186 research outputs found
Differentiation of Pre-Ablation and Post-Ablation Late Gadolinium-Enhanced Cardiac MRI Scans of Longstanding Persistent Atrial Fibrillation Patients
Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is an emerging non-invasive technique to image and quantify preablation native and post-ablation atrial scarring. Previous studies have reported that enhanced image intensities of the atrial scarring in the LGE CMRI inversely correlate with the left atrial endocardial voltage invasively obtained by electro-anatomical mapping. However, the reported reproducibility of using LGE CMRI to identify and quantify atrial scarring is variable. This may be due to two reasons: first, delineation of the left atrium (LA) and pulmonary veins (PVs) anatomy generally relies on manual operation that is highly subjective, and this could substantially affect the subsequent atrial scarring segmentation; second, simple intensity based image features may not be good enough to detect subtle changes in atrial scarring. In this study, we hypothesized that texture analysis can provide reliable image features for the LGE CMRI images subject to accurate and objective delineation of the heart anatomy based on a fully-automated whole heart segmentation (WHS) method. We tested the extracted texture features to differentiate between pre-ablation and post-ablation LGE CMRI studies in longstanding persistent atrial fibrillation patients. These patients often have extensive native scarring and differentiation from post-ablation scarring can be difficult. Quantification results showed that our method is capable of solving this classification task, and we can envisage further deployment of this texture analysis based method for other clinical problems using LGE CMRI.</p
Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is commonly
used to visualize and quantify left atrial (LA) scars. The position and extent
of scars provide important information of the pathophysiology and progression
of atrial fibrillation (AF). Hence, LA scar segmentation and quantification
from LGE MRI can be useful in computer-assisted diagnosis and treatment
stratification of AF patients. Since manual delineation can be time-consuming
and subject to intra- and inter-expert variability, automating this computing
is highly desired, which nevertheless is still challenging and
under-researched.
This paper aims to provide a systematic review on computing methods for LA
cavity, wall, scar and ablation gap segmentation and quantification from LGE
MRI, and the related literature for AF studies. Specifically, we first
summarize AF-related imaging techniques, particularly LGE MRI. Then, we review
the methodologies of the four computing tasks in detail, and summarize the
validation strategies applied in each task. Finally, the possible future
developments are outlined, with a brief survey on the potential clinical
applications of the aforementioned methods. The review shows that the research
into this topic is still in early stages. Although several methods have been
proposed, especially for LA segmentation, there is still large scope for
further algorithmic developments due to performance issues related to the high
variability of enhancement appearance and differences in image acquisition.Comment: 23 page
Markers of Left Atrial Fibrosis in Atrial Fibrillation and Prediction of Successful Rhythm Control Intervention
Introduction
Methods to restore atrial fibrillation (AF) to sinus rhythm include catheter ablation and electrical cardioversion. Myocardial fibrosis is associated with recurrence and may be measurable using circulating biomarkers. Other methods include cardiac magnetic resonance (CMR) and electro-anatomical mapping. The aims were: 1) Compare biomarkers in AF patients and controls. 2) Assess biomarker levels at multiple sampling sites. 3) Determine associations between methods of fibrosis quantification. 4) Determine their predictive value for arrhythmia recurrence.
Methods
93 AF ablation patients, 79 cardioversion patients, and 40 control patients were enrolled. Enzyme-linked immunosorbent assay was used to determine peripheral serum levels of galectin-3 (gal-3), type I collagen C terminal peptide (ICTP), type III procollagen N terminal peptide (PIIINP), and fibroblast growth factor 23 (FGF-23). Additionally, in ablation patients, levels were measured in the coronary sinus and both atria. 31 ablation patients underwent CMR. Follow up was 12 months.
Results
ICTP levels were higher in ablation patients than in controls (p=0.007). Peripheral ICTP levels were higher than intracardiac levels (p<0.001), and CS levels were higher than atrial levels (p<0.001). Peripheral gal-3 levels were higher than left atrial levels (p=0.001). FGF-23 was weakly predictive of AF recurrence after cardioversion (HR 1.003 p=0.012). No other biomarkers predicted AF recurrence. Low voltage in the left atrium was the only independent predictor of AF recurrence, mapped in sinus rhythm (HR 4.323 p=0.014) or AF (HR 5.195 p=0.046). LV extracellular volume was associated with LA pressure (beta 0.49, P=0.008) and coronary sinus ICTP (beta 0.75, P<0.001).
