Intra-cochlear electrode position impacts the preservation of residual hearing in an animal model of cochlear implant surgery.

INTRODUCTION: Preservation of residual hearing after cochlear implantation remains challenging. There are several approaches to preserve residual hearing, but the configuration of the implant electrode array seems to play a major role. Lateral wall electrode arrays are seemingly more favorable in this context. To date, there are no experimental data available which correlate the spatial electrode position in the scala tympani with the extent of hearing preservation. METHODS: Based on µCT imaging data, this study analyses the exact position of a pure- silicone electrode array inserted into the cochlea of four guinea pigs. Array position data were correlated with the extent of hearing loss after implantation, measured using auditory brainstem measurements in the frequency range of the area occupied by the electrode array area as well as apical to the array. RESULTS: The use of pure-silicone arrays without electrodes resulted in artifact-free, high-resolution µCT images that allowed precise determination of the arrays' positions within the scala tympani. The electrode arrays' locations ranged from peri-modiolar to an anti-modiolar. These revealed a correlation of a lower postoperative hearing loss with a higher spatial proximity to the lateral wall. This correlation was found in the low-frequency range only. A significant correlation between the interindividual differences in the diameter of the scala tympani and the postoperative hearing loss could not be observed. CONCLUSION: This study demonstrates the importance of the intra-cochlear electrode array's position for the preservation of residual hearing. The advantage of such an electrode array's position approximated to the lateral wall suggests, at least for this type of electrode array applied in the guinea pig, would be advantageous in the preservation of residual hearing for the apical part of the cochlea, beyond the area occupied by the electrode array.

Patient-specific multi-physics simulations of fibrotic changes in left atrial tissue mechanics impact on hemodynamics.

Stroke is a leading cause of death and disability worldwide. Atrial myopathy, including fibrosis, is associated with an increased risk of ischemic stroke, but the mechanisms underlying this association are poorly understood. Fibrosis modifies myocardial structure, impairing electrical propagation and tissue biomechanics, and creating stagnant flow regions where clots could form. Fibrosis can be mapped non-invasively using late gadolinium enhancement magnetic resonance imaging (LGE-MRI). However, fibrosis maps are not currently incorporated into stroke risk calculations or computational electro-mechano-fluidic models. We present multi-physics simulations of left atrial (LA) myocardial motion and hemodynamics using patient-specific anatomies and fibrotic maps from LGE-MRI. We modify tissue stiffness and active tension generation in fibrotic regions and investigate how these changes affect LA flow for different fibrotic burdens. We find that fibrotic regions and, to a lesser extent, non-fibrotic regions experience reduced myocardial strain, resulting in decreased LA emptying fraction consistent with clinical observations. Both fibrotic tissue stiffening and hypocontractility independently reduce LA function, but together, these two alterations cause more pronounced effects than either one alone. Fibrosis significantly alters flow patterns throughout the atrial chamber, and particularly, the filling and emptying jets of the left atrial appendage (LAA). The effects of fibrosis in LA flow are largely captured by the concomitant changes in LA emptying fraction except inside the LAA, where a multi-factorial behavior is observed. This work illustrates how high-fidelity, multi-physics models can be used to study thrombogenesis mechanisms in a patient-specific manner, shedding light onto the link between atrial fibrosis and ischemic stroke. Key points: Left atrial (LA) fibrosis is associated with arrhythmogenesis and increased risk of ischemic stroke; its extent and pattern can be quantified on a patient-specific basis using late gadolinium enhancement magnetic resonance imaging.Current stroke risk prediction tools have limited personalization, and their accuracy could be improvedfib by incorporating patient-specific information like fibrotic maps and hemodynamic patterns.We present the first electro-mechano-fluidic multi-physics computational simulations of LA flow, including fibrosis and anatomies from medical imaging.Mechanical changes in fibrotic tissue impair global LA motion, decreasing LA and left atrial appendage (LAA) emptying fractions, especially in subjects with higher fibrosis burdens.Fibrotic-mediated LA motion impairment alters LA and LAA flow near the endocardium and the whole cavity, ultimately leading to more stagnant blood regions in the LAA.

