An Experimental Framework to Validate 3D Models of Cardiac Electrophysiology Via Optical Imaging and MRI

Pop, Mihaela; Sermesant, Maxime; Chung, Desmond; Liu, Garry; McVeigh, Elliot R.; Crystal, Eugene; Wright, Graham A.

doi:10.1007/978-3-540-72907-5_11

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…Other studies mapped the AP propagation in the presence of macroscopic obstacles created by thermally damaging the tissue using cryoablation, high intensity focused ultrasound or laser energy (Juong et al 2006, Qu et al 2004, Pastore and Rosenbaum 2000, Girouard and Rosenbaum 2001. Using our experimental set-up (Pop et al 2007) we recently reported results obtained by mapping optical AP waves in large, healthy porcine hearts. We also performed 3D model construction from MRI scans of the same hearts and adjusted the associated model based on optical measurements (Pop et al 2009a).…”

Section: Introductionmentioning

confidence: 88%

“…The 3D optical stereo-surface of epicardium was further registered with the 3D surface of the MR image-based model as in (Pop et al 2007), via opaque markers visible in MR images, and using a rigid registration method implemented in Matlab (Horn, 1987). This step allowed us to project the measured isochronal maps onto each 3D heart mesh, similarly as presented in (Pop et al 2007 and).…”

Section: Optical Experimentsmentioning

confidence: 99%

“…The pig ventricles were imaged using a 1.5-Tesla Signa GE MR scanner; the gross anatomy, fiber directions, fiducial markers, infarct, and infarct heterogeneity were all visualized in the MR images. As previously described (Pop et al 2007(Pop et al , 2009a, for determining the marker locations on the hearts, we used a 3D fast spin echo (FSE) sequence with the following MR parameters: TE = 60 ms; TR = 700 ms; slice thickness = 2 mm; a 10cm FOV; and 256x256 matrix acquisition yielding an in-plane resolution of 0.4x0.4 mm. The diffusion-weighted imaging sequence (Helm et al, 2005) was developed at the Laboratory of Cardiac Energetics (NIH/NHLBI, USA) and implemented on our research scanner, for which we used the following MR parameters:…”

Section: Magnetic Resonance Imaging Heart Segmentation and Histologymentioning

confidence: 99%

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

Pop¹,

Sermesant²,

Liu³

et al. 2012

Medical Image Analysis

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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 ~318 ms 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 (22 cm/s and 60 cm/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 58 ms to 11 ms) in the infarcted heart, and by a factor of 6 (i.e., from 60 ms to 9 ms) 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 10-12 ms independent of pacing location used to adjust model parameters, suggesting that any location can be used for model predictions.

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Section: Introductionmentioning

confidence: 88%

Section: Optical Experimentsmentioning

confidence: 99%

Section: Magnetic Resonance Imaging Heart Segmentation and Histologymentioning

confidence: 99%

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

Pop¹,

Sermesant²,

Liu³

et al. 2012

Medical Image Analysis

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“…The explanted hearts were attached to a Langendorff perfusion system which permits to maintain the electrophysiological integrity of the hearts over 1-2 hours. The fluorescence dye (reflecting directly the changes of transmembrane potential) and the electromechanical uncoupler were injected into the perfusion line (more details are given in [9]). The hearts were paced with an electrode near the apex for 5 ms.…”

Section: Data Acquisition Processing and Fusionmentioning

confidence: 99%

Cardiac Electrophysiology Model Adjustment Using the Fusion of MR and Optical Imaging

Lepiller

Sermesant

Pop

et al. 2008

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008

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Abstract. Despite important recent efforts in cardiac electrophysiology modelling, there is still a strong need for validating macroscopic models, that are well suited for diagnosis and treatment planning. In this paper we present a method to adjust the parameters of a macroscopic electrophysiology model on depolarisation and repolarisation maps obtained ex-vivo from optical imaging. With this imaging technique, optical fluorescence data are recorded with high spatial and temporal resolution on a large healthy porcine heart. A model of the myocardium is built from the MR images of the same heart, which also integrates the myocardial fibre orientation measured with DTI. We then present the first quantitative adjustment of a personalised volumetric model of the myocardium.

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Inter-model consistency and complementarity: Learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology

Cámara

Sermesant

Lamata

et al. 2011

Progress in Biophysics and Molecular Biology

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An Experimental Framework to Validate 3D Models of Cardiac Electrophysiology Via Optical Imaging and MRI

Cited by 3 publications

References 18 publications

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

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

Cardiac Electrophysiology Model Adjustment Using the Fusion of MR and Optical Imaging

Inter-model consistency and complementarity: Learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology

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