Conclusion
There is no clinically useful predictive effect of the biomarkers in this study. Further research into FGF-23 is warranted. Associations between LV extracellular volume, ICTP and LA pressure may suggest elevated ventricular myocardial turnover of type I collagen in this cohort, and a possible link with atrial pathology
Doctor of Philosophy
dissertationAtrial fibrillation (AF) is the leading cause of ischemic stroke and is the most commonly observed arrhythmia in clinical cardiology. Catheter ablation of AF, in which specific regions of cardiac anatomy associated with AF are intenionally injured to create scar tissue, has been honed over the last 15 years to become a relatively common and safe treatment option. However, the success of these anatomically driven ablation strategies, particularly in hearts that have been exposed to AF for extended periods, remains poor. AF induces changes in the electrical and structural properties of the cardiac tissue that further promotes the permanence of AF. In a process known as electroanatomical (EAM) mapping, clinicians record time signals known as electrograms (EGMs) from the heart and the locations of the recording sites to create geometric representations, or maps, of the electrophysiological properties of the heart. Analysis of the maps and the individual EGM morphologies can indicate regions of abnormal tissue, or substrates that facilitate arrhythmogenesis and AF perpetuation. Despite this progress, limitations in the control of devices currently used for EAM acquisition and reliance on suboptimal metrics of tissue viability appear to be hindering the potential of treatment guided by substrate mapping. In this research, we used computational models of cardiac excitation to evaluate param- eters of EAM that affect the performance of substrate mapping. These models, which have been validated with experimental and clinical studies, have yielded new insights into the limitations of current mapping systems, but more importantly, they guided us to develop new systems and metrics for robust substrate mapping. We report here on the progress in these simulation studies and on novel measurement approaches that have the potential to improve the robustness and precision of EAM in patients with arrhythmias. Appropriate detection of proarrhythmic substrates promises to improve ablation of AF beyond rudimentary destruction of anatomical targets to directed targeting of complicit tissues. Targeted treatment of AF sustaining tissues, based on the substrate mapping approaches described in this dissertation, has the potential to improve upon the efficacy of current AF treatment options
Estimation of Atrial Electrical Complexity during Atrial Fibrillation by Solving the Inverse Problem of Electrocardiography
Tesis por compendio[ES] La fibrilación auricular (FA) es la arritmia más prevalente en el mundo y está asociada con una
elevada morbilidad, mortalidad y costes sanitarios. A pesar de los avances en opciones de
tratamiento farmacológico y terapia de ablación, el manejo de la FA todavía tiene margen de
mejora. La imagen electrocardiográfica (ECGI) se ha destacado como un prometedor método no
invasivo para evaluar la electrofisiología cardíaca y guiar las decisiones terapéuticas en casos de
fibrilación auricular. No obstante, el ECGI se enfrenta a desafíos como la necesidad de resolver
de manera precisa el denominado problema inverso de la electrocardiografía y de optimizar la
calidad de las reconstrucciones de ECGI. Además, la integración del ECGI en los procesos
clínicos rutinarios sigue siendo un reto, en gran medida debido a los costos que supone la
necesidad de imágenes cardíacas.
Por ello, los objetivos principales de esta tesis doctoral son impulsar la tecnología ECGI
mediante la determinación de sus requisitos técnicos mínimos y la mejora de las metodologías
existentes para obtener señales de ECGI precisas. Asimismo, buscamos evaluar la capacidad de
ECGI para cuantificar de forma no invasiva la complejidad de la FA. Para lograr estos objetivos,
se han llevado a cabo diversos estudios a lo largo de la tesis, desde el perfeccionamiento del ECGI
hasta la evaluación de la FA utilizando esta tecnología.
