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Background: Stress echocardiography (SE) is one of the most commonly used diagnostic imaging tests for coronary artery disease (CAD) but requires clinicians to visually assess scans to identify patients who may benefit from invasive investigation and treatment. EchoGo Pro provides an automated interpretation of SE based on artificial intelligence (AI) image analysis. In reader studies, use of EchoGo Pro when making clinical decisions improves diagnostic accuracy and confidence. Prospective evaluation in real world practice is now important to understand the impact of EchoGo Pro on the patient pathway and outcome., Methods: PROTEUS is a randomized, multicenter, 2-armed, noninferiority study aiming to recruit 2,500 participants from National Health Service (NHS) hospitals in the UK referred to SE clinics for investigation of suspected CAD. All participants will undergo a stress echocardiogram protocol as per local hospital policy. Participants will be randomized 1:1 to a control group, representing current practice, or an intervention group, in which clinicians will receive an AI image analysis report (EchoGo Pro, Ultromics Ltd, Oxford, UK) to use during image interpretation, indicating the likelihood of severe CAD. The primary outcome will be appropriateness of clinician decision to refer for coronary angiography. Secondary outcomes will assess other health impacts including appropriate use of other clinical management approaches, impact on variability in decision making, patient and clinician qualitative experience and a health economic analysis., Discussion: This will be the first study to assess the impact of introducing an AI medical diagnostic aid into the standard care pathway of patients with suspected CAD being investigated with SE., Trial Registration: Clinicaltrials.gov registration number NCT05028179, registered on 31 August 2021; ISRCTN: ISRCTN15113915; IRAS ref: 293515; REC ref: 21/NW/0199., Competing Interests: Declaration of Competing Interest GW, RS, WH, TD, ES, MB, OH, LT, JL, RU are all employees of Ultromics Ltd GW, RS, WH, BT, JL hold share options for Ultromics Ltd PL and RU are founders and shareholders of Ultromics Ltd and have patents in the field of AI and imaging. SEP provides consultancy to Circle Cardiovascular Imaging, Inc, Calgary, Alberta, Canada. All other authors declare that they have no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: The purpose of this study was to establish whether an artificially intelligent (AI) system can be developed to automate stress echocardiography analysis and support clinician interpretation., Background: Coronary artery disease is the leading global cause of mortality and morbidity and stress echocardiography remains one of the most commonly used diagnostic imaging tests., Methods: An automated image processing pipeline was developed to extract novel geometric and kinematic features from stress echocardiograms collected as part of a large, United Kingdom-based prospective, multicenter, multivendor study. An ensemble machine learning classifier was trained, using the extracted features, to identify patients with severe coronary artery disease on invasive coronary angiography. The model was tested in an independent U.S., Study: How availability of an AI classification might impact clinical interpretation of stress echocardiograms was evaluated in a randomized crossover reader study., Results: Acceptable classification accuracy for identification of patients with severe coronary artery disease in the training data set was achieved on cross-fold validation based on 31 unique geometric and kinematic features, with a specificity of 92.7% and a sensitivity of 84.4%. This accuracy was maintained in the independent validation data set. The use of the AI classification tool by clinicians increased inter-reader agreement and confidence as well as sensitivity for detection of disease by 10% to achieve an area under the receiver-operating characteristic curve of 0.93., Conclusions: Automated analysis of stress echocardiograms is possible using AI and provision of automated classifications to clinicians when reading stress echocardiograms could improve accuracy, inter-reader agreement, and reader confidence., Competing Interests: Funding Support and Author Disclosures Data and images used in the training data set were collected with the support of a National Institute of Health Research (NIHR) Health Education England (HEE) Healthcare Science Research Fellowship (NIHR-HCS-P13-04-001); Cardiovascular Clinical Research Facility, University of Oxford; Ultromics Ltd; Lantheus Medical Imaging Inc; NIHR Oxford Biomedical Research Centre; University of Oxford; and Oxford British Heart Foundation Centre for Research Excellence. Dr Lamata holds a Wellcome Trust Senior Research Fellowship (209450/Z/17/Z). Dr Upton is the CEO, co-founder, and a shareholder of Ultromics Ltd, which develops artificial intelligence echocardiography software. Dr Leeson is a co-founder and a shareholder of Ultromics Ltd; has previously consulted for Intelligent Ultrasound; and has held research grants from Lantheus Medical Imaging. Drs Upton, Leeson, Markham, and Wilkes are inventors on filed patents in the field of echocardiography. Drs Mumith, Beqiri, Parker, Hawkes, Gao, Porumb, Markham, O'Driscoll, Hassanali, Groves, and Woodward, Ms Marques, and Mr Kenworthy are employees of Ultromics Ltd. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Aims: Stress echocardiography is widely used to identify obstructive coronary artery disease (CAD). High accuracy is reported in expert hands but is dependent on operator training and image quality. The EVAREST study provides UK-wide data to evaluate real-world performance and accuracy of stress echocardiography., Methods and Results: Participants undergoing stress echocardiography for CAD were recruited from 31 hospitals. Participants were followed up through health records which underwent expert adjudication. Cardiac outcome was defined as anatomically or functionally significant stenosis on angiography, revascularization, medical management of ischaemia, acute coronary syndrome, or cardiac-related death within 6 months. A total of 5131 patients (55% male) participated with a median age of 65 years (interquartile range 57-74). 72.9% of studies used dobutamine and 68.5% were contrast studies. Inducible ischaemia was present in 19.3% of scans. Sensitivity and specificity for prediction of a cardiac outcome were 95.4% and 96.0%, respectively, with an accuracy of 95.9%. Sub-group analysis revealed high levels of predictive accuracy across a wide range of patient and protocol sub-groups, with the presence of a resting regional wall motion abnormalitiy significantly reducing the performance of both dobutamine (P < 0.01) and exercise (P < 0.05) stress echocardiography. Overall accuracy remained consistently high across all participating hospitals., Conclusion: Stress echocardiography has high accuracy across UK-based hospitals and thus indicates stress echocardiography is being delivered effectively in real-world practice, reinforcing its role as a first-line investigation in the assessment of patients with stable chest pain., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)