Assessment of lesion-associated myocardial ischemia based on fusion coronary CT imaging - the FUSE-HEART study: A protocol for non-randomized clinical trial.

INTRODUCTION: Multimodality assessment of coronary artery lesions has demonstrated superior effectiveness compared to the conventional approach, for assessing both anatomical and functional significance of a coronary stenosis. Multiple imaging modalities can be integrated into a fusion imaging tool to better assess myocardial ischemia. MATERIAL AND METHODS: The FUSE-HEART trial is a single center, prospective, cohort study that will assess the impact of a coronary artery stenosis on myocardial function and viability, based on advanced fusion imaging technics derived from Cardiac Computed Tomography Angiography (CCTA). Moreover, the study will investigate the correlation between morphology and composition of the coronary plaques and myocardial ischemia in the territory irrigated by the same coronary artery. At the same time, imaging parameters will be correlated with inflammatory status of the subjects. The trial will include 100 subjects with coronary lesions found on CCTA examination. The study population will be divided into 2 groups: first group will consist of subjects with anatomically significant coronary lesions on native coronary arteries and the second one will include subjects surviving an acute myocardial infarction. The vulnerability score of the subjects will be calculated based on presence of CCTA vulnerability markers of the coronary plaques: napkin ring sign, positive remodeling, spotty calcifications, necrotic core, and low-density plaques. 3D fusion images of the coronary tree will be generated, integrating the images reflecting wall motion with the ones of coronary circulation. The fusion models will establish the correspondence between plaque composition and wall motion in the subtended myocardium of the coronary artery. The study primary outcome will be represented by the rate of major adverse cardiac events related to myocardial ischemia at 1-year post assessment, in correlation with the degree of coronary artery stenosis and myocardial ischemia or viability.The secondary outcomes are represented by the rate of re-hospitalization, rate of survival and rate of major adverse cardiovascular events (including cardiovascular death or stroke), in correlation with the morphology and composition of atheromatous plaques located in a coronary artery, and myocardial ischemia in the territory irrigated by the same coronary artery. CONCLUSION: In conclusion, FUSE-HEART will be a study based on modern imaging tools that will investigate the impact of a coronary artery stenosis on myocardial function and viability, using advanced fusion imaging technics derived from CCTA, sighting to validate plaque composition and morphology, together with inflammatory biomarkers, as predictors to myocardial viability.

From CT to artificial intelligence for complex assessment of plaque-associated risk.

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.