Self-Assessment of Cochlear Health by New Cochlear Implant Recipients: Daily Impedance, Electrically Evoked Compound Action Potential and Electrocochleography Measurements Over the First Three Postoperative Months.

HYPOTHESES: In newly implanted cochlear implant (CI) users, electrically evoked compound action (eCAPs) and electrocochleography (ECochGs) will remain stable over time. Electrode impedances will increase immediately postimplantation due to the initial inflammatory response, before decreasing after CI switch-on and stabilizing thereafter. BACKGROUND: The study of cochlear health (CH) has several applications, including explaining variation in CI outcomes, informing CI programming strategies, and evaluating the safety and efficacy of novel biological treatments for hearing loss. Very early postoperative CH patterns have not previously been intensively explored through longitudinal daily testing. Thanks to technological advances, electrode impedances, eCAPs, and ECochGs can be independently performed by CI users at home to monitor CH over time. METHODS: A group of newly implanted CI users performed daily impedances, eCAPs, and ECochGs for 3 months at home, starting from the first day postsurgery (N = 7) using the Active Insertion Monitoring system by Advanced Bionics. RESULTS: Measurement validity of 93.5, 93.0, and 81.6% for impedances, eCAPs, and ECochGs, respectively, revealed high participant compliance. Impedances increased postsurgery before dropping and stabilizing after switch-on. eCAPs showed good stability, though statistical analyses revealed a very small but significant increase in thresholds over time. Most ECochG thresholds did not reach the liberal signal-to-noise criterion of 2:1, with low threshold stability over time. CONCLUSION: Newly implanted CI recipients can confidently and successfully perform CH recordings at home, highlighting the valuable role of patients in longitudinal data collection. Electrode impedances and eCAPs are promising objective measurements for evaluating CH in newly implanted CI users.

Time to ECG diagnosis delays inter-hospital transfer to revascularization in STEMI patients presenting to a regional emergency department: a five-year audit.

BACKGROUND: Reducing the door-to-balloon time (D2BT) in ST-elevation myocardial infarction (STEMI) patients maximizes myocardial salvage and mitigates morbidity/mortality. AIMS: To assess the D2BT in STEMI patients requiring inter-hospital transfer for revascularization and identify any potential causes of delay. METHODS: Consecutive patients presenting to the Connolly Hospital Blanchardstown (CHB) emergency department (ED) who were transferred to the Mater Misericordiae University Hospital in Dublin for primary percutaneous coronary intervention from January 2018 to October 2022 were identified in a regional database and their D2BTs calculated. D2BTs were further sub-categorized into key intervals to identify any potential causes of delay. RESULTS: A total of 90 patients were included for analysis, with a median D2BT of 117.5 min (interquartile range [IQR]: 99.3-170.8 min) and 52.5% of patients achieving the ≤ 120 min target. Despite being the shortest interval considered, the time from arrival at the CHB ED to diagnostic electrocardiogram (ECG) was a substantial contributor to the overall delay to revascularization given its wide variability (median: 18.0 min; IQR: 9.0-46.8 min), with only 28.8% of patients achieving the ≤ 10 min target. CONCLUSIONS: Nearly half of the patients studied failed to achieve the overall target D2BT for revascularization. The time from arrival at the CHB ED to diagnostic ECG was identified as a substantial contributor to this failure, with a median time almost twice that of the target and a quarter of all patients spending longer than 46.8 min. These findings highlight a need to improve the implementation of ECG triage and interpretation in the ED.

Far-red and sensitive sensor for monitoring real time H2O2 dynamics with subcellular resolution and in multi-parametric imaging applications.

