Contrast Recovery Coefficient Research Articles

Analysis of the influence of 111In on 90Y-bremsstrahlung SPECT based on Monte Carlo simulation.

90Y-ibritumomab tiuxetan (Zevalin) which is used for the treatment of malignant lymphomas can be used for SPECT imaging based on bremsstrahlung from 90Y beta particles. However, gamma rays emitted by 111In, which is administered to evaluate the indication for the treatment, contaminate the 90Y bremsstrahlung images. Our objective is to investigate the influence of 111In on the 90Y SPECT images using Monte Carlo simulation. We used an in-house developed simulation code for the Monte Carlo simulation of electrons and photons (MCEP). Two hot spheres with diameters of 40mm were put in an elliptical phantom. Both spheres ("sphere 1" and "sphere 2") were filled with 90Y and 111In mixed solutions. The activities of 90Y in sphere 1 and sphere 2 were 241 and 394kBq/mL, respectively, and the ones of 111In were 8.14 and 13.3kBq/mL, respectively. The background activity of 90Y was 38.6kBq/mL, whereas that of 111In was 1.30kBq/mL; moreover, the acquisition time was 30min. Two energy windows were used: one is 90-190keV included the 111In photopeak; the other is 90-160keV. To evaluate the quality of the SPECT images, the contrast recovery coefficient (CRC) and the constant noise ratio (CNR) of the SPECT images were derived. For the energy window between 90 and 160keV, the 111In count was 74% of the total. In that case, the CRC values were 30.1 and 30.7% for "sphere 1" and "sphere 2", respectively, whereas the CNR values were 6.8 and 12.1, respectively. For the energy window between 90 and 190keV, the 111In count reached 85% of the total count. The CRC and CNR values were 38.6 and 40.0% and 10.6 and 19.4, respectively. Our simulation study revealed that the cross talk between 111In and 90Y in SPECT imaging is rather serious. Even for the energy window excluding the 111In photopeak, the count ratio of 90Y was less than 30% of the total. However, the influence of 111In on 90Y-SPECT imaging cannot be ignored, and the count ratio because of 111In is important to estimate the density of 90Y.

Towards tracer dose reduction in PET studies: Simulation of dose reduction by retrospective randomized undersampling of list-mode data.

Optimization of tracer dose regimes in positron emission tomography (PET) imaging is a trade-off between diagnostic image quality and radiation exposure. The challenge lies in defining minimal tracer doses that still result in sufficient diagnostic image quality. In order to find such minimal doses, it would be useful to simulate tracer dose reduction as this would enable to study the effects of tracer dose reduction on image quality in single patients without repeated injections of different amounts of tracer. The aim of our study was to introduce and validate a method for simulation of low-dose PET images enabling direct comparison of different tracer doses in single patients and under constant influencing factors. (18)F-fluoride PET data were acquired on a combined PET/magnetic resonance imaging (MRI) scanner. PET data were stored together with the temporal information of the occurrence of single events (list-mode format). A predefined proportion of PET events were then randomly deleted resulting in undersampled PET data. These data sets were subsequently reconstructed resulting in simulated low-dose PET images (retrospective undersampling of list-mode data). This approach was validated in phantom experiments by visual inspection and by comparison of PET quality metrics contrast recovery coefficient (CRC), background-variability (BV) and signal-to-noise ratio (SNR) of measured and simulated PET images for different activity concentrations. In addition, reduced-dose PET images of a clinical (18)F-FDG PET dataset were simulated using the proposed approach. (18)F-PET image quality degraded with decreasing activity concentrations with comparable visual image characteristics in measured and in corresponding simulated PET images. This result was confirmed by quantification of image quality metrics. CRC, SNR and BV showed concordant behavior with decreasing activity concentrations for measured and for corresponding simulated PET images. Simulation of dose-reduced datasets based on clinical (18)F-FDG PET data demonstrated the clinical applicability of the proposed data. Simulation of PET tracer dose reduction is possible with retrospective undersampling of list-mode data. Resulting simulated low-dose images have equivalent characteristics with PET images actually measured at lower doses and can be used to derive optimal tracer dose regimes.

