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

• Published in: PloS one Vol. 17; no. 9; p. e0274296
• Main Authors: Ploscaru, Vlad, Popa-Fotea, Nicoleta-Monica, Calmac, Lucian, Itu, Lucian Mihai, Mihai, Cosmin, Bataila, Vlad, Dragoescu, Bogdan, Puiu, Andrei, Cojocaru, Cosmin, Costin, Minoiu Aurelian, Scafa-Udriste, Alexandru
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 09.09.2022; Public Library of Science (PLoS)
• Subjects: Acute coronary syndromes; Algorithms; Analysis; Angiography; Annotations; Artificial intelligence; Biology and Life Sciences; Cardiovascular disease; Cardiovascular diseases; Cloud computing; Computer and Information Sciences; Coronary artery disease; Diagnosis; Engineering and Technology; Evaluation; Health services; Heart diseases; Ischemia; Medical imaging; Medicine and Health Sciences; Research and Analysis Methods; Strategy; Study Protocol; Workflow; Romania
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0274296

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.