In silico optimization of left atrial appendage Occluder implantation using interactive and modeling tools

Altres ajuts: This work was supported by the Retos I+D Programme (DPI2015-71640-R).According to clinical studies, around one third of patients with atrial fibrillation (AF) will suffer a stroke during their lifetime. Between 70 and 90% of these strokes are caused by thrombus formed in the left atrial appendage. In patients with contraindications to oral anticoagulants, a left atrial appendage occluder (LAAO) is often implanted to prevent blood flow entering in the LAA. A limited range of LAAO devices is available, with different designs and sizes. Together with the heterogeneity of LAA morphology, these factors make LAAO success dependent on clinician's experience. A sub-optimal LAAO implantation can generate thrombi outside the device, eventually leading to stroke if not treated. The aim of this study was to develop clinician-friendly tools based on biophysical models to optimize LAAO device therapies. A web-based 3D interactive virtual implantation platform, so-called VIDAA, was created to select the most appropriate LAAO configurations (type of device, size, landing zone) for a given patient-specific LAA morphology. An initial LAAO configuration is proposed in VIDAA, automatically computed from LAA shape features (centreline, diameters). The most promising LAAO settings and LAA geometries were exported from VIDAA to build volumetric meshes and run Computational Fluid Dynamics (CFD) simulations to assess blood flow patterns after implantation. Risk of thrombus formation was estimated from the simulated hemodynamics with an index combining information from blood flow velocity and complexity. The combination of the VIDAA platform with in silico indices allowed to identify the LAAO configurations associated to a lower risk of thrombus formation; device positioning was key to the creation of regions with turbulent flows after implantation. Our results demonstrate the potential for optimizing LAAO therapy settings during pre-implant planning based on modeling tools and contribute to reduce the risk of thrombus formation after treatment

DNA methylation signatures of aggression and closely related constructs : A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 x 10(-7); Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.Peer reviewe

Genetic variation at 16q24.2 is associated with small vessel stroke.

OBJECTIVE: Genome-wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger-onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age-at-onset informed GWAS meta-analysis, including a large younger-onset SVS population, to identify novel associations with stroke. METHODS: We used a three-stage age-at-onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain. RESULTS: We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10-1.22]; p = 3.2 × 10-9 ). The lead single-nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05-1.16]; p = 5.3 × 10-5 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84-1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues (p = 9.4 × 10-7 ) and DNA methylation at probe cg16596957 in whole blood (p = 5.3 × 10-6 ). INTERPRETATION: 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383-394.Matthew Traylor is funded by the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. Hugh Markus is supported by an NIHR Senior Investigator award and his work is supported by NIHR Comprehensive Biomedical Research Unit funding awarded to Cambridge University Hospitals Trust. Cathryn Lewis receives salary support from the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. Collection of the UK Young Lacunar Stroke DNA Study (DNA Lacunar) was primarily supported by the Wellcome Trust (WT072952) with additional support from the Stroke Association (TSA 2010/01). Genotyping of the DNA Lacunar samples was supported by a Stroke Association Grant (TSA 2013/01). Robin Lemmens is a senior clinical investigator of FWO Flanders. Martin Dichgans received funding from the DFG (CRC 1123, B3) and a EU Horizon 2020 grant (agreement No 666881 SVDs@target). The TwinsUK study was funded in part by the European Research Council (ERC 250157), and from the TwinsUK resource, which receives support from the Wellcome Trust and the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. SNP Genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. The SiGN study was funded by a cooperative agreement grant from the US National Institute of Neurological Disorders and Stroke, National Institutes of Health (U01 NS069208)

DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.</p

Computational fluid simulations in clinical datasets for understanding thrombus formation before and after left atrial appendage occlusion

