Model-based image processing derived parameters of ventricular filling: Can they predict exercise capacity in subjects with chronic heart failure?

T. E. Meyer, J. Singh, M. Karamanoglu, A. Ehsani, S. Kovács

Research output: Contribution to journalConference article

Abstract

Model-based image processing (MBIP) of Doppler echocardiographic transmitral flow (E-waves) has been validated as a method of quantitative diastolic function (DF) assessment. MBIP incorporates the mechanical suction-pump role of the heart, uses the E-wave as input, solves the 'inverse problem' of diastole and generates three unique parameters (x0c,k) for each E-wave. The model's spring constant k is the analogue of (average) chamber stiffness (ΔP/ΔV). Exercising subjects with chronic heart failure (CHF) attaining an oxygen consumption peak VO2 ≤ 14 ml/kg/min are likely to benefit from transplantation whereas those attaining peak VO2 > 14 ml/kg/min do not. The relationship between peak VO2 and DF has not been determined in CHF. Doppler E-waves of 31 pre-transplant subjects were analyzed using MBIP. Least squares linear best fit determined the k vs. peak VO2 relation. For subjects with VO2 ≤ 14 ml/kg/min (n=12) k was linearly proportional to peak VO2 with r=0.57. We conclude that: k is inversely correlated with peak VO2; a clear delineation exists for k at a VO2 ≤ or > 14 ml/kg/min. These results show that the stiffer the chamber the worse the exercise tolerance, and MBIP facilitates quantitative DF determination in subjects with CHF.

Original languageEnglish
Pages (from-to)1268-1269
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
StatePublished - Dec 1 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

Keywords

  • Diastolic function
  • Echocardiography
  • Heart failure
  • Mathematical modeling
  • Transplantation

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