Mediated spatiotemporal fusion of multiple cardiac magnetic resonance datasets for patient-specific perfusion analysis

Patient-specific correlation of perfusion defects and coronary arteries responsible for blood supply in the affected territories has the potential to improve accuracy of diagnosis and intervention planning, but cardiac cycle phase difference between perfusion and angiography datasets precludes the use of standard methods of 2D/3D registration. This paper presents a work-flow for mediated spatiotemporal registration of perfusion series and angiography volumes; the solution of the registration problem relies on the use of the 4D wall motion series as a mediator for non-rigid registration of perfusion and angiography datasets. The work-flow assumes the availability of the localised/segmented main coronary arteries in the angiography dataset. Results of evaluation on clinical data show the utility of the method in perfusion analysis while highlighting its potential applicability to other areas of cardiac image analysis.

[1]  F. Cheriet,et al.  Computation of coronary perfusion territories from CT angiography , 2007, 2007 Computers in Cardiology.

[2]  J. Schnabel,et al.  Correction of misaligned slices in multi-slice cardiovascular magnetic resonance using slice-to-volume registration , 2008, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[3]  D. Magee,et al.  Mediated Spatiotemporal Registration of Cardiac DCE-MRI and Coronary MR Angiography , 2010 .

[4]  Jean-Philippe Thirion,et al.  Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..

[5]  S. Plein,et al.  Coronary artery disease: myocardial perfusion MR imaging with sensitivity encoding versus conventional angiography. , 2005, Radiology.

[6]  S. Plein,et al.  Assessment of non-ST-segment elevation acute coronary syndromes with cardiac magnetic resonance imaging. , 2004, Journal of the American College of Cardiology.

[7]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[9]  M. Cerqueira,et al.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. , 2002, Circulation.

[10]  M. Sculpher,et al.  Clinical evaluation of magnetic resonance imaging in coronary heart disease: The CE-MARC study , 2009, Trials.

[11]  Brian B. Avants,et al.  Non-Rigid Image Registration , 2004 .

[12]  Guido Gerig,et al.  Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data , 2012, Lecture Notes in Computer Science.

[13]  M. Cerqueira,et al.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart: A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association , 2002, The international journal of cardiovascular imaging.

[14]  Heinz-Otto Peitgen,et al.  A Comprehensive Approach to the Analysis of Contrast Enhanced Cardiac MR Images , 2008, IEEE Transactions on Medical Imaging.