Fusion of myocardial perfusion data with CT coronary angiography

Our current approach to fusion of CTCA and PET perfusion data uses the epicardial surface from the perfusion data onto which the CT coronary arteries are aligned and warped. This work was undertaken to improve the alignment and the display realism by using CT epicardial boundary information. PET and CTCA images from a combined scanner were used. Based on the location of the LV detected from PET during standard perfusion processing, the LV chamber of the CT was located. Hounsfield units were used to define an estimated endocardial surface in the CT. Based on the endocardial surface, the epicardial boundary was detected, again using Hounsfield units, or when that failed, by estimating its position based on the detected endocardium. Coronary arteries were detected using a commercial program; the epicardial surface was forced to be congruent with all detected artery points. A confidence factor in each epicardial boundary point was maintained based on how each was detected, whether through threshold, through estimation, or by using he coronary artery points. The epicardial boundary surface points were nonlinearly filtered; erroneous surface points, as defined by local properties and confidence factors, were replaced with values interpolated from the nearest points deemed more accurate. The resulting epicardial surface was linearly aligned to the epicardial boundary detected from the PET, and the CT boundaries were then color-coded based on the PET perfusion. Resulting surfaces were much more realistic than those created using PET epicardial boundaries (Fig 1.) Forcing the CT epicardial surface to He on the detected coronary arteries eliminated problems with alignment and warping of the coronary arteries onto the PET surface.