Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2017, Article ID 3087407, 9 pages
https://doi.org/10.1155/2017/3087407
Research Article

Automated Classification of Severity in Cardiac Dyssynchrony Merging Clinical Data and Mechanical Descriptors

1Bioengineering Department, Instituto Tecnológico y de Estudios Superiores de Monterrey, Campus Ciudad de México, Mexico City, Mexico
2Neuroimaging Laboratory, Electrical Engineering Department, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, Mexico
3Centro Medico ABC (American British Cowdray Hospital), Mexico City, Mexico
4Nuclear Cardiology Department, Instituto Nacional de Cardiología “Ignacio Chávez”, Mexico City, Mexico
5Engineering in Biomedical Systems Department, Faculty of Engineering, Universidad Nacional Autónoma de México, Mexico City, Mexico

Correspondence should be addressed to Luis Jiménez-Ángeles; gro.eeei@zenemij.siul

Received 2 September 2016; Revised 18 December 2016; Accepted 23 January 2017; Published 19 February 2017

Academic Editor: Marcelo Mamede

Copyright © 2017 Alejandro Santos-Díaz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. G. F. Cleland, A. Khand, and A. Clark, “The heart failure epidemic: exactly how big is it?” European Heart Journal, vol. 22, no. 8, pp. 623–626, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Nichols, N. Townsend, P. Scarborough, and M. Rayner, “Cardiovascular disease in Europe 2014: epidemiological update,” European Heart Journal, vol. 35, no. 42, pp. 2950–2959, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. S. E. Ramsay, P. H. Whincup, O. Papacosta, R. W. Morris, L. T. Lennon, and S. Goya Wannamethee, “Inequalities in heart failure in older men: prospective associations between socioeconomic measures and heart failure incidence in a 10-year follow-up study,” European Heart Journal, vol. 35, no. 7, pp. 442–447, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Komajda and C. S. P. Lam, “Heart failure with preserved ejection fraction: a clinical dilemma,” European Heart Journal, vol. 35, no. 16, pp. 1022–1032, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. F. P. Brouwers, R. A. De Boer, P. Van Der Harst et al., “Incidence and epidemiology of new onset heart failure with preserved vs. reduced ejection fraction in a community-based cohort: 11-year follow-up of PREVEND,” European Heart Journal, vol. 34, no. 19, pp. 1424–1431, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. Writing Group Members, D. Mozaffarian, E. J. Benjamin et al., “Heart disease and stroke statistics-2016 update: a report from the American Heart Association,” Circulation, vol. 133, no. 4, pp. e38–e360, 2016. View at Publisher · View at Google Scholar
  7. S. Stewart, I. Ekman, T. Ekman, A. Odén, and A. Rosengren, “Population impact of heart failure and the most common forms of cancer: a study of 1 162 309 hospital cases in Sweden (1988 to 2004),” Circulation: Cardiovascular Quality and Outcomes, vol. 3, no. 6, pp. 573–580, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. U. Piamjariyakul, D. M. Yadrich, C. Russell et al., “Patients' annual income adequacy, insurance premiums and out-of-pocket expenses related to heart failure care,” Heart & Lung, vol. 43, no. 5, pp. 469–475, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Cook, G. Cole, P. Asaria, R. Jabbour, and D. P. Francis, “The annual global economic burden of heart failure,” International Journal of Cardiology, vol. 171, no. 3, pp. 368–376, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Gheorghiade and P. S. Pang, “Acute heart failure syndromes,” Journal of the American College of Cardiology, vol. 53, no. 7, pp. 557–573, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. P. Ponikowski, A. A. Voors, S. D. Anker et al., “2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure,” European Journal of Heart Failure, vol. 18, no. 8, pp. 891–975, 2016. View at Publisher · View at Google Scholar
  12. S. Nattel, A. Maguy, S. Le Bouter, and Y.-H. Yeh, “Arrhythmogenic ion-channel remodeling in the heart: heart failure, myocardial infarction, and atrial fibrillation,” Physiological Reviews, vol. 87, no. 2, pp. 425–456, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. N. Y. H. A. C. Committee and N. Y. H. Association, Nomenclature and Criteria for Diagnosis of Diseases of the Heart and Great Vessels, Little, Brown Medical Division, 1979.
  14. J. E. Poole, “Present guidelines for device implantation: clinical considerations and clinical challenges from pacing, implantable cardiac defibrillator, and cardiac resynchronization therapy,” Circulation, vol. 129, no. 3, pp. 383–394, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. F. W. Prinzen, K. Vernooy, and A. Auricchio, “Cardiac resynchronization therapy: state-of-the-art of current applications, guidelines, ongoing trials, and areas of controversy,” Circulation, vol. 128, no. 22, pp. 2407–2418, 2013. View at Publisher · View at Google Scholar · View at Scopus
