The automated MATLAB program decreased analysis time by 30-fold (50 vs 1500 minutes) and reduced intra- and inter-observer variability compared to manual analysis of murine coronary flow patterns.
Effect estimate: 30-fold decrease
Absolute Event Rate: 50% vs 1500%
The coronary microcirculation (CM) plays a critical role in the regulation of blood flow and nutrient exchange to support the viability of the heart. In many disease states, the CM becomes structurally and functionally impaired, and transthoracic Doppler echocardiography can be used as a non-invasive surrogate to assess CM disease. Analysis of Doppler echocardiography is prone to user bias and can be laborious, especially if additional parameters are collected. We hypothesized that we could develop a MATLAB algorithm to automatically analyze clinically-relevant and non-traditional parameters from murine PW Doppler coronary flow patterns that would reduce intra- and inter-operator bias, and analysis time. Our results show a significant reduction in intra- and inter-observer variability as well as a 30 fold decrease in analysis time with the automated program vs. manual analysis. Finally, we demonstrated good agreement between automated and manual analysis for clinically-relevant parameters under baseline and hyperemic conditions. Resulting coronary flow velocity reserve calculations were also found to be in good agreement. We present a MATLAB algorithm that is user friendly and robust in defining and measuring Doppler coronary flow pattern parameters for more efficient and potentially more insightful analysis assessed via Doppler echocardiography.
Sunyecz et al. (Fri,) conducted a other in Coronary microcirculation assessment in diabetes (n=44). Automated MATLAB program analysis vs. Manual analysis was evaluated on Total analysis time for both viewings (30-fold decrease). The automated MATLAB program decreased analysis time by 30-fold (50 vs 1500 minutes) and reduced intra- and inter-observer variability compared to manual analysis of murine coronary flow patterns.