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1.
J Physiol ; 2023 Apr 15.
Artículo en Inglés | MEDLINE | ID: mdl-37060278

RESUMEN

Personalized, image-based computational heart modelling is a powerful technology that can be used to improve patient-specific arrhythmia risk stratification and ventricular tachycardia (VT) ablation targeting. However, most state-of-the-art methods still require manual interactions by expert users. The goal of this study is to evaluate the feasibility of an automated, deep learning-based workflow for reconstructing personalized computational electrophysiological heart models to guide patient-specific treatment of VT. Contrast-enhanced computed tomography (CE-CT) images with expert ventricular myocardium segmentations were acquired from 111 patients across five cohorts from three different institutions. A deep convolutional neural network (CNN) for segmenting left ventricular myocardium from CE-CT was developed, trained and evaluated. From both CNN-based and expert segmentations in a subset of patients, personalized electrophysiological heart models were reconstructed and rapid pacing was used to induce VTs. CNN-based and expert segmentations were more concordant in the middle myocardium than in the heart's base or apex. Wavefront propagation during pacing was similar between CNN-based and original heart models. Between most sets of heart models, VT inducibility was the same, the number of induced VTs was strongly correlated, and VT circuits co-localized. Our results demonstrate that personalized computational heart models reconstructed from deep learning-based segmentations even with a small training set size can predict similar VT inducibility and circuit locations as those from expertly-derived heart models. Hence, a user-independent, automated framework for simulating arrhythmias in personalized heart models could feasibly be used in clinical settings to aid VT risk stratification and guide VT ablation therapy. KEY POINTS: Personalized electrophysiological heart modelling can aid in patient-specific ventricular tachycardia (VT) risk stratification and VT ablation targeting. Current state-of-the-art, image-based heart models for VT prediction require expert-dependent, manual interactions that may not be accessible across clinical settings. In this study, we develop an automated, deep learning-based workflow for reconstructing personalized heart models capable of simulating arrhythmias and compare its predictions with that of expert-generated heart models. The number and location of VTs was similar between heart models generated from the deep learning-based workflow and expert-generated heart models. These results demonstrate the feasibility of using an automated computational heart modelling workflow to aid in VT therapeutics and has implications for generalizing personalized computational heart technology to a broad range of clinical centres.

2.
Europace ; 25(1): 223-235, 2023 02 08.
Artículo en Inglés | MEDLINE | ID: mdl-36006658

RESUMEN

AIMS: Multiple wavefront pacing (MWP) and decremental pacing (DP) are two electroanatomic mapping (EAM) strategies that have emerged to better characterize the ventricular tachycardia (VT) substrate. The aim of this study was to assess how well MWP, DP, and their combination improve identification of electrophysiological abnormalities on EAM that reflect infarct remodelling and critical VT sites. METHODS AND RESULTS: Forty-eight personalized computational heart models were reconstructed using images from post-infarct patients undergoing VT ablation. Paced rhythms were simulated by delivering an initial (S1) and an extra-stimulus (S2) from one of 100 locations throughout each heart model. For each pacing, unipolar signals were computed along the myocardial surface to simulate substrate EAM. Six EAM features were extracted and compared with the infarct remodelling and critical VT sites. Concordance of S1 EAM features between different maps was lower in hearts with smaller amounts of remodelling. Incorporating S1 EAM features from multiple maps greatly improved the detection of remodelling, especially in hearts with less remodelling. Adding S2 EAM features from multiple maps decreased the number of maps required to achieve the same detection accuracy. S1 EAM features from multiple maps poorly identified critical VT sites. However, combining S1 and S2 EAM features from multiple maps paced near VT circuits greatly improved identification of critical VT sites. CONCLUSION: Electroanatomic mapping with MWP is more advantageous for characterization of substrate in hearts with less remodelling. During substrate EAM, MWP and DP should be combined and delivered from locations proximal to a suspected VT circuit to optimize identification of the critical VT site.