H2O2 is a key oxidant in mammalian biology and a pleiotropic signaling molecule at the physiological level, and its excessive accumulation in conjunction with decreased cellular reduction capacity is often found to be a common pathological marker. Here, we present a red fluorescent Genetically Encoded H2O2 Indicator (GEHI) allowing versatile optogenetic dissection of redox biology. Our new GEHI, oROS-HT, is a chemigenetic sensor utilizing a HaloTag and Janelia Fluor (JF) rhodamine dye as fluorescent reporters. We developed oROS-HT through a structure-guided approach aided by classic protein structures and recent protein structure prediction tools. Optimized with JF635, oROS-HT is a sensor with 635 nm excitation and 650 nm emission peaks, allowing it to retain its brightness while monitoring intracellular H2O2 dynamics. Furthermore, it enables multi-color imaging in combination with blue-green fluorescent sensors for orthogonal analytes and low auto-fluorescence interference in biological tissues. Other advantages of oROS-HT over alternative GEHIs are its fast kinetics, oxygen-independent maturation, low pH sensitivity, lack of photo-artifact, and lack of intracellular aggregation. Here, we demonstrated efficient subcellular targeting and how oROS-HT can map inter and intracellular H2O2 diffusion at subcellular resolution. Lastly, we used oROS-HT with other green fluorescence reporters to investigate the transient effect of the anti-inflammatory agent auranofin on cellular redox physiology and calcium levels via multi-parametric, dual-color imaging.

Electrocardiographic predictors of response to sacubitril/valsartan therapy in heart failure with reduced ejection fraction.

BACKGROUND: Sacubitril/valsartan (SV) is currently recommended as a first-line therapy in patients with heart failure and reduced ejection fraction (HFrEF) due to its significant clinical and prognostic benefit; however, not all patients respond to therapy and predictors of clinical response to SV remain under-studied. AIMS: To identify electrocardiographic (ECG) predictors of response to SV therapy in HFrEF patients. METHODS: A retrospective analysis of a hospital heart failure registry was undertaken. Consecutive HFrEF patients (New York Heart Association class II-III) on maximal-dose SV were studied. Response to SV was defined as ≥10% relative improvement in left ventricular ejection fraction (LVEF) at 3-months post-maximal-dose therapy. Pre-therapy ECGs were retrospectively analyzed for axes and standard wave and interval durations. Logistic regression was used to estimate odds ratios and 95% confidence intervals for associations between predictors and therapeutic response. Backward stepwise regression was employed to develop a parsimonious model. RESULTS: P-wave duration (PWD) 100-120 ms, PWD >120 ms, and QTc >460 ms were associated with response to SV on univariate analysis: OR 18.00 (4.45-122.90), 5.00 (1.47-20.42), and 3.10 (1.18-9.22), respectively. The preferred model that included the former two predictors in combination with pre-therapy creatinine, mineralocorticoid receptor antagonist use, and LVEF was highly selective (area under the ROC curve = 0.868). CONCLUSIONS: Prolongation of both PWD and QTc interval on baseline ECG in HFrEF patients is predictive of therapeutic response to maximal-dose SV therapy and may indicate early cardiac remodeling that is highly amenable to reversal.

Far-red and sensitive sensor for monitoring real time H2O2 dynamics with subcellular resolution and in multi-parametric imaging applications.

H2O2 is a key oxidant in mammalian biology and a pleiotropic signaling molecule at the physiological level, and its excessive accumulation in conjunction with decreased cellular reduction capacity is often found to be a common pathological marker. Here, we present a red fluorescent Genetically Encoded H2O2 Indicator (GEHI) allowing versatile optogenetic dissection of redox biology. Our new GEHI, oROS-HT, is a chemigenetic sensor utilizing a HaloTag and Janelia Fluor (JF) rhodamine dye as fluorescent reporters. We developed oROS-HT through a structure-guided approach aided by classic protein structures and recent protein structure prediction tools. Optimized with JF635, oROS-HT is a sensor with 635 nm excitation and 650 nm emission peaks, allowing it to retain its brightness while monitoring intracellular H2O2 dynamics. Furthermore, it enables multi-color imaging in combination with blue-green fluorescent sensors for orthogonal analytes and low auto-fluorescence interference in biological tissues. Other advantages of oROS-HT over alternative GEHIs are its fast kinetics, oxygen-independent maturation, low pH sensitivity, lack of photo-artifact, and lack of intracellular aggregation. Here, we demonstrated efficient subcellular targeting and how oROS-HT can map inter and intracellular H2O2 diffusion at subcellular resolution. Lastly, we used oROS-HT with the green fluorescent calcium indicator Fluo-4 to investigate the transient effect of the anti-inflammatory agent auranofin on cellular redox physiology and calcium levels via multi-parametric, dual-color imaging.

