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Optimization of a Model Corrected Blood Input Function From Dynamic FDG-PET Images of Small Animal Heart In Vivo
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 parti...
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Published in: | IEEE transactions on nuclear science 2013-10, Vol.60 (5), p.3417-3422 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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 18 F-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. |
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ISSN: | 0018-9499 1558-1578 |
DOI: | 10.1109/TNS.2013.2269032 |