Asunto(s)
Ablación por Catéter , Taquicardia Ventricular , Humanos , Arritmias Cardíacas/cirugía , Miocardio , Infarto/cirugía
3.
Eur Heart J ; 43(22): 2139-2156, 2022 06 06.
Artículo en Inglés | MEDLINE | ID: mdl-35262692

RESUMEN

AIMS: Cardiomyopathy patients are prone to ventricular arrhythmias (VA) and sudden cardiac death. Current therapies to prevent VA include radiofrequency ablation to destroy slowly conducting pathways of viable myocardium which support re-entry. Here, we tested the reverse concept, namely that boosting local tissue viability in zones of slow conduction might eliminate slow conduction and suppress VA in ischaemic cardiomyopathy. METHODS AND RESULTS: Exosomes are extracellular vesicles laden with bioactive cargo. Exosomes secreted by cardiosphere-derived cells (CDCEXO) reduce scar and improve heart function after intramyocardial delivery. In a VA-prone porcine model of ischaemic cardiomyopathy, we injected CDCEXO or vehicle into zones of delayed conduction defined by electroanatomic mapping. Up to 1-month post-injection, CDCEXO, but not the vehicle, decreased myocardial scar, suppressed slowly conducting electrical pathways, and inhibited VA induction by programmed electrical stimulation. In silico reconstruction of electrical activity based on magnetic resonance images accurately reproduced the suppression of VA inducibility by CDCEXO. Strong anti-fibrotic effects of CDCEXO, evident histologically and by proteomic analysis from pig hearts, were confirmed in a co-culture assay of cardiomyocytes and fibroblasts. CONCLUSION: Biological substrate modification by exosome injection may be worth developing as a non-destructive alternative to conventional ablation for the prevention of recurrent ventricular tachyarrhythmias.


Asunto(s)
Cardiomiopatías , Ablación por Catéter , Isquemia Miocárdica , Taquicardia Ventricular , Animales , Arritmias Cardíacas/etiología , Arritmias Cardíacas/prevención & control , Cardiomiopatías/cirugía , Ablación por Catéter/métodos , Cicatriz/prevención & control , Humanos , Isquemia Miocárdica/cirugía , Isquemia Miocárdica/terapia , Proteómica , Porcinos , Taquicardia Ventricular/etiología , Taquicardia Ventricular/prevención & control
4.
J Electrocardiol ; 74: 122-127, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36183522

RESUMEN

BACKGROUND: Hypertrophic cardiomyopathy (HCM), a disease with myocardial fibrosis manifestation, is a common cause of sudden cardiac death (SCD) due to ventricular arrhythmias (VA). Current clinical risk stratification criteria are inadequate in identifying patients who are at risk for VA and in need of an implantable cardioverter defibrillator (ICD) for primary prevention. OBJECTIVE: We aimed to develop a risk prediction approach based on imaging biomarkers from the combination of late gadolinium contrast-enhanced (LGE) MRI and T1 mapping. We then aimed to compare the prediction to a virtual heart computational risk assessment approach based on LGE-T1 virtual heart models. METHODS: The methodology involved combining short-axis LGE-MRI with post-contrast T1 maps to define personalized thresholds for diffuse and dense fibrosis. The combined LGE-T1 maps were used to evaluate imaging biomarkers for VA risk prediction. The risk prediction capability of the biomarkers was compared with that of the LGE-T1 virtual heart arrhythmia inducibility simulation. VA risk prediction performance from both approaches was compared to clinical outcome (presence of clinical VA). RESULTS: Image-based biomarkers, including hypertrophy, signal intensity heterogeneity, and fibrotic border complexity, could not discriminate high vs low VA risk. LGE-T1 virtual heart technology outperformed all the image-based biomarker metrics and was statistically significant in predicting VA risk in HCM. CONCLUSIONS: We combined two MR imaging techniques to analyze imaging biomarkers in HCM. Raw and processed image-based biomarkers cannot discriminate patients with VA from those without VA. Hybrid LGE-T1 virtual heart models could correctly predict VA risk for this cohort and may improve SCD risk stratification to better identify HCM patients for primary preventative ICD implantation.


