title: Quantitative assessment of myocardial ultrasound tissue characterization through receiver operating characteristic analysis of Bayesian classifiers.
abstract: OBJECTIVE
  This work proposes a self-consistent assessment methodology for quantitative evaluation of any combination of diagnostic features, with the immediate goal of quantitatively assessing the discriminating power in diabetic patients of features derived from ultrasound backscatter from myocardium.
  
  
  BACKGROUND
  Four features from analysis of left ventricular myocardial ultrasound backscatter have previously been shown to be sensitive to potentially cardiomyopathic changes in patients with insulin-dependent diabetes mellitus who have no overt heart disease. The measured features were significantly different between such patients and normal control subjects, as well as among groups of such patients with and without systemic complications of the disease. The quantitative discriminating potential of the features was not assessed.
  
  
  METHODS
  Multivariate classifier functions were constructed and analyzed by using the methodology of the receiver operating characteristic curve, which allows quantitative assessment of the discriminating power of these features, alone or in combination. The area under the receiver operating characteristic curve--the true positive rate averaged over all false positive rates--was used as a summary measure of performance.
  
  
  RESULTS
  In distinguishing patients with insulin-dependent diabetes mellitus from normal control subjects, the most discriminating combination of ultrasound features for the detection of such changes in these patients yielded receiver operating characteristic curves with area measures of approximately 0.80; for such patients with retinopathy the measure increased to 0.90. This performance is comparable to that of many commonly used diagnostic tests.
  
  
  CONCLUSIONS
  A self-consistent set of evaluation methodologies has quantitatively demonstrated the sensitivity of four ultrasound backscatter features to otherwise latent changes in myocardial structure that accompany the evolution of insulin-dependent diabetes mellitus. The results are remarkable in themselves and suggest the potential of the features for the general field of cardiac ultrasound tissue characterization.
authors.affiliation: Office of Science and Technology, U.S. Food and Drug Administration, Rockville, Maryland 20857, USA.
authors.forename: R F
authors.initials: RF
authors.lastname: Wagner
authors.forename: K A
authors.initials: KA
authors.lastname: Wear
authors.forename: J E
authors.initials: JE
authors.lastname: Perez
authors.forename: J B
authors.initials: JB
authors.lastname: McGill
authors.forename: K B
authors.initials: KB
authors.lastname: Schechtman
authors.forename: J G
authors.initials: JG
authors.lastname: Miller
mesh_terms: D001499:Bayes Theorem; D009202:Cardiomyopathies / Q000000981:diagnostic imaging* / Q000209:etiology; D016022:Case-Control Studies; D003922:Diabetes Mellitus, Type 1 / Q000150:complications / Q000000981:diagnostic imaging*; D004452:Echocardiography / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D015999:Multivariate Analysis; D012372:ROC Curve; D012680:Sensitivity and Specificity