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The clinical value of artificial intelligence (AI)-based diagnostic systems depends not only on their accuracy but also on how well their outputs integrate with clinicians' judgments in practice. Critical knowledge gaps remain regarding diagnostic concordance between AI and clinicians in stress echocardiography interpretation, patient characteristics predicting discordance, and how cardiologists respond when AI recommendations conflict with their clinical diagnoses. This study examined the diagnostic alignment between an AI-driven stress echocardiography system (EchoGo Pro [EGP]) and cardiologists' diagnoses of coronary artery disease (CAD), identified predictors of concordance and AI scan rejection, and explored cardiologists' decision-making strategies when disagreements arise. We conducted mixed methods research. The quantitative study analyzed concordance between EGP and cardiologists using data from 854 participants with suspected CAD in the multicenter PROTEUS randomized controlled trial. Logistic regression identified predictors of agreement, disagreement, and scan rejection, adjusting for age, sex, smoking status, BMI, and cardiovascular risk factors (hypertension, hypercholesterolemia, diabetes, family history of CAD, and prior CAD events). To gain deeper insight into discordance, we conducted a qualitative study analyzing survey responses from 61 UK consultant cardiologists recruited via Qualtrics, exploring their perceptions of AI tools, the risks of following discordant AI recommendations, and their typical responses to AI-clinician disagreement. EGP and cardiologists agreed in 60% (512/854) of the cases, but agreement was significantly lower among patients with hypertension (OR 0.58, 95% CI 0.38-0.89; P=.01), diabetes (OR 0.56, 95% CI 0.35-0.90; P=.02), and pre-existing CAD (OR 0.48, 95% CI 0.30-0.77; P=.002). EGP rejected 26.1% (222/854) of the scans due to insufficient image quality, with rejection significantly more common in male patients (β=0.35; P=.03) and those with a family history of CAD. If a positive CAD diagnosis was assigned when either cardiologists or EGP identified CAD, the proportion of positive cases increased from 17.9% (153/854) to 22.1% (189/854), potentially identifying additional at-risk patients. Survey respondents (50/60, 85% male; 26/57, 46% aged 40-49 years; 39/61, 64% White) required 65% to 69% confidence in their initial diagnosis to justify disregarding contradictory AI recommendations. The survey findings revealed cardiologists treated AI recommendations as advisory rather than definitive. When facing discordance, they retained confidence in their judgment and sought corroboration through additional testing, data review, or second opinions rather than deferring to AI. Paradoxically, cardiologists with higher confidence in AI tools required greater confidence in their own diagnosis to disregard AI recommendations (β=7.73; P=.02). Cardiologists attributed discordance primarily to AI's inability to incorporate patient history, comorbidities, and broader clinical context. EGP shows promise as an adjunctive tool but struggles with multimorbid patients and exhibits high, uneven rejection rates. Cardiologists use AI to prompt scrutiny, not replace judgment. Future systems need to integrate wider patient data with imaging and minimize bias through representative training to avoid exacerbating inequities.

To the Editor: The DIGIT-HF (Digitoxin to Improve Outcomes in Patients with Advanced Chronic Heart Failure) trial, conducted by Bavendiek et al. (Sept. 25 issue), 1 showed the superiority of digitoxin plus guideline-directed medical therapy over placebo plus guideline-directed medical therapy for the primary outcome (composite of death from any cause or hospital admission for worsening heart failure). However, the primary-outcome curves for the digitoxin and placebo groups reconverged, which suggests that the benefit observed at a median follow-up of 36 months may not be sustained. 2 Does prolonged therapy with digitoxin result in neutral or detrimental effects? In addition, subgroup analyses . . .

Herceptin (trastuzumab) is a recombinant, humanized, monoclonal antibody that targets the human epidermal growth factor receptor 2 (HER2) and is used in the treatment of HER2-positive breast and gastric cancers. However, it carries a risk of cardiotoxicity, manifesting as left ventricular (LV) systolic dysfunction, conventionally assessed for by transthoracic echocardiography. Clinical surveillance of cardiac function and discontinuation of trastuzumab at an early stage of LV systolic dysfunction allow for the timely initiation of heart failure drug therapies that can result in the rapid recovery of cardiac function in most patients. Often considered the reference standard for the noninvasive assessment of cardiac volume and function, cardiac magnetic resonance (CMR) imaging has superior reproducibility and accuracy compared to other noninvasive imaging modalities. However, due to limited availability, it is not routinely used in the serial assessment of cardiac function in patients receiving trastuzumab. In this article, we review the diagnostic and prognostic role of CMR in trastuzumab-mediated cardiotoxicity.

