Artificial intelligence in cardiology: the debate continues

In 1955, when John McCarthy and his colleagues proposed their first study of artificial intelligence, they suggested that ‘every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it’. Whether that might ever be possible would depend on how we define intelligence, but what is indisputable is that new methods are needed to analyse and interpret the copious information provided by digital medical images, genomic databases, and biobanks. Technological advances have enabled applications of artificial intelligence (AI) including machine learning (ML) to be implemented into clinical practice, and their related scientific literature is exploding. Advocates argue enthusiastically that AI will transform many aspects of clinical cardiovascular medicine, while sceptics stress the importance of caution and the need for more evidence. This report summarizes the main opposing arguments that were presented in a debate at the 2021 Congress of the European Society of Cardiology. Artificial intelligence is an advanced analytical technique that should be considered when conventional statistical methods are insufficient, but testing a hypothesis or solving a clinical problem—not finding another application for AI—remains the most important objective. Artificial intelligence and ML methods should be transparent and interpretable, if they are to be approved by regulators and trusted to provide support for clinical decisions. Physicians need to understand AI methods and collaborate with engineers. Few applications have yet been shown to have a positive impact on clinical outcomes, so investment in research is essential

A counterblast to pessimists and naysayers – intelligent echocardiography remains the foundation stone of evidence-based clinical cardiology

Provocative comments can entertain and instruct as long as they are used to stimulate a civilized discussion, and it is fun to embrace an opportunity to change one’s mind (and learn). I am therefore delighted to respond to Adrian Ionescu’s comments, although I think he has got it wrong—as I will aim to demonstrate. In the spirit of this debate, please indulge me while I too let off some steam! I have always disliked the fact that one of the subspecialties within cardiology, which did not exist when I qualified in the 1970s, has come to be known as “cardiac imaging.” Cardiac diagnosis is not about pictures, although some conditions are indeed instantly recognizable. Usually, what we need to know to understand disease is how the heart is functioning, much more than what it looks like. That is true for coronary arteriography as much as for non-invasive imaging. If I am forced to adopt a subspeciality label, then I would much prefer to be considered a clinical pathophysiologist. Accurate diagnosis is the sine qua non of logical evidence-based clinical practice, yet we often get it wrong. And there remain many patients with disease that we cannot diagnose precisely because we do not understand it sufficiently. Why does this patient with heart failure with reduced ejection fraction have impaired left ventricular function? Why does that patient with normal blood pressure have left ventricular hypertrophy? In this patient in sinus rhythm, which particular aspects of cardiovascular function will influence the development of dementia? Cardiologists who are expert in performing, analyzing, and interpreting detailed echocardiographic and cardiovascular investigations are needed to give us the best chance of answering such questions. They cannot be replaced by an uninterpretable computer algorithm when no-one yet knows the answer—but by staying in control, researchers can use artificial intelligence (AI) to help their thinking

Diagnostic recommendations and phenotyping for heart failure with preserved ejection fraction:knowing more and understanding less?

This article refers to 'Diagnostic scores predict morbidity and mortality in patients hospitalised for heart failure with preserved ejection fraction' by F.H. Verbrugge et al., published in this issue on pages xxx

Longitudinal evaluation of myocardial function in preterm infants with respiratory distress syndrome

Aim Preterm births and respiratory distress syndrome (RDS) are associated with pulmonary vascular disease and altered myocardial function. We serially assessed up to 1 year of age the effects of RDS on global and regional myocardial function of preterm infants, compared to preterm and term controls using conventional echocardiography parameters, tissue Doppler velocities and deformation analysis. Methods and results A total of 120 infants (30 preterm [PT] with RDS, 30 PT controls without RDS, and 60 term controls) underwent conventional and tissue Doppler echocardiography within 72 hours of birth, at corrected term age for the preterm infants, at 1 month corrected, and at 1 year corrected age. At birth, compared to preterm and term controls, the PT‐RDS group had decreased right ventricular (RV) long‐axis function, systolic velocity, peak systolic strain, shorter pulmonary arterial acceleration time (PAAT), and lower ratio of PAAT to RV ejection time (PAAT:RVET). Preterm infants had left ventricular (LV) diastolic dysfunction at birth (lower early diastolic myocardial velocity, mitral E velocity, and mitral E:A ratio), and reduced long‐axis systolic velocities and shortening. Differences between groups disappeared by 1 month corrected age, except PAAT:RVET which remained lower in the PT‐RDS group. At 1 year, RV function was normal in PT‐RDS apart from systolic strain rate, and LV function was normal apart from lower stroke volume and shortening, relative to body weight. Conclusion PT‐RDS had lower left and right ventricular systolic and diastolic function at birth which improved over time, suggesting postnatal maturation of cardiac function and resolution of lung disease

When does the E/e’ index not work? The pitfalls of oversimplifying diastolic function

