Correction for Collimator-Detector Response in SPECT Using Point Spread Function Template

Abstract

Compensating for the collimator-detector response (CDR) in SPECT is important for accurate quantification. The CDR consists of both a geometric response and a septal penetration and collimator scatter response. The geometric response can be modeled analytically and is often used for modeling the whole CDR if the geometric response dominates. However, for radionuclides that emit medium or high-energy photons such as I-131, the septal penetration and collimator scatter response is significant and its modeling in the CDR correction is important for accurate quantification. There are two main methods for modeling the depth-dependent CDR so as to include both the geometric response and the septal penetration and collimator scatter response. One is to fit a Gaussian plus exponential function that is rotationally invariant to the measured point source response at several source-detector distances. However, a rotationally-invariant exponential function cannot represent the star-shaped septal penetration tails in detail. Another is to perform Monte-Carlo (MC) simulations to generate the depth-dependent point spread functions (PSFs) for all necessary distances. However, MC simulations, which require careful modeling of the SPECT detector components, can be challenging and accurate results may not be available for all of the different SPECT scanners in clinics. In this paper, we propose an alternative approach to CDR modeling. We use a Gaussian function plus a 2-D B-spline PSF template and fit the model to measurements of an I-131 point source at several distances. The proposed PSF-template-based approach is nearly non-parametric, captures the characteristics of the septal penetration tails, and minimizes the difference between the fitted and measured CDR at the distances of interest. The new model is applied to I-131 SPECT reconstructions of experimental phantom measurements, a patient study, and a MC patient simulation study employing the XCAT phantom. The proposed model yields up to a 16.5 and 10.8% higher recovery coefficient compared to the results with the conventional Gaussian model and the Gaussian plus exponential model, respectively.

Non-local means methods using CT side information for I-131 SPECT image reconstruction

“…We placed two spherical uniform tumors with the size of 72 cc and 11 cc in both SPECT and CT images. We generated projection data using the system matrix that incorporates the attenuation maps and full collimator-detector response including penetration tails [9]. After adjusting the total count number to be similar to the total count number in a patient data, we added a Poisson noise.…”

“…We incorporated the attenuation maps from the CT data and the full collimator-detector response including penetration tails [9] in the matrix A. We assumed known S i .…”

“…One regularizer that is similar to (4) is RNLMCT1(Xlg) .£ 2:: wa(i, jlg)(l -wf(i, jl x )) (9) i , j and the gradient of (9) at x( n) is…”

The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction

“…The ML-OS-EM algorithm with 35 iterations, 6 subsets was performed to reconstruct all SPECT images. Collimator detector response was implemented in the system matrix of reconstruction algorithm [90]. Figure 1b shows a reconstructed SPECT image of a patient with both attenuation and scatter corrections.…”

Alternating Direction Method of Multiplier for Tomography With Nonlocal Regularizers

“…We focus on SPECT imaging where we incorporate an attenuation map and a depth-dependent point spread function model including penetration tails [20] in the system matrix A . We assume known s l ; in practice, this scatter component can be estimated by using a triple energy window (TEW) method or by Monte Carlo methods [21].…”