The digital journey: 25 years of digital development in electrophysiology from an Europace perspective.

AIMS: Over the past 25 years there has been a substantial development in the field of digital electrophysiology (EP) and in parallel a substantial increase in publications on digital cardiology.In this celebratory paper, we provide an overview of the digital field by highlighting publications from the field focusing on the EP Europace journal. RESULTS: In this journey across the past quarter of a century we follow the development of digital tools commonly used in the clinic spanning from the initiation of digital clinics through the early days of telemonitoring, to wearables, mobile applications, and the use of fully virtual clinics. We then provide a chronicle of the field of artificial intelligence, a regulatory perspective, and at the end of our journey provide a future outlook for digital EP. CONCLUSION: Over the past 25 years Europace has published a substantial number of papers on digital EP, with a marked expansion in digital publications in recent years.

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.

The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not.

Electrocardiographic imaging-based recognition of possible induced bundle branch blocks during transcatheter aortic valve implantations.

AIMS: Conventional electrocardiogram (ECG)-based diagnosis of left bundle branch block (LBBB) in patients with left ventricular hypertrophy (LVH) is ambiguous. Left ventricular hypertrophy is often seen in patients with severe aortic stenosis in which a transcatheter aortic valve implantation (TAVI) frequently results in a LBBB due to the mechanical interaction of the artificial valve and the conduction system. In this feasibility study, we propose and evaluate the sensitivity of a new electrocardiographic imaging tool; the cardiac isochrone positioning system (CIPS), visualizing the cardiac activation to detect interventricular conduction patterns pre- and post-TAVI. METHODS AND RESULTS: The CIPS translates standard 12-lead ECG into ventricular isochrones, representing the activation sequence. It requires a patient-specific model integrating heart, lungs, and other thoracic structures derived from multi-slice computed tomography. The fastest route-based algorithm was used to estimate the activation isochrones and the results were compared with standard ECG analysis. In 10 patients the CIPS was used to analyse 20 ECGs, 10 pre- and 10 post-TAVI. In 11 cases the CIPS results were in agreement with the ECG-based diagnosis. In two cases there was partial agreement and in seven cases there was disagreement. In four of these cases, the clinical history of the patients favoured interpretation as assessed by CIPS, for the remaining three, it is unknown which method correctly classified the activation. CONCLUSION: This feasibility study applying the CIPS shows promising results to classify conduction disorders originating from the left anterior or posterior ventricular wall, or the septum. The visualization of the activation isochrones as well as ventricular model-derived features might support TAVI procedures and the therapy selection afterwards.

Machine learning-based analysis of non-invasive measurements for predicting intracardiac pressures.

Aims: Early detection of congestion has demonstrated to improve outcomes in heart failure (HF) patients. However, there is limited access to invasively haemodynamic parameters to guide treatment. This study aims to develop a model to estimate the invasively measured pulmonary capillary wedge pressure (PCWP) using non-invasive measurements with both traditional statistics and machine learning (ML) techniques. Methods and results: The study involved patients undergoing right-sided heart catheterization at Erasmus MC, Rotterdam, from 2017 to 2022. Invasively measured PCWP served as outcomes. Model features included non-invasive measurements of arterial blood pressure, saturation, heart rate (variability), weight, and temperature. Various traditional and ML techniques were used, and performance was assessed using R2 and area under the curve (AUC) for regression and classification models, respectively. A total of 853 procedures were included, of which 31% had HF as primary diagnosis and 49% had a PCWP of 12 mmHg or higher. The mean age of the cohort was 59 ± 14 years, and 52% were male. The heart rate variability had the highest correlation with the PCWP with a correlation of 0.16. All the regression models resulted in low R2 values of up to 0.04, and the classification models resulted in AUC values of up to 0.59. Conclusion: In this study, non-invasive methods, both traditional and ML-based, showed limited correlation to PCWP. This highlights the weak correlation between traditional HF monitoring and haemodynamic parameters, also emphasizing the limitations of single non-invasive measurements. Future research should explore trend analysis and additional features to improve non-invasive haemodynamic monitoring, as there is a clear demand for further advancements in this field.

