Semi-Automated Measurement of Central Retinal Artery Blood Flow Using Doppler Ultrasound Coupled With Electrocardiography

Purpose: To design, implement, and test a semi-automated method for measuring central retinal artery (CRA) blood flow using color Doppler imaging (CDI) waveforms synchronized with electrocardiography (ECG). Methods: Twenty-four patients (48 eyes; 16/8 male/female; mean age 64.5 ± 15.8 years) underwent CDI-ECG imaging. Peak systolic velocity (PSV), end-diastolic velocity (EDV) and time from the ECG r-wave to the CRA PSV (r_PSV) were measured manually and with a semi-automated method. Results: PSV showed excellent correlation and agreement between manual and semi-automated methods (right eye [OD] r = 0.95, intraclass correlation coefficient [ICC] = 0.945; left eye [OS] r = 0.94, ICC = 0.928). EDV had weaker results (OD r = 0.67, ICC = 0.441; OS r = 0.86, ICC = 0.585). The r_PSV had moderate correlations (OD r = 0.75; OS r = 0.42) and agreement (ICC = 0.702 and 0.387). Bland-Altman analysis showed small PSV bias (OD = 0.327; OS 0.419 cm/s), EDV overestimation (bias OD -0.556; OS -0.886 cm/s), and minimal r_PSV bias (OD = -0.012; OS = -0.010 s). Mixed-effects modeling found a significant method and eye effect only for EDV. Conclusions: Semi-automated PSV measurements show excellent agreement with manual analysis and represent the most robust and clinically applicable output of the method. In contrast, EDV and r_PSV demonstrate lower agreement and should be considered exploratory, likely reflecting sensitivity to waveform morphology and low-magnitude signal characteristics. Translational Relevance: A semi-automated CDI-ECG waveform analysis could allow for reproducible assessment of ocular blood flow and enable large-scale assessment of data examining the heart-eye relationship.