Literature DB >> 30137268

Performance of computed tomography-derived fractional flow reserve using reduced-order modelling and static computed tomography stress myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis.

Abdul Rahman Ihdayhid1, Takuya Sakaguchi2, Jesper J Linde3, Mathias H Sørgaard3, Klaus F Kofoed3, Yasuko Fujisawa2, Jacqui Hislop-Jambrich4, Nitesh Nerlekar1, James D Cameron1, Ravi K Munnur1, Marcus Crosset1, Dennis T L Wong1,5, Sujith K Seneviratne1, Brian S Ko1.   

Abstract

Aims: To compare the diagnostic performance of a reduced-order computed tomography-derived fractional flow reserve (CT-FFR) technique derived from luminal deformation and static CT stress myocardial perfusion (CTP). Methods and results: Forty-six patients (84 vessels) with suspected coronary artery disease from a single institution planned for elective coronary angiography prospectively underwent research indicated invasive fractional flow reserve (FFR) and 320-detector CT coronary angiography (CTA) and static CTP. Analyses were performed in separate blinded core laboratories for CT-FFR and CTP. CT-FFR was derived using a reduced-order model with dedicated software on a standard desktop computer. CTP was assessed visually and quantitatively by transmural perfusion ratio (TPR). Invasive FFR was significant in 33% (28/84) of vessels. Overall per-vessel sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for CT-FFR were 81%, 84%, 71%, 90%, and 83%, respectively, those of visual CTP were 54%, 92%, 79%, 77%, and 78%, respectively, and TPR were 64%, 48%, 42%, 70%, and 54%, respectively. Per-vessel receiver operator curve analysis demonstrated a significantly larger area under the curve (AUC) for CT-FFR (0.89) with that for visual CTP (0.72; P = 0.016), TPR (0.55; P < 0.0001), and CTA (0.76; P = 0.04). The addition of CT-FFR to CTA provided superior improvement in performance (AUC 0.93; P < 0.0001) compared with CTA alone, a combination of CTA with visual CTP (AUC 0.82; P = 0.007) and CTA with TPR (AUC 0.78; P = 0.0006).
Conclusion: Based on this selected cohort of patients, a reduced-order CT-FFR technique is superior to visual and quantitatively assessed static CTP in detecting haemodynamically significant coronary stenosis as assessed by invasive FFR.

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Year:  2018        PMID: 30137268     DOI: 10.1093/ehjci/jey114

Source DB:  PubMed          Journal:  Eur Heart J Cardiovasc Imaging        ISSN: 2047-2404            Impact factor:   6.875


  10 in total

1.  Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation.

Authors:  Lauren M Shepard; Kelsey N Sommer; Erin Angel; Vijay Iyer; Michael F Wilson; Frank J Rybicki; Dimitrios Mitsouras; Sabee Molloi; Ciprian N Ionita
Journal:  J Med Imaging (Bellingham)       Date:  2019-03-12

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

Review 3.  [Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion].

Authors:  Moon Young Kim; Dong Hyun Yang; Ki Seok Choo; Whal Lee
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2022-01-21

4.  Machine Learning CT FFR: The Evolving Role of On-Site Techniques.

Authors:  Abdul Rahman Ihdayhid; Sagit Ben Zekry
Journal:  Radiol Cardiothorac Imaging       Date:  2020-06-25

Review 5.  Computed tomographic evaluation of myocardial ischemia.

Authors:  Yuki Tanabe; Akira Kurata; Takuya Matsuda; Kazuki Yoshida; Dhiraj Baruah; Teruhito Kido; Teruhito Mochizuki; Prabhakar Rajiah
Journal:  Jpn J Radiol       Date:  2020-02-05       Impact factor: 2.374

6.  Non-invasive CT-derived fractional flow reserve and static rest and stress CT myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis.

Authors:  Brian S Ko; Jesper J Linde; Abdul-Rahman Ihdayhid; Bjarne L Norgaard; Klaus F Kofoed; Mathias Sørgaard; Daniel Adams; Marcus Crossett; James D Cameron; Sujith K Seneviratne
Journal:  Int J Cardiovasc Imaging       Date:  2019-07-04       Impact factor: 2.357

7.  Static CT myocardial perfusion imaging: image quality, artifacts including distribution and diagnostic performance compared to 82Rb PET.

Authors:  João R Inácio; Sriraag Balaji Srinivasan; Terrence D Ruddy; Robert A deKemp; Frank Rybicki; Rob S Beanlands; Benjamin J W Chow; Girish Dwivedi
Journal:  Eur J Hybrid Imaging       Date:  2022-01-04

Review 8.  Fractional Flow Reserve: Patient Selection and Perspectives.

Authors:  Joyce Peper; Leonie M Becker; Jan-Peter van Kuijk; Tim Leiner; Martin J Swaans
Journal:  Vasc Health Risk Manag       Date:  2021-12-14

9.  Diagnostic performance of coronary computed tomography angiography-derived fractional flow reverse in lesion-specific ischemia patients with different Gensini score levels.

Authors:  Mengya Dong; Chen Li; Guang Yang; Qiling Gou; Qinghua Zhao; Yuqi Liu; Xiling Shou
Journal:  Ann Transl Med       Date:  2022-04

10.  Coronary CT angiography-based estimation of myocardial perfusion territories for coronary artery FFR and wall shear stress simulation.

Authors:  Yu-Fang Hsieh; Chih-Kuo Lee; Weichung Wang; Yu-Cheng Huang; Wen-Jeng Lee; Tzung-Dau Wang; Cheng-Ying Chou
Journal:  Sci Rep       Date:  2021-07-05       Impact factor: 4.379

  10 in total

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