Photoplethysmography and intracardiac pressures: early insights from a pilot study.

Aims: Invasive haemodynamic monitoring of heart failure (HF) is used to detect deterioration in an early phase thereby preventing hospitalizations. However, this invasive approach is costly and presently lacks widespread accessibility. Hence, there is a pressing need to identify an alternative non-invasive method that is reliable and more readily available. In this pilot study, we investigated the relation between wrist-derived photoplethysmography (PPG) signals and the invasively measured pulmonary capillary wedge pressure (PCWP). Methods and results: Fourteen patients with aortic valve stenosis who underwent transcatheter aortic valve replacement with concomitant right heart catheterization and PPG measurements were included. Six unique features of the PPG signals [heart rate, heart rate variability, systolic amplitude (SA), diastolic amplitude, crest time (CT), and large artery stiffness index (LASI)] were extracted. These features were used to estimate the continuous PCWP values and the categorized PCWP (low < 12 mmHg vs. high ≥ 12 mmHg). All PPG features resulted in regression models that showed low correlations with the invasively measured PCWP. Classification models resulted in higher performances: the model based on the SA and the model based on the LASI both resulted in an area under the curve (AUC) of 0.86 and the model based on the CT resulted in an AUC of 0.72. Conclusion: These results demonstrate the capability to non-invasively classify patients into clinically meaningful categories of PCWP using PPG signals from a wrist-worn wearable device. To enhance and fully explore its potential, the relationship between PPG and PCWP should be further investigated in a larger cohort of HF patients.

Risks and benefits of sharing patient information on social media: a digital dilemma.

Social media (SoMe) has witnessed remarkable growth and emerged as a dominant method of communication worldwide. Platforms such as Facebook, X (formerly Twitter), LinkedIn, Instagram, TikTok, and YouTube have become important tools of the digital native generation. In the field of medicine, particularly, cardiology, attitudes towards SoMe have shifted, and professionals increasingly utilize it to share scientific findings, network with experts, and enhance teaching and learning. Notably, SoMe is being leveraged for teaching purposes, including the sharing of challenging and intriguing cases. However, sharing patient data, including photos or images, online carries significant implications and risks, potentially compromising individual privacy both online and offline. Privacy and data protection are fundamental rights within European Union treaties, and the General Data Protection Regulation (GDPR) serves as the cornerstone of data protection legislation. The GDPR outlines crucial requirements, such as obtaining 'consent' and implementing 'anonymization', that must be met before sharing sensitive and patient-identifiable information. Additionally, it is vital to consider the patient's perspective and prioritize ethical and social considerations when addressing challenges associated with sharing patient information on SoMe platforms. Given the absence of a peer-review process and clear guidelines, we present an initial approach, a code of conduct, and recommendations for the ethical use of SoMe. In conclusion, this comprehensive review underscores the importance of a balanced approach that ensures patient privacy and upholds ethical standards while harnessing the immense potential of SoMe to advance cardiology practice and facilitate knowledge dissemination.

Standards for quantitative assessments by coronary computed tomography angiography (CCTA): An expert consensus document of the society of cardiovascular computed tomography (SCCT).

In current clinical practice, qualitative or semi-quantitative measures are primarily used to report coronary artery disease on cardiac CT. With advancements in cardiac CT technology and automated post-processing tools, quantitative measures of coronary disease severity have become more broadly available. Quantitative coronary CT angiography has great potential value for clinical management of patients, but also for research. This document aims to provide definitions and standards for the performance and reporting of quantitative measures of coronary artery disease by cardiac CT.

Long-Term (>10 Years) clinical outcomes of first-in-human biodegradable poly-l-lactic acid coronary stents: Igaki-Tamai stents.

