Yonsei Med J.  2020 Feb;61(2):137-144. 10.3349/ymj.2020.61.2.137.

Diagnostic Accuracy of a Novel On-site Virtual Fractional Flow Reserve Parallel Computing System

Affiliations
  • 1Connect-AI Research Center, Yonsei University College of Medicine, Seoul, Korea.
  • 2Department of Cardiology, International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon, Korea.
  • 3Mayo Clinic, Division of Cardiology, Department of Internal Medicine, Scottsdale, AZ, USA.
  • 4School of Mechanical Engineering, University of Ulsan, Ulsan, Korea. leesw@ulsan.ac.kr
  • 5Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Korea.

Abstract

PURPOSE
To evaluate the diagnostic accuracy of a novel on-site virtual fractional flow reserve (vFFR) derived from coronary computed tomography angiography (CTA).
MATERIALS AND METHODS
We analyzed 100 vessels from 57 patients who had undergone CTA followed by invasive FFR during coronary angiography. Coronary lumen segmentation and three-dimensional reconstruction were conducted using a completely automated algorithm, and parallel computing based vFFR prediction was performed. Lesion-specific ischemia based on FFR was defined as significant at ≤0.8, as well as ≤0.75, and obstructive CTA stenosis was defined that ≥50%. The diagnostic performance of vFFR was compared to invasive FFR at both ≤0.8 and ≤0.75.
RESULTS
The average computation time was 12 minutes per patient. The correlation coefficient (r) between vFFR and invasive FFR was 0.75 [95% confidence interval (CI) 0.65 to 0.83], and Bland-Altman analysis showed a mean bias of 0.005 (95% CI −0.011 to 0.021) with 95% limits of agreement of −0.16 to 0.17 between vFFR and FFR. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 78.0%, 87.1%, 72.5%, 58.7%, and 92.6%, respectively, using the FFR cutoff of 0.80. They were 87.0%, 95.0%, 80.0%, 54.3%, and 98.5%, respectively, with the FFR cutoff of 0.75. The area under the receiver-operating characteristics curve of vFFR versus obstructive CTA stenosis was 0.88 versus 0.61 for the FFR cutoff of 0.80, respectively; it was 0.94 versus 0.62 for the FFR cutoff of 0.75.
CONCLUSION
Our novel, fully automated, on-site vFFR technology showed excellent diagnostic performance for the detection of lesion-specific ischemia.

Keyword

Fractional flow reserve, myocardial; computed tomography angiography; patient-specific computational modeling

MeSH Terms

Angiography
Bias (Epidemiology)
Constriction, Pathologic
Coronary Angiography
Fractional Flow Reserve, Myocardial
Humans
Ischemia
Patient-Specific Modeling
Sensitivity and Specificity
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