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Predictive Model for Thrombus Formation After Transcatheter Valve Replacement

Cardiovascular Engineering and Technology volume 12, pages 576–588 (2021)Cite this article

A Correction to this article was published on 07 January 2022

This article has been updated

Abstract

Purpose

Leaflet thrombosis is a significant adverse event after transcatheter aortic valve (TAV) replacement (TAVR). The purpose of our study was to present a semi-empirical, mathematical model that links patient-specific anatomic, valve, and flow parameters to predict likelihood of leaflet thrombosis.

Methods

The two main energy sources of neo-sinus (NS) washout after TAVR include the jet flow downstream of the TAV and NS geometric change in volume due to the leaflets opening and closing. Both are highly dependent on patient anatomic and hemodynamic factors. As rotation of blood flow is prevalent in both the sinus of Valsalva and then the NS, we adopted the vorticity flux or circulation (\(\Gamma\)) as a metric quantifying overall washout. Leaflet thrombus volumes were segmented based on hypo-attenuating leaflet thickening (HALT) in post-TAVR patient’s gated computed tomography. \(\Gamma\) was assessed using dimensional scaling as well as computational fluid dynamics (CFD) respectively and correlated to the thrombosis volumes using sensitivity and specificity analysis.

Results

\(\Gamma\) in the NS, that accounted for patient flow and anatomic conditions derived from scaling arguments significantly better predicted the occurrence of leaflet thrombus than CFD derived measures such as stasis volumes or wall shear stress. Given results from the six patient datasets considered herein, a threshold \(\Gamma\) value of 28.0 yielded a sensitivity and specificity of 100% where patients with Gamma < 28 developed valve thrombosis. A 10% error in measurements of all variables can bring the sensitivity specificity down to 87%.

Conclusion

A predictive model relating likelihood of valve thrombosis using \(\Gamma\) in the NS was developed with promising sensitivity and specificity. With further studies and improvements, this predictive technology may lead to alerting physicians on the risk for thrombus formation following TAVR.

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Change history

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Funding

This research was partly supported by the National Institutes of Health under Award Number R01HL119824 and the American Heart Association under Award Number 19POST34380804.

Conflict of interest

L.P. Dasi reports having patent applications filed on novel polymeric valves, vortex generators and superhydrophobic/omniphobic surfaces. Ajit Yoganathan is a Consultant or Researcher for St. Jude Medical, Boston Scientific, Sorin Biomedica and Edwards Lifesciences. Vinod Thourani is a consultant for Abbott Vascular, Boston Scientific, Edwards Lifesciences, Cryolife, Shockwave, and Jenavalve. The other authors report no conflict. Hatoum, Singh-Gryzbon, Yoganathan, Thourani, and Dasi have filed patent application on computational predictive modeling of thrombosis in heart valves.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Georgia Institute of Technology, 387 Technology Circle, Atlanta, GA, 30313, USA

    Hoda Hatoum, Shelly Singh-Gryzbon, Fateme Esmailie, Ajit P. Yoganathan & Lakshmi Prasad Dasi

  2. Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA

    Hoda Hatoum

  3. Department of Chemical & Process Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago

    Shelly Singh-Gryzbon

  4. Department of Cardiology and Angiology II, University Heart Center Freiburg-Bad Krozingen, Bad Krozingen, Germany

    Philipp Ruile & Franz-Josef Neumann

  5. University of British Columbia and St. Paul’s Hospital in Vancouver, Vancouver, Canada

    Philipp Blanke

  6. Department of Cardiovascular Surgery, Marcus Heart Valve Center, Piedmont Heart Institute, Atlanta, GA, USA

    Vinod H. Thourani

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  1. Hoda Hatoum
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  2. Shelly Singh-Gryzbon
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  9. Lakshmi Prasad Dasi
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Correspondence to Lakshmi Prasad Dasi.

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The wrong symbol appeared in the article and has been corrected to show the Gamma Symbol.

Communicated by Igor Efimov.

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Hatoum, H., Singh-Gryzbon, S., Esmailie, F. et al. Predictive Model for Thrombus Formation After Transcatheter Valve Replacement. Cardiovasc Eng Tech 12, 576–588 (2021). https://doi.org/10.1007/s13239-021-00596-x

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Keywords

  • Predictive Model
  • Leaflet thrombosis
  • Transcatheter aortic valve replacement
  • Neosinus
  • Flow stasis