Combining CT diagnostic data and interventional approaches for futureproof cardiology care

ongoing

"Coronary artery disease (CAD) is caused by the pathological process in which fat, cholesterol and calcium accumulate on the arterial wall. It is the leading cause of mortality in the world, affecting in 2019 about 200 million individuals or 2.5% of the global population and resulting in over 9 million deaths annually. The prevalence of CAD in the European Union (EU) reached 5.11% in 2019 . As a result, CAD-related deaths topped 973,000 in the EU in 2019. CAD incidence is expected to rise further due to the increased prevalence of risk factors including obesity, diabetes, and increasing age. For a patient with CAD, the care pathway still involves enormous variability and complexities. Inefficiencies and challenges in the treatment pathway are associated with poorer patient outcomes including recurrent cardiac events, incomplete revascularization in complex patients, and increased risk of mortality in patients with both acute and chronic CAD. Due to the low sensitivity or specificity of the standard diagnostic tests, 60% of CAD patients unnecessarily undergo an ICA, as they are found to have non-significant coronary stenoses and do not require revascularization. Coronary Computed Tomography Angiography (CCTA) uses X-ray technology and computer processing to create a detailed 3D image of the coronary arteries, revealing the degree of lumen obstruction. It provides non-invasive access to the coronary anatomy, also for asymptomatic patients who would normally not undergo invasive coronary angiography (ICA). Current guidelines adopted in the US, EU, and the UK recommend CCTA as a first-line test for evaluation of CAD, positioning it as a ""gatekeeper"" to the Cath lab. In COMBINE-CT, we will deliver a fully automated, vendor agnostic CCTA-enabled workflow for chronic CAD patients, covering diagnosis, treatment, and follow-up. COMBINE-CT will close the gaps in the existing workflow for the treatment of chronic CAD, to improve hospital efficiency and patient outcomes. AI-powered CCTA algorithms will enable definitive ischemia diagnosis, accurate patient stratification and efficient planning of the interventions, as well as patient specific follow-up. While our focus on CAD is justified by the large patient population, the CCTA-enabled diagnostic accuracy and seamless workflow, backed by the clinical evidence generated in five multicentre clinical trials, will be directly transferable to other clinical domains using CT. Interdisciplinarity is intrinsically built in the design of the COMBINE-CT consortium, combining expertise in cardiology, cardiovascular radiology, interventional cardiology, cardiac surgery, pharmacology – with expertise from engineering (medical imaging) and AI. The public-private partnership in COMBINE-CT integrates top knowledge on several medical disciplines (cardiology, radiology, interventional cardiology) with engineering, AI, design expertise - as well as the involvement of health economists and patient organizations, to fill in the gaps of the current CAD clinical pathways and prepare the ground for the imminent high-volume CCTA needs, beyond the research hospital setting. Clinical partners represent more than half of the COMBINE-CT consortium, ensuring access to large cohorts for stable CAD patients. COMBINE-CT will also lay the ground for further research that is likely to trigger a paradigm shift towards the use of imaging markers in the medical treatment evaluation and clinical trial design."