Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Abstract

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera.

Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K₁) and wash-out (k₂) rates at each gate were also estimated.

Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K₁ and k₂ were also consistent with the ground truth.

Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

Keywords: cardiac motion; continuous acquisition; dynamic SPECT; motion correction; myocardial perfusion imaging.

FIGURE 1

The 4D XCAT whole-body phantom (A) was cropped and simplified to model a cardiac torso (B). The torso was then imported to a SPECT system geometry (C) with collimator (gray), detector crystal (yellow), back-compartment (white) and lead-shields (blue and green). Also shown are the rear (D) and side (E) view of the detector.

FIGURE 2

A chart depicting the motion of cardiac and respiratory series for 40 phantoms with 5 cardiac and 1 respiratory cycle from end-inhalation to exhalation.

FIGURE 3

Time activity curves used for the activity map (top) and the corresponding coronal views of the activity distribution in the phantom at time t = 60 s, t = 120 s, and t = 360 s (bottom).

FIGURE 4

Approximate activity distribution in the myocardium for three different TBRs: 8 (Case 1), 5 (Case 2), and 10 (Case 3).

FIGURE 5

(Top) Coronal view of the activity maps for different TBRs at time t = 360 s after the tracer injection (Case 1, 2, 3). All images were normalized by the maximum pixel value of the image with TBR = 10 (Bottom).

FIGURE 6

Similar activity map as in Figure 5 for non-uniform LV thickness (Case 4) and uniform LV thickness but with diaphragm displacement of D = 1.5 cm (Case 5) and their corresponding differences.

FIGURE 7

Gating scheme for the reconstruction: There are 8 cardiac and 5 respiratory gates corresponding to 40 gates for each 4D XCAT phantom configuration.

FIGURE 8

A representative set of temporal cubic B-spline basis functions that were optimized for a specific input time activity curve (TAC) in Figure 3.

FIGURE 9

Reconstructed image of myocardial activity distribution during diastole and systole phases of the heart for three different TBRs at full exhalation.

FIGURE 10

Coronal views of heart in an exhalation-inhalation sequence during one respiratory cycle. The respiratory period was 5 s while the heart beating period was 1 s. The cross hair marks the center of the left ventricle and the first frame represents the end-exhalation. The vertical shift of the myocardium is represented by an arrow.

FIGURE 11

Liver displacement over a respiratory cycle.

FIGURE 12

Performance evaluation: Mean Stabilized Activity (MSA), SNR and Bias for three different TBRs for myocardium and systole and diastole phases.

FIGURE 13

Comparison of gated reconstruction proposed in this work with conventional 4D spatiotemporal reconstruction without gating. Ground truth image (A) and the corresponding reconstructed images with the method proposed in this work with only 18 views per rotation (B) and with the conventional method with 120 views per rotation for the same data set (C) without gating.

FIGURE 14

Effect of LV wall non-uniformity (Case 4): Comparison of the difference in LV wall thickness between the ground truth (left) and the reconstructed image.

FIGURE 15

Effect of diaphragm displacement (Case 5). The images are shown at the interval of 0.5 s after full inhalation to show the myocardial displacement due to respiration for diaphragm displacement D = 1.5.

FIGURE 16

TACs of the myocardium at systole and diastole phase and corresponding fits along with the input function (LV blood pool) for Case 1 study. The data was fitted with the 1TCM for the simulation using LV blood pool as an input function.