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Image Registration and Analysis for Quantitative Myocardial Perfusion: Application to Dynamic Circular Cardiac CT


These file attachments have been under embargo and were made available to the public after the embargo was lifted on 29 February 2012.

Author: Isola, A. · Schmitt, H. · Van Stevendaal, U. · Begemann, P.G.C. (Univ. Hamburg) · Coulon, P. · Boussel, L. · Grass, M.
Embargo lifted:2012-02-29
Publisher: IoP (Institute of Physics)
Institution: Philips Research
Source:Physics in Medicine & Bio; authors version
Identifier: MS 31.897
Keywords: cone beam circular ct · elastic medical image registration · myocardial blood flow · myocardial perfusion · perfusion maps
Rights: (c) IoP (Institute of Physics)


Large area detector computed tomography systems with fastrotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce X-ray dose andlimit motion artifacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occurdue to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in thiscontribution. After circular cone-beam CT reconstruction of cardiacvolumes covering large areas of the myocardial tissue, the completeseries is aligned with respect to a chosen reference volume. The results of the quantitative perfusion analysis are compared on pig datausing the non-registered versus the registered data set. The reduced spatial misalignment leads to an improved characterization of myocardial perfusion confirming the potential of this method. Conclusions - In conclusion, an elastic image registration-based method was proposed to improve the characterization of CT-based estimates of myocardial perfusion. The technique’s performance, that was visually and quantitatively assessed on three pig data sets, confirmed its potential. The proposed method may also be applied to other perfusion studies being limited by inconsistent motion states.

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