Machine learning identifies esophageal luminal temperature patterns associated with thermal injury in catheter ablation for atrial fibrillation.

INTRODUCTION: Luminal esophageal temperature (LET) monitoring during atrial fibrillation (AF) ablation is widely used to reduce the incidence of endoscopically detected esophageal lesion (EDEL). We sought to assess whether specific patterns of LET variation are associated with EDEL. METHODS: A high-fidelity multisensor probe was used to record LET in AF patients undergoing radiofrequency ablation (RFA) or cryoballoon ablation (CBA). Explainable machine learning and SHapley Additive exPlanations (SHAP) analysis were used to predict EDEL and assess feature importance. RESULTS: A total of 94 patients (38.3% persistent AF, 71.3% male, 72 RFA, and 22 CBA) were included. EDEL was detected in 11 patients (10 RFA and one CBA). In the RFA group, the highest LET recorded was similar between patients with and without EDEL (40.6 [40.1-41]°C vs. 40.2 [39.1-40.9]°C; p = .313), however, the rate of LET rise for the highest recorded peak was higher (0.08 [0.03-0.12]°C/s vs. 0.02 [0.01-0.05]°C/s; p = .033), and the area under the curve (AUC) for the highest peak was smaller (412.5 [206.8-634.1] vs. 588.6 [380.4-861.1]; p = .047) in patients who had EDEL. In case of CBA, the patient with EDEL had a faster LET decline (0.12 vs. 0.07 [0.02-0.14]°C/s), and a smaller AUC for the lowest trough (2491.3 vs. 2629.3 [1712.6-5283.2]). SHAP analysis revealed that a rate of LET change higher than 0.05°C/s and an AUC less than 600 were more predictive of EDEL in RFA. CONCLUSION: The rate of LET change and AUC for the recorded temperature predicted EDEL, whereas absolute peak temperatures did not.

Reduced-order models of wall shear stress patterns in the left atrial appendage from a data-augmented atrial database.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, affecting over 1% of the population. It is usually triggered by irregular electrical impulses that cause the atria to contract irregularly and ineffectively. It increases blood stasis and the risk of thrombus formation within the left atrial appendage (LAA) and aggravates adverse atrial remodeling. Despite recent efforts, LAA flow patterns representative of AF conditions and their association with LAA stasis remain poorly characterized. AIM: To develop reduced-order data-driven models of LAA flow patterns during atrial remodeling in order to uncover flow disturbances concurrent with LAA stasis that could add granularity to clinical decision criteria. METHODS: We combined a geometric data augmentation process with projection of results from 180 CFD atrial simulations on a universal LAA coordinate (ULAAC) system. The projection approach enhances data visualization and facilitates direct comparison between different anatomical and functional states. ULAAC projections were used as input for a proper orthogonal decomposition (POD) algorithm to build reduced-order models of hemodynamic metrics, extracting flow characteristics associated with AF and non-AF anatomies. RESULTS: We verified that the ULAAC system provides an adequate representation to visualize data distributions on the LAA surface and to build POD-based reduced-order models. These models revealed significant differences in LAA flow patterns for atrial geometries that underwent adverse atrial remodeling and experienced elevated blood stasis. Together with anatomical morphing-based patient-specific data augmentation, this approach could facilitate data-driven analyses to identify flow features associated with thrombosis risk due to atrial remodeling.

The effect of photobiomodulation on hearing loss: A systematic review.

