Prediction of myocardial perfusion abnormalities by quantitative regional function using a radionuclide angiography database: a comparison with wall motion analysis.

Published

Journal Article

PURPOSE: Myocardial perfusion and functional information during the same study is now feasible. A new assessment of regional ejection fraction at rest and peak exercise by first-pass radionuclide angiography using a "normal" database file has been developed. OBJECTIVE: This study was performed to assess the relation between this new method of quantitative regional ejection fraction and myocardial perfusion abnormalities and to compare this new technique with visual analysis of regional wall motion. METHODS: Consecutive patients (n = 126) with simultaneous first-pass radionuclide angiography and perfusion SPECT imaging were studied at rest and peak exercise using a same-day protocol. The area under the receiver-operator characteristic curve (C index) was used to assess the concordance probability between perfusion and functional measurements, and logistic regression models were used to examine the ability of functional variables to predict perfusion results. RESULTS: A high concordance was found between the visual analysis of wall motion and perfusion abnormalities (C index = 0.796), and also between regional ejection fraction and perfusion defects (C index = 0.784). The maximal predictive power of functional variables was obtained by combining wall motion analysis and regional ejection fraction (C index = 0.859). Regional ejection fraction contributed, with 20% more information than provided by wall motion analysis alone (chi2 = 9.2, P = 0.0025). CONCLUSIONS: Quantitative regional ejection fraction using a normal database file has a strong relation to perfusion abnormalities and provides incremental information to regional wall motion analysis for predicting perfusion abnormalities. This new technique should be regarded as a potential adjunct to functional studies to evaluate patients with ischemic heart disease.

Full Text

Duke Authors

Cited Authors

  • Borges-Neto, S; Javid, A; Kong, D; Shaw, L; Coleman, RE

Published Date

  • February 2000

Published In

Volume / Issue

  • 25 / 2

Start / End Page

  • 110 - 114

PubMed ID

  • 10656645

Pubmed Central ID

  • 10656645

International Standard Serial Number (ISSN)

  • 0363-9762

Digital Object Identifier (DOI)

  • 10.1097/00003072-200002000-00006

Language

  • eng

Conference Location

  • United States