942 research outputs found

    A compact multi-functional model of the rabbit atrioventricular node with dual pathways

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    The atrioventricular node (AVN) is considered a “black box”, and the functioning of its dual pathways remains controversial and not fully understood. In contrast to numerous clinical studies, there are only a few mathematical models of the node. In this paper, we present a compact, computationally lightweight multi-functional rabbit AVN model based on the Aliev-Panfilov two-variable cardiac cell model. The one-dimensional AVN model includes fast (FP) and slow (SP) pathways, primary pacemaking in the sinoatrial node, and subsidiary pacemaking in the SP. To obtain the direction-dependent conduction properties of the AVN, together with gradients of intercellular coupling and cell refractoriness, we implemented the asymmetry of coupling between model cells. We hypothesized that the asymmetry can reflect some effects related to the complexity of the real 3D structure of AVN. In addition, the model is accompanied by a visualization of electrical conduction in the AVN, revealing the interaction between SP and FP in the form of ladder diagrams. The AVN model demonstrates broad functionality, including normal sinus rhythm, AVN automaticity, filtering of high-rate atrial rhythms during atrial fibrillation and atrial flutter with Wenckebach periodicity, direction-dependent properties, and realistic anterograde and retrograde conduction curves in the control case and the cases of FP and SP ablation. To show the validity of the proposed model, we compare the simulation results with the available experimental data. Despite its simplicity, the proposed model can be used both as a stand-alone module and as a part of complex three-dimensional atrial or whole heart simulation systems, and can help to understand some puzzling functions of AVN

    Effects of BNP and LBQ657 + Valsartan on Atrial in-vitro Function in Human Myocardium

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    Hintergrund: Das Brain Natriuretic Peptide (BNP) gehört zur Gruppe der Natriuretischen Peptide (NPs). Am Myokard entfaltet es antifibrotische und antihypertrophe, an der Niere zudem die namensgebenden diuretischen Effekte. Mit dem Angiotensin-Rezeptor-Neprilysin-Inhibitor (ARNI) Sacubitril/Valsartan ist eine Substanz verfügbar, welche den endogenen Abbau der NPs vermindert. In Studien führte Sacubitril/Valsartan zu einer deutlichen Reduktion der Morbidität und Mortalität von Patient:innen mit Herzinsuffizienz mit reduzierter Pumpfunktion (HFrEF). Obwohl dieser Wirkmechanismus einen neuen Therapieansatz in der HFrEF-Behandlung darstellt, ist bisher nur wenig über den direkten Einfluss von BNP und ARNIs auf die atriale Myokardfunktion und Arrhythmogenese bekannt. In der vorliegenden Arbeit wird aus diesem Grund der Effekt einer BNP- und ARNI-Therapie auf die atriale funktionelle Reserve und Arrhythmogenese unter β-adrenerger Stimulation (Isoproterenol; ISO) in-vitro untersucht. Methoden und Ergebnisse: Im Rahmen von offenen Herzoperationen wurden N=42 Patient:innen atriale Biopsien entnommen, aus welchen n=101 Muskelstreifen-Präparate für Kontraktilitätsmessungen gewonnen wurden. Außerdem wurden atriale und ventrikuläre Biopsien von N=10 Patient:innen mit terminaler Herzinsuffizienz akquiriert und auf ihre Neprilysin (NEP)-Expression untersucht. BNP zeigte keine Kurzzeiteffekte auf die Kraftentwicklung im menschlichen Myokard unter ISO-Stimulation, reduzierte jedoch signifikant die diastolische Spannung der Muskelstreifen (ISO vs. ISO + BNP; p<0,01) und die Wahrscheinlichkeit für das Auftreten von Arrhythmien (Frequenzprotokoll: ISO vs. ISO + BNP insgesamt p<0,01). Darüber hinaus korrelierte der Plasma NT-proBNP-Spiegel der Patient:innen signifikant mit dem ISO-induzierten