Since the E/e’ ratio was first described in 1997 as a noninvasive surrogate marker of mean pulmonary capillary wedge pressure, it has gained a central role in diagnostic recommendations and a supremacy in clinical use that require critical reappraisal. We review technical factors, physiological influences, and pathophysiological processes that can complicate the interpretation of E/e’. The index has been validated in certain circumstances, but its use cannot be extrapolated to other situations—such as critically ill patients or children—in which it has either been shown not to work or it has not been well validated. Meta-analyses demonstrated that E/e’ is not useful for the diagnosis of HFpEF and that changes in E/e’ are uninformative during diastolic stress echocardiography. A similar ratio has been applied to estimate right heart filling pressure despite insufficient evidence. As a composite index, changes in E/e’ should only be interpreted with knowledge of changes in its components. Sometimes, e’ alone may be as informative. Using a scoring system for diastolic function that relies on E/e’, as recommended in consensus documents, leaves some patients unclassified and others in an intermediate category. Alternative methods for estimating left heart filling pressures may be more accurate, including the duration of retrograde pulmonary venous flow, or contractile deformation during atrial pump function. Using all measurements as continuous variables may demonstrate abnormal diastolic function that is missed by using the reductive index E/e’ alone. With developments in diagnostic methods and clinical decision support tools, this may become easier to implement

Improved clinical investigation and evaluation of high-risk medical devices: the rationale and objectives of CORE-MD (Coordinating Research and Evidence for Medical Devices).

In the European Union (EU), the delivery of health services is a national responsibility but there are concerted actions between member states to protect public health. Approval of pharmaceutical products is the responsibility of the European Medicines Agency, while authorising the placing on the market of medical devices is decentralised to independent 'conformity assessment' organisations called notified bodies. The first legal basis for an EU system of evaluating medical devices and approving their market access was the Medical Device Directive, from the 1990s. Uncertainties about clinical evidence requirements, among other reasons, led to the EU Medical Device Regulation (2017/745) that has applied since May 2021. It provides general principles for clinical investigations but few methodological details - which challenges responsible authorities to set appropriate balances between regulation and innovation, pre- and post-market studies, and clinical trials and real-world evidence. Scientific experts should advise on methods and standards for assessing and approving new high-risk devices, and safety, efficacy, and transparency of evidence should be paramount. The European Commission recently awarded a Horizon 2020 grant to a consortium led by the European Society of Cardiology and the European Federation of National Associations of Orthopaedics and Traumatology, that will review methodologies of clinical investigations, advise on study designs, and develop recommendations for aggregating clinical data from registries and other real-world sources. The CORE-MD project (Coordinating Research and Evidence for Medical Devices) will run until March 2024. Here, we describe how it may contribute to the development of regulatory science in Europe. Cite this article: EFORT Open Rev 2021;6:839-849. DOI: 10.1302/2058-5241.6.210081

Association Analysis of ULK1 with Crohn's Disease in a New Zealand Population

The gene ULK1 is an excellent candidate for Crohn's disease (CD) due to its role in autophagy. A recent study provided evidence for the involvement of ULK1 in the pathogenesis of CD (Henckaerts et al., 2011). We attempted to validate this association, using a candidate gene SNP study of ULK1 in CD. We identified tagging SNPs and genotyped these SNPs using the Sequenom platform in a Caucasian New Zealand dataset consisting of 406 CD patients and 638 controls. In this sample, we were able to demonstrate an association between CD and several different ULK1 SNPs and haplotypes. Phenotypic analysis showed an association with age of diagnosis 17–40 years and inflammatory behaviour. The findings of this study provide evidence to suggest that genetic variation in ULK1 may play a role in interindividual differences in CD susceptibility and clinical outcome

DNase1: No Association with Crohn's Disease in a New Zealand Population

DNase1 has been implicated in a number of immune disorders and is an excellent candidate gene for Crohn's disease (CD). We investigated whether DNase1 SNPs rs1053874 and rs8176938 were associated with CD in a well-characterized New Zealand dataset consisting of 447 cases and 716 controls. Furthermore, we measured serum DNase1 activity levels in a number of CD patients and controls. We did not find any evidence of association for either DNase1 genetic variation or DNase1 activity levels with CD. The lack of association indicates that DNase1 does not play a significant role in predisposing to CD in the New Zealand population

Evidence from clinical trials on high-risk medical devices in children

BACKGROUND: Meeting increased regulatory requirements for clinical evaluation of medical devices marketed in Europe in accordance with the Medical Device Regulation (EU 2017/745) is challenging, particularly for high-risk devices used in children. METHODS: Within the CORE-MD project, we performed a scoping review on evidence from clinical trials investigating high-risk paediatric medical devices used in paediatric cardiology, diabetology, orthopaedics and surgery, in patients aged 0–21 years. We searched Medline and Embase from 1st January 2017 to 9th November 2022. RESULTS: From 1692 records screened, 99 trials were included. Most were multicentre studies performed in North America and Europe that mainly had evaluated medical devices from the specialty of diabetology. Most had enrolled adolescents and 39% of trials included both children and adults. Randomized controlled trials accounted for 38% of the sample. Other frequently used designs were before-after studies (21%) and crossover trials (20%). Included trials were mainly small, with a sample size <100 participants in 64% of the studies. Most frequently assessed outcomes were efficacy and effectiveness as well as safety. CONCLUSION: Within the assessed sample, clinical trials on high-risk medical devices in children were of various designs, often lacked a concurrent control group, and recruited few infants and young children