Coronary fractional flow reserve derived from intravascular ultrasound imaging: Validation of a new computational method of fusion between anatomy and physiology

Carregando...
Imagem de Miniatura
Citações na Scopus
26
Tipo de produção
article
Data de publicação
2019
Título da Revista
ISSN da Revista
Título do Volume
Editora
WILEY
Autores
HIDEO-KAJITA, Alexandre
BULANT, Carlos A.
MASO-TALOU, Gonzalo D.
FRANKEN, Marcelo
FEIJOO, Raul A.
Citação
CATHETERIZATION AND CARDIOVASCULAR INTERVENTIONS, v.93, n.2, p.266-274, 2019
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Objectives: To evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional intravascular ultrasound (IVUS) imaging in estimating fractional flow reserve (IVUSFR), compared to gold-standard invasive measurements (FFRINVAS). Background: IVUS provides accurate anatomical evaluation of the lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention. However, IVUS poorly represents the functional status (i.e., flow-related information) of the imaged vessel. Methods: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRINVAS measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Computation of IVUSFR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFRINVAS measurements were dichotomized at the 0.80 threshold to define hemodynamically significant lesions. Results: A total of 24 patients with 34 vessels were analyzed. IVUSFR significantly correlated (r = 0.79; P < 0.001) and showed good agreement with FFRINVAS, with a mean difference of -0.008 +/- 0.067 (P = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96%, respectively, to detect significant stenosis. Conclusion: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of grayscale IVUS.
Palavras-chave
computational fluid dynamics, coronary blood flow/physiology/microvascular function, coronary artery disease, fractional flow reserve, imaging intravascular ultrasound, interventional devices/innovation, quantitative coronary angiography, three-dimensional coronary models
Referências
  1. Bavishi C, 2017, AM HEART J, V185, P26, DOI [10.10164/j.ahj.2016.10.008, 10.1016/j.ahj.2016.10.008]
  2. Blanco PJ, 2013, INT J NUMER METH BIO, V29, P601, DOI 10.1002/cnm.2547
  3. BLAND JM, 1995, LANCET, V346, P1085, DOI 10.1016/S0140-6736(95)91748-9
  4. BLAND JM, 1986, LANCET, V1, P307
  5. Bulant CA, 2017, J BIOMECH, V51, P65, DOI 10.1016/j.jbiomech.2016.11.070
  6. Carrizo S, 2014, REV PORT CARDIOL, V33
  7. Chu M, 2017, INT J CARDIOVAS IMAG, V33, P975, DOI 10.1007/s10554-017-1085-3
  8. D'Ascenzo F, 2015, AM HEART J, V169, P663, DOI 10.1016/j.ahj.2015.01.013
  9. de Simone G, 1999, HYPERTENSION, V33, P800, DOI 10.1161/01.HYP.33.3.800
  10. GUYTON AC, 1955, PHYSIOL REV, V35, P123
  11. Ha J, 2016, CIRC-CARDIOVASC INTE, V9, DOI 10.1161/CIRCINTERVENTIONS.116.003613
  12. Hall JE, 2005, SER CENT ES, P11, DOI 10.1007/0-387-27424-3_2
  13. Johnson NP, 2012, JACC-CARDIOVASC IMAG, V5, P193, DOI 10.1016/j.jcmg.2011.09.020
  14. Mariani J, 2014, JACC-CARDIOVASC INTE, V7, P1287, DOI 10.1016/j.jcin.2014.05.024
  15. Talou GDM, 2017, IEEE T BIO-MED ENG, V64, P890, DOI 10.1109/TBME.2016.2581583
  16. Talou GDM, 2015, IEEE T BIO-MED ENG, V62, P2867, DOI 10.1109/TBME.2015.2449232
  17. Sakamoto S, 2013, AM J CARDIOL, V111, P1420, DOI 10.1016/j.amjcard.2013.01.290
  18. Siogkas PK, 2015, IEEE ENG MED BIO, P973, DOI 10.1109/EMBC.2015.7318526
  19. Takayama T, 2001, CATHETER CARDIO INTE, V53, P48, DOI 10.1002/ccd.1129
  20. Tan XW, 2017, INT J CARDIOL, V236, P100, DOI 10.1016/j.ijcard.2017.02.053
  21. Taylor CA, 2013, J AM COLL CARDIOL, V61, P2233, DOI 10.1016/j.jacc.2012.11.083
  22. Trobs M, 2016, AM J CARDIOL, V117, P29, DOI 10.1016/j.amjcard.2015.10.008
  23. Tu SX, 2014, JACC-CARDIOVASC INTE, V7, P768, DOI 10.1016/j.jcin.2014.03.004
  24. Waksman R, 2013, J AM COLL CARDIOL, V61, P917, DOI 10.1016/j.jacc.2012.12.012
  25. Wentzel JJ, 2001, CIRCULATION, V103, P1740, DOI 10.1161/01.CIR.103.13.1740
  26. West GB, 1997, SCIENCE, V276, P122, DOI 10.1126/science.276.5309.122