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

Gamma radiation detector selection for CT scanner

Three types of gamma radiation detectors associated with distributed electronics namely, NaI (Tl), HPGe and LaBr3(Ce) are compared primarily focusing on electronic noise and scattering noise. Additionally, detectors of same make, material, size and electronics are also compared. A methodology is proposed to select the most suitable detector for computed tomography (CT) among the available options. Standard deviation parameter is employed to estimate electronic noise without performing CT experiment. Kanpur theorem-1(KT-1) is used to estimate the scattering noise quantitatively after verifying its sensitivity to scattering noise. The impact of scattering noise on CT profiles is evaluated using dice similarity dice coefficient. A good resemblance between KT-1 and dice coefficient is observed. A maximum difference of 56% in scattering noise is observed when five detectors used simultaneously instead of single detector whereas a discrepancy of 85% is observed between different types of radiation detectors. As far as ease of handling, operational and capital cost is concern one has to compromise minimum 12% of accuracy in CT reconstruction if NaI (Tl) detector is used with respect to best alternative available. The proposed methodology can be applied to measurement that require minimal scattering interference data other than CT experiments. The manufacturer can add noise level of detector as a characteristic parameter in the data sheet.

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.

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.

Correction technique for cascade gammas in I-124 imaging on a fully-3D, Time-of-Flight PET Scanner

It has been shown that I-124 PET imaging can be used for accurate dose estimation in radio-immunotherapy techniques. However, I-124 is not a pure positron emitter, leading to two types of coincidence events not typically encountered: increased random coincidences due to non-annihilation cascade photons, and true coincidences between an annihilation photon and primarily a coincident 602 keV cascade gamma (true coincidence gamma-ray background). The increased random coincidences are accurately estimated by the delayed window technique. Here we evaluate the radial and time distributions of the true coincidence gamma-ray background in order to correct and accurately estimate lesion uptake for I-124 imaging in a time-of-flight (TOF) PET scanner. We performed measurements using a line source of activity placed in air and a water-filled cylinder, using F-18 and I-124 radio-isotopes. Our results show that the true coincidence gamma-ray backgrounds in I-124 have a uniform radial distribution, while the time distribution is similar to the scattered annihilation coincidences. As a result, we implemented a TOF-extended single scatter simulation algorithm with a uniform radial offset in the tail-fitting procedure for accurate correction of TOF data in I-124 imaging. Imaging results show that the contrast recovery for large spheres in a uniform activity background is similar in F-18 and I-124 imaging. There is some degradation in contrast recovery for small spheres in I-124, which is explained by the increased positron range, and reduced spatial resolution, of I-124 compared to F-18. Our results show that it is possible to perform accurate TOF based corrections for I-124 imaging.

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.

Optimization of a fully 3D single scatter simulation algorithm for 3D PET

We describe a new implementation of a single scatter simulation (SSS) algorithm for the prediction and correction of scatter in 3D PET. In this implementation, out of field of view (FoV) scatter and activity, side shields and oblique tilts are explicitly modelled. Comparison of SSS predictions with Monte Carlo simulations and experimental data from uniform, line and cold-bar phantoms showed that the code is accurate for uniform as well as asymmetric objects and can model different energy resolution crystals and low level discriminator (LLD) settings. Absolute quantitation studies show that for most applications, the code provides a better scatter estimate than the tail-fitting scatter correction method currently in use at our institution. Several parameters such as the density of scatter points, the number of scatter distribution sampling points and the axial extent of the FoV were optimized to minimize execution time, with particular emphasis on patient studies. Development and optimization were carried out in the case of GSO-based scanners, which enjoy relatively good energy resolution. SSS estimates for scanners with lower energy resolution may result in different agreement, especially because of a higher fraction of multiple scatter events. The algorithm was applied to a brain phantom as well as to clinical whole-body studies. It proved robust in the case of large patients, where the scatter fraction increases. The execution time, inclusive of interpolation, is typically under 5 min for a whole-body study (axial FoV: 81 cm) of a 100 kg patient.

PET instrumentation

PET is a nuclear medicine imaging modality and belongs to the family of emission CT, which also includes single-photon emission CT. PET measures the physiologic function inside the human body by measuring the concentration of a radioactively-labeled compound that is taken up by and accumulated in the body's organs. This article discusses the instrumentation used in PET.

Postnatal hypoxic-ischemic brain injury alters mechanisms mediating neuronal glucose transport

We examined the effect of hypoxic ischemia and hypoxia vs. normoxia on postnatal murine brain substrate transporter concentrations and function. We detected a transient increase in the neuronal brain glucose transporter isoform (GLUT-3) in response to hypoxic ischemia after 4 h of reoxygenation. This increase was associated with no change in GLUT-1 (blood-brain barrier/glial isoform), monocarboxylate transporter isoforms 1 and 2, synapsin I (neuronal marker), or Bax (proapoptotic protein) but with a modest increase in Bcl-2 (antiapoptotic mitochondrial protein) protein concentrations. At 24 h of reoxygenation, the increase in GLUT-3 disappeared but was associated with a decline in Bcl-2 protein concentrations and the Bcl2:Bax ratio, an increase in caspase-3 enzyme activity (apoptotic effector enzyme), and extensive DNA fragmentation, which persisted later in time (48 h) only in the hippocampus. Hypoxia alone in the absence of ischemia was associated with a transient but modest increase in GLUT-3 and synapsin I protein concentrations, which did not cause significant apoptosis and/or necrosis. Assessment of glucose transporter function by 2-deoxyglucose (2-DG) uptake using two distinct techniques, namely positron emission tomography (PET) and the modified Sokoloff method, revealed a discrepancy due to glucose uptake by extracranial Harderian glands that masked the accurate detection of intracranial brain glucose uptake by PET scanning. The modified Sokoloff method assessing 2-DG uptake revealed that the transient increase in GLUT-3 was critical in protecting against a decline in brain glucose uptake. We conclude that hypoxic-ischemic brain injury is associated with transient compensatory changes targeted at protecting glucose delivery to fuel cellular energy metabolism, which then may delay the processes of apoptosis and cell necrosis.