Asunto(s)
Cardiomiopatía Hipertrófica , Electrocardiografía , Humanos , Cardiomiopatía Hipertrófica/complicaciones , Cardiomiopatía Hipertrófica/diagnóstico por imagen , Imagen por Resonancia Magnética , Tecnología
5.
Pacing Clin Electrophysiol ; 44(12): 2067-2074, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34766627

RESUMEN

BACKGROUND: Patients with cardiac sarcoidosis (CS) are at increased risk of life-threatening ventricular arrhythmias (VA). Current approaches to risk stratification have limited predictive value. OBJECTIVES: To assess the utility of spatial dispersion analysis of late gadolinium enhancement cardiac magnetic resonance (LGE-CMR), as a quantitative measure of myocardial tissue heterogeneity, in risk stratifying patients with CS for VA and death. METHODS: Sixty two patients with CS underwent LGE-CMR. LGE images were segmented and dispersion maps of the left and right ventricles were generated as follows. Based on signal intensity (SI), each pixel was categorized as abnormal (SI ≥3SD above the mean), intermediate (SI 1-3 SD above the mean) or normal (SI <1SD above the mean); and each pixel was then assigned a value of 0 to 8 based on the number of adjacent pixels of a different category. Average dispersion score was calculated for each patient. The primary endpoint was VA during follow up. The composite of VA or death was assessed as a secondary endpoint. RESULTS: During 4.7 ± 3.5 years of follow up, six patients had VA, and five without documented VA died. Average dispersion score was significantly higher in patients with VA versus those without (0.87 ± 0.08 vs. 0.71 ± 0.16; p = .002) and in patients with events versus those without (0.83 ± 0.08 vs. 0.70 ± 0.16; p = .003). Patients at higher tertiles of dispersion score had a higher incidence of VA (p = .03) and the composite of VA or death (p = .01). CONCLUSIONS: Increased substrate heterogeneity, quantified by spatial dispersion analysis of LGE-CMR, may be helpful in risk-stratifying patients with CS for adverse events, including life-threatening arrhythmias.


Asunto(s)
Arritmias Cardíacas/diagnóstico por imagen , Arritmias Cardíacas/etiología , Imagen por Resonancia Magnética/métodos , Sarcoidosis/complicaciones , Sarcoidosis/diagnóstico por imagen , Medios de Contraste , Femenino , Gadolinio , Humanos , Interpretación de Imagen Asistida por Computador , Masculino , Persona de Mediana Edad , Medición de Riesgo
6.
Pacing Clin Electrophysiol ; 44(3): 432-441, 2021 03.
Artículo en Inglés | MEDLINE | ID: mdl-33527422

RESUMEN

INTRODUCTION: We recently developed two noninvasive methodologies to help guide VT ablation: population-derived automated VT exit localization (PAVEL) and virtual-heart arrhythmia ablation targeting (VAAT). We hypothesized that while very different in their nature, limitations, and type of ablation targets (substrate-based vs. clinical VT), the image-based VAAT and the ECG-based PAVEL technologies would be spatially concordant in their predictions. OBJECTIVE: The objective is to test this hypothesis in ischemic cardiomyopathy patients in a retrospective feasibility study. METHODS: Four post-infarct patients who underwent LV VT ablation and had pre-procedural LGE-CMRs were enrolled. Virtual hearts with patient-specific scar and border zone identified potential VTs and ablation targets. Patient-specific PAVEL based on a population-derived statistical method localized VT exit sites onto a patient-specific 238-triangle LV endocardial surface. RESULTS: Ten induced VTs were analyzed and 9-exit sites were localized by PAVEL onto the patient-specific LV endocardial surface. All nine predicted VT exit sites were in the scar border zone defined by voltage mapping and spatially correlated with successful clinical lesions. There were 2.3 ± 1.9 VTs per patient in the models. All five VAAT lesions fell within regions ablated clinically. VAAT targets correlated well with 6 PAVEL-predicted VT exit sites. The distance between the center of the predicted VT-exit-site triangle and nearest corresponding VAAT ablation lesion was 10.7 ± 7.3 mm. CONCLUSIONS: VAAT targets are concordant with the patient-specific PAVEL-predicted VT exit sites. These findings support investigation into combining these two complementary technologies as a noninvasive, clinical tool for targeting clinically induced VTs and regions likely to harbor potential VTs.


