Heart in 3D

Heart in 3D project

Cardiovascular Magnetic Resonance Imaging (MRI) provides three-dimensional and dynamic set of images of the beating heart (multiple frames per cardiac cycle). Apart from geometrical anatomical information, additional information about cardiac function can be collected during the same patient examination with perfusion studies. The information from cardiac MR can be complemented with Cardiac computed tomography (CT) based angiography (CTA) that provides significant details of coronary arteries.

As the cardiovascular diseases continue to be the major cause of deaths in the world, there is a requirement of tools that facilitate and automate the accurate analysis of cardiac images so that the relevant clinical information about the function of the heart and the status of the coronary arteries from thousands of images can be extracted within a matter of minutes.
The "Heart in 3D" project aims to meet these challenges with the collaboration of four biomedical imaging research groups at three universities (Delft University of Technology, Leiden University Medical Centre, Erasmus Medical Centre Rotterdam), as part of the Medical Delta program.

The goal of this project is to develop novel algorithms and quantitative analysis tools to connect three types of diagnostic information on cardiac function (myocardial perfusion, the status of the coronary arteries, and ventricular function) from multi-modality imaging studies. Such fusion of multi-modal cardiac imaging data will allow early diagnosis of cardiovascular disease and subsequent therapeutic planning.

Relating MR perfusion data to the CTA data is the first step in this project. Combining the indicators of myocardial viability derived from cardiac MRI with the coronary anatomy information from the data acquired by cardiac CT angiography enables the fusion of 3D models of the coronaries and myocardium, and facilitates integrated analysis and display. From a clinical perspective, it would be of practical value to analyze several image sets at the same time, because these image sets contain complementary diagnostic information.

People involved:

Vikas Gupta

Hortense A. Kirisli

Rahil Shahzad

Related articles:


V. Gupta, E.A. Hendriks, J. Milles, R.J. van der Geest, M.
Jerosch-Herold, J.H.C. Reiber, and B.P.F. Lelieveldt. Fully
Automatic Registration and Segmentation of First-Pass Myocardial Perfusion MR
Image Sequences. Academic Radiology, 17(11):1375-1385, November 2010.

H.A. Kirisli, M. Schaap, S. Klein, S.L. Papadopoulou, M. Bonardi,
C.H. Chen, A.C. Weustink, N.R.A. Mollet, E. P. A. Vonken, R.J. van der Geest,
T. van Walsum and W.J. Niessen, Evaluation of a multi-atlas based method for
segmentation of cardiac CTA data: a large-scale, multi-center and multi-vendor
study, Medical Physics, 2010

R. Shahzad, M. Schaap, T. van Walsum, S. Klein, A.C. Weustink, L. J.
van Vliet and W.J. Niessen, A patient-specific coronary density estimate,
Proceedings of IEEE International Symposium on Biomedical Imaging: from Nano to
Macro, 2010