- Mihaela Pop22,23,
- Maxime Sermesant24,
- Samuel Oduneye22,23,
- Sudip Ghate22,
- Labonny Biswas22,
- Roey Flor22,
- Susan Newbigging23,25,
- Eugene Crystal22,23,
- Nicholas Ayache24 &
- …
- Graham A. Wright22,23
Part of the book series:Lecture Notes in Computer Science ((LNIP,volume 8330))
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Abstract
MR image-based computer heart models are powerful non-invasive tools that can help us predict the transmural electrical propagation of abnormal depolarization-repolarization waves in the presence of infarct scars (i.e., collagenous fibrosis), a major cause of sudden death; however, an important step is the customization of these models from electrophysiology studies (EP) . In this work, we used MR-EP data obtained in a pre-clinical animal model (i.e., three healthy and two infarcted swine hearts) and customized a simple mono-domain model (i.e., the Aliev-Panfilov model). Specifically, we estimated the mathematical parameters corresponding to: a) the repolarization phase fromin vivo activation-recovery intervals, ARIs (recordedin vivo with a CARTO system), and b) the anisotropy ratio (from fluorescence microscopic imaging of connexin 43, Cx43). Our measurements showed that in the ischemic peri-infarct areas the ARIs intervals were shorter by ~ 14% compared to those in normal tissue, and that there was a significant reduction (> 50%) in the Cx43 density (which tunes the cell-to-cell coupling and tissue bulk conductivity) with respect to both longitudinal and transverse directions of the myocyte. In addition, we included comparisons between virtualin silico simulations of activation maps obtained with different parameters used as input to a 3D MR-based biventricular model. Our preliminary results demonstrated the feasibility of usinggeneric parameters to customize such MR-based models; however, further quantitative studies are needed. Finally, we discussed the overall advantages and limitations of our simplified approach, along with future directions.
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Authors and Affiliations
Sunnybrook Research Institute, Toronto, Canada
Mihaela Pop, Samuel Oduneye, Sudip Ghate, Labonny Biswas, Roey Flor, Eugene Crystal & Graham A. Wright
University of Toronto, Canada
Mihaela Pop, Samuel Oduneye, Susan Newbigging, Eugene Crystal & Graham A. Wright
Inria - Asclepios Project, Sophia Antipolis, France
Maxime Sermesant & Nicholas Ayache
CMHD Pathology Core, Toronto, Canada
Susan Newbigging
- Mihaela Pop
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- Maxime Sermesant
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- Samuel Oduneye
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- Sudip Ghate
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- Labonny Biswas
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- Roey Flor
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- Susan Newbigging
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- Eugene Crystal
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- Nicholas Ayache
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- Graham A. Wright
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Editors and Affiliations
Universitat Pompeu Fabra, Barcelona, Spain
Oscar Camara
Siemens Corporation, Corporate Technology, Princeton, NJ, USA
Tommaso Mansi
University of Toronto, ON, Canada
Mihaela Pop
King’s College London, UK
Kawal Rhode
Inria, Sophia Antipolis, France
Maxime Sermesant
University of Auckland, New Zealand
Alistair Young
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Pop, M.et al. (2014). Progress on Customization of Predictive MRI-Based Macroscopic Models from Experimental Data. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2013. Lecture Notes in Computer Science, vol 8330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54268-8_18
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