Multimodal ventricular tachycardia analysis : towards the accurate parametrization of predictive HPC electrophysiological computational models

After a myocardial infarction, the affected areas of the cardiac tissue suffer changes in their electrical and mechanical properties. This post-infarction scar tissue has been related with a particular type of arrhythmia: ventricular tachycardia (VT). A thorough study on the experimental data acquired with clinical tools is presented in this thesis with the objective of defining the limitations of the clinical data towards predictive computational models. Computational models have a large potential as predictive tools for VT, but the verification, validation and uncertain quantification of the numerical results is required before they can be employed as a clinical tool. Swine experimental data from an invasive electrophysiological study and Cardiac Magnetic Resonance imaging is processed to obtain accurate characterizations of the post-infarction scar. Based on the results, the limitation of each technique is described. Furthermore, the volume of the scar is evaluated as marker for post-infarction VT induction mechanisms. A control case from the animal experimental protocol is employed to build a simulation scenario in which biventricular simulations are done using a detailed cell model adapted to the ionic currents present in the swine myocytes. The uncertainty of the model derived from diffusion and fibre orientation is quantified. Finally, the recovery of the model to an extrastimulus is compared to experimental data by computationally reproducing an S1-S2 protocol. Results from the cardiac computational model show that the propagation wave patterns from numerical results match the one described by the experimental activation maps if the DTI fibre orientations are used. The electrophysiological activation is sensitive to fibre orientation. Therefore simulations including the fibre orientations from DTI are able to reproduce a physiological wave propagation pattern. The diffusion coefficients highly determine the conduction velocity. The S1-S2 protocol produced restitution curves that have similar slopes to the experimental curves. This work is a first step forward towards validation of cardiac electrophysiology simulations. Future work will address the limitations about optimal parametrization of the O'Hara-Rudy cell model to fully validate the cardiac computational model for prediction of VT inducibility.Tras un infarto de miocardio, las zonas de tejido cardiaco afectadas sufren cambios en sus propiedades eléctricas y mecánicas. Este substrato miocárdico se ha relacionado con la taquicardia ventricular (TV), un tipo de arritmia. En esta tesis se presenta un estudio exhaustivo de los datos experimentales adquiridos con protocolos clínicos con el objetivo de definir las limitaciones de los datos clínicos antes de avanzar hacia modelos computacionales. Los modelos computacionales tienen un gran potencial como herramientas para la predicción de TV, pero es necesaria su verificación, validación y la cuantificación de la incertidumbre en los resultados numéricos antes de poderlos emplear como herramientas clínicas. La caracterización precisa del sustrato miocárdico, cicatriz, se realiza mediante el procesado de los datos experimentales porcinos obtenidos del estudio electrofisiológico invasivo y la resonancia magnética cardiaca. Como consecuencia, se describen las limitaciones de cada técnica. Ademas, se estudia si el volumen da la cicatriz puede actuar como indicador de la aparición de VT. El escenario de simulación para los modelos computacionales biventriulares se construye a partir de los datos experimentales de un caso control incluido en el protocolo experimental. En el, se realizan simulaciones electrofisiológicas empleando un modelo celular detallado adaptado a las propiedades de las corrientes iónicas en los miocitos de los cerdos. Se cuantifica la incertidumbre del modelo generada por la difusión y la orientación de las fibras. Por ultimo, se compara la recuperación del modelo a un extraestímulo con datas experimentales mediante la simulación de un protocolo S1-S2. Los resultado numéricos obtenidos muestran que los patrones de propagación de la onda de las simulación cardiaca coinciden con los descritos por los mapas de activación experimentales si la fibras incluidas en el modelo corresponden a los datos de DTI. El modelo de activación es sensible a la orientación de fibras impuesta. Las simulaciones incluyendo la orientación de fibras de DTI es capaz de reproducir los patrones fisiológicos de la onda de propagación eléctrica en ambos ventrículos. El velocidad de conducción obtenida es muy dependiente del coeficiente de difusión impuesto. El protocolo S1-S2 protocolo genera curvas de restitución con pendientes simulares a las curvas experimentales. Esta tesis es un primer paso hacia la validación de las simulaciones electrofisiológicas cardiacas. En el futuro, se mejoraran las limitaciones relacionadas con una optima parametrización del modelo celular de O?Hara-Rudy para validar por completo el modelo computacional cardiaco para avanzar hacia la predicción de la predicción de VT.Postprint (published version