Asunto(s)
Ablación por Catéter/métodos , Isquemia Miocárdica/cirugía , Taquicardia Ventricular/cirugía , Anciano de 80 o más Años , Electrocardiografía , Estudios de Factibilidad , Femenino , Humanos , Masculino , Persona de Mediana Edad , Isquemia Miocárdica/diagnóstico por imagen , Modelación Específica para el Paciente , Estudios Retrospectivos , Taquicardia Ventricular/diagnóstico por imagen
7.
Biophys J ; 117(12): 2287-2294, 2019 12 17.
Artículo en Inglés | MEDLINE | ID: mdl-31447108

RESUMEN

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs' 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients.


Asunto(s)
Sistema de Conducción Cardíaco/fisiopatología , Infarto del Miocardio/fisiopatología , Modelación Específica para el Paciente , Humanos , Modelos Cardiovasculares , Interfaz Usuario-Computador
8.
Pediatr Cardiol ; 40(4): 857-864, 2019 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-30840104

RESUMEN

Children with myocarditis have increased risk of ventricular tachycardia (VT) due to myocardial inflammation and remodeling. There is currently no accepted method for VT risk stratification in this population. We hypothesized that personalized models developed from cardiac late gadolinium enhancement magnetic resonance imaging (LGE-MRI) could determine VT risk in patients with myocarditis using a previously-validated protocol. Personalized three-dimensional computational cardiac models were reconstructed from LGE-MRI scans of 12 patients diagnosed with myocarditis. Four patients with clinical VT and eight patients without VT were included in this retrospective analysis. In each model, we incorporated a personalized spatial distribution of fibrosis and myocardial fiber orientations. Then, VT inducibility was assessed in each model by pacing rapidly from 26 sites distributed throughout both ventricles. Sustained reentrant VT was induced from multiple pacing sites in all patients with clinical VT. In the eight patients without clinical VT, we were unable to induce sustained reentry in our simulations using rapid ventricular pacing. Application of our non-invasive approach in children with myocarditis has the potential to correctly identify those at risk for developing VT.


Asunto(s)
Ventrículos Cardíacos/diagnóstico por imagen , Imagenología Tridimensional/métodos , Imagen por Resonancia Cinemagnética/métodos , Miocarditis/complicaciones , Taquicardia Ventricular/diagnóstico por imagen , Adolescente , Niño , Simulación por Computador , Femenino , Gadolinio , Ventrículos Cardíacos/fisiopatología , Humanos , Masculino , Proyectos Piloto , Estudios Retrospectivos , Medición de Riesgo/métodos , Taquicardia Ventricular/etiología
9.
Europace ; 18(suppl 4): iv60-iv66, 2016 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-28011832

RESUMEN

AIM: To predict arrhythmia susceptibility in myocardial infarction (MI) patients with left ventricular ejection fraction (LVEF) >35% using a personalized virtual heart simulation approach. METHODS AND RESULTS: A total of four contrast enhanced magnetic resonance imaging (MRI) datasets of patient hearts with MI and average LVEF of 44.0 ± 2.6% were used in this study. Because of the preserved LVEF, the patients were not indicated for implantable cardioverter defibrillator (ICD) insertion. One patient had spontaneous ventricular tachycardia (VT) prior to the MRI scan; the others had no arrhythmic events. Simulations of arrhythmia susceptibility were blind to clinical outcome. Models were constructed from patient MRI images segmented to identify myocardium, grey zone, and scar based on pixel intensity. Grey zone was modelled as having altered electrophysiology. Programmed electrical stimulation (PES) was performed to assess VT inducibility from 19 bi-ventricular sites in each heart model. Simulations successfully predicted arrhythmia risk in all four patients. For the patient with arrhythmic event, in-silico PES resulted in VT induction. Simulations correctly predicted that VT was non-inducible for the three patients with no recorded VT events. CONCLUSIONS: Results demonstrate that the personalized virtual heart simulation approach may provide a novel risk stratification modality to non-invasively and effectively identify patients with LVEF >35% who could benefit from ICD implantation.


