Bio-informatics assessment schema (BIAS) to improve myocardial perfusion image diagnostic and prognostic value: the NHLBI-sponsored women's ischemia syndrome evaluation (WISE) study

Background Introduction: When assessing myocardial perfusion image (MPI) data for diagnosis or prediction of prognosis it is common to evaluate the technology using a ReceiverOperator Characteristic (ROC) curve. The diagonal response represents the knowledge prior to conducting the test (i.e. the diagonal represents random chance). We present an approach termed Bio-Informatics Assessment Schema (BIAS) that provides an elevated baseline from which to evaluate the MPI reading, i.e. indicating that at baseline, more data is available than random chance. Here we describe how the BIAS formulae are generated for cardiovascular magnetic resonance image (CMRI) data applied to the Women’s Ischemia Syndrome Evaluation (WISE) Study.