title: Methodology for image-based reconstruction of ventricular geometry for patient-specific modeling of cardiac electrophysiology.
abstract: Patient-specific modeling of ventricular electrophysiology requires an interpolated reconstruction of the 3-dimensional (3D) geometry of the patient ventricles from the low-resolution (Lo-res) clinical images. The goal of this study was to implement a processing pipeline for obtaining the interpolated reconstruction, and thoroughly evaluate the efficacy of this pipeline in comparison with alternative methods. The pipeline implemented here involves contouring the epi- and endocardial boundaries in Lo-res images, interpolating the contours using the variational implicit functions method, and merging the interpolation results to obtain the ventricular reconstruction. Five alternative interpolation methods, namely linear, cubic spline, spherical harmonics, cylindrical harmonics, and shape-based interpolation were implemented for comparison. In the thorough evaluation of the processing pipeline, Hi-res magnetic resonance (MR), computed tomography (CT), and diffusion tensor (DT) MR images from numerous hearts were used. Reconstructions obtained from the Hi-res images were compared with the reconstructions computed by each of the interpolation methods from a sparse sample of the Hi-res contours, which mimicked Lo-res clinical images. Qualitative and quantitative comparison of these ventricular geometry reconstructions showed that the variational implicit functions approach performed better than others. Additionally, the outcomes of electrophysiological simulations (sinus rhythm activation maps and pseudo-ECGs) conducted using models based on the various reconstructions were compared. These electrophysiological simulations demonstrated that our implementation of the variational implicit functions-based method had the best accuracy.
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: A
authors.initials: A
authors.lastname: Prakosa
authors.affiliation: Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: P
authors.initials: P
authors.lastname: Malamas
authors.affiliation: Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: S
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: F
authors.initials: F
authors.lastname: Pashakhanloo
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: H
authors.initials: H
authors.lastname: Arevalo
authors.affiliation: School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: D A
authors.initials: DA
authors.lastname: Herzka
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: A
authors.initials: A
authors.lastname: Lardo
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: H
authors.initials: H
authors.lastname: Halperin
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: E
authors.initials: E
authors.lastname: McVeigh
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA. Electronic address: ntrayanova@jhu.edu.
authors.forename: N
authors.initials: N
authors.lastname: Trayanova
authors.affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: F
authors.initials: F
authors.lastname: Vadakkumpadan
mesh_terms: D059925:Anatomic Landmarks / Q000473:pathology; D000818:Animals; D018780:Body Surface Potential Mapping / Q000379:methods*; D004285:Dogs; D006329:Heart Conduction System / Q000473:pathology* / Q000503:physiopathology*; D006352:Heart Ventricles / Q000473:pathology* / Q000503:physiopathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods; D066230:Patient-Specific Modeling; D013552:Swine
keywords: Cardiac electrophysiology; Cardiac ventricular geometry reconstruction; Interpolation; Validation; Variational implicit functions