Atrial fibrillation is considered the most common arrhythmia in humans. Because the left atrium of the heart stops beating properly and begins to do so in an arrhythmic manner, the blood may become stagnant in a small cavity attached to the left atrium called the left atrium. If this happens, a thrombus forms in this cavity which can lead to an stroke. One of the possible treatments, especially if the patient has contraindications to anticoagulants is the closure of the left atrial appendage with a device introduced non-invasively. However, the reason why some shapes of left atrial appendages form a thrombus or not, or why after the intervention some patients form them on the device surface is not entirely clear. Blood velocity is known to be one of the most important factors in the process of thrombogenesis, but current imaging techniques do not have enough resolution to assess flow so locally. For this reason flow simulations based on computational fluid dynamics and numerical methods, already used in other sectors of the industry (e.g. aeronautics or automotive), could be used to predict which patients will form thrombus or not in a personalized manner. The thesis below aims to help clarify the role of flow in the thrombus formation process in patients with atrial fibrillation using computational fluid dynamics simulations personalized to each patient. To do this, the thesis is divided into three main contributions. First, a sensitivity analysis to test all the approaches published so far and new methods developed during the course of this thesis. Second, it will be shown how pulmonary veins, an understudied factor, have a key role in the hemodynamics of flow within the left atrium and therefore in thrombus formation along with other cavity morphological factors using the largest simulated cohort of patients to this date. Finally, it will be shown how the position of the device is key when creating local flow re-circulations at low velocities which can then activate the coagulation process forming a thrombus.La fibril·lació auricular esta considerada la arítmia més comuna en humans. Degut a que la aurícula esquerra del cor deixa de bategar correctament i ho comenc¸a fer de una forma arítmica, la sang es pot quedar estancada en una petita cavitat adjunta a la aurícula esquerra anomenada orelleta esquerra. Si això passa, es forma un trombe en aquesta cavitat que pot derivar en una embòlia. Un dels possibles tractaments, sobretot si el pacient té contraindicació als anticoagulants es el tancament de la orelleta esquerra amb un dispositiu introdïıt de manera no-invasiva. Tot i així, el motiu per el qual algunes orelletes formen trombe o no, o perquè després de la intervenció alguns pacients en formen sobre la superfície dispositiu no esta del tot clar. Se sap que la velocitat de la sang es un dels factors més importants en el procés de trombogénesis, però les actuals tècniques d’imatge no tenen prou resolució per avaluar el flux de forma tant local. Per aquest motiu les simulacions de flux basades en la din`amica de fluids computacional i en mètodes numèrics, ja utilitzades en altres sectors de la industria (p. e. aeronàutica o automobilística), podrien arribar a predir quins pacients formaran trombe o no de forma personalitzada. La tesis que trobareu a continuació intenta ajudar a esclarir el paper del flux en el procés de formació de trombe en pacients amb fibril·lació auricular utilitzant simulacions de dinàmica de fluid computacional personalitzades a cada pacient. Per fer-ho, la tesis es divideix en tres aportacions principals. En primer lloc, anàlisis sensitius, per testejar tots els mètodes provats fins ara i a on també es provaran mètodes nous desenvolupats durant el transcurs d’aquesta tesis. Segon, es mostrarà com les venes pulmonars, un factor molt poc estudiat, tenen un paper clau en la hemodinàmica del flux dintre de l’aurícula esquerra i per tant, en la formació de trombe juntament amb altres factors morfològics de la cavitat utilitzant el cohort de pacients simulat més gran fins el dia d’avui. Per últim, es mostrarà com la posició del dispositiu es clau a la hora de crear recirculacions de flux local a velocitats baixes que després poden activar el procés de coagulació formant un trombe.Programa de doctorat en Tecnologies de la Informació i les Comunicacion

Towards real-time optimization of left atrial appendage occlusion device placement through physics-informed neural networks