Kraftanstieg der Muskelstreifen (r=0,65; p<0,01). Für die aktive ARNI-Wirkstoffkombination LBQ657/Valsartan (LBQ/Val) zeigten sich keine Kurzzeiteffekte auf die kontraktile Funktion. Eine Reduktion arrhythmischer Ereignisse durch LBQ/Val, ähnlich zu BNP, wurde jedoch nachgewiesen. Weiterhin zeigten die Analysen, dass NEP in humanem atrialen und ventrikulären Myokard gleichermaßen exprimiert wird. Die rechtsatriale NEP-Expression korrelierte positiv mit der rechtsatrialen Auswurffraktion (r=0,806; p<0,05), die linksventrikuläre NEP-Expression korrelierte negativ mit dem linksatrialen Volumen (r= -0,691; p<0,05). Schlussfolgerungen: BNP bewirkte in humanem atrialen Myokard in-vitro keine kurzfristigen Effekte auf die ISO-vermittelte Inotropie, verringerte aber die diastolische Spannung. Die zunehmend auch in Studien beobachteten antiarrhythmischen Eigenschaften von ARNIs könnten basierend auf den Ergebnissen dieser Arbeit durch eine Verstärkung der parakrinen (B)NP-Wirkung bei LBQ/Val-Behandlung erklärt werden. Zudem scheint die myokardiale NEP-Expression im Rahmen eines kompensatorischen Mechanismus bei HFrEF mit fortschreitender Funktionseinschränkung herabreguliert zu werden.Background: Brain natriuretic peptide (BNP) is one of the central hormones in the natriuretic peptide (NP) group. It exerts antifibrotic and antihypertrophic effects on the myocardium and diuretic effects on the kidney (hence the name natriuretic peptides). With the angiotensin receptor-neprilysin inhibitor (ARNI) sacubitril/valsartan, a substance is available that reduces the endogenous degradation of NPs. In clinical studies, sacubitril/valsartan led to a significant reduction in morbidity and mortality in patients with heart failure with reduced ejection fraction (HFrEF). Although this mechanism of action represents a new therapeutic approach for HFrEF treatment, to date only little is known about the direct effects of BNP and ARNIs on atrial myocardial function and arrhythmogenesis. For this reason, the present work investigates the in-vitro effects of BNP and ARNI therapy on atrial functional reserve and arrhythmogenesis under β-adrenergic stimulation (by isoproterenol; ISO). Methods and Results: Atrial biopsies were obtained from N=42 patients during open heart surgery, from which n=101 muscle strip preparations were prepared for contractility measurements. In addition, atrial and ventricular biopsies were acquired from another N=10 patients with terminal heart failure and analyzed for neprilysin (NEP) expression. BNP exerted no short-term effects on force development in human myocardium under ISO stimulation, but significantly reduced diastolic tension of muscle strips (ISO vs. ISO + BNP; p<0.01) and the probability of arrhythmia induction (frequency protocol: ISO vs. ISO + BNP; pooled p<0.01). Furthermore, the patients’ plasma NT-proBNP levels significantly correlated with relative ISO-induced muscle strip force increase (r=0.65; p<0.01). Similarly to BNP, no short-term effects on contractile function for the pharmacologically active ARNI combination LBQ657/valsartan (LBQ/Val) were observed. However, a reduction of arrhythmic events by LBQ/Val, as seen with BNP, could be demonstrated. Furthermore, analyses revealed that NEP is equally expressed in human atrial and ventricular myocardium. Right atrial NEP expression correlated positively with right atrial ejection fraction (r=0.806; p<0.05), while left ventricular NEP expression correlated negatively with left atrial volume (r= -0.691; p<0.05). Conclusions: In-vitro, BNP did not facilitate additional short-term effects on ISO-mediated inotropy in human atrial myocardium, but reduced diastolic tension. The antiarrhythmic properties of ARNIs, which have also increasingly been observed in clinical studies, could be explained by an enhancement of the paracrine (B)NP effect by LBQ/Val treatment based on the results of this thesis. Moreover, myocardial NEP expression seemed to be downregulated as part of a compensatory mechanism in HFrEF in the course of progressive functional impairment