  16. G. F. Lewis and M. R. Gold, “Developments in cardiac resynchronisation therapy,” Arrhythmia & Electrophysiology Review, vol. 4, pp. 122–128, 2015. View at Google Scholar
  17. F. Leyva, S. Nisam, and A. Auricchio, “20 years of cardiac resynchronization therapy,” Journal of the American College of Cardiology, vol. 64, no. 10, pp. 1047–1058, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. M. Frigerio, M. Lunati, D. Pasqualucci et al., “Left ventricular ejection fraction overcrossing 35% after one year of cardiac resynchronization therapy predicts long term survival and freedom from sudden cardiac death: single center observational experience,” International Journal of Cardiology, vol. 172, no. 1, pp. 64–71, 2014. View at Publisher · View at Google Scholar · View at Scopus
  19. A. Menet, Y. Guyomar, P.-V. Ennezat et al., “Prognostic value of left ventricular reverse remodeling and performance improvement after cardiac resynchronization therapy: A Prospective Study,” International Journal of Cardiology, vol. 204, pp. 6–11, 2016. View at Publisher · View at Google Scholar · View at Scopus
  20. P. Carità, E. Corrado, G. Pontone et al., “Non-responders to cardiac resynchronization therapy: insights from multimodality imaging and electrocardiography. A brief review,” International Journal of Cardiology, vol. 225, pp. 402–407, 2016. View at Publisher · View at Google Scholar
  21. W. Zhou and E. V. Garcia, “Nuclear image-guided approaches for Cardiac Resynchronization Therapy (CRT),” Current Cardiology Reports, vol. 18, no. 1, pp. 1–11, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. S. L. Liao and M. J. Garcia, “New advances in quantitative echocardiography,” Journal of Nuclear Cardiology, vol. 15, no. 2, pp. 255–265, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. E. S. Chung, A. R. Leon, L. Tavazzi et al., “Results of the predictors of response to crt (prospect) trial,” Circulation, vol. 117, no. 20, pp. 2608–2616, 2008. View at Publisher · View at Google Scholar · View at Scopus
  24. S. Chalil, B. Stegemann, S. Muhyaldeen et al., “Intraventricular dyssynchrony predicts mortality and morbidity after cardiac resynchronization therapy. A study using cardiovascular magnetic resonance tissue synchronization imaging,” Journal of the American College of Cardiology, vol. 50, no. 3, pp. 243–252, 2007. View at Publisher · View at Google Scholar · View at Scopus
  25. G. V. Chow and S. Nazarian, “MRI for patients with cardiac implantable electrical devices,” Cardiology Clinics, vol. 32, no. 2, pp. 299–304, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. J. Chen, E. V. Garcia, R. D. Folks et al., “Onset of left ventricular mechanical contraction as determined by phase analysis of ECG-gated myocardial perfusion SPECT imaging: development of a diagnostic tool for assessment of cardiac mechanical dyssynchrony,” Journal of Nuclear Cardiology, vol. 12, no. 6, pp. 687–695, 2005. View at Publisher · View at Google Scholar · View at Scopus
  27. J. Chen, M. M. Henneman, M. A. Trimble et al., “Assessment of left ventricular mechanical dyssynchrony by phase analysis of ECG-gated SPECT myocardial perfusion imaging,” Journal of Nuclear Cardiology, vol. 15, no. 1, pp. 127–136, 2008. View at Publisher · View at Google Scholar · View at Scopus
  28. W. Zhou, Z. Jiang, J. Chen, E. V. Garcia, and D. Li, “Development and validation of a phase analysis tool to measure interventricular mechanical dyssynchrony from gated SPECT MPI,” Journal of Nuclear Cardiology, pp. 1–7, 2016. View at Publisher · View at Google Scholar · View at Scopus
  29. S. Aguadé-Bruix, G. Romero-Farina, J. Candell-Riera, M. Pizzi, and D. García-Dorado, “Mechanical dyssynchrony according to validated cut-off values using gated SPECT myocardial perfusion imaging,” Journal of Nuclear Cardiology, 2016. View at Publisher · View at Google Scholar
  30. E. H. Botvinick, “Scintigraphic blood pool and phase image analysis: the optimal tool for the evaluation of resynchronization therapy,” Journal of Nuclear Cardiology, vol. 10, no. 4, pp. 424–428, 2003. View at Publisher · View at Google Scholar · View at Scopus
  31. J. W. O'Connell, C. Schreck, M. Moles et al., “A unique method by which to quantitate synchrony with equilibrium radionuclide angiography,” Journal of Nuclear Cardiology, vol. 12, no. 4, pp. 441–450, 2005. View at Publisher · View at Google Scholar · View at Scopus
  32. E. Vallejo, L. Jiménez, G. Rodríguez, F. Roffe, and D. Bialostozky, “Evaluation of ventricular synchrony with equilibrium radionuclide angiography: assessment of variability and accuracy,” Archives of Medical Research, vol. 41, no. 2, pp. 83–91, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. H. Singh, A. Singhal, P. Sharma, C. D. Patel, S. Seth, and A. Malhotra, “Quantitative assessment of cardiac mechanical synchrony using equilibrium radionuclide angiography,” Journal of Nuclear Cardiology, vol. 20, no. 3, pp. 415–425, 2013. View at Publisher · View at Google Scholar · View at Scopus
