Medical Image Analysis
Volume 16, Issue 2 , Pages 505-523, February 2012

Construction of 3D MR image-based computer models of pathologic hearts, augmented with histology and optical fluorescence imaging to characterize action potential propagation

  • Mihaela Pop

      Affiliations

    • Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, Ontario, Canada M4N 3M5
    • Corresponding Author InformationCorresponding author. Address: Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, Room SG-18, Sunnybrook Research Institute, Toronto, Ontario, Canada M4N 3M5. Tel.: +1 416 4806100x7129.
  • ,
  • Maxime Sermesant

      Affiliations

    • INRIA–Asclepios Project, Sophia Antipolis, Cedex 06902, France
  • ,
  • Garry Liu

      Affiliations

    • Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, Ontario, Canada M4N 3M5
  • ,
  • Jatin Relan

      Affiliations

    • INRIA–Asclepios Project, Sophia Antipolis, Cedex 06902, France
  • ,
  • Tommaso Mansi

      Affiliations

    • Siemens Corporate Research, Princeton, NJ 08540, USA
  • ,
  • Alan Soong

      Affiliations

    • Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, Ontario, Canada M4N 3M5
  • ,
  • Jean-Marc Peyrat

      Affiliations

    • Siemens Molecular Imaging, Oxford OX1 2EP, UK
  • ,
  • Michael V. Truong

      Affiliations

    • King’s College London, London SE1 7EH, UK
  • ,
  • Paul Fefer

      Affiliations

    • Department of Cardiology, Sunnybrook Research Institute, Toronto, ON, Canada M4N 3M5
  • ,
  • Elliot R. McVeigh

      Affiliations

    • Department of Biomedical Engineering, Johns Hopkins Medical School, Baltimore, MA 21205, USA
  • ,
  • Herve Delingette

      Affiliations

    • INRIA–Asclepios Project, Sophia Antipolis, Cedex 06902, France
  • ,
  • Alexander J. Dick

      Affiliations

    • Heart Institute, University of Ottawa, Ottawa, ON, Canada K1Y 4W7
  • ,
  • Nicholas Ayache

      Affiliations

    • INRIA–Asclepios Project, Sophia Antipolis, Cedex 06902, France
  • ,
  • Graham A. Wright

      Affiliations

    • Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, Ontario, Canada M4N 3M5

Received 21 June 2010; received in revised form 6 November 2011; accepted 15 November 2011. published online 07 December 2011.

Highlights

► Successful construction of 3D MRI-based models of pathologic pig hearts. ► 3D model accurately depicts anatomy, scar heterogeneity and fiber directions. ► Categorization of heterogeneous zones was validated using histology. ► Model parameterization used action potential waves from optical imaging.

Abstract 

Cardiac computer models can help us understand and predict the propagation of excitation waves (i.e., action potential, AP) in healthy and pathologic hearts. Our broad aim is to develop accurate 3D MR image-based computer models of electrophysiology in large hearts (translatable to clinical applications) and to validate them experimentally. The specific goals of this paper were to match models with maps of the propagation of optical AP on the epicardial surface using large porcine hearts with scars, estimating several parameters relevant to macroscopic reaction–diffusion electrophysiological models. We used voltage-sensitive dyes to image AP in large porcine hearts with scars (three specimens had chronic myocardial infarct, and three had radiofrequency RF acute scars). We first analyzed the main AP waves’ characteristics: duration (APD) and propagation under controlled pacing locations and frequencies as recorded from 2D optical images. We further built 3D MR image-based computer models that have information derived from the optical measures, as well as morphologic MRI data (i.e., myocardial anatomy, fiber directions and scar definition). The scar morphology from MR images was validated against corresponding whole-mount histology. We also compared the measured 3D isochronal maps of depolarization to simulated isochrones (the latter replicating precisely the experimental conditions), performing model customization and 3D volumetric adjustments of the local conductivity. Our results demonstrated that mean APD in the border zone (BZ) of the infarct scars was reduced by ∼13% (compared to ∼318ms measured in normal zone, NZ), but APD did not change significantly in the thin BZ of the ablation scars. A generic value for velocity ratio (1:2.7) in healthy myocardial tissue was derived from measured values of transverse and longitudinal conduction velocities relative to fibers direction (22cm/s and 60cm/s, respectively). The model customization and 3D volumetric adjustment reduced the differences between measurements and simulations; for example, from one pacing location, the adjustment reduced the absolute error in local depolarization times by a factor of 5 (i.e., from 58ms to 11ms) in the infarcted heart, and by a factor of 6 (i.e., from 60ms to 9ms) in the heart with the RF scar. Moreover, the sensitivity of adjusted conductivity maps to different pacing locations was tested, and the errors in activation times were found to be of approximately 10–12ms independent of pacing location used to adjust model parameters, suggesting that any location can be used for model predictions.

Keywords: Cardiac computer models, MRI, Optical imaging, Electrophysiology

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PII: S1361-8415(11)00169-1

doi:10.1016/j.media.2011.11.007

Medical Image Analysis
Volume 16, Issue 2 , Pages 505-523, February 2012