Comunicació presentada a 13th International Workshop, STACOM 2022, conjuntament amb MICCAI 2022, celebrada el 18 de setembre de 2022 a Singapur.The adoption of patient-specific computational fluid dynamics (CFD) simulations has been instrumental toward a better understanding of the mechanisms underlying thrombogenesis in the left atrial appendage. Such simulations can help optimize the placement of left atrial appendage occlusion (LAAO) devices in atrial fibrillation patients and avoid the generation of device-related thrombosis. However, integrating conventional solvers into clinical practice is cumbersome, as even the slightest change in model geometry involves computing the entire simulation from scratch. In contrast, neural networks can entirely circumvent this issue by transferring knowledge across models targeted at similar physical domains. Thus, in the present study, we introduced a neural network capable of predicting left atrial hemodynamics under different occlusion device configurations, relying solely on a single finite element simulation for training. To this end, we leveraged physics-informed neural networks (PINN), which embed the physical laws governing the domain of interest into the model, exhibiting far superior generalization capabilities than conventional data-driven models. Several device types and positions have been tested in two distinct left atrial geometries. By employing a single reference simulation per patient the network can predict the updated hemodynamics for a variety of device types and positions, orders of magnitude faster than with conventional CFD solvers.This work was funded by the Agency for Management of University and Research Grants of the Generalitat de Catalunya under the Grants for the Contracting of New Research Staff Programme - FI (2020 FI_B 00608) and the Spanish Ministry of Economy and Competitiveness under the Programme for the Formation of Doctors (PRE2018-084062), and the Retos Investigación project (RTI2018-101193-B-I00), and the H2020 EU SimCardioTest project (Digital transformation in Health and Care SC1-DTH-06-2020; grant agreement No. 101016496). Additionally, this research was supported by grants from NVIDIA and utilized NVIDIA RTX A6000

Impact of blood rheological strategies on the optimization of patient-specific LAAO configurations for thrombus assessment

Comunicació presentada a 12th International Conference, Functional Imaging and Modeling of the Heart, FIMH 2023, celebrada del 19 al 22 de juny de 2023 a Lió, França.Left atrial appendage occlusion devices (LAAO) are a feasible alternative for non-valvular atrial fibrillation (AF) patients at high risk of thromboembolic stroke and contraindication to antithrombotic therapies. However, optimal LAAO device configurations (i.e., size, type, location) remain unstandardized due to the large anatomical variability of the left atrial appendage (LAA) morphology, leading to a 4–6% incidence of device-related thrombus (DRT). In-silico simulations can be used to estimate the risk of DRT and identify the critical parameters, such as suboptimal device positioning. However, simulation outcomes depend a lot on a series of modelling assumptions such as blood behaviour. Therefore, in this work, we present fluid simulations results computed on two patient-specific LA geometries, using two different commercially available LAAO devices, located in two positions: 1) mimicking the real post-LAAO intervention configuration; and 2) an improved one better covering the pulmonary ridge for DRT prevention. Different blood modeling strategies were also tested. The results show flow re-circulations at low velocities with significant platelet accumulation in LAA-deep device positioning uncovering the pulmonary ridge, potentially leading to thrombus formation. In addition, assuming Newtonian blood behaviour may result in an overestimation of DRT risk.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement, No 101016496 (SimCardioTest)

Patient-specific flow simulation analysis to predict device-related thrombosis in left atrial appendage occluders