Three-dimensional cardiac fibre disorganization as a novel parameter for ventricular arrhythmia stratification after myocardial infarction

Aims: Myocardial infarction (MI) alters cardiac fibre organization with unknown consequences on ventricular arrhythmia. We used diffusion tensor imaging (DTI) of three-dimensional (3D) cardiac fibres and scar reconstructions to identify the main parameters associated with ventricular arrhythmia inducibility and ventricular tachycardia (VT) features after MI. Methods and results: Twelve pigs with established MI and three controls underwent invasive electrophysiological characterization of ventricular arrhythmia inducibility and VT features. Animal-specific 3D scar and myocardial fibre distribution were obtained from ex vivo high-resolution contrast-enhanced T1 mapping and DTI sequences. Diffusion tensor imaging-derived parameters significantly different between healthy and scarring myocardium, scar volumes, and left ventricular ejection fraction (LVEF) were included for arrhythmia risk stratification and correlation analyses with VT features. Ventricular fibrillation (VF) was the only inducible arrhythmia in 4 out of 12 infarcted pigs and all controls. Ventricular tachycardia was also inducible in the remaining eight pigs during programmed ventricular stimulation. A DTI-based 3D fibre disorganization index (FDI) showed higher disorganization within dense scar regions of VF-only inducible pigs compared with VT inducible animals (FDI: 0.36; 0.36-0.37 vs. 0.32; 0.26-0.33, respectively, P = 0.0485). Ventricular fibrillation induction required lower programmed stimulation aggressiveness in VF-only inducible pigs than VT inducible and control animals. Neither LVEF nor scar volumes differentiated between VF and VT inducible animals. Re-entrant VT circuits were localized within areas of highly disorganized fibres. Moreover, the FDI within heterogeneous scar regions was associated with the median VT cycle length per animal (R2 = 0.5320). Conclusion: The amount of scar-related cardiac fibre disorganization in DTI sequences is a promising approach for ventricular arrhythmia stratification after MI.The CNIC (Madrid, Spain) is supported by the Ministry of Science, Innovation and Universities and the Pro CNIC Foundation. The CNIC and the BSC (Barcelona, Spain) are Severo Ochoa Centers of Excellence (SEV-2015-0505 and SEV-2011-0067, respectively). This study was supported by grants from Instituto de Salud Carlos III, Fondo Europeo de Desarrollo Regional (RD12/0042/0036, CB16/11/00458), Spanish Ministry of Science, Innovation and Universities (SAF2016-80324-R, PI16/02110, and DTS17/00136), and by the European Commission [ERA-CVD Joint Call (JTC2016/APCIN-ISCIII-2016), grant#AC16/00021]. The study was also partially supported by the Fundacion Interhospitalaria para la Investigacion Cardiovascular (FIC, Madrid, Spain), the Spanish Society of Cardiology (Dr. Pedro Zarco award) and the Heart Rhythm section of the Spanish Society of Cardiology (DFR). J.J. is supported by R01 Grant HL122352 from the National Heart Lung and Blood Institute, USA National Institutes of Health. J.A.S. is funded by the CompBioMed project, H2020-EU.1.4.1.3 European Union's Horizon 2020 research and innovation programme, grant#675451. D.G.L. has received financial support through the 'la Caixa' Fellowship Grant for Doctoral Studies, 'la Caixa' Banking Foundation, Barcelona, Spain.S

Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy

Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.The Centro Nacional de Investigaciones Cardiovasculares (CNIC) is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación and the ProCNIC Foundation (Madrid, Spain). The CNIC and the Barcelona Supercomputing Center (BSC, Barcelona, Spain) are Severo Ochoa Centers of Excellence (SEV-2015-0505 and SEV-2011-0067, respectively). This study was also supported by grants from the Fondo Europeo de Desarrollo Regional (CB16/11/00458), the Ministerio de Ciencia e Innovación (PID2019-109329RB-I00) and the Heart Rhythm Association of the Spanish Society of Cardiology (ARC). The study was also part of a Master Research Agreement between CNIC and Philips Healthcare. The study was partially supported by the Fundación Interhospitalaria para la Investigación Cardiovascular (FIC, Madrid, Spain) and the Fundación Eugenio Rodríguez Pascual (Madrid, Spain). J.A.-S. is funded by the CompBioMed2 project grant agreement 823712, H2020-EU.1.4.1.3 European Union’s Horizon 2020 research and innovation program, the SILICOFCM project, grant agreement 777204, H2020-EU.3.1.5 and by a Ramón y Cajal fellowship (RYC-2017-22532), MINECO, Spain. L.K.G was funded by the Fundación Carolina-BBVA. Grant TEC2017-82408-R is also acknowledged.Peer Reviewed"Article signat per 25 autors/es: Susana Merino-Caviedes, Lilian K. Gutierrez, José Manuel Alfonso-Almazán, Santiago Sanz-Estébanez, Lucilio Cordero-Grande, Jorge G. Quintanilla, Javier Sánchez-González, Manuel Marina-Breysse, Carlos Galán-Arriola, Daniel Enríquez-Vázquez, Carlos Torres, Gonzalo Pizarro, Borja Ibáñez, Rafael Peinado, Jose Luis Merino, Julián Pérez-Villacastín, José Jalife, Mariña López-Yunta, Mariano Vázquez, Jazmín Aguado-Sierra, Juan José González-Ferrer, Nicasio Pérez-Castellano, Marcos Martín-Fernández, Carlos Alberola-López & David Filgueiras-Rama"Postprint (published version

Implications of bipolar voltage mapping and magnetic resonance imaging resolution in biventricular scar characterization after myocardial infarction

Aims: We aimed to study the differences in biventricular scar characterization using bipolar voltage mapping compared with state-of-the-art in vivo delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging and ex vivo T1 mapping. Methods and results: Ten pigs with established myocardial infarction (MI) underwent in vivo scar characterization using LGE-CMR imaging and high-density voltage mapping of both ventricles using a 3.5-mm tip catheter. Ex vivo post-contrast T1 mapping provided a high-resolution reference. Voltage maps were registered onto the left and right ventricular (LV and RV) endocardium, and epicardium of CMR-based geometries to compare voltage-derived scars with surface-projected 3D scars. Voltage-derived scar tissue of the LV endocardium and the epicardium resembled surface projections of 3D in vivo and ex vivo CMR-derived scars using 1-mm of surface projection distance. The thinner wall of the RV was especially sensitive to lower resolution in vivo LGE-CMR images, in which differences between normalized low bipolar voltage areas and CMR-derived scar areas did not decrease below a median of 8.84% [interquartile range (IQR) (3.58, 12.70%)]. Overall, voltage-derived scars and surface scar projections from in vivo LGE-CMR sequences showed larger normalized scar areas than high-resolution ex vivo images [12.87% (4.59, 27.15%), 18.51% (11.25, 24.61%), and 9.30% (3.84, 19.59%), respectively], despite having used optimized surface projection distances. Importantly, 43.02% (36.54, 48.72%) of voltage-derived scar areas from the LV endocardium were classified as non-enhanced healthy myocardium using ex vivo CMR imaging. Conclusion: In vivo LGE-CMR sequences and high-density voltage mapping using a conventional linear catheter fail to provide accurate characterization of post-MI scar, limiting the specificity of voltage-based strategies and imaging-guided procedures.The CNIC (Madrid, Spain) is supported by the Ministry of Economy, Industry and Competitiveness (MEIC) and the Pro CNIC Foundation; The CNIC and the BSC (Barcelona, Spain) are Severo Ochoa Centers of Excellence (SEV-2015-0505 and SEV-2011-0067, respectively); Instituto de Salud Carlos III, Fondo Europeo de Desarrollo Regional (RD12/0042/0036, CB16/11/00458), Spanish Ministry of Economy and Competitiveness (MINECO) (SAF2016-80324-R, PI16/02110, and DTS17/00136), and by the European Commission [ERA-CVD Joint Call (JTC2016/APCIN-ISCIII-2016), Grant no. AC16/00021]; Fundacion Interhospitalaria para la Investigacion Cardiovascular (FIC, Madrid, Spain) and the heart rhyhtm section of the Spanish Society of Cardiology (DFR), in part; R01 Grant HL122352 from the National Heart Lung and Blood Institute, USA, National Institutes of Health to J.J.; CompBioMed project, H2020-EU.1.4.1.3 European Union's Horizon 2020 research and innovation program, (Grant no. 675451 to J.A.-S.); D.G.L. has received financial support through the 'la Caixa' Fellowship Grant for Doctoral Studies, 'la Caixa' Banking Foundation, Barcelona, Spain.S