Literature DB >> 31628575

On-site evaluation of CT-based fractional flow reserve using simple boundary conditions for computational fluid dynamics.

Yusuke Yoshikawa1, Masahiko Nakamoto2, Masanori Nakamura3, Takeharu Hoshi2, Erika Yamamoto1, Shunsuke Imai4, Yoshiaki Kawase4, Munenori Okubo4, Hiroki Shiomi1, Takeshi Kondo4, Hitoshi Matsuo4, Takeshi Kimura1, Naritatsu Saito5.   

Abstract

Fractional flow reserve (FFR) is an established method for diagnosing physiological coronary artery stenosis. A method for computing FFR using coronary computed tomography (CT) images was recently developed. However, its calculation requires off-site supercomputer analysis. Here, we report the preliminary result of a method using simple estimation of boundary conditions. The lumen boundaries of the coronary arteries were semi-automatically delineated using full width at half maximum of CT number profiles. The computational fluid dynamics (CFD) of the blood flow was performed using the boundary conditions of a fixed pressure at the coronary ostium and flow rates at each outlet. The total inflow at the coronary ostium was estimated based on the uniform wall shear stress hypothesis and corrected using a hyperemic multiplier to gain a hyperemic flow rate. The flow distribution from a parent vessel to the downstream daughter vessels was determined according to Murray's law. FFR estimated by CFD was calculated as FFRCFD = Pd/Pa. We collected patients who underwent coronary CT and coronary angiography followed by invasively measured FFR and compared FFRCFD with FFR. Sensitivity, specificity, and correlations were assessed. A total of 48 patients and 72 arteries were assessed. The correlation coefficient of FFRCFD with FFR was 0.56. The cut-off value was ≤ 0.80, sensitivity was 59.1%, and specificity was 94.0%. CFD-based FFR using simple boundary conditions for on-site clinical computation provided FFRCFD values that were moderately correlated with invasively measured FFR.

Entities:  

Keywords:  Computational fluid dynamics; Computed tomography; Coronary physiology; Fractional flow reserve

Mesh:

Year:  2019        PMID: 31628575     DOI: 10.1007/s10554-019-01709-3

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  27 in total

1.  SCCT guidelines for performance of coronary computed tomographic angiography: a report of the Society of Cardiovascular Computed Tomography Guidelines Committee.

Authors:  Suhny Abbara; Armin Arbab-Zadeh; Tracy Q Callister; Milind Y Desai; Wilfred Mamuya; Louise Thomson; Wm Guy Weigold
Journal:  J Cardiovasc Comput Tomogr       Date:  2009-03-31

2.  Effects of alogliptin on fractional flow reserve evaluated by coronary computed tomography angiography in patients with type 2 diabetes: Rationale and design of the TRACT study.

Authors:  Tsuyoshi Nozue; Kazuki Fukui; Takeshi Takamura; Takashi Sozu; Kiyoshi Hibi; Satoru Kishi; Ichiro Michishita
Journal:  J Cardiol       Date:  2016-05-25       Impact factor: 3.159

3.  Computational fluid dynamic measures of wall shear stress are related to coronary lesion characteristics.

Authors:  Jun-Bean Park; Gilwoo Choi; Eun Ju Chun; Hyun Jin Kim; Jonghanne Park; Ji-Hyun Jung; Min-Ho Lee; Hiromasa Otake; Joon-Hyung Doh; Chang-Wook Nam; Eun-Seok Shin; Bernard De Bruyne; Charles A Taylor; Bon-Kwon Koo
Journal:  Heart       Date:  2016-06-14       Impact factor: 5.994

4.  Fractional flow reserve versus angiography for guiding percutaneous coronary intervention.

Authors:  Pim A L Tonino; Bernard De Bruyne; Nico H J Pijls; Uwe Siebert; Fumiaki Ikeno; Marcel van' t Veer; Volker Klauss; Ganesh Manoharan; Thomas Engstrøm; Keith G Oldroyd; Peter N Ver Lee; Philip A MacCarthy; William F Fearon
Journal:  N Engl J Med       Date:  2009-01-15       Impact factor: 91.245

5.  Fractional flow reserve-guided PCI for stable coronary artery disease.

Authors:  Bernard De Bruyne; William F Fearon; Nico H J Pijls; Emanuele Barbato; Pim Tonino; Zsolt Piroth; Nikola Jagic; Sven Mobius-Winckler; Gilles Rioufol; Nils Witt; Petr Kala; Philip MacCarthy; Thomas Engström; Keith Oldroyd; Kreton Mavromatis; Ganesh Manoharan; Peter Verlee; Ole Frobert; Nick Curzen; Jane B Johnson; Andreas Limacher; Eveline Nüesch; Peter Jüni
Journal:  N Engl J Med       Date:  2014-09-01       Impact factor: 91.245

6.  Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study.

Authors:  Ryo Nakazato; Hyung-Bok Park; Daniel S Berman; Heidi Gransar; Bon-Kwon Koo; Andrejs Erglis; Fay Y Lin; Allison M Dunning; Matthew J Budoff; Jennifer Malpeso; Jonathon Leipsic; James K Min
Journal:  Circ Cardiovasc Imaging       Date:  2013-09-30       Impact factor: 7.792

7.  Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses.

Authors:  N H Pijls; B De Bruyne; K Peels; P H Van Der Voort; H J Bonnier; J J Bartunek J Koolen; J J Koolen
Journal:  N Engl J Med       Date:  1996-06-27       Impact factor: 91.245

8.  Treatment strategy modification and its implication on the medical cost of fractional flow reserve-guided percutaneous coronary intervention in Japan.

Authors:  Nobuhiro Tanaka; Shun Kohsaka; Tatsunori Murata; Takashi Akasaka; Kazushige Kadota; Shirou Uemura; Tetsuya Amano; Nobuo Shiode; Yoshihiro Morino; Kenshi Fujii; Yutaka Hikichi; Masato Nakamura
Journal:  J Cardiol       Date:  2018-07-02       Impact factor: 3.159

9.  A study of noninvasive fractional flow reserve derived from a simplified method based on coronary computed tomography angiography in suspected coronary artery disease.

Authors:  Changzheng Shi; Dong Zhang; Kunlin Cao; Tao Zhang; Liangping Luo; Xin Liu; Heye Zhang
Journal:  Biomed Eng Online       Date:  2017-04-14       Impact factor: 2.819

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

Authors:  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
Journal:  PLoS One       Date:  2016-05-17       Impact factor: 3.240

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  2 in total

1.  Cardiovascular imaging 2019 in the International Journal of Cardiovascular Imaging.

Authors:  Johan H C Reiber; Gabriel T R Pereira; Luis A P Dallan; Hiram G Bezerra; Johan De Sutter; Arthur E Stillman; Nico R L Van de Veire; Joachim Lotz
Journal:  Int J Cardiovasc Imaging       Date:  2020-05       Impact factor: 2.357

Review 2.  Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.

Authors:  Joyce Peper; Dominika Suchá; Martin Swaans; Tim Leiner
Journal:  Br J Radiol       Date:  2020-08-12       Impact factor: 3.039

  2 in total

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