Influence of slice overlap on positron emission tomography image quality

PET scans use overlapping acquisition beds to correct for reduced sensitivity at bed edges. The optimum overlap size for the General Electric (GE) Discovery 690 has not been established. This study assesses how image quality is affected by slice overlap. Efficacy of 23% overlaps (recommended by GE) and 49% overlaps (maximum possible overlap) were specifically assessed. European Association of Nuclear Medicine (EANM) guidelines for calculating minimum injected activities based on overlap size were also reviewed.A uniform flood phantom was used to assess noise (coefficient of variation, (COV)) and voxel accuracy (activity concentrations, Bq ml−1). A NEMA (National Electrical Manufacturers Association) body phantom with hot/cold spheres in a background activity was used to assess contrast recovery coefficients (CRCs) and signal to noise ratios (SNR). Different overlap sizes and sphere-to-background ratios were assessed.COVs for 49% and 23% overlaps were 9% and 13% respectively. This increased noise was difficult to visualise on the 23% overlap images. Mean voxel activity concentrations were not affected by overlap size. No clinically significant differences in CRCs were observed. However, visibility and SNR of small, low contrast spheres (⩽13 mm diameter, 2:1 sphere to background ratio) may be affected by overlap size in low count studies if they are located in the overlap area.There was minimal detectable influence on image quality in terms of noise, mean activity concentrations or mean CRCs when comparing 23% overlap with 49% overlap. Detectability of small, low contrast lesions may be affected in low count studies—however, this is a worst-case scenario. The marginal benefits of increasing overlap from 23% to 49% are likely to be offset by increased patient scan times. A 23% overlap is therefore appropriate for clinical use. An amendment to EANM guidelines for calculating injected activities is also proposed which better reflects the effect overlap size has on image noise.

Performance of 3DOSEM and MAP algorithms for reconstructing low count SPECT acquisitions

PurposeLow count single photon emission computed tomography (SPECT) is becoming more important in view of whole body SPECT and reduction of radiation dose. In this study, we investigated the performance of several 3D ordered subset expectation maximization (3DOSEM) and maximum a posteriori (MAP) algorithms for reconstructing low count SPECT images. Materials and MethodsPhantom experiments were conducted using the National Electrical Manufacturers Association (NEMA) NU2 image quality (IQ) phantom. The background compartment of the phantom was filled with varying concentrations of pertechnetate and indiumchloride, simulating various clinical imaging conditions. Images were acquired using a hybrid SPECT/CT scanner and reconstructed with 3DOSEM and MAP reconstruction algorithms implemented in Siemens Syngo MI.SPECT (Flash3D) and Hermes Hybrid Recon Oncology (Hyrid Recon 3DOSEM and MAP). Image analysis was performed by calculating the contrast recovery coefficient (CRC),percentage background variability (N%), and contrast-to-noise ratio (CNR), defined as the ratio between CRC and N%. Furthermore, image distortion is characterized by calculating the aspect ratio (AR) of ellipses fitted to the hot spheres. Additionally, the performance of these algorithms to reconstruct clinical images was investigated. ResultsImages reconstructed with 3DOSEM algorithms demonstrated superior image quality in terms of contrast and resolution recovery when compared to images reconstructed with filtered-back-projection (FBP), OSEM and 2DOSEM. However, occurrence of correlated noise patterns and image distortions significantly deteriorated the quality of 3DOSEM reconstructed images. The mean AR for the 37, 28, 22, and 17mm spheres was 1.3, 1.3, 1.6, and 1.7 respectively. The mean N% increase in high and low count Flash3D and Hybrid Recon 3DOSEM from 5.9% and 4.0% to 11.1% and 9.0%, respectively. Similarly, the mean CNR decreased in high and low count Flash3D and Hybrid Recon 3DOSEM from 8.7 and 8.8 to 3.6 and 4.2, respectively. Regularization with smoothing priors could suppress these noise patterns at the cost of reduced image contrast. The mean N% was 6.4% and 6.8% for low count QSP and MRP MAP reconstructed images. Alternatively, regularization with an anatomical Bowhser prior resulted in sharp images with high contrast, limited image distortion, and low N% of 8.3% in low count images, although some image artifacts did occur. Analysis of clinical images suggested that the same effects occur in clinical imaging. ConclusionImage quality of low count SPECT acquisitions reconstructed with modern 3DOSEM algorithms is deteriorated by the occurrence of correlated noise patterns and image distortions. The artifacts observed in the phantom experiments can also occur in clinical imaging.

