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  • Title: A Novel Data-Driven Cardiac Gating Signal Extraction Method for PET.
    Author: Feng T, Wang J, Dong Y, Zhao J, Li H.
    Journal: IEEE Trans Med Imaging; 2019 Feb; 38(2):629-637. PubMed ID: 30188816.
    Abstract:
    Compared to external device based approaches, a data-driven gating technique in PET imaging is advantageous as it does not require additional hardware or procedure. Currently, data-driven cardiac gating is less studied than respiratory gating. The aim of this paper is to develop a robust data-driven cardiac gating approach for clinical application. First, the central location of the heart is obtained from the corresponding CT image. A cylinder-shaped volume of interest (VOI) centered at the central location of the heart is used to confine cardiac signal calculation. The cardiac signal modeling the expansion/contraction of the heart is calculated using the second order moment of the tracer distribution in the VOI in the projection domain. The signal-to-noise ratio (SNR) of the cardiac motion signal is defined as the energy of the cardiac frequency components over the energy of other non-cardiac frequencies. The optimal cardiac signal with maximal SNR is obtained through an iterative optimization of signal extraction parameters. To validate our method, simulations of different scan parameters including tracer uptake and noise level were generated from the 4D XCAT phantom. Quantitative evaluation was achieved by comparing the extracted signal with the truth in the simulation study. Our method was also applied to 19 patients with high myocardium uptake and compared with the conventional center-of-mass based data-driven method. The simulation study suggests that two major limiting factors in the performance of our method are the myocardium/body uptake ratio and the count rate of the whole field of view. High accuracy of the detected signal was observed with myocardium/body uptake ratio > 7 and count rate > 100 counts/ms. Cardiac peak frequencies were successfully detected in all 19 patients using our method, while the conventional method obtained peaks in only 12 data sets. Our method was also visually validated by gated reconstructions. In summary, we have developed a novel dedicated data-driven cardiac gating method for PET by tracking the contraction/expansion of the heart during the scan. Quantitative evaluation using simulations and qualitative validation with clinical datasets both demonstrate that our method is a robust alternative to the device-based method with a high success rate.
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