Asunto(s)
Arritmias Cardíacas/etiología , Modelos Cardiovasculares , Infarto del Miocardio/complicaciones , Modelación Específica para el Paciente , Volumen Sistólico , Función Ventricular Izquierda , Potenciales de Acción , Adulto , Arritmias Cardíacas/diagnóstico , Arritmias Cardíacas/fisiopatología , Estimulación Cardíaca Artificial , Técnicas Electrofisiológicas Cardíacas , Estudios de Factibilidad , Femenino , Sistema de Conducción Cardíaco/fisiopatología , Frecuencia Cardíaca , Humanos , Imagen por Resonancia Magnética , Persona de Mediana Edad , Infarto del Miocardio/diagnóstico por imagen , Infarto del Miocardio/fisiopatología , Valor Predictivo de las Pruebas , Estudios Retrospectivos , Medición de Riesgo , Factores de Riesgo
10.
Heart Rhythm ; 21(1): 89-99, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-37871809

RESUMEN

Precision medicine is the vision of health care where therapy is tailored to each patient. As part of this vision, digital twinning technology promises to deliver a digital representation of organs or even patients by using tools capable of simulating personal health conditions and predicting patient or disease trajectories on the basis of relationships learned both from data and from biophysics knowledge. Such virtual replicas would update themselves with data from monitoring devices and medical tests and assessments, reflecting dynamically the changes in our health conditions and the responses to treatment. In precision cardiology, the concepts and initial applications of heart digital twins have slowly been gaining popularity and the trust of the clinical community. In this article, we review the advancement in heart digital twinning and its initial translation to the management of heart rhythm disorders.


Asunto(s)
Fibrilación Atrial , Humanos , Fibrilación Atrial/terapia , Corazón , Atención al Paciente
11.
Artículo en Inglés | MEDLINE | ID: mdl-38934970

RESUMEN

BACKGROUND: Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients after myocardial infarction. Radiofrequency catheter ablation (RFA) is a modestly effective treatment of VT, but it has limitations and risks. Cardiac magnetic resonance (CMR)-based heart digital twins have emerged as a useful tool for identifying VT circuits for RFA treatment planning. However, the CMR resolution used to reconstruct these digital twins may impact VT circuit predictions, leading to incorrect RFA treatment planning. OBJECTIVES: This study sought to predict RFA targets in the arrhythmogenic substrate using heart digital twins reconstructed from both clinical and high-resolution 2-dimensional CMR datasets and compare the predictions. METHODS: High-resolution (1.35 × 1.35 × 3 mm), or oversampled resolution (Ov-Res), short-axis late gadolinium-enhanced CMR was acquired by combining 2 subsequent clinical resolution (Clin-Res) (1.35 × 1.35 × 6 mm) short-axis late gadolinium-enhanced CMR scans from 6 post-myocardial infarction patients undergoing VT ablation and used to reconstruct a total of 3 digital twins (1 Ov-Res, 2 Clin-Res) for each patient. Rapid pacing was used to assess VT circuits and identify the optimal ablation targets in each digital twin. VT circuits predicted by the digital twins were compared with intraprocedural electroanatomic mapping data and used to identify emergent VT. RESULTS: The Ov-Res digital twins reduced partial volume effects and better predicted unique VT circuits compared with the Clin-Res digital twins (66.6% vs 54.5%; P < 0.01). Only the Ov-Res digital twin successfully identified emergent VT after a failed initial ablation. CONCLUSIONS: Digital twin infarct geometry and VT circuit predictions depend on the magnetic resonance resolution. Ov-Res digital twins better predict VT circuits and emergent VT, which may improve RFA outcomes.

12.
JACC Clin Electrophysiol ; 9(3): 301-310, 2023 03.
Artículo en Inglés | MEDLINE | ID: mdl-36752477

RESUMEN

BACKGROUND: Ventricular tachycardias (VTs) in patients with myocardial infarction (MI) are often treated with catheter ablation. However, the VT induction during this procedure does not always identify all of the relevant activation pathways or may not be possible or tolerated. The re-entry vulnerability index (RVI) quantifies regional activation-repolarization differences and can detect multiple regions susceptible to re-entry without the need to induce the arrhythmia. OBJECTIVES: This study aimed to further develop and validate the RVI mapping in patient-specific computational models of post-MI VTs. METHODS: Cardiac magnetic resonance imaging data from 4 patients with post-MI VTs were used to induce VTs in a computational electrophysiological model by pacing. The RVI map of a premature beat in each patient model was used to guide virtual ablations. We compared our results with those of clinical ablation in the same patients. RESULTS: Single-site virtual RVI-guided ablation prevented VT induction in 3 of 9 cases. Multisite virtual ablations guided by RVI mapping successfully prevented re-entry in all cases (9 of 9). Overall, virtual ablation required 15-fold fewer ablation sites (235.5 ± 97.4 vs 17.0 ± 6.8) and 2-fold less ablation volume (5.34 ± 1.79 mL vs 2.11 ± 0.65 mL) than the clinical ablation. CONCLUSIONS: RVI mapping allows localization of multiple regions susceptible to re-entry and may help guide VT ablation. RVI mapping does not require the induction of arrhythmia and may result in less ablated myocardial volumes with fewer ablation sites.


