mode PET data using spatial and energy dependent corrections

With the widespread use of positron emission tomography (PET) crystals with greatly improved energy resolution (e.g., 11.5% with LYSO as compared to 20% with BGO) and of list-mode acquisitions, the use of the energy of individual events in scatter correction schemes becomes feasible. We propose a novel scatter approach that incorporates the energy of individual photons in the scatter correction and reconstruction of list-mode PET data in addition to the spatial information presently used in clinical scanners. First, we rewrite the Poisson likelihood function of list-mode PET data including the energy distributions of primary and scatter coincidences and show that this expression yields an MLEM reconstruction algorithm containing both energy and spatial dependent corrections. To estimate the spatial distribution of scatter coincidences we use the single scatter simulation (SSS). Next, we derive two new formulae which allow estimation of the 2-D (coincidences) energy probability density functions (E-PDF) of primary and scatter coincidences from the 1-D (photons) E-PDFs associated with each photon. We also describe an accurate and robust object-specific method for estimating these 1-D E-PDFs based on a decomposition of the total energy spectra detected across the scanner into primary and scattered components. Finally, we show that the energy information can be used to accurately normalize the scatter sinogram to the data. We compared the performance of this novel scatter correction incorporating both the position and energy of detected coincidences to that of the traditional approach modeling only the spatial distribution of scatter coincidences in 3-D Monte Carlo simulations of a medium cylindrical phantom and a large, nonuniform NCAT phantom. Incorporating the energy information in the scatter correction decreased bias in the activity distribution estimation by ~20% and ~40% in the cold regions of the large NCAT phantom at energy resolutions 11.5% and 20% at 511 keV, respectively, compared to when using the spatial information alone.

Simultaneous attenuation and scatter corrections in small animal PET imaging

The aim of this work is to simultaneously correct for attenuation and scatter in PET by analytically assessing the distribution of the scattered photons using the emission and the transmission images, the probability of scatter interactions and the detection efficiency. Above the usual lower energy threshold of 350 keV, the attenuated photons are dominantly those which have undergone a Compton scattering. By considering that each pixel in the image is the measurement of the transmitted photons through the subject, added to the contribution from the other sources by means of their scatter at this position, a simple equation is established accounting for the primaries by simultaneously correcting the data for attenuation and scatter for all emitting sources. This new method was applied in Monte Carlo simulated and measured data with the Sherbrooke small animal PET scanner in line sources, hot spot phantoms, and in rat hearts and tumors, and was compared to the approach developed by Watson et al.

PET energy-based scatter estimation and image reconstruction with energy-dependent corrections

In this paper we propose a comprehensive energy-based scatter correction approach for positron emission tomography (PET). We take advantage of the marked difference between the energy spectra of the unscattered and scattered photons, and use the detailed energy information that comes with the list-mode data for the estimation of the scattered events distribution in the data space. Also, inside the maximum-likelihood expectation maximization (ML-EM) image reconstruction algorithm, we introduce energy-dependent factors that individualize the correction terms for each event, given its position and energy information. The central piece of our approach is the two-dimensional detector energy response model represented as a linear combination of four components, each one representing a particular state a PET event can be found in: both photons unscattered, the second scattered while the first not, the first photon scattered while the second not and both photons scattered. For a set of events collected in the vicinity of a point in the projection space, the coefficient of each component is determined by applying a statistical estimator. As a result we obtain the number of scattered events that are in the given set. The model also gives us the variation of scatter fraction with the photon pair energies for that particular position in the data space. A simulation study that demonstrates the proposed methods is presented.

[Influence of photon scattering on the quantification of relative changes in longitudinal brain PET studies with 18F-FDG]

AIM

To study the effect of photon scattering on the quantification of relative changes of 18F-FDG uptake in longitudinal brain PET studies.

MATERIALS AND METHODS

Two studies from a numerical Zubal phantom were simulated. One of these was a basal reference study and the other was an activated study showing an increase or decrease in the uptake in a region of the anterior cingulated cortex. SimSET Monte Carlo code was used to simulate PET sinograms. Primary photons, which did not undergo interactions, and scattered photons, which underwent one or more interactions, were stored in separate files to assess the effect of scattering. Reconstruction was carried out using an iterative algorithm based on ordered subsets of projections (OSEM-2D). The relative changes in uptake were calculated from images reconstructed with all the photons (primary and scattered) and from images reconstructed with only primary photons.

