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

• Park HB
• Jang Y
• Arsanjani
• Nguyen MT
• Lee SE
• Jeon B
• Jung S
• Hong Y
• Ha S
• Kim S
• Lee SW
• Chang HJ

• KMID: 2468488
• DOI: http://doi.org/10.3349/ymj.2020.61.2.137

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

Figure

• 

  Fig. 1 Workflow of the automated segmentation algorithm and the novel parallel computing method. (A) A fully automated lumen segmentation algorithm was applied to reconstruct patient-specific coronary geometry. (B) A novel parallel computing procedure based on a cluster with 40 cores decomposing the domain into 40 sub-domains and assigning a sub-domain to each computing core was applied.

• 

  Fig. 2 Example simulation case of on-site virtual fractional flow reserve (vFFR). A noninvasive on-site vFFR simulation defined the distal portion of the right coronary artery (A) as an ischemic lesion (0.76) and the middle portion of the left anterior descending artery (B) as a non-ischemic lesion (0.84). These simulation derived values matched perfectly with the invasively measured FFR values.

• 

  Fig. 3 Linear regression (A) and Bland-Altman analysis (B) between vFFR and FFR. Correlation coefficient (r) between vFFR and FFR was 0.75 (95% 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. vFFR, virtual fractional flow reserve; CI, confidence interval.

• 

  Fig. 4 ROC demonstrating AUCs for vFFR and obstructive (≥50%) CTA stenosis for the discrimination of lesion-specific ischemia using FFR cutoff values of 0.8 and 0.75. (A) The AUC for vFFR was significantly higher (0.88, 95% CI 0.80–0.94) than CTA ≥50% stenosis (0.61, 95% CI 0.51–0.71) when an FFR cutoff of 0.8 was used. (B) The AUC value for vFFR was excellent (0.94, 95% CI 0.88–0.98), compared to the CTA ≥50% stenosis (0.62, 95% CI 0.52–0.71), when an FFR cutoff of 0.75 was used. ROC, receiver operating characteristic curve; AUC, areas under receiver operating characteristic curve; vFFR, virtual fractional flow reserve; CTA, com-puted tomography angiography; CI, confidence interval.

• 

  Fig. 5 Diagnostic performance of vFFR using a cutoff of 0.75 (red), vFFR using a cutoff of 0.8 (green), and obstructive (≥50%) CTA stenosis (blue) for lesion-specific ischemia detection. vFFR, virtual fractional flow reserve; CTA, computed tomography angiography.

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