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Co-registered optical coherence tomography and X-ray angiography for the prediction of fractional flow reserve

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Abstract

Cardiovascular disease (CVD) stands as the leading global cause of mortality, and coronary artery disease (CAD) has the highest prevalence, contributing to 42% of these fatalities. Recognizing the constraints inherent in the anatomical assessment of CAD, Fractional Flow Reserve (FFR) has emerged as a pivotal functional diagnostic metric. Herein, we assess the potential of employing an ensemble approach with deep neural networks (DNN) to predict invasively measured Fractional Flow Reserve (FFR) using raw anatomical data extracted from both optical coherence tomography (OCT) and X-ray coronary angiography (XA). In this study, we used a challenging dataset, with 46% of the lesions falling within the FFR range of 0.75 to 0.85. Despite this complexity, our model achieved an accuracy of 84.3%, demonstrating a sensitivity of 87.5% and a specificity of 81.4%. Our results demonstrate that incorporating both OCT and XA signals, co-registered, as inputs for the DNN model leads to an important increase in overall accuracy.

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Funding

The research leading to these results has received funding from the EEA Grants 2014–2021, under Project contract no. 33/2021. This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI – UEFISCDI, project number ERANET-PERMED-PROGRESS, within PNCDI III.

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Authors and Affiliations

  1. Advanta, Siemens SRL, 15 Noiembrie Bvd, Brasov, 500097, Romania

    Cosmin-Andrei Hatfaludi, Irina-Andra Tache, Costin-Florian Ciusdel, Andrei Puiu, Diana Stoian & Lucian Mihai Itu

  2. Automation and Information Technology, Transilvania University of Brasov, Mihai Viteazu nr. 5, Brasov, 5000174, Romania

    Cosmin-Andrei Hatfaludi, Costin-Florian Ciusdel, Andrei Puiu, Diana Stoian & Lucian Mihai Itu

  3. Department of Automatic Control and Systems Engineering, University Politehnica of Bucharest, Bucharest, 014461, Romania

    Irina-Andra Tache

  4. Department of Cardiology, Emergency Clinical Hospital, 8 Calea Floreasca, Bucharest, 014461, Romania

    Lucian Calmac, Nicoleta-Monica Popa-Fotea, Vlad Bataila & Alexandru Scafa-Udriste

  5. Department Cardio-Thoracic, University of Medicine and Pharmacy “Carol Davila”, 8 Eroii Sanitari, Bucharest, 050474, Romania

    Lucian Calmac, Nicoleta-Monica Popa-Fotea & Alexandru Scafa-Udriste

Authors
  1. Cosmin-Andrei Hatfaludi
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  2. Irina-Andra Tache
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  10. Lucian Mihai Itu
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Contributions

Conceptualization, C.-A.H., I.-A.T., and L.M.I.; methodology, C.-A.H., C.F.C., I.-A.T., and A.P.; software, C.-A.H., A.P., and D.S.; validation, L.C., N.-M.P.-F., V.B., and A.S.-U.; formal analysis, C.F.C.; investigation, L.C., N.-M.P.-F., and V.B.; resources, I.-A.T. and L.M.I.; data curation, I.-A.T. and L.C.; writing—original draft preparation, C.-A.H., I.-A.T., and L.M.I.; writing—review and editing, C.F.C.; visualization, C.-A.H. and L.M.I.; supervision, L.M.I. and A.S.-U.; project administration, L.M.I. and A.S.-U.; funding acquisition, L.M.I. and A.S.-U. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Cosmin-Andrei Hatfaludi.

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Hatfaludi, CA., Tache, IA., Ciusdel, CF. et al. Co-registered optical coherence tomography and X-ray angiography for the prediction of fractional flow reserve. Int J Cardiovasc Imaging 40, 1029–1039 (2024). https://doi.org/10.1007/s10554-024-03069-z

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