Digitizing ECG image: A new method and open-source software code

Background and Objective: We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads. Methods: We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis. Results: The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9–13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρ_c 0.97(95% confidence interval [CI] 0.95–0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2–30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρ_c 0.90(95%CI 0.82–0.95)]. Conclusions: We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.