Optimization and Validation of Radionuclide Angiography Phase Analysis Parameters for Quantification of Mechanical Dyssynchrony

Introduction: Cardiac resynchronization therapy (CRT) has the potential to improve the outcome of patients suffering from mechanical dyssynchrony and heart failure. It has been suggested that accurate quantification of baseline extent of mechanical dyssynchrony may lead to pre-selection of patients likely to respond to CRT. The standard deviation from a phase histogram (phaseSD), synchrony (S) and entropy (E) are parameters obtained from phase analysis of planar radionuclide angiography (RNA) that may provide an accurate means of assessing mechanical dyssynchrony. In this paper, the ability of phaseSD, S, and E to detect mechanical dyssynchrony was investigated and optimal values for image smoothing, histogram noise thresholding, and bin size were defined. Finally, the intra- and inter-observer reproducibility of the methodology was assessed.

Methods: PhaseSD, S, and E were calculated for 37 normal subjects (LVEF > 50%, end-diastolic volume < 120 mL, end-systolic volume < 60 mL, QRS < 120 ms, and normal wall motion) and 53 patients with mechanical dyssynchrony (LVEF < 30%, QRS > 120 ms, and typical LBBB). Receiver-operator characteristics (ROC) curves were created and the area under the curve (AUC), for each parameter, was determined using three different imaging filters (no filter and an order 5 Hann filter with cut-off of 5/50 and 10/50). The AUC was also determined using histogram threshold values varying between 0% and 50% (of the max amplitude value). Finally, AUC for E was determined for bins sizes varying between 1 degrees and 20 degrees . Inter- and intra-observer variability was calculated at optimal imaging values.

Results: No smoothing was found to maximize the AUC. The AUC was independent of histogram threshold value. However, a value of 20% provided optimal visualization of the phase image. The AUC was also independent of bin size. At the optimal imaging values, the sensitivity and specificity for all parameters for detection of mechanical dyssynchrony was measured to be 89-100%. Inter- and intra-observer correlation coefficients >0.99 were found for phaseSD, S and E.

Conclusions: Optimized planar RNA phase analysis parameters, phaseSD, S, and E, were able to detect mechanical dyssynchrony with low inter- and intra-observer variability. Studies assessing the ability of these parameters to predict CRT outcome are required.