BACKGROUND: The purpose of this study was to evaluate the long-term safety of the Igaki-Tamai stent, the first-in-human fully biodegradable coronary stent made of poly-l-lactic acid. METHODS AND RESULTS: Between September 1998 and April 2000, 50 patients with 63 lesions were treated electively with 84 Igaki-Tamai stents. Overall clinical follow-up (>10 years) of major adverse cardiac events and rates of scaffold thrombosis was analyzed together with the results of angiography and intravascular ultrasound. Major adverse cardiac events included all-cause death, nonfatal myocardial infarction, and target lesion revascularization/target vessel revascularization. During the overall clinical follow-up period (121 ± 17 months), 2 patients were lost to follow-up. There were 1 cardiac death, 6 noncardiac deaths, and 4 myocardial infarctions. Survival rates free of all-cause death, cardiac death, and major adverse cardiac events at 10 years were 87%, 98%, and 50%, respectively. The cumulative rates of target lesion revascularization (target vessel revascularization) were 16% (16%) at 1 year, 18% (22%) at 5 years, and 28% (38%) at 10 years. Two definite scaffold thromboses (1 subacute, 1 very late) were recorded. The latter case was related to a sirolimus-eluting stent, which was implanted for a lesion proximal to an Igaki-Tamai stent. From the analysis of intravascular ultrasound data, the stent struts mostly disappeared within 3 years. The external elastic membrane area and stent area did not change. CONCLUSION: Acceptable major adverse cardiac events and scaffold thrombosis rates without stent recoil and vessel remodeling suggested the long-term safety of the Igaki-Tamai stent.

Endothelial-dependent vasomotion in a coronary segment treated by ABSORB everolimus-eluting bioresorbable vascular scaffold system is related to plaque composition at the time of bioresorption of the polymer: indirect finding of vascular reparative therapy?

AIMS: To analyse the vasoreactivity of a coronary segment, previously scaffolded by the ABSORB bioresorbable vascular scaffold (BVS) device, in relationship to its intravascular ultrasound-virtual histology (IVUS-VH) composition and reduction in greyscale echogenicity of the struts. Coronary segments, transiently scaffolded by a polymeric device, may in the long-term recover a normal vasomotor tone. Recovery of a normal endothelial-dependent vasomotion may be enabled by scaffold bioresorption, composition of the underlying tissue, or a combination of both mechanisms. METHODS AND RESULTS: All patients from the ABSORB Cohort A and B trials, who underwent a vasomotion test and IVUS-VH investigation at 12 and 24 months, were included. Acetylcholine (Ach) and nitroglycerin were used to test either the endothelial-dependent or -independent vasomotion of the treated segment. Changes in polymeric strut echogenicity-a surrogate for bioresorption-IVUS-VH composition of the tissue underneath the scaffold and their relationship with the pharmacologically induced vasomotion were all evaluated. Overall, 26 patients underwent the vasomotion test (18 at 12 and 8 at 24 months). Vasodilatory response to Ach was quantitatively associated with larger reductions over time in polymeric strut echogenicity (y= -0.159x- 6.85; r= -0.781, P< 0.001). Scaffolded segments with vasoconstriction to Ach had larger vessel areas (14.37 ± 2.50 vs. 11.85 ± 2.54 mm(2), P= 0.030), larger plaque burden (57.31 ± 5.96 vs. 49.09 ± 9.10%, P= 0.018), and larger necrotic core (NC) areas [1.39 (+1.14, +1.74) vs. 0.78 mm(2) (+0.20, +0.98), P= 0.006] compared with those with vasodilation. CONCLUSION: Vasodilatory response to Ach, in coronary segments scaffolded by the ABSORB BVS device, is associated with a reduction in echogenicity of the scaffold over time, and a low amount of NC. In particular, the latter finding resembles the behaviour of a native coronary artery not caged by an intracoronary device.

Optimized preoperative planning of double outlet right ventricle patients by 3D printing and virtual reality: a pilot study.