Effects of point spread function-based image reconstruction on neuroreceptor binding in positron emission tomography study with [(11)C]FLB 457.

The ordered subset expectation maximization with a point spread function (OSEM-PSF) was developed to improve the spatial resolution of reconstructed positron emission tomography (PET) images and has been reported to improve the contrast of hot spots in PET studies for oncology. However, in neuroreceptor imaging, the regional radioactivity concentration changes dynamically during the scan, and the effects of the PSF may differ among various radioligands or quantification methods. In this study, we investigated the effects of the PSF on quantification in PET studies with [(11)C]FLB 457 of dopamine D2 receptors, using both phantom and human data acquired by the Siemens Biograph 16 imaging platform. In the phantom studies, we evaluated the hot contrast recovery coefficient (HCRC) for variously sized hot spheres and the linearity between the measured and true radioactivities in OSEM-PSF images. Next, in the human studies with [(11)C]FLB 457, radioactivity concentrations and binding potentials for the cerebral cortex and thalamus were compared between images reconstructed with and without PSF. In the phantom studies, the OSEM-PSF images showed a better HCRC compared to images without PSF, and they showed a good linear correlation with true radioactivity. In the human studies, the radioactivity concentration increased especially in small regions with high accumulation of [(11)C]FLB 457 when the PSF was included. However, little difference in the binding potentials was observed for the target regions between both types of reconstructed images. In conclusion, PSF-based reconstruction reduced the spill-over phenomena in small hot regions; however, it caused no increase in the binding potentials in the [(11)C]FLB 457 studies.

The edge artifact in the point-spread function-based PET reconstruction at different sphere-to-background ratios of radioactivity.

The aim of this study was to quantitatively evaluate the edge artifacts in PET images reconstructed using the point-spread function (PSF) algorithm at different sphere-to-background ratios of radioactivity (SBRs). We used a NEMA IEC body phantom consisting of six spheres with 37, 28, 22, 17, 13 and 10 mm in inner diameter. The background was filled with (18)F solution with a radioactivity concentration of 2.65 kBq/mL. We prepared three sets of phantoms with SBRs of 16, 8, 4 and 2. The PET data were acquired for 20 min using a Biograph mCT scanner. The images were reconstructed with the baseline ordered subsets expectation maximization (OSEM) algorithm, and with the OSEM + PSF correction model (PSF). For the image reconstruction, the number of iterations ranged from one to 10. The phantom PET image analyses were performed by a visual assessment of the PET images and profiles, a contrast recovery coefficient (CRC), which is the ratio of SBR in the images to the true SBR, and the percent change in the maximum count between the OSEM and PSF images (Δ % counts). In the PSF images, the spheres with a diameter of 17 mm or larger were surrounded by a dense edge in comparison with the OSEM images. In the spheres with a diameter of 22 mm or smaller, an overshoot appeared in the center of the spheres as a sharp peak in the PSF images in low SBR. These edge artifacts were clearly observed in relation to the increase of the SBR. The overestimation of the CRC was observed in 13 mm spheres in the PSF images. In the spheres with a diameter of 17 mm or smaller, the Δ % counts increased with an increasing SBR. The Δ % counts increased to 91 % in the 10-mm sphere at the SBR of 16. The edge artifacts in the PET images reconstructed using the PSF algorithm increased with an increasing SBR. In the small spheres, the edge artifact was observed as a sharp peak at the center of spheres and could result in overestimation.

스플라인 정칙자를 사용한 투과 단층촬영을 위한 벌점우도 영상재구성

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

Fast GPU-based computation of spatial multigrid multiframe LMEM for PET.