RESULTS

A linear relationship between the calculated and theoretical values was obtained both for the images reconstructed with all the photons and for those reconstructed with primary photons. Our findings show a relative change recovery of 79% +/- 0.4% for all photons and 91% +/- 0.5% for primary photons only.

CONCLUSIONS

Our results highlight subestimation of relative changes of 12% +/- 0.7% when scattered photons are used. Thus the importance of correcting this degradation in order to improve quantification is shown.

Scatter correction for 3D PET using beam stoppers combined with dual-energy window acquisition: a feasibility study

Fully three-dimensional (3D) positron emission tomography (PET) can achieve high sensitivity of coincidence events, but the absence of inter-slice septa inevitably leads to increased scattered events. The scattered events can represent as much as 50% of the total detected events. In this research, we proposed a scatter correction method for 3D PET based on beam stoppers and dual-energy window acquisition. The beam stoppers were placed surrounding the object to attenuate primary beams. The scatter fractions were directly estimated at those blocked lines of response and then the entire scatter fraction distribution was recovered using the dual-energy window ratio as reference. The performance was evaluated by using Monte Carlo simulations of various digital phantoms. For the Utah phantom study, the proposed method accurately estimated the scatter fraction distribution, and improved image contrast and quantification based on four different quality indices as performance measures. For the non-homogeneous Zubal phantom, the simulated results also demonstrated that the proposed method achieved a better restoration of image contrast than the dual-energy window method. We conclude that the proposed scatter correction method could effectively suppress various kinds of scattered events, including multiple scatter and scatter from outside the field of view.

Scatter modelling and compensation in emission tomography

In nuclear medicine, clinical assessment and diagnosis are generally based on qualitative assessment of the distribution pattern of radiotracers used. In addition, emission tomography (SPECT and PET) imaging methods offer the possibility of quantitative assessment of tracer concentration in vivo to quantify relevant parameters in clinical and research settings, provided accurate correction for the physical degrading factors (e.g. attenuation, scatter, partial volume effects) hampering their quantitative accuracy are applied. This review addresses the problem of Compton scattering as the dominant photon interaction phenomenon in emission tomography and discusses its impact on both the quality of reconstructed clinical images and the accuracy of quantitative analysis. After a general introduction, there is a section in which scatter modelling in uniform and non-uniform media is described in detail. This is followed by an overview of scatter compensation techniques and evaluation strategies used for the assessment of these correction methods. In the process, emphasis is placed on the clinical impact of image degradation due to Compton scattering. This, in turn, stresses the need for implementation of more accurate algorithms in software supplied by scanner manufacturers, although the choice of a general-purpose algorithm or algorithms may be difficult.

Energy-based scatter correction for 3-D PET scanners using NaI(T1) detectors

Earlier investigations with BGO positron emission tomography (PET) scanners showed that the scatter correction technique based on multiple acquisitions with different energy windows are problematic to implement because of the poor energy resolution of BGO (22%), particularly for whole-body studies. We believe that these methods are likely to work better with NaI(TI) because of the better energy resolution achievable with NaI(TI) detectors (10%). Therefore, we investigate two different choices for the energy window, a low-energy window (LEW) on the Compton spectrum at 400-450 keV, and a high-energy window (HEW) within the photopeak (lower threshold above 511 keV). The results obtained for our three-dimensional (3-D) (septa-less) whole-body scanners [axial field of view (FOV) of 12.8 cm and 25.6 cm] as well as for our 3-D brain scanner (axial FOV of 25.6 cm) show an accurate prediction of the scatter distribution for the estimation of trues method (ETM) using a HEW, leading to a significant reduction of the scatter contamination. The dual-energy window (DEW) technique using a LEW is shown to be intrinsically wrong; in particular, it fails for line source and bar phantom measurements. However, the method is able to produce good results for homogeneous activity distributions. Both methods are easy to implement, are fast, have a low noise propagation, and will be applicable to other PET scanners with good energy resolution and stability, such as hybrid NaI(TI) PET/SPECT dual-head cameras and future PET cameras with GSO or LSO scintillators.