Asunto(s)
Ablación por Catéter , Infarto del Miocardio , Taquicardia Ventricular , Humanos , Taquicardia Ventricular/etiología , Taquicardia Ventricular/cirugía , Infarto del Miocardio/complicaciones , Infarto del Miocardio/cirugía , Corazón , Miocardio , Ablación por Catéter/efectos adversos , Ablación por Catéter/métodos
13.
medRxiv ; 2023 Aug 01.
Artículo en Inglés | MEDLINE | ID: mdl-37398074

RESUMEN

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes. This approach integrates the patient's disease-induced structural remodeling reconstructed from contrast-enhanced magnetic-resonance imaging and genotype-specific cellular EP properties. In our retrospective study of 16 ARVC patients with two genotypes: plakophilin-2 (PKP2, n = 8) and gene-elusive (GE, n = 8), we found that Geno-DT accurately and non-invasively predicted the VT circuit locations for both genotypes (with 100%, 94%, 96% sensitivity, specificity, and accuracy for GE patient group, and 86%, 90%, 89% sensitivity, specificity, and accuracy for PKP2 patient group), when compared to VT circuit locations identified during clinical EP studies. Moreover, our results revealed that the underlying VT mechanisms differ among ARVC genotypes. We determined that in GE patients, fibrotic remodeling is the primary contributor to VT circuits, while in PKP2 patients, slowed conduction velocity and altered restitution properties of cardiac tissue, in addition to the structural substrate, are directly responsible for the formation of VT circuits. Our novel Geno-DT approach has the potential to augment therapeutic precision in the clinical setting and lead to more personalized treatment strategies in ARVC.

14.
Artículo en Inglés | MEDLINE | ID: mdl-37287952

RESUMEN

Accurate quantification of left atrium (LA) scar in patients with atrial fibrillation is essential to guide successful ablation strategies. Prior to LA scar quantification, a proper LA cavity segmentation is required to ensure exact location of scar. Both tasks can be extremely time-consuming and are subject to inter-observer disagreements when done manually. We developed and validated a deep neural network to automatically segment the LA cavity and the LA scar. The global architecture uses a multi-network sequential approach in two stages which segment the LA cavity and the LA Scar. Each stage has two steps: a region of interest Neural Network and a refined segmentation network. We analysed the performances of our network according to different parameters and applied data triaging. 200+ late gadolinium enhancement magnetic resonance images were provided by the LAScarQS 2022 Challenge. Finally, we compared our performances for scar quantification to the literature and demonstrated improved performances.

15.
Elife ; 122023 10 18.
Artículo en Inglés | MEDLINE | ID: mdl-37851708

RESUMEN

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes. This approach integrates the patient's disease-induced structural remodeling reconstructed from contrast-enhanced magnetic-resonance imaging and genotype-specific cellular EP properties. In our retrospective study of 16 ARVC patients with two genotypes: plakophilin-2 (PKP2, n = 8) and gene-elusive (GE, n = 8), we found that Geno-DT accurately and non-invasively predicted the VT circuit locations for both genotypes (with 100%, 94%, 96% sensitivity, specificity, and accuracy for GE patient group, and 86%, 90%, 89% sensitivity, specificity, and accuracy for PKP2 patient group), when compared to VT circuit locations identified during clinical EP studies. Moreover, our results revealed that the underlying VT mechanisms differ among ARVC genotypes. We determined that in GE patients, fibrotic remodeling is the primary contributor to VT circuits, while in PKP2 patients, slowed conduction velocity and altered restitution properties of cardiac tissue, in addition to the structural substrate, are directly responsible for the formation of VT circuits. Our novel Geno-DT approach has the potential to augment therapeutic precision in the clinical setting and lead to more personalized treatment strategies in ARVC.