En primer lugar, se han estudiado los requisitos geométricos y de señal del problema inverso
mediante el estudio de los efectos de la densidad de la malla del torso y la distribución de
electrodos en la precisión del ECGI, lo que ha conducido a la identificación del número mínimo
de nodos y su distribución en la malla del torso. Además, hemos identificado que para obtener
señales de ECGI de alta calidad, es crucial la correcta disposición de los electrodos en la malla
del torso reconstruido. Asimismo, se ha definido y evaluado una nueva metodología de ECGI sin
necesidad de usar técnicas de imagen cardiaca. Para ello, hemos comparado métricas derivadas
del ECGI calculadas con la geometría original del corazón de los pacientes con las métricas
medidas en diferentes geometrías cardíacas. Nuestros resultados han mostrado que el ECGI sin
necesidad de imágenes cardíacas es efectivo para la correcta cuantificación y localización de los
patrones y zonas que mantienen la FA. En paralelo, hemos optimizado la regularización de
Tikhonov de orden cero actual y la optimización de la curva L para el cálculo de las señales ECGI,
investigando cómo el ruido eléctrico y las incertidumbres geométricas influyen en la
regularización. A partir de ello, propusimos un nuevo criterio que realza la precisión de las
soluciones de ECGI en escenarios con incertidumbre debido a condiciones de señal no ideales.
En segundo lugar, en esta tesis doctoral, se han llevado a cabo múltiples análisis relativos a
diferentes metodologías de procesado de señales y obtención métricas derivadas del ECGI con el
fin de caracterizar mejor el sustrato cardíaco y la actividad reentrante en las señales de ECGI de
pacientes con FA. Con el objetivo de obtener una comprensión más profunda de los mecanismos
electrofisiológicos subyacentes a la FA, hemos establecido la estrategia de filtrado óptima para
extraer patrones reentrantes específicos del paciente y métricas derivadas de señales ECGI.
Además, hemos investigado la reproducibilidad de los mapas de reentradas derivados de las
señales de ECGI y hemos encontrado su relación con el éxito de la ablación de venas pulmonares
(PVI). Nuestros resultados han mostrado que una mayor reproducibilidad en los patrones
reentrantes de FA detectados con ECGI está relacionada con el éxito de la PVI, creando una
metodología para estratificar a los pacientes con FA antes de los procedimientos de ablación.[CA] La fibril·lació auricular (FA) és l'arrítmia més prevalent al món i està associada amb una elevada
morbiditat, mortalitat i costos sanitaris. Malgrat els avanços en opcions de tractament
farmacològic i teràpies d'ablació, el maneig de la FA encara té marge de millora. La imatge
electrocardiogràfica (ECGI) s'ha destacat com un prometedor mètode no invasiu per a avaluar
l'electrofisiologia cardíaca i guiar les decisions terapèutiques en casos de fibril·lació auricular. No
obstant això, l'ECGI s'enfronta a desafiaments com la necessitat de resoldre de manera precisa el
denominat problema invers de la electrocardiografia i d'optimitzar la qualitat de les
reconstruccions de ECGI. A més, la integració del ECGI en els processos clínics rutinaris continua
sent un repte, en gran manera a causa dels costos que suposa la necessitat d'imatges cardíaques.
Per això, els objectius principals d'aquesta tesi doctoral són impulsar la tecnologia de l'ECGI
mitjançant la determinació dels seus requisits tècnics mínims i la millora de les metodologies
existents per obtenir senyals d'ECGI precises. A més, busquem avaluar la capacitat de l'ECGI per
quantificar de forma no invasiva la complexitat de la FA. Per a aconseguir aquests objectius, s'han
dut a terme diversos estudis al llarg de la tesi, des del perfeccionament de l'ECGI fins a l'avaluació
de la FA utilitzant aquesta tecnologia.
