Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography
Apostolos Tsiachristas, Kenneth Chan, Elizabeth Wahome, Benjamin Kearns, Parijat Patel, Maria Lyasheva, Nigar Syed, Sam Fry, Thomas Halborg, Henry West, Ed Nicol, David Adlam, Bhavik Modi, Attila Kardos, John P. Greenwood, Nikant Sabharwal, Giovanni Luigi De Maria, Shahzad Munir, Elisa McAlindon, Yogesh Sohan, Pete Tomlins, Muhammad Hussnain Siddique, Cheerag Shirodaria, Ron Blankstein, Milind Y. Desai, Stefan Neubauer, Keith M. Channon, John Deanfield, Ron Akehurst, Charalambos Antoniades, Sheena Thomas, Jon Denton, Robyn Farrall, Caroline Taylor, Wendy Qin, Mary Kasongo, Chrisha Ledesma, Damaris Darby, Bruno Silva Santos, Alexios S Antonopoulos, Michail C Mavrogiannis, Andrew Kelion, Susan Anthony, Adrian Banning, Cheng Xie, Rafail A Kotronias, Lucy Kingham, Rajesh K Kharbanda, Chris Mathers, Tarun K Mittal, Anne Rose, George Hudson, Amrita Bajaj, Intrajeet Das, Aparna Deshpande, Praveen Rao, Dan Lawday, Francesca Pugliese, Steffen E Petersen, Saeed Mirsadraee, Nicholas Screaton, Jonathan Rodrigues, Benjamin Hudson, John Graby, Colin Berry, Mohamed Marwan, Pál Maurovich-Horvat, Guo-Wei He, Wen-Hua Lin, Li-Juan Fan, Naohiko Takahashi, Hidekazu Kondo, Neng Dai, Junbo Ge, Bon-Kwon Koo, Marco Guglielmo, Gianluca Pontone, Daniel Huck, Theodora Benedek, Ronak Rajani, Dijana Vilic, Haleema Aljazzaf, Mak S Mun, Giulia Benedetti, Rebecca L Preston, Zahra Raisi-Estabragh, Derek L Connolly, Vinoda Sharma, Rebecca Grenfell, William Bradlow, Matthias Schmitt, Fabiano Serfaty, Ilan Gottlieb, Mario F T Neves, David E Newby, Marc R Dweck, Bernard J Gersh, Stéphane Hatem, Alban Redheuil, Georgios Benetos
Abstract
AIMS: Coronary computed tomography angiography (CCTA) is a first-line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We assessed the lifetime cost-effectiveness of integrating a novel artificial intelligence-enhanced image analysis algorithm (AI-Risk) that stratifies the risk of cardiac events by quantifying coronary inflammation, combined with the extent of coronary artery plaque and clinical risk factors, by analysing images from routine CCTA. METHODS AND RESULTS: A hybrid decision-tree with population cohort Markov model was developed from 3393 consecutive patients who underwent routine CCTA for suspected obstructive CAD and followed up for major adverse cardiac events over a median (interquartile range) of 7.7(6.4-9.1) years. In a prospective real-world evaluation survey of 744 consecutive patients undergoing CCTA for chest pain investigation, the availability of AI-Risk assessment led to treatment initiation or intensification in 45% of patients. In a further prospective study of 1214 consecutive patients with extensive guidelines recommended cardiovascular risk profiling, AI-Risk stratification led to treatment initiation or intensification in 39% of patients beyond the current clinical guideline recommendations. Treatment guided by AI-Risk modelled over a lifetime horizon could lead to fewer cardiac events (relative reductions of 11%, 4%, 4%, and 12% for myocardial infarction, ischaemic stroke, heart failure, and cardiac death, respectively). Implementing AI-Risk Classification in routine interpretation of CCTA is highly likely to be cost-effective (incremental cost-effectiveness ratio £1371-3244), both in scenarios of current guideline compliance, or when applied only to patients without obstructive CAD. CONCLUSIONS: Compared with standard care, the addition of AI-Risk assessment in routine CCTA interpretation is cost-effective, by refining risk-guided medical management.