    A highly-detailed anatomical study of left atrial auricle as revealed by in-vivo computed tomography

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    The left atrial auricle (LAA) is the main source of intracardiac thrombi, which contribute significantly to the total number of stroke cases. It is also considered a major site of origin for atrial fibrillation in patients undergoing ablation procedures. The LAA is known to have a high degree of morphological variability, with shape and structure identified as important contributors to thrombus formation. A detailed understanding of LAA form, dimension, and function is crucial for radiologists, cardiologists, and cardiac surgeons.This review describes the normal anatomy of the LAA as visualized through multiple imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and echocardi-ography. Special emphasis is devoted to a discussion on how the morphological characteristics of the LAA are closely related to the likelihood of developing LAA thrombi, including insights into LAA embryology

    Utvrđivanje povezanosti genotipa i fenotipa hipertrofične kardiomiopatije primenom mašinskog učenja

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    Hypertrophic cardiomyopathy (HCM) is the most prevailing heritable cardiomyopathy. HCM is diagnosed by the existence of left ventricular hypertrophy despite the lack of abnormal loading conditions causing it. HCM is a heterogeneous disease regarding genetic mutations. Clinical manifestations and prognosis vary widely as well. Some patients are completely asymptomatic, in some others, severe heart failure and sudden cardiac death may arise. Definitive genotype-phenotype associations are still unknown. Machine learning (ML) is a subdiscipline of artificial intelligence, wherein computer algorithms are used for learning complex patterns from data. The aim of this research was to decipher genotype-phenotype associations in HCM using ML. The study was multi-centric and retroprospective, and involved 143 adult HCM patients. Medical and family history, anthropometric measurements, genetic testing, blood markers, transthoracic echocardiography with Doppler, cardiopulmonary exercise testing (CPET), ECG and ECG-holter-monitoring data were collected and further analysed. HCM subphenotypes were identified using clustering. Associations of genotype and phenotype were evaluated used Python modules Scikit-learn and SHapley Additive exPlanation (SHAP). Genotype-specific echocardiogram findings were identified using Python deep learning (DL) and computer vision library Fast AI, by generation of DL models for classification of ultrasonic images, and later analysis of the most decisive image regions. Four HCM subtypes were identified based on the overall phenotypic appearance: cluster 0 (“AHOLD”), distinguishable by aortic root diameter (AO) and lactate dehydrogenase (LDH), with values mostly AO > 30 mm, and LDH > 300 U/L; cluster 1 (“RVSP ASCAOVS”), distinguishable by right ventricle systolic pressure (RVSP), diameter of ascending aorta (AscAO), and aortic leaflet separation diameter (AOvs), with the values of RVSP 27 m/s; cluster 2 (“weight”), recognizable by weight, wherein values being mostly > 95 kg; and cluster 3 (“AV LVOT PG”) distinguishable by aortic valve mean pressure gradient (AV meanPG), aortic valve peak pressure gradient (AV maxPG), and left ventricular outflow tract peak gradient (LVOT maxPG) wherein AV maxPG > 15 mmHg, AV meanPG > 6 mmHg, and LVOT maxPG > 15 mmHg. ML algorithms confirmed that the determination of genotype-phenotype associations in HCM is a cumbersome task. Two phenotypic outcomes that can be predicted from