Artificial intelligence and cloud based platform for fully automated PCI guidance from coronary angiography-study protocol

PLoS One. 2022 Sep 9;17(9):e0274296. doi: 10.1371/journal.pone.0274296. eCollection 2022.

Abstract

Ischemic heart disease represent a heavy burden for the medical systems irrespective of the methods used for diagnosis and treatment of such patients in the daily medical routine. The present paper depicts the protocol of a study whose main aim is to develop, implement and test an artificial intelligence algorithm and cloud based platform for fully automated PCI guidance using coronary angiography images. We propose the utilisation of multiple artificial intelligence based models to produce three-dimensional coronary anatomy reconstruction and assess function- post-PCI FFR computation- for developing an extensive report describing and motivating the optimal PCI strategy selection. All the relevant artificial intelligence model outputs (anatomical and functional assessment-pre- and post-PCI) are presented to the clinician via a cloud platform, who can then take the utmost treatment decision. The physician will be provided with multiple scenarios and treatment possibilities for the same case allowing a real-time evaluation of the most appropriate PCI strategy planning and follow-up. The artificial intelligence algorithms and cloud based PCI selection workflow will be verified and validated in a pilot clinical study including subjects prospectively to compare the artificial intelligence services and results against annotations and invasive measurements.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence
  • Cloud Computing
  • Coronary Angiography / methods
  • Coronary Artery Disease* / diagnosis
  • Fractional Flow Reserve, Myocardial*
  • Humans
  • Percutaneous Coronary Intervention* / methods
  • Treatment Outcome

Grants and funding

This research was funded by PN-III-P2-2.1-PED- 2019-2434 “Artificial intelligence based-evaluation of the coronary anatomy and the evolution of coronary lesions using routine angiography”, obtained by Alexandru Scafa-Udriste. The funders had and will not have a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.