Semi-automated assessment of left ventricular performance from on-line pressure-area relations

William A. Mandarino, Lee G. Deneault, Robert L. Kormos, John Gorcsan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new method of assessing ventricular function was developed which utilizes left ventricular (LV) cross-sectional area as an index of ventricular volume. Echocardiographic automated border detection can measure LV cavity area and be combined with pressure to display pressure-area loops in real time. This methodology was applied to an open-chest dog model during inotropic modulation to test its feasibility to assess LV performance. Preload was varied by apneic inferior vena caval (IVC) occlusions before and after administration of dibutamine and propranolol as positive and negative inotropes, respectively. From these pressure-area loops, various indices describing ventricular contractile stat and pump performance were derived, including : end-systolic pressure area relationship, maximal elastance, and preload recruitable stroke force.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Conference on Engineering in Medicine and Biology
EditorsAndrew Y.J. Szeto, Rangaraj M. Rangayyan
PublisherPubl by IEEE
Pages883-884
Number of pages2
Editionpt 2
ISBN (Print)0780313771
StatePublished - 1993
EventProceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 2 (of 3) - San Diego, CA, USA
Duration: Oct 28 1993Oct 31 1993

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 2
Volume15
ISSN (Print)0589-1019

Conference

ConferenceProceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 2 (of 3)
CitySan Diego, CA, USA
Period10/28/9310/31/93

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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