mutated genes are the absence or presence of sinus rhythm and the absence or presence of myocardial injury. Models predicting the absence or presence of sinus rhythm had similar performance when they were built using only causative genes and when using all analyzed genes, indicating potential importance of causative genes and irrelevance of non-causative genes for that outcome. On the other hand, models predicting myocardial injury — infarction had better performance when they were built using all analyzed genes (and not just causative ones), indicating a potentially significant role of non-causative genes in that outcome. The ML algorithms were able to predict phenotypic outcomes — fatigue, dyspnea, chest pain, palpitations, syncope, heart murmur, pretibial edema, systolic anterior motion, papillary muscle abnormalities, hypokinesia, atrial fibrillation (AF), first-degree atrioventricular (AV) block, left bundle branch block (LBBB), right bundle branch block (RBBB), left anterior hemiblock, ST segment abnormalities, and negative T wave — using genotypic and phenotypic data. The combination of a mutation in TNNT2 and peak respiratory exchange ratio (RER) contributed the most in predicting fatigue. The combination of a mutation in MYBPC3 and peak VO2 contributed the most in predicting dyspnea. The combination of a mutation in TNNI3 and high-density lipoprotein (HDL) level contributed the most in predicting chest pain. The combination of a mutation in MYH7 and pacemaker/defibrillator implants in family history, as well as the combination of a mutation in TNNT2 and left atrial volume (LAV), contributed the most in predicting heart murmur. Lastly, the combination of a mutation in MYBPC3 and transmitral maximal pressure gradient (MV maxPG) aided the most in predicting negative T wave. Genotype-specific echocardiogram findings were identified: for mutations in the MYH7 gene (vs. mutation not detected), the most discriminative structures are the left ventricular outflow tract, septum, anterior wall, apex, right ventricle, and mitral apparatus; for mutations in the TNNT2 gene (vs. mutation not detected), the most discriminative structures are septum and right ventricle; while for mutations in MYBPC3 gene (vs. mutation not detected) these are septum, left ventricle, and left ventricle chamber. ML has thus been demonstrated to be useful in deciphering genotype-phenotype associations in HCM.Hipertrofična kardiomiopatija (HCM) je najčešća nasledna kardiomiopatija. Dijagnoza HCM se postavlja na osnovu prisustva hipertrofije leve komore, uz isključivanje drugih uzroka hipertrofije. U pogledu genetičkih mutacija, HCM je heterogena bolest. Kliničke manifestacije i prognoza takođe mogu da budu veoma različite. Kod nekih pacijenata HCM je potpuno asimptomatska, dok kod drugih mogu da se razviju teška srčana insuficijencija i iznenadna srčana smrt. Povezanost genotipa i fenotipa HCM još uvek nije u potpunosti utvrđena. Mašinsko učenje je subdisciplina veštačke inteligencije u kojoj se kompjuterski algoritmi koriste za učenje kompleksnih šablona iz podataka. Cilj ovog istraživanja je bilo utvrđivanje povezanosti genotipa i fenotipa HCM primenom mašinskog učenja. Studija je bila multicentrična i retroprospektivna, obuhvatila je 143 odrasla pacijenta sa potvrđenom dijagnozom HCM. Anamnestički podaci, antropometrijska merenja, rezultati genetičkog testiranja, biohemijskih analiza, nalazi transtorakalne ehokardiografije sa doplerom, kardiopulmonalnog testa fizičkim opterećenjem, elektrokardiograma (EKG) i EKG-holter-monitoringa su prikupljeni i korišćeni u daljoj analizi. HCM subfenotipi su identifikovani klasterizacijom. Povezanost genotipa i fenotipa je evaluirana korišćenjem Python modula Scikit-learn i SHapley Additive exPlanation (SHAP). Genotip-specifični nalazi ehokardiograma su identifikovani korišćenjem Python biblioteke za duboko