Publications (32) View all
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Article: Regional Myocardial Wall Thinning at Multi-Detector Computed Tomography Correlates to Arrhythmogenic Substrate in Post-Infarction Ventricular Tachycardia: Assessment of Structural and Electrical Substrate.
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ABSTRACT: BACKGROUND: -A majority of patients undergoing ablation of ventricular tachycardia (VT) have implanted devices precluding substrate imaging with delayed-enhancement magnetic resonance imaging (MRI). Contrast-enhanced multi-detector computed tomography (MDCT) can depict myocardial wall thickness with submillimetric resolution. We evaluated the relationship between regional myocardial wall thinning (WT) imaged by MDCT and arrhythmogenic substrate in post-infarction VT. METHODS AND RESULTS: -We studied 13 consecutive post-infarction patients undergoing MDCT before ablation. MDCT data was integrated with high-density 3D-electroanatomic maps acquired during sinus rhythm (endocardium: 509±291 points/map, epicardium: 716±323 points/map). Low-voltage areas (<1.5 mV) and local abnormal ventricular activities (LAVA) during sinus rhythm were assessed with regard to the WT. A significant correlation was found between the areas of WT<5mm and endocardial low-voltage (correlation-R=0.82, p=0.001), but no such correlation was found in the epicardium. The WT<5mm area was smaller than the endocardial low-voltage area (54cm2 [Q1-Q3: 46-92] versus 71cm2 [Q1-Q3: 59-124], p=0.001). Among a total of 13,060 electrograms reviewed in the whole study population, 538 LAVA were detected and analyzed. LAVA were located within the WT<5mm (469/538 [87%]) or at its border (100% within 23mm). Very late LAVA (>100ms after QRS complex) were almost exclusively detected within the thinnest area (93% in the WT<3mm). CONCLUSIONS: -Regional myocardial WT correlates to low-voltage regions and distribution of LAVA critical for the generation and maintenance of post-infarction VT. The integration of MDCT WT with 3D-electroanatomic maps can help focus mapping and ablation on the culprit regions, even when MRI is precluded by the presence of implanted devices.Circulation Arrhythmia and Electrophysiology 03/2013; · 6.46 Impact Factor -
Article: Integration of Merged Delayed-Enhanced Magnetic Resonance Imaging and Multidetector Computed Tomography for the Guidance of Ventricular Tachycardia Ablation: A Pilot Study.
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ABSTRACT: MDCT/MRI Fusion for the Guidance of VT Ablation. Background: Delayed enhancement (DE) MRI can assess the fibrotic substrate of scar-related VT. MDCT has the advantage of inframillimetric spatial resolution and better 3D reconstructions. We sought to evaluate the feasibility and usefulness of integrating merged MDCT/MRI data in 3D-mapping systems for structure-function assessment and multimodal guidance of VT mapping and ablation. Methods: Nine patients, including 3 ischemic cardiomyopathy (ICM), 3 nonischemic cardiomyopathy (NICM), 2 myocarditis, and 1 redo procedure for idiopathic VT, underwent MRI and MDCT before VT ablation. Merged MRI/MDCT data were integrated in 3D-mapping systems and registered to high-density endocardial and epicardial maps. Low-voltage areas (<1.5 mV) and local abnormal ventricular activities (LAVA) during sinus rhythm were correlated to DE at MRI, and wall-thinning (WT) at MDCT. Results: Endocardium and epicardium were mapped with 391 ± 388 and 1098 ± 734 points per map, respectively. Registration of MDCT allowed visualization of coronary arteries during epicardial mapping/ablation. In the idiopathic patient, integration of MRI data identified previously ablated regions. In ICM patients, both DE at MRI and WT at MDCT matched areas of low voltage (overlap 94 ± 6% and 79 ± 5%, respectively). In NICM patients, wall-thinning areas matched areas of low voltage (overlap 63 ± 21%). In patients with myocarditis, subepicardial DE matched areas of epicardial low voltage (overlap 92 ± 12%). A total number of 266 LAVA sites were found in 7/9 patients. All LAVA sites were associated to structural substrate at imaging (90% inside, 100% within 18 mm). Conclusion: The integration of merged MDCT and DEMRI data is feasible and allows combining substrate assessment with high-spatial resolution to better define structure-function relationship in scar-related VT. (J Cardiovasc Electrophysiol, Vol. pp. 1-8).Journal of Cardiovascular Electrophysiology 11/2012; · 3.06 Impact Factor -
Article: Strain-based regional nonlinear cardiac material properties estimation from medical images.
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ABSTRACT: Model personalization is essential for model-based surgical planning and treatment assessment. As alteration in material elasticity is a fundamental cause to various cardiac pathologies, estimation of material properties is important to model personalization. Although the myocardium is heterogeneous, hyperelastic, and orthotropic, existing image-based estimation frameworks treat the tissue as either heterogeneous but linear, or hyperelastic but homogeneous. In view of these, we present a physiology-based framework for estimating regional, hyperelastic, and orthotropic material properties. A cardiac physiological model is adopted to describe the macroscopic cardiac physiology. By using a strain-based objective function which properly reflects the change of material constants, the regional material properties of a hyperelastic and orthotropic constitutive law are estimated using derivative-free optimization. Experiments were performed on synthetic and real data to show the characteristics of the framework.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2012; 15(Pt 1):617-24. -
Article: Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: A preliminary clinical validation.
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ABSTRACT: Cardiac resynchronisation therapy (CRT) is an effective treatment for patients with congestive heart failure and a wide QRS complex. However, up to 30% of patients are non-responders to therapy in terms of exercise capacity or left ventricular reverse remodelling. A number of controversies still remain surrounding patient selection, targeted lead implantation and optimisation of this important treatment. The development of biophysical models to predict the response to CRT represents a potential strategy to address these issues. In this article, we present how the personalisation of an electromechanical model of the myocardium can predict the acute haemodynamic changes associated with CRT. In order to introduce such an approach as a clinical application, we needed to design models that can be individualised from images and electrophysiological mapping of the left ventricle. In this paper the personalisation of the anatomy, the electrophysiology, the kinematics and the mechanics are described. The acute effects of pacing on pressure development were predicted with the in silico model for several pacing conditions on two patients, achieving good agreement with invasive haemodynamic measurements: the mean error on dP/dt(max) is 47.5±35mmHgs(-1), less than 5% error. These promising results demonstrate the potential of physiological models personalised from images and electrophysiology signals to improve patient selection and plan CRT.Medical image analysis 01/2012; 16:201-215. · 3.09 Impact Factor -
Article: Construction of 3D MR image-based computer models of pathologic hearts, augmented with histology and optical fluorescence imaging to characterize action potential propagation.
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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 ~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.Medical image analysis 12/2011; 16(2):505-23. · 3.09 Impact Factor