Significant efforts were invested during the last decade to accelerate PET list-mode reconstructions, notably with GPU devices. However, the computation time per event is still relatively long, and the list-mode efficiency on the GPU is well below the histogram-mode efficiency. Since list-mode data are not arranged in any regular pattern, costly accesses to the GPU global memory can hardly be optimized and geometrical symmetries cannot be used. To overcome obstacles that limit the acceleration of reconstruction from list-mode on the GPU, a multigrid and multiframe approach of an expectation-maximization algorithm was developed. The reconstruction process is started during data acquisition, and calculations are executed concurrently on the GPU and the CPU, while the system matrix is computed on-the-fly. A new convergence criterion also was introduced, which is computationally more efficient on the GPU. The implementation was tested on a Tesla C2050 GPU device for a Gemini GXL PET system geometry. The results show that the proposed algorithm (multigrid and multiframe list-mode expectation-maximization, MGMF-LMEM) converges to the same solution as the LMEM algorithm more than three times faster. The execution time of the MGMF-LMEM algorithm was 1.1 s per million of events on the Tesla C2050 hardware used, for a reconstructed space of 188 x 188 x 57 voxels of 2 x 2 x 3.15 mm3. For 17- and 22-mm simulated hot lesions, the MGMF-LMEM algorithm led on the first iteration to contrast recovery coefficients (CRC) of more than 75 % of the maximum CRC while achieving a minimum in the relative mean square error. Therefore, the MGMF-LMEM algorithm can be used as a one-pass method to perform real-time reconstructions for low-count acquisitions, as in list-mode gated studies. The computation time for one iteration and 60 millions of events was approximately 66 s.

A parallel-cone collimator for high-energy SPECT.

In SPECT using high-energy photon-emitting isotopes, such as (131)I, parallel-hole collimators with thick septa are required to limit septal penetration, at the cost of sensitivity and resolution. This study investigated a parallel-hole collimator with cone-shaped holes, which was designed to limit collimator penetration while preserving resolution and sensitivity. The objective was to demonstrate that a single-slice prototype of the parallel-cone (PC) collimator was capable of improving the image quality of high-energy SPECT. The image quality of the PC collimator was quantitatively compared with that of clinically used low-energy high-resolution (LEHR; for (99m)Tc) and high-energy general-purpose (HEGP; for (131)I and (18)F) parallel-hole collimators. First, Monte Carlo simulations of single and double point sources were performed to assess sensitivity and resolution by comparing point-spread functions (PSFs). Second, a prototype PC collimator was used in an experimental phantom study to assess and compare contrast recovery coefficients and image noise. Monte Carlo simulations showed reduced broadening of the PSF due to collimator penetration for the PC collimator as compared with the HEGP collimator (e.g., 0.9 vs. 1.4 cm in full width at half maximum for (131)I). Simulated double point sources placed 2 cm apart were separately detectable for the PC collimator, whereas this was not the case for (131)I and (18)F at distances from the collimator face of 10 cm or more for the HEGP collimator. The sensitivity, measured over the simulated profiles as the total amount of counts per decay, was found to be higher for the LEHR and HEGP collimators than for the PC collimator (e.g., 3.1 × 10(-5) vs. 2.9 × 10(-5) counts per decay for (131)I). However, at equal noise level, phantom measurements showed that contrast recovery coefficients were similar for the PC and LEHR collimators for (99m)Tc but that the PC collimator significantly improved the contrast recovery coefficients as compared with the HEGP collimator for (131)I and (18)F. High-energy SPECT imaging with a single-slice prototype of the proposed PC collimator has shown the potential for significantly improved image quality in comparison with standard parallel-hole collimators.

Improving the detection of small lesions using a state-of-the-art time-of-flight PET/CT system and small-voxel reconstructions.

