OCT2013, an ischaemia-activated antiarrhythmic prodrug, devoid of the systemic side effects of lidocaine.

BACKGROUND AND PURPOSE: Sudden cardiac death (SCD) caused by acute myocardial ischaemia and ventricular fibrillation (VF) is an unmet therapeutic need. Lidocaine suppresses ischaemia-induced VF, but its utility is limited by side effects and a narrow therapeutic index. Here, we characterise OCT2013, a putative ischaemia-activated prodrug of lidocaine. EXPERIMENTAL APPROACH: The rat Langendorff-perfused isolated heart, anaesthetised rat and rat ventricular myocyte preparations were utilised in a series of blinded and randomised studies to investigate the antiarrhythmic effectiveness, adverse effects and mechanism of action of OCT2013, compared with lidocaine. KEY RESULTS: In isolated hearts, OCT2013 and lidocaine prevented ischaemia-induced VF equi-effectively, but OCT2013 did not share lidocaine's adverse effects (PR widening, bradycardia and negative inotropy). In anaesthetised rats, i.v. OCT2013 and lidocaine suppressed VF and increased survival equi-effectively; OCT2013 had no effect on cardiac output even at 64 mg·kg-1 i.v., whereas lidocaine reduced it even at 1 mg·kg-1 . In adult rat ventricular myocytes, OCT2013 had no effect on Ca2+ handling, whereas lidocaine impaired it. In paced isolated hearts, lidocaine caused rate-dependent conduction slowing and block, whereas OCT2013 was inactive. However, during regional ischaemia, OCT2013 and lidocaine equi-effectively hastened conduction block. Chromatography and MS analysis revealed that OCT2013, detectable in normoxic OCT2013-perfused hearts, became undetectable during global ischaemia, with lidocaine becoming detectable. CONCLUSIONS AND IMPLICATIONS: OCT2013 is inactive but is bio-reduced locally in ischaemic myocardium to lidocaine, acting as an ischaemia-activated and ischaemia-selective antiarrhythmic prodrug with a large therapeutic index, mimicking lidocaine's benefit without adversity.

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often through catheter ablation, which involves the targeted localised destruction of regions of the myocardium responsible for initiating or perpetuating the arrhythmia. Ablation targets are either anatomically defined, or identified based on their functional properties as determined through the analysis of contact intracardiac electrograms acquired with increasing spatial density by modern electroanatomic mapping systems. While numerous quantitative approaches have been investigated over the past decades for identifying these critical curative sites, few have provided a reliable and reproducible advance in success rates. Machine learning techniques, including recent deep-learning approaches, offer a potential route to gaining new insight from this wealth of highly complex spatio-temporal information that existing methods struggle to analyse. Coupled with predictive modelling, these techniques offer exciting opportunities to advance the field and produce more accurate diagnoses and robust personalised treatment. We outline some of these methods and illustrate their use in making predictions from the contact electrogram and augmenting predictive modelling tools, both by more rapidly predicting future states of the system and by inferring the parameters of these models from experimental observations.

Concurrent micro- to macro-cardiac electrophysiology in myocyte cultures and human heart slices.

The contact cardiac electrogram is derived from the extracellular manifestation of cellular action potentials and cell-to-cell communication. It is used to guide catheter based clinical procedures. Theoretically, the contact electrogram and the cellular action potential are directly related, and should change in conjunction with each other during arrhythmogenesis, however there is currently no methodology by which to concurrently record both electrograms and action potentials in the same preparation for direct validation of their relationships and their direct mechanistic links. We report a novel dual modality apparatus for concurrent electrogram and cellular action potential recording at a single cell level within multicellular preparations. We further demonstrate the capabilities of this system to validate the direct link between these two modalities of voltage recordings.

Characterisation of re-entrant circuit (or rotational activity) in vitro using the HL1-6 myocyte cell line.

Fibrillation is the most common arrhythmia observed in clinical practice. Understanding of the mechanisms underlying its initiation and maintenance remains incomplete. Functional re-entries are potential drivers of the arrhythmia. Two main concepts are still debated, the "leading circle" and the "spiral wave or rotor" theories. The homogeneous subclone of the HL1 atrial-derived cardiomyocyte cell line, HL1-6, spontaneously exhibits re-entry on a microscopic scale due to its slow conduction velocity and the presence of triggers, making it possible to examine re-entry at the cellular level. We therefore investigated the re-entry cores in cell monolayers through the use of fluorescence optical mapping at high spatiotemporal resolution in order to obtain insights into the mechanisms of re-entry. Re-entries in HL1-6 myocytes required at least two triggers and a minimum colony area to initiate (3.5 to 6.4 mm2). After electrical activity was completely stopped and re-started by varying the extracellular K+ concentration, re-entries never returned to the same location while 35% of triggers re-appeared at the same position. A conduction delay algorithm also allows visualisation of the core of the re-entries. This work has revealed that the core of re-entries is conduction blocks constituted by lines and/or groups of cells rather than the round area assumed by the other concepts of functional re-entry. This highlights the importance of experimentation at the microscopic level in the study of re-entry mechanisms.

A technique for visualising three-dimensional left atrial cardiac activation data in two dimensions with minimal distance distortion.

Electro-anatomic mapping and medical imaging systems, used during clinical procedures for treatment of atrial arrhythmias, frequently record and display measurements on an anatomical surface of the left atrium. As such, obtaining a complete picture of activation necessitates simultaneous views from multiple angles. In addition, post-processing of three-dimensional surface data is challenging, since algorithms are typically applicable to planar or volumetric data. We applied a surface flattening methodology to medical imaging data and electro-anatomic mapping data to generate a two-dimensional representation that best preserves distances, since the calculation of many clinically relevant metrics, including conduction velocity and rotor trajectory identification require an accurate representation of distance. Distance distortions were small and improved upon exclusion of the pulmonary veins. The technique is demonstrated using maps of local activation time, based on clinical data, and plotting rotor-core trajectories, using simulated data.