Asunto(s)
Displasia Ventricular Derecha Arritmogénica , Taquicardia Ventricular , Humanos , Displasia Ventricular Derecha Arritmogénica/genética , Estudios Retrospectivos , Taquicardia Ventricular/genética , Arritmias Cardíacas , Genotipo
16.
Nat Cardiovasc Res ; 1(10): 933-945, 2022 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-36589896

RESUMEN

Infiltrating adipose tissue (inFAT) has been recently found to co-localize with scar in infarcted hearts and may contribute to ventricular arrhythmias (VAs), a life-threatening heart rhythm disorder. However, the contribution of inFAT to VA has not been well-established. We investigated the role of inFAT versus scar in VA through a combined prospective clinical and mechanistic computational study. Using personalized computational heart models and comparing the results from simulations of VA dynamics with measured electrophysiological abnormalities during the clinical procedure, we demonstrate that inFAT, rather than scar, is a primary driver of arrhythmogenic propensity and is frequently present in critical regions of the VA circuit. We determined that, within the VA circuitry, inFAT, as opposed to scar, is primarily responsible for conduction slowing in critical sites, mechanistically promoting VA. Our findings implicate inFAT as a dominant player in infarct-related VA, challenging existing paradigms and opening the door for unexplored anti-arrhythmic strategies.

17.
Elife ; 112022 01 25.
Artículo en Inglés | MEDLINE | ID: mdl-35076018

RESUMEN

Hypertrophic cardiomyopathy (HCM) is associated with risk of sudden cardiac death (SCD) due to ventricular arrhythmias (VAs) arising from the proliferation of fibrosis in the heart. Current clinical risk stratification criteria inadequately identify at-risk patients in need of primary prevention of VA. Here, we use mechanistic computational modeling of the heart to analyze how HCM-specific remodeling promotes arrhythmogenesis and to develop a personalized strategy to forecast risk of VAs in these patients. We combine contrast-enhanced cardiac magnetic resonance imaging and T1 mapping data to construct digital replicas of HCM patient hearts that represent the patient-specific distribution of focal and diffuse fibrosis and evaluate the substrate propensity to VA. Our analysis indicates that the presence of diffuse fibrosis, which is rarely assessed in these patients, increases arrhythmogenic propensity. In forecasting future VA events in HCM patients, the imaging-based computational heart approach achieved 84.6%, 76.9%, and 80.1% sensitivity, specificity, and accuracy, respectively, and significantly outperformed current clinical risk predictors. This novel VA risk assessment may have the potential to prevent SCD and help deploy primary prevention appropriately in HCM patients.


Asunto(s)
Cardiomiopatía Hipertrófica/diagnóstico por imagen , Simulación por Computador , Imagen por Resonancia Magnética , Taquicardia Ventricular/etiología , Adulto , Anciano , Cardiomiopatía Hipertrófica/complicaciones , Cardiomiopatía Hipertrófica/patología , Cardiomiopatía Hipertrófica/fisiopatología , Muerte Súbita Cardíaca/etiología , Muerte Súbita Cardíaca/prevención & control , Femenino , Fibrosis , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Miocardio/patología , Valor Predictivo de las Pruebas , Estudios Retrospectivos , Medición de Riesgo , Factores de Riesgo , Taquicardia Ventricular/diagnóstico , Taquicardia Ventricular/fisiopatología , Taquicardia Ventricular/terapia , Adulto Joven
18.
Front Physiol ; 12: 740389, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34658925