  34. L. Fauchier, O. Marie, D. Casset-Senon, D. Babuty, P. Cosnay, and J. P. Fauchier, “Interventricular and intraventricular dyssynchrony in idiopathic dilated cardiomyopathy: a prognostic study with Fourier phase analysis of radionuclide angioscintigraphy,” Journal of the American College of Cardiology, vol. 40, no. 11, pp. 2022–2030, 2002. View at Publisher · View at Google Scholar · View at Scopus
  35. R. Pagnanelli, M. Fudim, and S. Borges-Neto, “Technologist Corner: value of radionuclide ventriculography to assess mechanical dyssynchrony and predict the cardiac resynchronization therapy response,” Journal of Nuclear Cardiology, vol. 23, no. 3, pp. 491–492, 2016. View at Publisher · View at Google Scholar · View at Scopus
  36. Y. Chen, J. Yan, S. Zhao, Q. Long, H. Wang, and L. Wang, “Efficacy of equilibrium radionuclide angiography to predict acute response to cardiac resynchronization therapy in patients with heart failure,” Nuclear Medicine Communications, vol. 36, no. 6, pp. 610–618, 2015. View at Publisher · View at Google Scholar · View at Scopus
  37. D. C. Barber, “The use of principal components in the quantitative analysis of gamma camera dynamic studies,” Physics in Medicine and Biology, vol. 25, no. 2, pp. 283–292, 1980. View at Publisher · View at Google Scholar · View at Scopus
  38. F. Cavaillolès, J. P. Bazin, D. Pavel et al., “Comparison between factor analysis of dynamic structures and Fourier analysis in detection of segmental wall motion abnormalities: a clinical evaluation,” The International Journal of Cardiac Imaging, vol. 11, no. 4, pp. 263–272, 1995. View at Publisher · View at Google Scholar · View at Scopus
  39. R. D. Paols, J. P. Bazin, F. Aubry et al., “Handling of dynamic sequences in nuclear medicine,” IEEE Transactions on Nuclear Science, vol. 29, no. 4, pp. 1310–1321, 1982. View at Publisher · View at Google Scholar · View at Scopus
  40. L. Jiménez-Ángeles, R. Valdés-Cristerna, E. Vallejo, D. Bialostozky, and V. Medina-Bañuelos, “Factorial phase analysis of ventricular contraction using equilibrium radionuclide angiography images,” Biomedical Signal Processing and Control, vol. 4, no. 2, pp. 149–161, 2009. View at Publisher · View at Google Scholar · View at Scopus
  41. L. Jiménez-Ángeles, R. Valdés-Cristerna, E. Vallejo, D. Bialostozky, and V. Medina-Bañuelos, “Normality index of ventricular contraction based on a statistical model from FADS,” Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 617604, 12 pages, 2013. View at Google Scholar · View at MathSciNet
  42. G. A. Diamond and J. S. Forrester, “Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease,” The New England Journal of Medicine, vol. 300, no. 24, pp. 1350–1358, 1979. View at Publisher · View at Google Scholar · View at Scopus
  43. A. C. Guyton, Basic Human Physiology: Normal Function and Mechanisms Of Disease, W.B. Saunders, Philadelphia, Pa, USA, 1971.
  44. World Medical Association, “World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects,” JAMA, vol. 310, no. 20, pp. 2191–2194, 2013. View at Publisher · View at Google Scholar
  45. R. J. Bunder, I. Haluszcynski, and H. Langhammer, “In vivo/in vitro labeling of red blood cells with Tc-99m,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 8, pp. 218–225, 1983. View at Google Scholar
  46. UltraTag™ RBC Kit, Mallinckrodt Medical, St. Louis, Mo, USA, 1995.
  47. A. Muxí, P. Paredes, L. Mont et al., “Left ventricular function and visual phase analysis with equilibrium radionuclide angiography in patients with biventricular device,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 35, no. 5, pp. 912–921, 2008. View at Publisher · View at Google Scholar · View at Scopus
  48. D. Meyer, E. Dimitriadou, K. Hornik et al., Misc Functions of the Department of Statistics. Probability Theory Group (Formerly: E1071), TU Wien. R Package, 2008.
  49. C.-C. Chang and C.-J. Lin, “LIBSVM: a library for support vector machines,” ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 3, article 27, 2011. View at Publisher · View at Google Scholar · View at Scopus
  50. C. M. Bishop, Pattern Recognition and Machine Learning, Information Science and Statistics, Springer, New York, NY, USA, 2nd edition, 2006.
  51. G. J. Fahy, S. L. Pinski, D. P. Miller et al., “Natural history of isolated bundle branch block,” American Journal of Cardiology, vol. 77, no. 14, pp. 1185–1190, 1996. View at Publisher · View at Google Scholar · View at Scopus
  52. S. Port, F. R. Cobb, R. E. Coleman, and R. H. Jones, “Effect of age on the response of the left ventricular ejection fraction to exercise,” New England Journal of Medicine, vol. 303, no. 20, pp. 1133–1137, 1980. View at Publisher · View at Google Scholar · View at Scopus