Cardiovascular magnetic resonance T1-mapping enables myocardial tissue characterisation, and is capable of quantifying both intracellular and extracellular volume. T1-mapping is conventionally performed in diastole, however, we hypothesised that systolic readout would reduce variability due to a reduction in myocardial blood volume. This study investigated whether T1-mapping in systole alters T1 values compared to diastole and whether reproducibility alters in atrial fibrillation compared to sinus rhythm. We prospectively identified 103 consecutive patients recruited to the Mitral FINDER study who had T1 mapping in systole and diastole. These patients had moderate or severe mitral regurgitation and a high incidence of ventricular dilatation and atrial fibrillation. T1, ECV and goodness-of-fit (R 2 ) values of the T1 times were calculated offline using Circle cvi42 and in house-developed software. Systolic T1 mapping was associated with fewer myocardial segments being affected by artefact compared to diastolic T1 mapping [217/2472 (9%) vs 515/2472 (21%)]. Mean native T1 values were not significantly different when measured in systole and diastole (985 ± 26 ms vs 988 ± 29 respectively; p  = 0.061) and mean post-contrast values showed similar good agreement (462 ± 32 ms vs 459 ± 33 respectively, p  = 0.052). No clinically significant differences in ECV, native T1 and post-contrast T1 were identified between diastolic and systolic T1 maps in males versus females, or in patients with permanent atrial fibrillation versus sinus rhythm. A statistically significant improvement in R 2 value was observed with systolic over diastolic T1 mapping in all analysed maps (n = 411) (96.2 ± 1.4% vs 96.0 ± 1.4%; p  < 0.001) and in subgroup analyses [Sinus rhythm: 96.1 ± 1.4 vs 96.3 ± 1.4 (n = 327); p  < 0.001. AF: 95.5 ± 1.3 vs 95.9 ± 1.2 (n = 80); p  < 0.001] [Males: 95.8 ± 1.4 vs 96.1 ± 1.3 (n = 264); p  < 0.001; Females: 96.2 ± 1.3 vs 96.4 ± 1.4 (n = 143); p  = 0.009]. In conclusion, myocardial T1 mapping is associated with similar T1 and ECV values in systole and diastole. Furthermore, systolic acquisition is less prone to gating artefact in arrhythmia.

Dilated cardiomyopathy (DCM) is a common cause of non-ischaemic heart failure, conferring high morbidity and mortality, including sudden cardiac death due to systolic dysfunction or arrhythmic sudden death. Within the DCM cohort exists a group of patients with familial disease. In this article we review the pathophysiology and cardiac imaging findings of familial DCM, with specific attention to known disease subtypes. The role of advanced cardiac imaging cardiovascular magnetic resonance is still accumulating, and there remains much to be elucidated. We discuss its potential clinical roles as currently known, with respect to diagnostic utility and risk stratification. Advances in such risk stratification may help target pharmacological and device therapies to those at highest risk.

IntroductionThe use and value of artificial intelligence (AI)-driven tools and techniques are under investigation in detecting coronary artery disease (CAD). EchoGo Pro is a patented AI-driven stress echocardiography analysis system produced by Ultromics Ltd. (henceforth Ultromics) to support clinicians in detecting cardiac ischaemia and potential CAD. This manuscript presents the research protocol for a field study to independently evaluate the accuracy, acceptability, implementation barriers, users’ experience and willingness to pay, cost-effectiveness and value of EchoGo Pro.Methods and analysisThe ‘Evaluating AI-driven stress echocardiography analysis system’ (EASE) study is a mixed-method evaluation, which will be conducted in five work packages (WPs). In WP1, we will examine the diagnostic accuracy by comparing test reports generated by EchoGo Pro and three manual raters. In WP2, we will focus on interviewing clinicians, innovation/transformation staff, and patients within the National Health Service (NHS), and staff within Ultromics, to assess the acceptability of this technology. In this WP, we will determine convergence and divergence between EchoGo Pro recommendations and cardiologists’ interpretations and will assess what profile of cases is linked with convergence and divergence between EchoGo Pro recommendations and cardiologists’ interpretations and how these link to outcomes. In WP4, we will conduct a quantitative cross-sectional survey of trust in AI tools applied to cardiac care settings among clinicians, healthcare commissioners and the general public. Lastly, in WP5, we will estimate the cost of deploying the EchoGo Pro technology, cost-effectiveness and willingness to pay cardiologists, healthcare commissioners and the general public. The results of this evaluation will support evidence-informed decision-making around the widespread adoption of EchoGo Pro and similar technologies in the NHS and other health systems.Ethics approval and disseminationThis research has been approved by the NHS Health Research Authority (IRAS No: 315284) and the London South Bank University Ethics Panel (ETH2223-0164). Alongside journal publications, we will disseminate study methods and findings in conferences, seminars and social media. We will produce additional outputs in appropriate forms, for example, research summaries and policy briefs, for diverse audiences in NHS.

