Heart Modeling

During the final year of my Master’s, I was working at Siemens Corporate Technology in Princeton, NJ, USA on a very interesting project dealing with various aspects of electrophysiology and biomechanics models of the human heart muscle. My time there was one of my most productive phases so far, with not only the successful completion of my MSc thesis titled “Efficient and Robust Patient-Specific Model of the Heart Function based on MRI Images” but also a great publication outcome (see below).

In my work, fast and robust patient-specific parameter estimation for a biomechanic model of the human heart from clinical and imaging data is investigated. Of course, my results are based on available models of heart anatomy and electrophysiology, and – working in a great team at Siemens – I could heavily benefit from extensive experience in heart segmentation and model generation.

My thesis has two major contributions: First, an integrated framework to compute cardiac motion using a finite element setup is presented, in particular including an efficient strategy to parallelize the evaluation of stress and mechanical boundary conditions for high-performance implementations. Second, a novel, data-driven approach to calibrate electrophysiology (EP) parameters from clinically available 12-lead electrocardiograms (ECGs) is introduced, as illustrated in the figure.

ECG-EP Workflow

Forward workflow to compute ECG parameters from electrophysiology (EP) model derived from segmented myocardium, and backward workflow to estimate EP model parameters from measured ECG features.

For more details, please refer to the following publications:

2014 [PDF] [DOI] O. Zettinig, T. Mansi, D. Neumann, B. Georgescu, S. Rapaka, P. Seegerer, E. Kayvanpour, F. Sedaghat-Hamedani, A. Amr, J. Haas, H. Steen, H. Katus, B. Meder, N. Navab, A. Kamen, and D. Comaniciu, “Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals,” Medical Image Analysis, vol. 18, iss. 8, pp. 1361-1376, 2014.
2013 [PDF] [DOI] O. Zettinig, T. Mansi, B. Georgescu, S. Rapaka, A. Kamen, J. Haas, K. S. Frese, F. Sedaghat-Hamedani, E. Kayvanpour, A. Amr, S. Hardt, D. Mereles, H. Steen, A. Keller, H. A. Katus, B. Meder, N. Navab, and D. Comaniciu, “From medical images to fast computational models of heart electromechanics: an integrated framework towards clinical use,” in Functional Imaging and Modeling of the Heart, Springer LNCS, 2013, vol. 7945, pp. 249-258.
2013 [PDF] [DOI] O. Zettinig, T. Mansi, B. Georgescu, E. Kayvanpour, F. Sedaghat-Hamedani, A. Amr, J. Haas, H. Steen, B. Meder, H. Katus, and others, “Fast data-driven calibration of a cardiac electrophysiology model from images and ECG,” in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013, Springer LNCS, 2013, vol. 8149, pp. 1-8.