Estimation of the local statistical noise in positron emission tomography revisited: practical implementation

The purpose of this report is to implement novel modifications to overcome the limitations of an existing algorithm for estimating the local statistical noise in a positron emission tomography (PET) image without performing repeated measures. The original algorithm is based on a modification of the filtered back-projection algorithm that allows the variance to be estimated using only a single sinogram. In addition, the effects of photon absorption, random coincidences, radioactive decay, and detector nonuniformity are taken into account. However, there are some limitations when applying this method with modern scanners. In particular, it is common practice to interleave the projections in the sinogram (to increase the sampling rate along each projection) and to perform an interpolation when actually back-projecting to reconstruct the images. Both of these procedures introduce covariance among the elements of the projections, which is cumbersome and impractical to deal with using the existing technique for creating a variance image. An alternative image reconstruction scheme that is shown to be equivalent to image reconstruction using traditional filtered back-projection greatly simplifies the estimation of the variance image. The proposed methods were tested by Monte Carlo simulations and by using repeated scans of a uniform phantom filled with F-18. Results demonstrate that the proposed methods are very rigorous and stable when compared to calculations of the local variance using either repeated measures with a large number of measurements, or region-of-interest estimates of the variance, assuming homogeneous variance structure. In addition, strategies for extending the proposed technique are discussed that would permit the estimation of the variance due to measurement error of a pixel in a brain map from both single subjects and pooled group data.

Staging of regional nodes in AJCC stage I and II melanoma: 18FDG PET imaging versus sentinel node detection

PRIMARY PURPOSE

The staging of regional nodes by means of sentinel node detection has been shown to accurately detect subclinical nodal metastases from cutaneous melanoma. On the other hand, the oncological applications of 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18FDG PET) are, nowadays, firmly established. However, the sensitivity of such metabolic imaging for staging the regional nodes in primary melanoma remains debatable. We prospectively assessed the actual value of PET for detecting sentinel node metastases in 21 consecutive patients presenting with early-stage melanoma.

MATERIALS AND METHODS

Twenty-one melanoma patients scheduled for lymphatic mapping and sentinel lymphadenectomy underwent fully corrected whole-body PET using 18FDG. In all cases, the disease was initially classified as either stage I or II, from the latest version of the American Joint Committee on Cancer staging system. The sentinel node detection was systematically performed within the week following the PET scan. Serial sections of the sentinel nodes were analyzed by both conventional pathology and immunohistochemical staining. Metastatic sentinel nodes were also assessed for the size of tumor deposits and the degree of nodal involvement (focal, partial, or massive). The median follow-up time was 12 months.

RESULTS

Six of the 21 patients (28.5%) had an involved sentinel node. PET was positive in only one case with a sentinel node >1 cm. In the five other cases, the sentinel nodes missed by PET were <1 cm with focal and/or partial involvements. One patient, free of regional nodal metastases in both sentinel node detection and PET imaging, had, however, a same-basin recurrence 3 months later. In another case, PET had one false positive result. Overall, the sentinel detection of subclinical nodal metastases had a sensitivity of 86%. PET detected only 14% of sentinel node metastases.

CONCLUSIONS

Sentinel node detection remains the procedure of choice for detecting subclinical lymph node involvement from primary cutaneous melanoma. Owing to its limited spatial resolution, PET appears insufficiently sensitive to identify microscopic nodal metastases. As a practical consequence, metabolic imaging is not recommended as a first-line imaging strategy for staging regional lymph nodes in patients with stage I or II melanoma.

A hybrid scatter correction for 3D PET based on an estimation of the distribution of unscattered coincidences: implementation on the ECAT EXACT HR+

We implemented a hybrid scatter-correction method for 3D PET that combines two scatter-correction methods in a complementary way. The implemented scheme uses a method based on the discrimination of the energy of events (the estimation of trues method (ETM)) and an auxiliary method (the single scatter simulation method (SSSI) or the convolution-subtraction method (CONV)) in an attempt to increase the accuracy of the correction over a wider range of acquisitions. The ETM takes into account the scatter from outside the field-of-view (FOV), which is not estimated with the auxiliary method. On the other hand, the auxiliary method accounts for events that have scattered with small angles, which have an energy that cannot be discriminated from that of unscattered events using the ETM. The ETM uses the data acquired in an upper energy window above the photopeak (550-650 keV) to obtain a noisy estimate of the unscattered events in the standard window (350-650 keV). Our implementation uses the auxiliary method to correct the residual scatter in the upper window. After appropriate scaling, the upper window data are subtracted from the total coincidences acquired in the standard window, resulting in the final scatter estimate, after smoothing. In this work we compare the hybrid method with the corrections used by default in the 2D and 3D modes of the ECAT EXACT HR+ using phantom measurements. Generally, the contrast was better with the hybrid method, although the relative errors of quantification were similar. We conclude that hybrid techniques such as the one implemented in this work can provide an accurate, general-purpose and practical way to correct the scatter in 3D PET, taking into account the scatter from outside the FOV.