OBJECTIVES: To assess outcomes associated with photobiomodulation therapy (PBMT) for hearing loss in human and animal studies. DESIGN: Systematic review and narrative synthesis in accordance with PRISMA guidelines. SETTING: Data bases searched: MEDLINE, EMBASE, CENTRAL, ClinicalTrials.gov and Web of Science. No limits were placed on language or year of publication. Review conducted in accordance with the PRISMA 2020 statement. PARTICIPANTS: All human and animal subjects treated with PBMT for hearing loss. MAIN OUTCOME MEASURES: Pre- and post-PBMT audio metric outcomes. RESULTS: Searches identified 122 abstracts and 49 full text articles. Of these, 17 studies met the inclusion criteria, reporting outcomes in 327 animals (11 studies), 30 humans (1 study), and 40 animal specimens (5 studies). PBMT parameters included 6 different wavelengths: 908 nm (1 study), 810 nm (1 study), 532 & 635 nm (1 study), 830 nm (3 studies), 808 nm (11 studies). The duration ranged from 4 to 60 minutes in a session, and the follow-up ranged from 5-28 days. Outcomes improved significantly when wavelengths within the range of 800-830 nm were used, and with greater duration of PBMT exposure. Included studies predominantly consisted of non-randomized controlled trials (10 studies). CONCLUSIONS: Hearing outcomes following PBMT appear to be superior to no PBMT for subjects with hearing loss, although higher level evidence is required to verify this. PBMT enables concentrated, focused delivery of light therapy to the inner ear through a non-invasive manner with minimal side effects. As a result of heterogeneity in reporting PBMT parameters and outcomes across the included studies, direct comparison is challenging.

Classification of Acoustic Hearing Preservation After Cochlear Implantation Using Electrocochleography.

The objective to preserve residual hearing during cochlear implantation has recently led to the use of intracochlear electrocochleography (ECochG) as an intraoperative monitoring tool. Currently, a decrease in the amplitude of the difference between responses to alternating-polarity stimuli (DIF response), predominantly reflecting the hair cell response, is used for providing feedback. Including other ECochG response components, such as phase changes and harmonic distortions, could improve the accuracy of surgical feedback. The objectives of the present study were (1) to compare simultaneously recorded stepwise intracochlear and extracochlear ECochG responses to 500 Hz tone bursts, (2) to explore patterns in features extracted from the intracochlear ECochG recordings relating to hearing preservation or hearing loss, and (3) to design support vector machine (SVM) and random forest (RF) classifiers of acoustic hearing preservation that treat each subject as a sample and use all intracochlear ECochG recordings made during electrode array insertion for classification. Forty subjects undergoing cochlear implant (CI) surgery at the Oslo University Hospital, St. Thomas' Hearing Implant Centre, or the University Hospital of Zurich were prospectively enrolled. In this cohort, DIF response amplitude decreases did not relate to postoperative acoustic hearing preservation. Exploratory analysis of the feature set extracted from the ECochG responses and preoperative audiogram showed that the features were not discriminative between outcome classes. The SVM and RF classifiers that were trained on these features could not distinguish cases with hearing loss and hearing preservation. These findings suggest that hearing loss following CI surgery is not always reflected in intraoperative ECochG recordings.

The effect of photobiomodulation on tinnitus: a systematic review.

OBJECTIVE: To establish outcomes following photobiomodulation therapy for tinnitus in humans and animal studies. METHODS: A systematic review and narrative synthesis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The databases searched were: Medline, Embase, Cochrane Central Register of Controlled Trials ('Central'), ClinicalTrials.gov and Web of Science including the Web of Science Core collection. There were no limits on language or year of publication. RESULTS: The searches identified 194 abstracts and 61 full texts. Twenty-eight studies met the inclusion criteria, reporting outcomes in 1483 humans (26 studies) and 34 animals (2 studies). Photobiomodulation therapy parameters included 10 different wavelengths, and duration ranged from 9 seconds to 30 minutes per session. Follow up ranged from 7 days to 6 months. CONCLUSION: Tinnitus outcomes following photobiomodulation therapy are generally positive and superior to no photobiomodulation therapy; however, evidence of long-term therapeutic benefit is deficient. Photobiomodulation therapy enables concentrated, focused delivery of light therapy to the inner ear through a non-invasive manner, with minimal side effects.

Personalized biomechanical insights in atrial fibrillation: opportunities & challenges.

INTRODUCTION: Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke. AREAS COVERED: In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care. EXPERT OPINION: Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.

