Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography
Authors: Tsiachristas Apostolos , Chan Kenneth , Wahome Elizabeth , Kearns Ben , Patel Parijat , Lyasheva Maria , Syed Nigar , Fry Sam , Halborg Thomas , West Henry , Nicol Edward , Adlam David , Modi Bhavik , Kardos Attila , Greenwood John P , Sabharwal Nikant , De Maria Giovanni Luigi , Munir Shahzad , McAlindon Elisa , Sohan Yogesh , Tomlins Pete , Siddique Muhammad , Shirodaria Cheerag , Blankstein Ron , Desai Milind , Neubauer Stefan , Channon Keith M , Deanfield John , Akehurst Ron , Antoniades Charalambos ,   the ORFAN Consortium, Thomas Sheena , Denton Jon , Farrall Robyn , Taylor Caroline , Qin Wendy , Kasongo Mary , Ledesma Chrisha , Darby Damaris , Santos Bruno Silva , Antonopoulos Alexios S , Mavrogiannis Michail C , Kelion Andrew , Anthony Susan , Banning Adrian , Xie Cheng , Kotronias Rafail A , Kingham Lucy , Kharbanda Rajesh K , Mathers Chris , Mittal Tarun K , Rose Anne , Hudson George , Bajaj Amrita , Das Intrajeet , Deshpande Aparna , Rao Praveen , Lawday Dan , Pugliese Francesca , Petersen Steffen E , Mirsadraee Saeed , Screaton Nicholas , Rodrigues Jonathan , Hudson Benjamin , Graby John , Berry Colin , Marwan Mohamed , Maurovich-Horvat Pál , He Guo-Wei , Lin Wen-Hua , Fan Li-Juan , Takahashi Naohiko , Kondo Hidekazu , Dai Neng , Ge Junbo , Koo Bon-Kwon , Guglielmo Marco , Pontone Gianluca , Huck Daniel , Benedek Theodora , Rajani Ronak , Vilic Dijana , Aljazzaf Haleema , Mun Mak S , Benedetti Giulia , Preston Rebecca L , Raisi-Estabragh Zahra , Connolly Derek L , Sharma Vinoda , Grenfell Rebecca , Bradlow William , Schmitt Matthias , Serfaty Fabiano , Gottlieb Ilan , Neves Mario F T , Newby David E , Dweck Marc R , Gersh Bernard J , Hatem Stéphane , Redheuil Alban , Benetos Georgios , Beer Meinrad , Rodriguez-Granillo Gastón A , Selvanayagam Joseph , Lopez-Jimenez Francisco , De Bosscher Ruben , Tavildari Alain , Figtree Gemma , Danad Ibrahim , Shantouf Ronney , Kietselaer Bas , Tousoulis Dimitris , Dangas George , Mehta Nehal N , Kotanidis Christos , Kunadian Vijay , Fairbairn Timothy A 
Published: September 2024

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.