En primer lloc, hem estudiat els requisits geomètrics i de senyal del problema invers mitjançant
l'estudi dels efectes de la densitat de la malla del tors i la distribució d'elèctrodes en la precisió de
l'ECGI, el que ha conduït a la identificació del nombre mínim de nodes i la seva distribució en la
malla del tors. A més, hem identificat que per obtindre senyals d'ECGI d'alta qualitat, és crucial
la correcta disposició dels elèctrodes en la malla del tors reconstruïda. També s'ha definit i avaluat
una nova metodologia d'ECGI sense necessitat d'utilitzar tècniques d'imatge cardíaca. Per a això,
hem comparat mètriques derivades de l'ECGI calculades amb la geometria original del cor dels
pacients amb les mètriques mesurades en diferents geometries cardíaques. Els nostres resultats
han mostrat que l'ECGI sense necessitat d'imatges cardíaques és efectiu per a la correcta quantificació
i localització dels patrons i zones que mantenen la FA. Paral·lelament, hem
optimitzat la regularització de Tikhonov d'ordre zero actual i l'optimització de la corba L per al
càlcul de les senyals d'ECGI, investigant com el soroll elèctric i les incerteses geomètriques
influeixen en la regularització. Addicionalment, vam proposar un nou criteri que reforça la
precisió de les solucions d'ECGI en escenaris amb incertesa degut a condicions de senyal no
ideals.
En segon lloc, en aquesta tesi doctoral, s'han dut a terme múltiples anàlisis relatius a diferents
metodologies de processament de senyals i obtenció de mètriques derivades de l'ECGI amb
l'objectiu de caracteritzar millor el substrat cardíac i l'activitat reentrant en les senyals d'ECGI de
pacients amb FA. Amb l'objectiu d'obtindre una comprensió més profunda dels mecanismes
electrofisiològics subjacents a la FA, hem establert l'estratègia de filtrat òptima per extreure
patrons reentrants específics del pacient i mètriques derivades de senyals ECGI. A més, hem
investigat la reproductibilitat dels mapes de reentrades derivats de les senyals d'ECGI i hem trobat
la seva relació amb l'èxit de l'ablació de venes pulmonars (PVI). Els nostres resultats han mostrat
que una major reproductibilitat en els patrons reentrants de FA detectats amb ECGI està
relacionada amb l'èxit de la PVI, creant una metodologia per estratificar els pacients amb FA abans
dels procediments d'ablació.[EN] Atrial fibrillation (AF) is the most prevalent arrhythmia in the world and is associated with
significant morbidity, mortality, and healthcare costs. Despite advancements in pharmaceutical
treatment alternatives and ablation therapy, AF management remains suboptimal.
Electrocardiographic Imaging (ECGI) has emerged as a promising non-invasive method for
assessing cardiac electrophysiology and guiding therapeutic decisions in atrial fibrillation.
However, ECGI faces challenges in dealing with accurately resolving the ill-posed inverse
problem of electrocardiography and optimizing the quality of ECGI reconstructions. Additionally,
the integration of ECGI into clinical workflows is still a challenge that is hindered by the
associated costs arising from the need for cardiac imaging.
For this purpose, the main objectives of this PhD thesis are to advance ECGI technology by
determining the minimal technical requirements and refining existing methodologies for
acquiring accurate ECGI signals. In addition, we aim to assess the capacity of ECGI for noninvasively
quantifying AF complexity. To fulfill these objectives, several studies were developed
throughout the thesis, advancing from ECGI enhancement to AF evaluation using ECGI.
Firstly, geometric and signal requirements of the inverse problem were addressed by studying
the effects of torso mesh density and electrode distribution on ECGI accuracy, leading to the
identification of the minimal number of nodes and their distribution on the torso mesh. Besides,
we identified that the correct location of the electrodes on the reconstructed torso mesh is critical
for the accurate ECGI signal obtention. Additionally, a new methodology of imageless ECGI was
defined and assessed by comparing ECGI-derived drivers computed with the original heart
geometry of the patients to the drivers measured in different heart geometries. Our results showed
the ability of imageless ECGI to the correct quantification and location of atrial fibrillation
drivers, validating the use of ECGI without the need for cardiac imaging. Also, the current state
of-the-art zero-order Tikhonov regularization and L-curve optimization for computing ECGI
signals were improved by investigating the impact of electrical noise and geometrical
uncertainties on the regularization. We proposed a new criterion that enhances the accuracy and
reliability of ECGI solutions in situations with uncertainty from unfavorable signal conditions.
