Efficacy of plaque morphology, physiology and biology in detecting vulnerable plaques: a computational biomechanical analysis study of a prospective multimodality intravascular imaging trial

After myocardial infarction, re-infarction rates are high.

Identifying at risk individuals is important as there are targetable treatment options (PCSK9 inhibitors, anti-inflammatory drugs). The direct assessment of non-culprit plaques by intravascular imaging at the time of revascularisation seems promising.

However, to best do this may require multiple approaches: intravascular ultrasound (IVUS) for plaque burden, near-infrared spectroscopy (NIRS) for lipid, optical coherence tomography (OCT) for cap thickness, macrophages, neovessels and cholesterol crystals, and computational modelling to assess local haemodynamics.

Remarkably, multimodality imaging data has been collected: the PACMAN-AMI study (a drug study, first result March 2022; n=300 patients with a heart attack, 537 vessels studied at two time points) passed two catheters down each non-culprit vessel.

All IVUS, NIRS and OCT have been analysed for drug efficacy endpoints - but not combined, and computational biomechanical analyses have not been performed. My group (clinicians, engineers, AI developers) will do this.

Thanks to prior BHF funded work (PG/17/18/32883) we developed AI pipelines and streamlined workflows to efficiently analyse and co-register these datasets along with the computational biomechanical analyses for all vessels.

Using data driven approaches, we will create risk scores for event prediction promising to guide future approaches to personalised secondary event prevention.