People with atrial fibrillation (AF) experience a fast, chaotic heartbeat. AF greatly increases the risk of stroke. The hearts of AF patients often have an accumulation of fibrous tissue (fibrosis). Fibrosis patterns can be detected via medical imaging scans, like MRI. These images can be used to build patient-specific digital representations. These models can be used to explore how fibrosis might cause AF, stroke, and other health risks. Insights from imaging and modeling are becoming more and more useful as tools for personalizing AF treatment.

Optogenetic Modulation of Arrhythmia Triggers: Proof-of-Concept from Computational Modeling.

Introduction: Early afterdepolarizations (EADs) are secondary voltage depolarizations associated with reduced repolarization reserve (RRR) that can trigger lethal arrhythmias. Relating EADs to triggered activity is difficult to study, so the ability to suppress or provoke EADs would be experimentally useful. Here, we use computational simulations to assess the feasibility of subthreshold optogenetic stimulation modulating the propensity for EADs (cell-scale) and EAD-associated ectopic beats (organ-scale). Methods: We modified a ventricular ionic model by reducing rapid delayed rectifier potassium (0.25-0.1 × baseline) and increasing L-type calcium (1.0-3.5 × baseline) currents to create RRR conditions with varying severity. We ran simulations in models of single cardiomyocytes and left ventricles from post-myocardial infarction patient MRI scans. Optogenetic stimulation was simulated using either ChR2 (depolarizing) or GtACR1 (repolarizing) opsins. Results: In cell-scale simulations without illumination, EADs were seen for 164 of 416 RRR conditions. Subthreshold stimulation of GtACR1 reduced EAD incidence by up to 84.8% (25/416 RRR conditions; 0.1 µW/mm2); in contrast, subthreshold ChR2 excitation increased EAD incidence by up to 136.6% (388/416 RRR conditions; 50 µW/mm2). At the organ scale, we assumed simultaneous, uniform illumination of the epicardial and endocardial surfaces. GtACR1-mediated suppression (10-50 µW/mm2) and ChR2-mediated unmasking (50-100 µW/mm2) of EAD-associated ectopic beats were feasible in three distinct ventricular models. Conclusions: Our findings suggest that optogenetics could be used to silence or provoke both EADs and EAD-associated ectopic beats. Validation in animal models could lead to exciting new experimental regimes and potentially to novel anti-arrhythmia treatments. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-023-00781-z.

Comparing Inducibility of Re-Entrant Arrhythmia in Patient-Specific Computational Models to Clinical Atrial Fibrillation Phenotypes.

BACKGROUND: Computational models of fibrosis-mediated, re-entrant left atrial (LA) arrhythmia can identify possible substrate for persistent atrial fibrillation (AF) ablation. Contemporary models use a 1-size-fits-all approach to represent electrophysiological properties, limiting agreement between simulations and patient outcomes. OBJECTIVES: The goal of this study was to test the hypothesis that conduction velocity (Ï´) modulation in persistent AF models can improve simulation agreement with clinical arrhythmias. METHODS: Patients with persistent AF (n = 37) underwent ablation and were followed up for ≥2 years to determine post-ablation outcomes: AF, atrial flutter (AFL), or no recurrence. Patient-specific LA models (n = 74) were constructed using pre-ablation and ≥90 days' post-ablation magnetic resonance imaging data. Simulated pacing gauged in silico arrhythmia inducibility due to AF-like rotors or AFL-like macro re-entrant tachycardias. A physiologically plausible range of Ï´ values (±10 or 20% vs. baseline) was tested, and model/clinical agreement was assessed. RESULTS: Fifteen (41%) patients had a recurrence with AF and 6 (16%) with AFL. Arrhythmia was induced in 1,078 of 5,550 simulations. Using baseline Ï´, model/clinical agreement was 46% (34 of 74 models), improving to 65% (48 of 74) when any possible Ï´ value was used (McNemar's test, P = 0.014). Ï´ modulation improved model/clinical agreement in both pre-ablation and post-ablation models. Pre-ablation model/clinical agreement was significantly greater for patients with extensive LA fibrosis (>17.2%) and an elevated body mass index (>32.0 kg/m2). CONCLUSIONS: Simulations in persistent AF models show a 41% relative improvement in model/clinical agreement when Ï´ is modulated. Patient-specific calibration of Ï´ values could improve model/clinical agreement and model usefulness, especially in patients with higher body mass index or LA fibrosis burden. This could ultimately facilitate better personalized modeling, with immediate clinical implications.

