Coronary interventions

Diagnostic accuracy of intracoronary optical coherence tomography-derived fractional flow reserve for assessment of coronary stenosis severity

EuroIntervention 2019;15:189-197. DOI: 10.4244/EIJ-D-19-00182

Wei Yu
Wei Yu 1, BSc; Jiayue Huang 1, BSc; Dean Jia 2, MD; Shaoliang Chen 3, MD, PhD; Owen Christopher Raffel 4, MB, MPH; Daixin Ding 1, BSc; Feng Tian 5, MD; Jing Kan 3, MBBS; Su Zhang 1, PhD; Fuhua Yan 6, MD; Yundai Chen 5, MD; Hiram G. Bezerra 7, MD, PhD; William Wijns 8, MD, PhD; Shengxian Tu 1, PhD
1. Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; 2. Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China; 3. Division of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China; 4. Department of Cardiology, Prince Charles Hospital, Queensland, Australia; 5. Department of Cardiology, Chinese PLA General Hospital, Beijing, China; 6. Department of Radiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; 7. Harrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, USA; 8. The Lambe Institute for Translational Medicine and Curam, National University of Ireland, Galway, and Saolta University Healthcare Group, Galway, Ireland

Aims: A novel method for computation of fractional flow reserve (FFR) from optical coherence tomography (OCT) was developed recently. This study aimed to evaluate the diagnostic accuracy of a new OCT-based FFR (OFR) computational approach, using wire-based FFR as the reference standard.

Methods and results: Patients who underwent both OCT and FFR prior to intervention were analysed. The lumen of the interrogated vessel and the ostia of the side branches were automatically delineated and used to compute OFR. Bifurcation fractal laws were applied to correct the change in reference lumen size due to the step-down phenomenon. OFR was compared with FFR, both using a cut-off value of 0.80 to define ischaemia. Computational analysis was performed in 125 vessels from 118 patients. Average FFR was 0.80±0.09. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for OFR to identify FFR ≤0.80 was 90% (95% CI: 84-95), 87% (95% CI: 77-94), 92% (95% CI: 82-97), 92% (95% CI: 82-97), and 88% (95% CI: 77-95), respectively. The AUC was higher for OFR than minimal lumen area (0.93 [95% CI: 0.87-0.97] versus 0.80 [95% CI: 0.72-0.86], p=0.002). Average OFR analysis time was 55±23 seconds for each OCT pullback. Intra- and inter-observer variability in OFR analysis was 0.00±0.02 and 0.00±0.03, respectively.

Conclusions: OFR is a novel and fast method allowing assessment of flow-limiting coronary stenosis without pressure wire and induced hyperaemia. The good diagnostic accuracy and low observer variability bear the potential of improved integration of intracoronary imaging and physiological assessment.

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bifurcationfractional flow reserveoptical coherence tomographystable angina
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