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Simplified Models of Non-Invasive Fractional Flow Reserve Based on CT Images

Author

Listed:
  • Jun-Mei Zhang
  • Liang Zhong
  • Tong Luo
  • Aileen Mae Lomarda
  • Yunlong Huo
  • Jonathan Yap
  • Soo Teik Lim
  • Ru San Tan
  • Aaron Sung Lung Wong
  • Jack Wei Chieh Tan
  • Khung Keong Yeo
  • Jiang Ming Fam
  • Felix Yung Jih Keng
  • Min Wan
  • Boyang Su
  • Xiaodan Zhao
  • John Carson Allen
  • Ghassan S Kassab
  • Terrance Siang Jin Chua
  • Swee Yaw Tan

Abstract

Invasive fractional flow reserve (FFR) is the gold standard to assess the functional coronary stenosis. The non-invasive assessment of diameter stenosis (DS) using coronary computed tomography angiography (CTA) has high false positive rate in contrast to FFR. Combining CTA with computational fluid dynamics (CFD), recent studies have shown promising predictions of FFRCT for superior assessment of lesion severity over CTA alone. The CFD models tend to be computationally expensive, however, and require several hours for completing analysis. Here, we introduce simplified models to predict noninvasive FFR at substantially less computational time. In this retrospective pilot study, 21 patients received coronary CTA. Subsequently a total of 32 vessels underwent invasive FFR measurement. For each vessel, FFR based on steady-state and analytical models (FFRSS and FFRAM, respectively) were calculated non-invasively based on CTA and compared with FFR. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value were 90.6% (87.5%), 80.0% (80.0%), 95.5% (90.9%), 88.9% (80.0%) and 91.3% (90.9%) respectively for FFRSS (and FFRAM) on a per-vessel basis, and were 75.0%, 50.0%, 86.4%, 62.5% and 79.2% respectively for DS. The area under the receiver operating characteristic curve (AUC) was 0.963, 0.954 and 0.741 for FFRSS, FFRAM and DS respectively, on a per-patient level. The results suggest that the CTA-derived FFRSS performed well in contrast to invasive FFR and they had better diagnostic performance than DS from CTA in the identification of functionally significant lesions. In contrast to FFRCT, FFRSS requires much less computational time.

Suggested Citation

  • Jun-Mei Zhang & Liang Zhong & Tong Luo & Aileen Mae Lomarda & Yunlong Huo & Jonathan Yap & Soo Teik Lim & Ru San Tan & Aaron Sung Lung Wong & Jack Wei Chieh Tan & Khung Keong Yeo & Jiang Ming Fam & Fe, 2016. "Simplified Models of Non-Invasive Fractional Flow Reserve Based on CT Images," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-20, May.
  • Handle: RePEc:plo:pone00:0153070
    DOI: 10.1371/journal.pone.0153070
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