Investigation of scattered radiation in 3D whole-body positron emission tomography using Monte Carlo simulations

The correction of scattered radiation is one of the most challenging tasks in 3D positron emission tomography (PET) and knowledge about the amount of scatter and its distribution is a prerequisite for performing an accurate correction. One concern in 3D PET in contrast to 2D PET is the scatter contribution from activity outside the field-of-view (FOV) and multiple scatter. Using Monte Carlo simulations, we examined the scatter distribution for various phantoms. The simulations were performed for a whole-body PET system (ECAT EXACT HR+, Siemens/CTI) with an axial FOV of 15.5 cm and a ring diameter of 82.7 cm. With (without) interplane septa, up to one (two) out of three detected events are scattered (for a centred point source in a water-filled cylinder that nearly fills out the patient port), whereby the relative scatter fraction varies significantly with the axial position. Our results show that for an accurate scatter correction, activity as well as scattering media outside the FOV have to be taken into account. Furthermore it could be shown that there is a considerable amount of multiple scatter which has a different spatial distribution from single scatter. This means that multiple scatter cannot be corrected by simply rescaling the single scatter component.

Pre-processing variance reducing techniques in multispectral positron emission tomography

Stochastic fluctuations and systematic errors severely restrict the potential of multispectral acquisition to improve scatter correction by energy-dependent processing in high-resolution positron emission tomography (PET). To overcome this limitation, three pre-processing approaches which reduce stochastic fluctuations and systematic errors without degrading spatial resolution were investigated: statistical variance was reduced by smoothing acquired data in energy space, systematic errors due to nonuniform detector efficiency were minimized by normalizing the data in the spatial domain and the overall variance was further reduced by selecting an optimal pre-processing sequence. Selection of the best protocol to reduce stochastic fluctuations entailed comparisons between four smoothing algorithms (prior constrained (PC) smoothing, weighted smoothing (WS), ideal low-pass filtering (ILF) and mean median (MM) smoothing) and permutations of three pre-processing procedures (smoothing, normalization and subtraction of random events). Results demonstrated that spectral smoothing by WS, ILF and MM efficiently reduces the statistical variance in both the energy and spatial domains without observable spatial resolution loss. The ILF algorithm was found to be the most convenient in terms of simplicity and efficiency. Regardless of the position of subtraction of randoms in the sequence, reduction of the systematic errors by normalization followed by spectral smoothing to suppress statistical noise produced the best results. However, subtraction of random events first in the sequence reduces computation load by half since the need to pre-process this distribution before subtraction is removed. In summary, normalizing data in the spatial domain and smoothing data in energy space are essential steps required to reduce systematic errors and statistical variance independently without degrading spatial resolution of multispectral PET data.

A method for calibrating three-dimensional positron emission tomography without scatter correction

Calibration for three-dimensional positron emission tomography (3D PET) using a uniform cylinder and cross-calibration with aliquots requires correction for scatter and attenuation. Thus the accuracy of the calibration is dependent on the scatter correction method, and on the applicability of the scatter correction for different regions of the body. A method has been developed which provides a calibration which does not require correction for scatter or attenuation, making it generally applicable and independent of the scatter correction. The method has been previously described for measurement of the absolute sensitivity of tomographic devices. This approach has been extended to give a calibration of the PET camera "in air" in units of kBq/pixel. The reconstructed images are multiplied by this factor to give accurate activity concentrations, after attenuation and scatter correction. The method has been used with a fully 3D filtered backprojection (reprojection) algorithm and iterative convolution-subtraction scatter correction on data from an ECAT 953B. Using this method 3D PET images have been calibrated to within +/-5% accuracy, but this is highly dependent on the accuracy of the scatter correction. The method described here is practical and provides a means of calibrating a 3D PET system without the need for correction for scatter or attenuation of the calibration data.

Model-based scatter correction for fully 3D PET

A method is presented that directly calculates the mean number of scattered coincidences in data acquired with fully 3D positron emission tomography (PET). This method uses a transmission scan, an emission scan, the physics of Compton scatter, and a mathematical model of the scanner in a forward calculation of the number of events for which one photon has undergone a single Compton interaction. The distribution of events for which multiple Compton interactions have occurred is modelled as a linear transformation of the single-scatter distribution. Computational efficiency is achieved by sampling at rates no higher than those required by the scatter distribution and by implementing the algorithm using look-up tables. Evaluation studies in phantoms with large scatter fractions show that the method yields images with quantitative accuracy equivalent to that of slice-collimated PET in clinically useful times.