A major disadvantage of (18)F-FDG PET involves poor detection of small lesions and lesions with low metabolism, caused by limited spatial resolution and relatively large image voxel size. As spatial resolution and sensitivity are better in new PET systems, it is expected that small-lesion detection could be improved using smaller voxels. The aim of this study was to test this hypothesis using a state-of-the-art time-of-flight PET/CT device. (18)F-FDG PET scans of 2 image-quality phantoms (sphere sizes, 4-37 mm) and 39 consecutive patients with lung cancer were analyzed on a time-of-flight PET/CT system. Images were iteratively reconstructed with standard 4 × 4 × 4 mm voxels and smaller 2 × 2 × 2 mm voxels. For the phantom study, we determined contrast-recovery coefficients and signal-to-noise ratios (SNRs). For the patient study, (18)F-FDG PET-positive lesions in the chest and upper abdomen with a volume less than 3.0 mL (diameter, <18 mm) were included. Lesion mean and maximum standardized uptake values (SUVmean and SUVmax, respectively) were determined in both image sets. SNRs were determined by comparing SUVmax and SUVmean with background noise levels. A subanalysis was performed for lesions less than 0.75 mL (diameter, <11 mm). For qualitative analysis of patient data, 3 experienced nuclear medicine physicians gave their preference after visual side-by-side analysis. For phantom spheres 13 mm or less, we found higher contrast-recovery coefficients and SNRs using small-voxel reconstructions. For 66 included (18)F-FDG PET-positive lesions, the average increase in SUVmean and SUVmax using the small-voxel images was 17% and 32%, respectively (P < 0.01). For lesions less than 0.75 mL (21 in total), the average increase was 21% and 44%, respectively. Moreover, averaged over all lesions, the mean and maximum SNR increased by 20% and 27%, respectively (P < 0.01). For lesions less than 0.75 mL, these values increased up to 23% and 46%, respectively. The physicians preferred the small-voxel reconstructions in 76% of cases. Supported by a phantom study, there was a visual preference toward (18)F-FDG PET images reconstructed with 2 × 2 × 2 mm voxels and a profound increase in standardized uptake value and SNR for small lesions. Hence, it is expected that small-lesion detection improves using small-voxel reconstructions.

Spatial resolution recovery utilizing multi-ray tracing and graphic processing unit in PET image reconstruction

Depth-of-interaction (DOI) poses a major challenge for a PET system to achieve uniform spatial resolution across the field-of-view, particularly for small animal and organ-dedicated PET systems. In this work, we implemented an analytical method to model system matrix for resolution recovery, which was then incorporated in PET image reconstruction on a graphical processing unit platform, due to its parallel processing capacity. The method utilizes the concepts of virtual DOI layers and multi-ray tracing to calculate the coincidence detection response function for a given line-of-response. The accuracy of the proposed method was validated for a small-bore PET insert to be used for simultaneous PET/MR breast imaging. In addition, the performance comparisons were studied among the following three cases: 1) no physical DOI and no resolution modeling; 2) two physical DOI layers and no resolution modeling; and 3) no physical DOI design but with a different number of virtual DOI layers. The image quality was quantitatively evaluated in terms of spatial resolution (full-width-half-maximum and position offset), contrast recovery coefficient and noise. The results indicate that the proposed method has the potential to be used as an alternative to other physical DOI designs and achieve comparable imaging performances, while reducing detector/system design cost and complexity.

Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate that the reconstructions from super-sampled data sets using a fine system matrix yield improved image quality compared to the reconstructions using a coarse system matrix. Super-sampling reconstructions with different count levels showed that the more spatial-resolution improvement can be obtained with higher count at a larger iteration number. The authors developed a super-sampling reconstruction framework that can reconstruct super-resolution images using the super-sampling data sets simultaneously with known acquisition motion. The super-sampling PET acquisition using the proposed algorithms provides an effective and economic way to improve image quality for PET imaging, which has an important implication in preclinical and clinical region-of-interest PET imaging applications.