Explainable Machine Learning to Predict Anchored Reentry Substrate Created by Persistent Atrial Fibrillation Ablation in Computational Models.

Background Postablation arrhythmia recurrence occurs in ~40% of patients with persistent atrial fibrillation. Fibrotic remodeling exacerbates arrhythmic activity in persistent atrial fibrillation and can play a key role in reentrant arrhythmia, but emergent interaction between nonconductive ablation-induced scar and native fibrosis (ie, residual fibrosis) is poorly understood. Methods and Results We conducted computational simulations in pre- and postablation left atrial models reconstructed from late gadolinium enhanced magnetic resonance imaging scans to test the hypothesis that ablation in patients with persistent atrial fibrillation creates new substrate conducive to recurrent arrhythmia mediated by anchored reentry. We trained a random forest machine learning classifier to accurately pinpoint specific nonconductive tissue regions (ie, areas of ablation-delivered scar or vein/valve boundaries) with the capacity to serve as substrate for anchored reentry-driven recurrent arrhythmia (area under the curve: 0.91±0.03). Our analysis suggests there is a distinctive nonconductive tissue pattern prone to serving as arrhythmogenic substrate in postablation models, defined by a specific size and proximity to residual fibrosis. Conclusions Overall, this suggests persistent atrial fibrillation ablation transforms substrate that favors functional reentry (ie, rotors meandering in excitable tissue) into an arrhythmogenic milieu more conducive to anchored reentry. Our work also indicates that explainable machine learning and computational simulations can be combined to effectively probe mechanisms of recurrent arrhythmia.

Fractional Flow Reserve-Guided Stent Optimisation in Focal and Diffuse Coronary Artery Disease.

Assessing coronary physiology after stent implantation facilitates the optimisation of percutaneous coronary intervention (PCI). Coronary artery disease (CAD) patterns can be characterised by the pullback pressure gradient (PPG) index. The impact of focal vs. diffuse disease on physiology-guided incremental optimisation strategy (PIOS) is unknown. This is a sub-study of the TARGET-FFR randomized clinical trial (NCT03259815). The study protocol directed that optimisation be attempted for patients in the PIOS arm when post-PCI FFR was <0.90. Overall, 114 patients (n = 61 PIOS and 53 controls) with both pre-PCI fractional flow reserve (FFR) pullbacks and post-PCI FFR were included. A PPG ≥ 0.74 defined focal CAD. The PPG correlated significantly with post-PCI FFR (r = 0.43; 95% CI 0.26 to 0.57; p-value < 0.001) and normalised delta FFR (r = 0.49; 95% CI 0.34 to 0.62; p-value < 0.001). PIOS was more frequently applied to vessels with diffuse CAD (6% focal vs. 42% diffuse; p-value = 0.006). In patients randomized to PIOS, those with focal disease achieved higher post-PCI FFR than patients with diffuse CAD (0.93 ± 0.05 vs. 0.83 ± 0.07, p < 0.001). There was a significant interaction between CAD patterns and the randomisation arm for post-PCI FFR (p-value for interaction = 0.004). Physiology-guided stent optimisation was applied more frequently to vessels with diffuse disease; however, patients with focal CAD at baseline achieved higher post-PCI FFR.

Machine Learning and the Conundrum of Stroke Risk Prediction.

Stroke is a leading cause of death worldwide. With escalating healthcare costs, early non-invasive stroke risk stratification is vital. The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. This review summarises recent efforts to deploy machine learning (ML) to predict stroke risk and enrich the understanding of the mechanisms underlying stroke. The surveyed body of literature includes studies comparing ML algorithms with conventional statistical models for predicting cardiovascular disease and, in particular, different stroke subtypes. Another avenue of research explored is ML as a means of enriching multiscale computational modelling, which holds great promise for revealing thrombogenesis mechanisms. Overall, ML offers a new approach to stroke risk stratification that accounts for subtle physiologic variants between patients, potentially leading to more reliable and personalised predictions than standard regression-based statistical associations.