Point-of-care ultrasound echocardiography has become an indispensable tool for rapid clinical assessment in emergency medicine. This review article examines the heterogeneity in training pathways globally, outlining the advantages and presenting the challenges to standardisation, documentation practices and quality assurance. By reviewing current curricula, training methods and international models, we aim to identify the positive elements and propose a framework for an ideal national training programme, including the potential role of an examination and higher education institutions.

Bicuspid Aortic Valve (BAV) disease is recognized as the most common congenital heart condition and is frequently associated with complex valvular and aortic disorders. Cardiovascular computed tomography (CT) has become essential for diagnosing BAV, planning procedures, and evaluating patients after treatment. This is largely due to CT’s high spatial resolution and its ability to perform volume imaging effectively. This review provides an up-to-date overview of the increasing role of cardiovascular CT in the management of bicuspid aortic valve (BAV). It covers various aspects, including BAV morphology, optimal sizing for transcatheter aortic valve replacement (TAVR), and post-procedural monitoring. We highlight significant innovations, such as supra-annular sizing techniques and artificial intelligence (AI)-guided analysis, that position CT at the nexus of anatomy, function, and targeted treatment. Additionally, we address controversies concerning inconsistencies in sizing algorithms, recent classification challenges, and radiation exposure. Future development areas include AI predictive tools, radiomic phenotyping, and CT-guided precision medicine. This synthesis aims to provide clinicians and researchers with a high-level guide to the clinical integration of cardiovascular CT and its future in the BAV population. This review provides the most current, comprehensive synthesis on the pivotal role of cardiovascular CT in BAV management, offering a roadmap for integrating advanced imaging into clinical practice and guiding future research priorities.

IntroductionSARS-CoV-2 disease (COVID-19) has had an enormous health and economic impact globally. Although primarily a respiratory illness, multi-organ involvement is common in COVID-19, with evidence of vascular-mediated damage in the heart, liver, kidneys and brain in a substantial proportion of patients following moderate-to-severe infection. The pathophysiology and long-term clinical implications of multi-organ injury remain to be fully elucidated. Age, gender, ethnicity, frailty and deprivation are key determinants of infection severity, and both morbidity and mortality appear higher in patients with underlying comorbidities such as ischaemic heart disease, hypertension and diabetes. Our aim is to gain mechanistic insights into the pathophysiology of multiorgan dysfunction in people with COVID-19 and maximise the impact of national COVID-19 studies with a comparison group of COVID-negative controls.Methods and analysisCOmorbidities and Sociodemographic factors on Multiorgan Injury following COVID-19 (COSMIC) is a prospective, multicentre UK study which will recruit 200 subjects without clinical evidence of prior COVID-19 and perform extensive phenotyping with multiorgan imaging, biobank serum storage, functional assessment and patient reported outcome measures, providing a robust control population to facilitate current work and serve as an invaluable bioresource for future observational studies.Ethics and disseminationApproved by the National Research Ethics Service Committee East Midlands (REC reference 19/EM/0295). Results will be disseminated via peer-reviewed journals and scientific meetings.Trial registration numberCOSMIC is registered as an extension of C-MORE (Capturing Multi-ORgan Effects of COVID-19) on ClinicalTrials.gov (NCT04510025).

Cardiovascular magnetic resonance (CMR) imaging has had a vast impact on the understanding of a wide range of disease processes and pathophysiological mechanisms. More recently, it has contributed significantly to the diagnosis and risk stratification of patients with valvular heart disease. With its increasing use, CMR allows for a detailed, reproducible, qualitative, and quantitative evaluation of left ventricular volumes and mass, thereby enabling assessment of the haemodynamic impact of a valvular lesion upon the myocardium. Postprocessing of the routinely acquired images with feature tracking CMR methodology can give invaluable information about myocardial deformation and strain parameters that suggest subclinical ventricular impairment that remains undetected by conventional measures such as the ejection fraction (EF). T1 mapping and late gadolinium enhancement (LGE) imaging provide deep myocardial tissue characterisation that is changing the approach towards risk stratification of patients as an increasing body of evidence suggests that the presence of fibrosis is related to adverse events and prognosis. This review summarises the current evidence regarding the utility of CMR in the left ventricular assessment of patients with aortic stenosis or mitral regurgitation and its value in diagnosis, risk stratification, and management.