Evaluation of applying space-variant resolution modeling to attenuation correction in PET

Attenuation correction aims to recover the underestimated tracer uptake and improve the image contrast recovery in positron emission tomography (PET). However, traditional ray-tracing-based projection of attenuation maps is inaccurate as some physical effects are not considered, such as finite crystal size, inter-crystal penetration and inter-crystal scatter. In this study, we evaluated the effects of applying resolution modeling (RM) to attenuation correction by implementing space-variant RM to complement physical effects which are usually omitted in the traditional projection model. We verified this method on a brain PET scanner developed by our group, in both Monte Carlo simulation and real-world data, in comparison with space-invariant Gaussian RM, average-depth-of-interaction, and multi-ray tracing methods. The results indicate that the space-variant RM is superior in terms of artifacts reduction and contrast recovery.

Experimental validation of absolute SPECT/CT quantification for response monitoring in breast cancer

PURPOSE

Recent developments in iterative image reconstruction enable absolute quantification of SPECT/CT studies by incorporating compensation for collimator-detector response, attenuation, and scatter as well as resolution recovery into the reconstruction process (Evolution; Q.Metrix package; GE Healthcare, Little Chalfont, UK). The aim of this experimental study is to assess its quantitative accuracy for potential clinical ^99m Tc-sestamibi (MIBI)-related SPECT/CT application in neoadjuvant chemotherapy response studies in breast cancer.

METHODS

Two phantoms were filled with MIBI and acquired on a SPECT/CT gamma camera (Discovery 670 Pro; GE Healthcare), that is, a water cylinder and a NEMA body phantom containing six spheres that were filled with an activity concentration reflecting clinical MIBI uptake. Subsequently, volumes-of-interest (VOI) of each sphere were drawn (semi)automatically on SPECT using various isocontour methods or manually on CT. Finally, prone MIBI SPECT/CT scans were acquired 5 and 90 min p.i. in a locally advanced breast cancer patient.

RESULTS

Activity concentration in the four largest spheres converged after nine iterations of evolution. Depending on the count statistics, the accuracy of the reconstructed activity concentration varied between -4.7 and -0.16% (VOI covering the entire phantom) and from 6.9% to 10% (8.8 cm ⌀ cylinder VOI placed in the center of the phantom). Recovery coefficients of SUV_max were 1.89 ± 0.18, 1.76 ± 0.17, 2.00 ± 0.38, 1.89 ± 0.35, and 0.90 ± 0.26 for spheres with 37, 28, 22, 17, and 13 mm ⌀, respectively. Recovery coefficients of SUV_mean were 1.07 ± 0.06, 1.03 ± 0.09, 1.17 ± 0.21, 1.10 ± 0.20, and 0.52 ± 0.14 (42% isocontour); 1.10 ± 0.07, 1.02 ± 0.09, 1.13 ± 0.19, 1.06 ± 0.19, and 0.51 ± 0.13 (36% isocontour with local background correction); and 0.96, 1.09, 1.03, 1.03, and 0.29 (CT). Patient study results were concordant with the phantom validation.

CONCLUSIONS

Absolute SPECT/CT quantification of breast studies using MIBI seems feasible (<17% deviation) when a 42% isocontour is used for delineation for tumors of at least 17 mm diameter. However, with tumor shrinkage, response evaluation should be handled with caution, especially when using SUV_max .

Sinogram Blurring Matrix Estimation From Point Sources Measurements With Rank-One Approximation for Fully 3-D PET

An accurate system matrix is essential in positron emission tomography (PET) for reconstructing high quality images. To reduce storage size and image reconstruction time, we factor the system matrix into a product of a geometry projection matrix and a sinogram blurring matrix. The geometric projection matrix is computed analytically and the sinogram blurring matrix is estimated from point source measurements. Previously, we have estimated a 2-D blurring matrix for a preclinical PET scanner. The 2-D blurring matrix only considers blurring effects within a transaxial sinogram and does not compensate for inter-sinogram blurring effects. For PET scanners with a long axial field of view, inter-sinogram blurring can be a major problem influencing the image quality in the axial direction. Hence, the estimation of a 4-D blurring matrix is desirable to further improve the image quality. The 4-D blurring matrix estimation is an ill-conditioned problem due to the large number of unknowns. Here, we propose a rank-one approximation for each blurring kernel image formed by a row vector of the sinogram blurring matrix to improve the stability of the 4-D blurring matrix estimation. The proposed method is applied to the simulated data as well as the real data obtained from an Inveon microPET scanner. The results show that the newly estimated 4-D blurring matrix can improve the image quality over those obtained with a 2-D blurring matrix and requires less point source scans to achieve similar image quality compared with an unconstrained 4-D blurring matrix estimation.

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.

Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls

In this paper, the authors review the field of resolution modeling in positron emission tomography (PET) image reconstruction, also referred to as point-spread-function modeling. The review includes theoretical analysis of the resolution modeling framework as well as an overview of various approaches in the literature. It also discusses potential advantages gained via this approach, as discussed with reference to various metrics and tasks, including lesion detection observer studies. Furthermore, attention is paid to issues arising from this approach including the pervasive problem of edge artifacts, as well as explanation and potential remedies for this phenomenon. Furthermore, the authors emphasize limitations encountered in the context of quantitative PET imaging, wherein increased intervoxel correlations due to resolution modeling can lead to significant loss of precision (reproducibility) for small regions of interest, which can be a considerable pitfall depending on the task of interest.