TU‐A‐18A‐01: Basic Principles of PET/CT, Calibration Methods and Contrast Recovery Across Multiple Cameras

This continuing education session will discuss the physical principles of PET/CT imaging and characterization of contrast recovery using accreditation phantoms.A detailed overview will be given on the physical principles of PET including positron decay physics, 2D and 3D data acquisition, time‐of‐flight, scatter correction, CT attenuation correction, and image reconstruction. Instrument quality control and calibration procedures will be discussed. Technical challenges, common image artifacts and strategies to mitigate these issues will also be discussed.Data will be presented on acquisition techniques and reconstruction parameters affecting contrast recovery. The discussion will emphasize the minimization of reconstruction differences in quantification metrics such as SUV and contrast recovery coefficients for the NEMA and ACR clinical trial phantoms. Data from new and older generation scanners will be shown including comparison of contrast recovery measurements to their analytical solutions.The goal of this session is to update attendees on the quality control and calibration of PET/CT scanners, on methods to establish a common calibration for PET/CT scanners to control for instrument variance across multiple sites.Learning Objectives: Review the physical principles of PET/CT, quality control and calibration Gain further understanding on how to apply techniques for improving quantitative agreement across multiple cameras Describe the differences between measured and expected contrast recovery for the NEMA and ACR PET phantoms

Cold wall effect eliminating method to determine the contrast recovery coefficient for small animal PET scanners using the NEMA NU-4 image quality phantom

The contrast recovery coefficients (CRC) were evaluated for five different small animal PET scanners: GE Explore Vista, Genisys4, MiniPET-2, nanoScan PC and Siemens Inveon. The NEMA NU-4 2008 performance test with the suggested image quality phantom (NU4IQ) does not allow the determination of the CRC values for the hot regions in the phantom. This drawback of NU4IQ phantom motivated us to develop a new method for this purpose. The method includes special acquisition and reconstruction protocols using the original phantom, and results in an artificially merged image enabling the evaluation of CRC values. An advantageous feature of this method is that it stops the cold wall effect from distorting the CRC calculation. Our suggested protocol results in a set of CRC values contributing to the characterization of small animal PET scanners. GATE simulations were also performed to validate the new method and verify the evaluated CRC values. We also demonstrated that the numerical values of this parameter depend on the actual object contrast of the hot region(s) and this mainly comes from the spillover effect. This effect was also studied while analysing the background activity level around the hot rods. We revealed that the calculated background mean values depended on the target contrast in a scanner specific manner. Performing the artificially merged imaging procedure and additional simulations using the micro hollow sphere (MHS) phantom geometry, we also proved that the inactive wall around the hot spheres can have a remarkable impact on the calculated CRC. In conclusion, we have shown that the proposed artificial merging procedure and the commonly used NU4IQ phantom prescribed by the NEMA NU-4 can easily deliver reliable CRC data otherwise unavailable for the NU4IQ phantom in the conventional protocol or the MHS phantom.

Event‐by‐event respiratory motion correction for PET with 3D internal‐1D external motion correlation

Respiratory motion during PET∕CT imaging can cause substantial image blurring and underestimation of tracer concentration for both static and dynamic studies. In this study, the authors developed an event-by-event respiratory motion correction method that used three-dimensional internal-one-dimensional external motion correlation (INTEX3D) in listmode reconstruction. The authors aim to fully correct for organ/tumor-specific rigid motion caused by respiration using all detected events to eliminate both intraframe and interframe motion, and investigate the quantitative improvement in static and dynamic imaging. The positional translation of an internal organ or tumor during respiration was first determined from the reconstructions of multiple phase-gated images. A level set (active contour) method was used to segment the targeted internal organs/tumors whose centroids were determined. The mean displacement of the external respiratory signal acquired by the Anzai system that corresponded to each phase-gated frame was determined. Three linear correlations between the 1D Anzai mean displacements and the 3D centroids of the internal organ/tumor were established. The 3D internal motion signal with high temporal resolution was then generated by applying each of the three correlation functions to the entire Anzai trace (40 Hz) to guide event-by-event motion correction in listmode reconstruction. The reference location was determined as the location where CT images were acquired to facilitate phase-matched attenuation correction and anatomical-based postfiltering. The proposed method was evaluated with a NEMA phantom driven by a QUASAR respiratory motion platform, and human studies with two tracers: pancreatic beta cell tracer [(18)F]FP(+)DTBZ and tumor hypoxia tracer [(18)F]fluoromisonidazole (FMISO). An anatomical-based postreconstruction filter was applied to the motion-corrected images to reduce noise while preserving quantitative accuracy and organ boundaries in the patient studies. The INTEX3D method yielded an increase of 5%-9% and 32%-40% in contrast recovery coefficient on the hot spheres in the NEMA phantom, compared to the reconstructions with only 1D motion correction (INTEX1D) and no motion correction, respectively. The proposed method also increased the mean activities of the pancreas and kidney by 9.3% and 11.2%, respectively, across three subjects in the FPDTBZ studies, and the average lesion-to-blood ratio by 20% across three lesions in the FMISO study, compared to the reconstructions without motion correction. In addition, the proposed method reduced intragate motion as compared to phase-gated images. The application of the anatomical-based postreconstruction filter further reduced noise in the background by >50% compared to reconstructions without postfiltering, while preserving quantitative accuracy and organ boundaries. Finally, the measurements of the time-activity curves from a subject with FPDTBZ showed that INTEX3D yielded 18% and 11% maximum increases in tracer concentration in the pancreas and kidney cortex, respectively. These results suggest that the proposed method can effectively compensate for both intragate and intergate respiratory motion while preserving all the counts, and is applicable to dynamic studies.