učenje i računarski vid Fast AI, izradom modela za klasifikaciju ehokardiograma i naknadnom analizom regiona koji su najviše doprineli razlikovanju klasa. Četiri podtipa HCM su identifikovana na osnovu svih dostupnih podataka o fenotipu: klaster 0 (“AHOLD”), koji se razlikuje od ostalih na osnovu prečnika korena aorte (AO) i laktat dehidrogenaze (LDH), pri čemu su vrednosti AO > 30 mm i LDH > 300 U/L; klaster 1 (“RVSP ASCAOVS”), koji se razlikuje od ostalih na osnovu sistolnog pritiska desne komore (RVSP), dijametra ascedentne aorte (AscAO), i separacije aortnih kuspisa (AOvs), pri čemu su vrednosti AOvs > 27 m/s, AscAO 95 kg; i klaster 3 (“AV LVOT PG”) koji se razlikuje od ostalih na osnovu srednjeg gradijenta pritisaka nad aortnom valvulom (AV meanPG), maksimalnog gradijenta pritisaka nad aortnom valvulom (AV maxPG), i maksimalnog gradijenta pritisaka nad izlaznim traktom leve komore (LVOT maxPG), pri čemu su vrednosti AV maxPG > 15 mmHg, AV meanPG > 6 mmHg, i LVOT maxPG > 15 mmHg. Algoritmi mašinskog učenja su potvrdili da utvrđivanje povezanosti genotipa i fenotipa HCM nije jednostavan zadatak. Predikcija ishoda fenotipa na osnovu informacije o mutiranim genima je moguća za prisustvo ili odsustvo sinusnog ritma i prisustvo ili odsustvo oštećenja miokarda. Modeli koji vrše predikciju prisustva ili odsustva sinusnog ritma su imali slične performanse kada su izrađeni samo na osnovu uzročnih gena za HCM i kada su izrađeni na osnovu svih analiziranih gena što sugeriše mogući značaj uzročnih gena za HCM i irelevantnost drugih analiziranih gena za ovaj ishod. Modeli koji vrše predikciju oštećenja miokarda su imali bolje performanse kada su korišćeni podaci o svim analiziranim genima (a ne samo o uzročnim genima za HCM), što sugeriše moguću važnu ulogu gena koji nisu uzročni, za ovaj ishod. Algoritmi mašinskog učenja su izvršili predikciju sledećih ishoda na osnovu podataka o genotipu i fenotipu: zamor, dispneja, bol u grudima, palpitacije, sinkopa, šum na srcu, pretibijalni edem, pokretanje mitralnog zalistka unapred (SAM), abnormalnost papilarnih mišića, hipokinezija, atrijalna fibrilacija, atrioventrikularni blok prvog stepena, blok leve grane (LBBB), blok desne grane (RBBB), prednji levi hemiblok, abnormalnosti ST segmenta, i negativni T talas. Prilikom predikcije zamora, najveći doprinos je imala kombinacija mutacije u TNNT2 i maksimalnog odnosa disajne razmene (RER). Prilikom predikcije dispneje najveći doprinos imala je kombinacija mutacije u MYBPC3 i vršne potrošnje kiseonika (peak VO2). Prilikom predikcije bola u grudima, najveći doprinos je imala kombinacija mutacije u TNNI3 i koncentracije lipoproteina visoke gustine (eng. high-density lipoprotein, HDL). Prilikom predikcije šuma na srcu najveći doprinos imala je kombinacija mutacije u MYH7 i podatka o implantiranju pejsmejkera/defibrilatora u porodičnoj istoriji, kao i kombinacija mutacije u TNNT2 i zapremine leve pretkomore (LAV). Prilikom predikcije negativnog T talasa, najveći doprinos imala je kombinacija mutacije u MYBPC3 i vrednosti transmitralnog maksimalnog gradijenta pritiska (MV maxPG). Identifikovani su genotip-specifični nalazi ehokardiograma: za mutaciju u MYH7 genu (nasuprot negativnom rezultatu na mutacije u analiziranim genima), strukture koje najviše utiču na raspoznavanje su septum, izlazni trakt leve komore (LVOT), prednji zid, vrh srca, desna komora i mitralni aparat; za mutaciju u TNNT2 genu (nasuprot negativnom rezultatu na mutacije u analiziranim genima) strukture koje najviše utiču na raspoznavanje su septum i desna komora; dok su za mutaciju u MYBPC3 genu (nasuprot negativnom rezultatu na mutacije u analiziranim genima) ove strukture septum, leva komora i šupljina leve komore. Mašinsko učenje je na ovaj način doprinelo u određenoj meri izučavanju povezanosti genotipa i fenotipa HCM
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