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Validation of Wall Shear Stress Assessment in Non-invasive Coronary CTA versus Invasive Imaging: A Patient-Specific Computational Study

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Abstract

Endothelial shear stress (ESS) identifies coronary plaques at high risk for progression and/or rupture leading to a future acute coronary syndrome. In this study an optimized methodology was developed to derive ESS, pressure drop and oscillatory shear index using computational fluid dynamics (CFD) in 3D models of coronary arteries derived from non-invasive coronary computed tomography angiography (CTA). These CTA-based ESS calculations were compared to the ESS calculations using the gold standard with fusion of invasive imaging and CTA. In 14 patients paired patient-specific CFD models based on invasive and non-invasive imaging of the left anterior descending (LAD) coronary arteries were created. Ten patients were used to optimize the methodology, and four patients to test this methodology. Time-averaged ESS (TAESS) was calculated for both coronary models applying patient-specific physiological data available at the time of imaging. For data analysis, each 3D reconstructed coronary artery was divided into 2 mm segments and each segment was subdivided into 8 arcs (45°).TAESS and other hemodynamic parameters were averaged per segment as well as per arc. Furthermore, the paired segment- and arc-averaged TAESS were categorized into patient-specific tertiles (low, medium and high). In the ten LADs, used for optimization of the methodology, we found high correlations between invasively-derived and non-invasively-derived TAESS averaged over segments (n = 263, r = 0.86) as well as arcs (n = 2104, r = 0.85, p < 0.001). The correlation was also strong in the four testing-patients with r = 0.95 (n = 117 segments, p = 0.001) and r = 0.93 (n = 936 arcs, p = 0.001).There was an overall high concordance of 78% of the three TAESS categories comparing both methodologies using the segment- and 76% for the arc-averages in the first ten patients. This concordance was lower in the four testing patients (64 and 64% in segment- and arc-averaged TAESS). Although the correlation and concordance were high for both patient groups, the absolute TAESS values averaged per segment and arc were overestimated using non-invasive vs. invasive imaging [testing patients: TAESS segment: 30.1(17.1–83.8) vs. 15.8(8.8–63.4) and TAESS arc: 29.4(16.2–74.7) vs 15.0(8.9–57.4) p < 0.001]. We showed that our methodology can accurately assess the TAESS distribution non-invasively from CTA and demonstrated a good correlation with TAESS calculated using IVUS/OCT 3D reconstructed models.

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Authors and Affiliations

  1. Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 165 Cambridge St, Suite 400, Boston, MA, 02114, USA

    Parastou Eslami, Julia Karady, Zexi Jin, Vikas Thondapu, Michael T. Lu & Udo Hoffmann

  2. Department of Cardiology, Biomedical Engineering, Erasmus MC, Rotterdam, The Netherlands

    Eline M. J. Hartman & Jolanda J. Wentzel

  3. Department of Cardiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Mazen Albaghadai

  4. Division of Cardiovascular Medicine, Harvard Medical School, Brigham Women’s Hospital, Boston, MA, USA

    Nicholas V. Cefalo & Peter H. Stone

  5. Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA

    Ahmet Coskun

  6. Institute of Computational and Mathematical Engineering, Departments of Bioengineering and Pediatrics, Stanford University, Stanford, CA, USA

    Alison Marsden

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Eslami, P., Hartman, E.M.J., Albaghadai, M. et al. Validation of Wall Shear Stress Assessment in Non-invasive Coronary CTA versus Invasive Imaging: A Patient-Specific Computational Study. Ann Biomed Eng 49, 1151–1168 (2021). https://doi.org/10.1007/s10439-020-02631-9

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