Quantitative Monte Carlo‐based holmium‐166 SPECT reconstruction

Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ((166)Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative (166)Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum. A fast Monte Carlo (MC) simulator was developed for simulation of (166)Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full (166)Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A(est)) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six (166)Ho RE patients. At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥ 17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96-106.21 ml were improved from 32%-63% (SPECT-DSW) and 50%-80% (SPECT-ppMC+DSW) to 76%-103% (SPECT-fMC). Furthermore, SPECT-fMC recovered whole-body activities were most accurate (A(est) = 1.06 × A - 5.90 MBq, R(2) = 0.97) and SPECT-fMC tumor absorbed doses were significantly higher than with SPECT-DSW (p = 0.031) and SPECT-ppMC+DSW (p = 0.031). The quantitative accuracy of (166)Ho SPECT is improved by Monte Carlo-based modeling of the image degrading factors. Consequently, the proposed reconstruction method enables accurate estimation of the radiation absorbed dose in clinical practice.

Design Study of a Whole-Body PET Scanner With Improved Spatial and Timing Resolution

Current state-of-art whole-body PET scanners achieve a system spatial resolution of 4-5 mm with limited sensitivity. Since the reconstructed spatial resolution and image quality are limited by the count statistics, there has not been a significant push for developing higher resolution whole-body PET scanners. Our goal in this study is to investigate the impact of improved spatial resolution together with time-of-flight (TOF) capability on lesion uptake estimation and lesion detectability, two important tasks in whole-body oncologic studies. The broader goal of this project is the development of a new state-of-art TOF PET scanner operating within an MRI while pushing the technology in PET system design. We performed Monte Carlo simulations to test the effects of crystal size (4 mm and 2.6 mm wide crystals), TOF timing resolution (300ps and 600ps), and 2-level depth-of-interaction (DOI) capability. Spatial resolution was calculated by simulating point sources in air at multiple positions. Results show that smaller crystals produced improved resolution, while degradation of resolution due to parallax error could be reduced with a 2-level DOI detector. Lesion phantoms were simulated to measure the contrast recovery coefficient (CRC) and area under the LROC curve (ALROC) for 0.5 cm diameter lesions with 6:1 activity uptake relative to the background. Smaller crystals produce higher CRC, leading to increased ALROC values or a reduction in scan time. Improved timing resolution provides faster CRC convergence and once again leads to an increase in ALROC value or reduced scan time. Based on our choice of timing resolution and crystal size, improved timing resolution (300ps) with larger crystals (4 mm wide) has similar ALROC as smaller crystals (2.6 mm wide) with 600ps timing resolution. A 2-level DOI measurement provides some CRC and ALROC improvement for lesions further away from the center, leading to a more uniform performance within the imaging field-of-view (FOV). Given a choice between having either an improved spatial resolution, improved timing resolution, or DOI capability, improved spatial or timing resolution provide an overall higher ALROC relative to a 2-level DOI detector.

