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. 2013 Oct;60(5):3417-3422.
doi: 10.1109/TNS.2013.2269032.

Optimization of a Model Corrected Blood Input Function from Dynamic FDG-PET Images of Small Animal Heart In Vivo

Affiliations

Optimization of a Model Corrected Blood Input Function from Dynamic FDG-PET Images of Small Animal Heart In Vivo

Min Zhong et al. IEEE Trans Nucl Sci. 2013 Oct.

Abstract

Quantitative evaluation of dynamic Positron Emission Tomography (PET) of mouse heart in vivo is challenging due to the small size of the heart and limited intrinsic spatial resolution of the PET scanner. Here, we optimized a compartment model which can simultaneously correct for spill over and partial volume effects for both blood pool and the myocardium, compute kinetic rate parameters and generate model corrected blood input function (MCBIF) from ordered subset expectation maximization - maximum a posteriori (OSEM-MAP) cardiac and respiratory gated 18F-FDG PET images of mouse heart with attenuation correction in vivo, without any invasive blood sampling. Arterial blood samples were collected from a single mouse to indicate the feasibility of the proposed method. In order to establish statistical significance, venous blood samples from n=6 mice were obtained at 2 late time points, when SP contamination from the tissue to the blood is maximum. We observed that correct bounds and initial guesses for the PV and SP coefficients accurately model the wash-in and wash-out dynamics of the tracer from mouse blood. The residual plot indicated an average difference of about 1.7% between the blood samples and MCBIF. The downstream rate of myocardial FDG influx constant, Ki (0.15±0.03 min-1), compared well with Ki obtained from arterial blood samples (P=0.716). In conclusion, the proposed methodology is not only quantitative but also reproducible.

Keywords: Blood Input Function; Cardiac and Respiratory Gating; FDG-PET; OSEM-MAP; Small Animals; Tracer Kinetic Modeling.

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Figures

Fig. 1
Fig. 1
Plot of RC with different rod sizes using OSEM-MAP (dash line with diamonds) and FBP reconstruction algorithm (dotted line with open squares).
Fig. 2
Fig. 2
Three compartment FDG model. Block diagram indicating the rate constants, K1–k4, between the 3 compartments of the FDG kinetic model.
Fig. 3
Fig. 3
(A–D) Select coronal dynamic end-diastolic PET images at 0, 0.5, 2 and 56 minutes fused with transmission images. A–D respectively stands for pre, early time points and a late time point. (E–F) Representative estimated results of mouse model correction. (E) Representative image-derived time activity curves of BP (squares) and myocardium (open circles) obtained from OSEM-MAP cardiac and respiratory gated images shown above and model estimated BP (line) and myocardium (dash line) time activity curves are shown here. (F) MCBIF applied to the IDIF obtained from OSEM-MAP gated image (solid line) and FBP ungated image (dashed line), compared to the arterial blood samples (open triangles) obtained during the scan time of 60 minutes.
Fig. 4
Fig. 4
Residual plot shows the difference between MCBIF applied to OSEM-MAP cardiac and respiratory gated images (diamonds) and FBP un-gated images (open squares), when compared to the 2 late venous blood samples obtained at 43 and 56 minutes post FDG administration.

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