Quantification of Cardiac Dyssynchrony Entropy Implemented in a Commercial Nuclear Medicine Software Application

Traditional patient selection criteria for cardiac resynchronization therapy (CRT) could be improved to predict patient response to CRT. Assessment of cardiac dyssynchrony using gated myocardial perfusion single-photon emission computed tomography (SPECT) or positron emission tomography (PET) in quantification software programs can be a reliable alternative. Quantitative parameters that describe the left ventricular phase analysis histogram such as phase standard deviation, bandwidth, and entropy aid in physician decision making. Entropy has been found in previous studies to be an effective parameter in identifying patients with left ventricular cardiac dyssynchrony. In this paper, we describe the characteristics of the entropy parameter with respect to other parameters such as phase standard deviation and histogram bandwidth. The implementation and testing of the entropy metric in the Corridor4DM (4DM) software package is also described. Algorithm testing and characterization were performed using computer-generated pseudorandom normal distributions. Implementation testing in 4DM was performed with two groups of patient data: patients with a left bundle branch block (LBBB) and patients with low pretest likelihood (LLk) for coronary artery disease. Entropy was found to monotonically increase in a semilogarithmic fashion with respect to phase standard deviation. For pseudorandom normal distributions with a constant standard deviation, the number of histogram bins used in calculating the entropy metric varied the metric by up to 61.3%; on average, an increase in histogram bins from 60 to 100 increased the mean entropy value by 11.0%. Implementation testing in 4DM showed agreement with the preliminary algorithm results and found a clear separation in entropy values between LLk and LBBB patients.