Design Optimization of a Time-Of-Flight, Breast PET Scanner

A dedicated breast positron emission tomography (PET) scanner with limited angle geometry can provide flexibility in detector placement around the patient as well as the ability to combine it with other imaging modalities. A primary challenge of a stationary limited angle scanner is the reduced image quality due to artifacts present in the reconstructed image leading to a loss in quantitative information. Previously it has been shown that using time-of-flight (TOF) information in image reconstruction can help reduce these image artifacts arising due to missing angular projections. Our goal in this work is to optimize the TOF, breast scanner design by performing studies for estimating image uniformity and lesion activity uptake as a function of system timing resolution, scanner angular coverage and shape. Our results show that (i) 1.5 × 1.5 × 15 mm3 lutetium oxy-orthosilicate (LSO) crystals provide a high spatial resolution and system sensitivity relative to clinical scanners, (ii) 2/3 angular coverage scanner design with TOF timing resolution less than 600 ps is appropriate for providing a tomographic image with fewer artifacts and good lesion uptake estimation relative to other partial ring designs studied in this work, (iii) a flat scanner design with 2/3 angular coverage is affected more by larger parallax error than a curved scanner geometry with the same angular coverage, but provides more uniform lesion contrast estimate over the imaging field-of-view (FOV), (iv) 2/3 angular coverage, flat, 300 ps TOF scanner design (for short, practical scan times of ≤ 5 mins per breast) provides similar precision of contrast recovery coefficient (CRC) values to a full curved, non-TOF scanner, and (v) employing depth-of-interaction (DOI) measuring detector and/or implementing resolution modeling (RM) in image reconstruction lead to improved and more uniform spatial resolution and lesion contrast over the whole FOV.

Evaluation of Image Quality Improvements When Adding Patient Outline Constraints into a Generalized Scatter PET Reconstruction Algorithm

Scattered coincidences degrade image contrast and compromise quantitative accuracy in positron emission tomography (PET). A number of approaches to estimating and correcting scattered coincidences have been proposed, but most of them are based on estimating and subtracting a scatter sinogram from the measured data. We have previously shown that both true and scattered coincidences can be treated similarly by using Compton scattering kinematics to define a locus of scattering which may in turn be used to reconstruct the activity distribution using a generalized scatter maximum-likelihood expectation maximization (GS-MLEM) algorithm. The annihilation position can be further confined by taking advantage of the patient outline (or a geometrical shape that encompasses the patient outline). The proposed method was tested on a phantom generated using GATE. The results have shown that for scatter fractions of 10–60% this algorithm improves the contrast recovery coefficients (CRC) by 4 to 28.6% for a source and 5.1 to 40% for a cold source while the relative standard deviation (RSD) was reduced. Including scattered photons directly into the reconstruction eliminates the need for (often empirical) scatter corrections, and further improvements in the contrast and noise properties of the reconstructed images can be made by including the patient outline in the reconstruction algorithm as a constraint.

TOF capability evaluation on a panel PET for human body imaging

Due to its unique structure, parallel panel configuration may lead to novel applications for positron emission tomography (PET). The major challenge of panel PET imaging is the limited angle problem, to which the time-of-flight (TOF) information seems to be a promising solution. This work investigated the required TOF capability of a panel PET design, which has a feasible size of field of view (FOV) for human torso. Such a system's corresponding angular coverage can vary from 70 to 102 degrees. The recovery ability of small lesions was assessed, and the contrast recovery coefficient (CRC) and signal-to-noise ratio (SNR) were analyzed, with a full ring PET as the benchmark system. We also varied the timing resolution and the distance between panels, to evaluate their impacts on image quality. Encouraging results were obtained in simulation study. Distortions and artifacts caused by the limited angular coverage were greatly reduced with timing resolutions better than 300 ps. The recovery ability of small lesions in most part of FOV was desirable. Meanwhile, varying panel distance in the range of 25 to 45 cm seemed to have trivial influence, when timing resolution was fixed at 300 ps. That means that such changes of panel distance might not affect the requirement on TOF capability, allowing more flexibility in panel PET's design and applications.