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7 March 2018 Development of a validation instrument in myocardial perfusion imaging: results of first flow experiments
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Institutional diagnostic workflows regarding coronary artery disease (CAD) may differ greatly. Myocardial perfusion imaging (MPI) is a commonly used diagnostic method in CAD, whereby multiple modalities are deployed to assess relative or absolute myocardial blood flow (MBF) (e.g. with SPECT, PET, MR, CT, or combinations). In line with proper clinical decision-making, it is essential to assess institutional MPI test validity by confronting MBF assessment to a ground truth. Our research focuses on developing such validation instrument/method for MPI by means of simulating controlled myocardial perfusion in a phantom flow setup. A first step was made in the process of method development and validation by specifying basic requirements for the phantom flow setup. First tests in CT-MPI were aimed to gain experience in clinical testing, to verify to which extent the set requirements are met, and to evaluate the steps needed to further improve accuracy and reproducibility of measurements. The myocardium was simulated as a static cylinder and placed in a controllable pulsatile flow circuit whereby using flow sensors as reference. First flow experiments were performed for different stroke volumes (20-35 mL/stroke). After contrast injection, dynamic MPI-CT scans (SOMATOM Force, Siemens) were obtained to investigate the relation between first-pass measured and computed flow. We observed a moderate correlation; hence, the required accuracy and reproducibility levels were not met. However, we have gained new insights in factors regarding the measurement setup and MBF computation process that might affect instrument validation, which we will incorporate in future flow setup design and testing.
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Marije E. Kamphuis, Gert Jan Pelgrim, Marcel J. W. Greuter, Riemer H. J. A. Slart, and Cornelis H. Slump "Development of a validation instrument in myocardial perfusion imaging: results of first flow experiments", Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 1057714 (7 March 2018);

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