Introduction and objectives: Left atrial appendage occlusion (LAAO) can be an efficient treatment to prevent strokes in patients who suffer from atrial fibrillation, especially those at risk of bleeding. A non-negligible number of patients treated with LAAO develop device-related thrombosis (DRT) after device implantation. Our study aimed to identify the key blood flow characteristics leading to DRT using patient-specific flow simulations. Methods: Patients treated with LAAO between 2014 and 2019 at a single center with preoperative and follow-up computerized tomography images and ultrasound imaging (US) were used to create patient-specific flow simulations. Amulet LAAO devices were implanted in the study patients. Flow simulations were blindly assessed to discard the presence of DRT in the follow-up imaging. Results: A total of 6 patients were processed in this pivotal study, half of them with DRT at the follow-up according to the imaging analysis. After a comprehensive analysis of the simulations, the most relevant in silico indices associated with DRT were the presence of stagnant blood flow, recirculation with low flow velocities (< 0.20 m/s) next to the device surface, and regions with high flow complexity combined with low wall shear stress. Conclusions: Patient-specific flow simulations of LAAO were successfully used to predict blood flow patterns with different device configurations. The results show the potential of the present modelling and simulation approach to recommend optimal settings capable of minimizing the risk of DRT.Introducción y objetivos: El cierre de la orejuela izquierda (COI) puede ser una alternativa de tratamiento eficaz para prevenir eventos cardiovasculares en pacientes con fibrilación auricular, en especial en aquellos con alto riesgo de sangrado. Sin embargo, algunos de estos pacientes en los que se realiza COI desarrollan trombosis relacionada con el dispositivo (TRD). Este estudio presenta las características del flujo sanguíneo que son clave en la formación de TDR, a partir de simulaciones personalizadas para cada paciente. Métodos: Para crear las simulaciones personalizadas se incluyeron en el estudio pacientes intervenidos de COI entre 2014 y 2019 en un único centro, de quienes se disponía de imágenes de tomografía computarizada previas al procedimiento y de seguimiento, así como de control ecocardiográfico. Para el COI se utilizaron los dispositivos Amulet. Las simulaciones se analizaron de forma ciega al diagnóstico de TRD. Resultados: En total se estudiaron 6 pacientes, de los que la mitad presentaban TRD según las imágenes del seguimiento clínico. Tras analizar los resultados de las simulaciones, los índices hemodinámicos asociados con TRD fueron la presencia de flujo estancado, las recirculaciones de sangre a velocidades bajas (< 0,20 m/s) cerca de la superficie del dispositivo y las regiones con alta complejidad de flujo y baja tensión de cizallamiento en la pared. Conclusiones: Las simulaciones de flujo personalizadas en pacientes con COI predijeron correctamente el diagnóstico clínico de TRD en todos los casos analizados. Los resultados obtenidos demuestran el potencial de los modelos personalizados para recomendar configuraciones óptimas del dispositivo y minimizar el riesgo de TRD.This work was supported by the Spanish Ministry of Science, Innovation and Universities under the Retos I+D (RTI2018-101193-B-I00), the Maria de Maeztu Units of Excellence (MDM-2015-0502), the Formation of Doctors (PRE2018-084062) and the Recruitment of Talents (RYC-2015-18888) programmes

Geometric deep learning for the assessment of thrombosis risk in the left atrial appendage

Comunicació presentada a: FIMH 2021 11th International Conference, celebrada a Stanford, CA, USA, del 21 al 25 de juny de 2021.The assessment of left atrial appendage (LAA) thrombogenesis has experienced major advances with the adoption of patient-specific computational fluid dynamics (CFD) simulations. Nonetheless, due to the vast computational resources and long execution times required by fluid dynamics solvers, there is an ever-growing body of work aiming to develop surrogate models of fluid flow simulations based on neural networks. The present study builds on this foundation by developing a deep learning (DL) framework capable of predicting the endothelial cell activation potential (ECAP), linked to the risk of thrombosis, solely from the patient-specific LAA geometry. To this end, we leveraged recent advancements in Geometric DL, which seamlessly extend the unparalleled potential of convolutional neural networks (CNN), to non-Euclidean data such as meshes. The model was trained with a dataset combining 202 synthetic and 54 real LAA, predicting the ECAP distributions instantaneously, with an average mean absolute error of 0.563. Moreover, the resulting framework manages to predict the anatomical features related to higher ECAP values even when trained exclusively on synthetic cases.This work was supported by the Agency for Management of University and Research Grants of the Generalitat de Catalunya under the the Grants for the Contracting of New Research Staff Programme - FI (2020 FI B 00608) and the Spanish Ministry of Economy and Competitiveness under the Programme for the Formation of Doctors (PRE2018-084062), the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502) and the Retos Investigaci´on project (RTI2018-101193-B-I00). Additionally, this work was supported by the H2020 EU SimCardioTest project (Digital transformation in Health and Care SC1- DTH-06-2020; grant agreement No. 101016496)