Secondly, in this PhD thesis, several analyses, signal processing methodologies, and ECGIderived
metrics were investigated to better characterize the cardiac substrate and reentrant activity
in ECGI signals from AF patients. With the objective of obtaining a deeper understanding of the
electrophysiological mechanisms underlying AF, we established the optimal filtering strategy to
extract patient-specific reentrant patterns and derived metrics in ECGI signals. Furthermore, we
investigated the reproducibility of the obtained ECGI-reentrant maps and linked them to the
success of PVI ablation. Our results showed that higher reproducibility on AF drivers detected
with ECGI is linked with the success of PVI, creating a proof-of-concept mechanism for
stratifying AF patients prior to ablation procedures.This work was supported by: Instituto de Salud Carlos III, and Ministerio de Ciencia e
Innovación (supported by FEDER Fondo Europeo de Desarrollo Regional DIDIMO PLEC2021-
007614, ESSENCE PID2020-119364RB-I00, and RYC2018- 024346B-750), EIT Health
(Activity code SAVE-COR 220385, EIT Health is supported by EIT, a body of the European
Union) and Generalitat Valenciana Conselleria d’Educació, Investigació, Cultura i Esport
(ACIF/2020/265 and BEFPI/2021/062).Molero Alabau, R. (2023). Estimation of Atrial Electrical Complexity during Atrial Fibrillation by Solving the Inverse Problem of Electrocardiography [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/199029Compendi
Personalized Multi-Scale Modeling of the Atria: Heterogeneities, Fiber Architecture, Hemodialysis and Ablation Therapy
This book targets three fields of computational multi-scale cardiac modeling. First, advanced models of the cellular atrial electrophysiology and fiber orientation are introduced. Second, novel methods to create patient-specific models of the atria are described. Third, applications of personalized models in basic research and clinical practice are presented. The results mark an important step towards the patient-specific model-based atrial fibrillation diagnosis, understanding and treatment
Automated algorithm-driven methods of localising drivers of persistent atrial fibrillation using atrial fibrillation cycle length and atrial fibrillation voltage
The assessment of atrial fibrillation cycle length has played a role in the development of atrial fibrillation ablation by pulmonary vein isolation (PVI) and has also been used to assess response to ablation. Areas of rapid rotational activity in the left atrium have been implied to act as drivers of persistent atrial fibrillation and several methods have been developed to identify these potential drivers. Unprocessed atrial fibrillation electrograms show large variation in cycle length and signal amplitude. Current methods of localising driver regions rely on complex pattern recognition and subjective assessment of operators. The main hypotheses of this thesis were as follows: 1) a technique can be developed to ascertain a clinically relevant, dominant cycle length for any AF segment, 2) the automated technique, can be used to map rapid and regular activity in the left atrium, 3) a patient-tailored definition of rapid activity and low AF voltage, calculated based on patient-specific parameters is feasible; 4) paired with automated low voltage substrate analysis, dominant cycle length analysis is able to provide a framework for localising drivers of AF that is objective, transparent and requires no complex pattern recognition of subjective judgement.
To test the hypotheses, a technique was developed based on manual annotation of real-world AF electrograms that was able to ascertain cycle length independent of missing segments or variable cycle length or signal amplitude. Following this, an automated algorithm was validated to determine dominant cycle length.
In the following chapter, the nature of AF cycle length was investigated by investigating the patterns of rapid activity with extended AF segments and the concept of patient-tailored definitions of rapid activity was introduced.
In the subsequent analysis, the effect of PVI was examined on AF voltage and the AF cycle length, focusing on rapid and regular areas and low voltage zones, and their changes.
The last chapter utilised the accumulated information to test the sensitivity and specificity of a percentile-based, patient-tailored approach to low AF voltage and to present an objective, automated method of localising rapid and regular areas within low voltage zones within the left atrium.
In summary, it is feasible to assess and locate rapid and regular areas, and localise low voltage zones in persistent AF with a completely automated algorithm, and patient-tailored definitions of low voltage rapid AF activity are a preferable alternative to absolute cut offs.Open Acces
- …