RESUMEN

Aims: Disease-induced repolarization heterogeneity in infarcted myocardium contributes to VT arrhythmogenesis but how apicobasal and transmural (AB-TM) repolarization gradients additionally affect post-infarct VT dynamics is unknown. The goal of this study is to assess how AB-TM repolarization gradients impact post-infarct VT dynamics using patient-specific heart models. Method: 3D late gadolinium-enhanced cardiac magnetic resonance images were acquired from seven post-infarct patients. Models representing the patient-specific scar and infarct border zone distributions were reconstructed without (baseline) and with repolarization gradients along both the AB-TM axes. AB only and TM only models were created to assess the effects of each ventricular gradient on VT dynamics. VTs were induced in all models via rapid pacing. Results: Ten baseline VTs were induced. VT inducibility in AB-TM models was not significantly different from baseline (p>0.05). Reentry pathways in AB-TM models were different than baseline pathways due to alterations in the location of conduction block (p<0.05). VT exit sites in AB-TM models were different than baseline VT exit sites (p<0.05). VT inducibility of AB only and TM only models were not significantly different than that of baseline (p>0.05) or AB-TM models (p>0.05). Reentry pathways and VT exit sites in AB only and TM only models were different than in baseline (p<0.05). Lastly, repolarization gradients uncovered multiple VT morphologies with different reentrant pathways and exit sites within the same structural, conducting channels. Conclusion: VT inducibility was not impacted by the addition of AB-TM repolarization gradients, but the VT reentrant pathway and exit sites were greatly affected due to modulation of conduction block. Thus, during ablation procedures, physiological and pharmacological factors that impact the ventricular repolarization gradient might need to be considered when targeting the VTs.

19.
Comput Biol Med ; 133: 104366, 2021 06.
Artículo en Inglés | MEDLINE | ID: mdl-33836448

RESUMEN

BACKGROUND: Recently, an augmented reality (AR) solution allows the physician to place the ablation catheter at the designated lesion site more accurately during cardiac electrophysiology studies. The improvement in navigation accuracy may positively affect ventricular tachycardia (VT) ablation termination, however assessment of this in the clinic would be difficult. Novel personalized virtual heart technology enables non-invasive identification of optimal lesion targets for infarct-related VT. This study aims to evaluate the potential impact of such catheter navigation accuracy improvement in virtual VT ablations. METHODS: 2 MRI-based virtual hearts with 2 in silico induced VTs (VT 1, VT 2) were included. VTs were terminated with virtual "ground truth" endocardial ablation lesions. 106 navigation error values that were previously assessed in a clinical study evaluating the improvement of ablation catheter navigation accuracy guided with AR (53 with, 53 without) were used to displace the "ground truth" ablation targets. The corresponding ablations were simulated based on these errors and VT termination for each simulation was assessed. RESULTS: In 54 VT 1 ablation simulations, smaller error with AR significantly resulted in more VT termination (25) compared to the error without AR (16) (P < 0.01). In 52 VT 2 ablation simulations, no significant difference was observed from error with (11) and without AR (13) (P = 0.58). The substrate characteristic may impact the effect of improved accuracy to an improved VT termination. CONCLUSION: Virtual heart shows that the increased catheter navigation accuracy provided by AR guidance can affect the VT termination.


Asunto(s)
Realidad Aumentada , Ablación por Catéter , Taquicardia Ventricular , Catéteres , Humanos , Taquicardia Ventricular/diagnóstico por imagen , Taquicardia Ventricular/cirugía , Resultado del Tratamiento
20.
Comput Biol Med ; 136: 104674, 2021 09.
Artículo en Inglés | MEDLINE | ID: mdl-34340126

RESUMEN

We developed a novel patient-specific computational model for the numerical simulation of ventricular electromechanics in patients with ischemic cardiomyopathy (ICM). This model reproduces the activity both in sinus rhythm (SR) and in ventricular tachycardia (VT). The presence of scars, grey zones and non-remodeled regions of the myocardium is accounted for by the introduction of a spatially heterogeneous coefficient in the 3D electromechanics model. This 3D electromechanics model is firstly coupled with a 2-element Windkessel afterload model to fit the pressure-volume (PV) loop of a patient-specific left ventricle (LV) with ICM in SR. Then, we employ the coupling with a 0D closed-loop circulation model to analyze a VT circuit over multiple heartbeats on the same LV. We highlight similarities and differences on the solutions obtained by the electrophysiology model and those of the electromechanics model, while considering different scenarios for the circulatory system. We observe that very different parametrizations of the circulation model induce the same hemodynamical considerations for the patient at hand. Specifically, we classify this VT as unstable. We conclude by stressing the importance of combining electrophysiological, mechanical and hemodynamical models to provide relevant clinical indicators in how arrhythmias evolve and can potentially lead to sudden cardiac death.


Asunto(s)
Cardiomiopatías , Ventrículos Cardíacos , Arritmias Cardíacas , Ventrículos Cardíacos/diagnóstico por imagen , Humanos
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