OBJECTIVES: In complex double outlet right ventricle (DORV) patients, the optimal surgical approach may be difficult to assess based on conventional 2-dimensional (2D) ultrasound (US) and computed tomography (CT) imaging. The aim of this study is to assess the added value of 3-dimensional (3D) printed and 3D virtual reality (3D-VR) models of the heart used for surgical planning in DORV patients, supplementary to the gold standard 2D imaging modalities. METHODS: Five patients with different DORV subtypes and high-quality CT scans were selected retrospectively. 3D prints and 3D-VR models were created. Twelve congenital cardiac surgeons and paediatric cardiologists, from 3 different hospitals, were shown 2D-CT first, after which they assessed the 3D print and 3D-VR models in random order. After each imaging method, a questionnaire was filled in on the visibility of essential structures and the surgical plan. RESULTS: Spatial relationships were generally better visualized using 3D methods (3D printing/3D-VR) than in 2D. The feasibility of ventricular septum defect patch closure could be determined best using 3D-VR reconstructions (3D-VR 92%, 3D print 66% and US/CT 46%, P < 0.01). The percentage of proposed surgical plans corresponding to the performed surgical approach was 66% for plans based on US/CT, 78% for plans based on 3D printing and 80% for plans based on 3D-VR visualization. CONCLUSIONS: This study shows that both 3D printing and 3D-VR have additional value for cardiac surgeons and cardiologists over 2D imaging, because of better visualization of spatial relationships. As a result, the proposed surgical plans based on the 3D visualizations matched the actual performed surgery to a greater extent.

Artificial intelligence in medical device software and high-risk medical devices - a review of definitions, expert recommendations and regulatory initiatives.

INTRODUCTION: Artificial intelligence (AI) encompasses a wide range of algorithms with risks when used to support decisions about diagnosis or treatment, so professional and regulatory bodies are recommending how they should be managed. AREAS COVERED: AI systems may qualify as standalone medical device software (MDSW) or be embedded within a medical device. Within the European Union (EU) AI software must undergo a conformity assessment procedure to be approved as a medical device. The draft EU Regulation on AI proposes rules that will apply across industry sectors, while for devices the Medical Device Regulation also applies. In the CORE-MD project (Coordinating Research and Evidence for Medical Devices), we have surveyed definitions and summarize initiatives made by professional consensus groups, regulators, and standardization bodies. EXPERT OPINION: The level of clinical evidence required should be determined according to each application and to legal and methodological factors that contribute to risk, including accountability, transparency, and interpretability. EU guidance for MDSW based on international recommendations does not yet describe the clinical evidence needed for medical AI software. Regulators, notified bodies, manufacturers, clinicians and patients would all benefit from common standards for the clinical evaluation of high-risk AI applications and transparency of their evidence and performance.

Quantitative optical frequency domain imaging assessment of in-stent structures in patients with ST-segment elevation myocardial infarction: impact of imaging sampling rate.

BACKGROUND: The impact of the sampling rate (SR) of optical frequency domain imaging (OFDI) on quantitative assessment of in-stent structures (ISS) such as plaque prolapse and thrombus remains unexplored. METHODS AND RESULTS: OFDI after stenting was performed in ST-segment elevation myocardial infarction (STEMI) patients using a TERUMO OFDI system (Terumo Europe, Leuven, Belgium) with 160 frames/s and pullback speed of 20 mm/s. A total of 126 stented segments were analyzed. ISS were classified as either attached or non-attached to stent area boundaries. The volume, mean area and largest area of ISS were assessed according to 4 frequencies of SR, corresponding to distances between the analyzed frames of 0.125, 0.25, 0.50 and 1.0 mm. ISS volume was calculated by integrating cross-sectional ISS areas multiplied by each sampling distance using the disk summation method. The volume and mean area of ISS became significantly larger, while the largest area became significantly smaller as sampling distance became larger (1.11 mm(2) for 0.125 mm vs. 1.00 mm(2) for 1.0 mm, P for trend=0.036). In addition, variance of difference was positively associated with increasing width of sampling distance. CONCLUSIONS: Quantification of ISS is significantly influenced by the applied frequency of SR. This should be taken into account when designing future OFDI studies in which quantitative assessment of ISS is critical for the evaluation of STEMI patients.

Artificial Intelligence and Transcatheter Interventions for Structural Heart Disease: A glance at the (near) future.

With innovations in therapeutic technologies and changes in population demographics, transcatheter interventions for structural heart disease have become the preferred treatment and will keep growing. Yet, a thorough clinical selection and efficient pathway from diagnosis to treatment and follow-up are mandatory. In this review we reflect on how artificial intelligence may help to improve patient selection, pre-procedural planning, procedure execution and follow-up so to establish efficient and high quality health care in an increasing number of patients.