Related Experiment Video
Updated: Jun 9, 2026
Ultrasound Assessment of Flow-Mediated Dilation of the Brachial and Superficial Femoral Arteries in Rats
Published on: November 3, 2016
AFMD Master: An open-source software for automated extraction of artery flow-mediated dilation from vascular
Alessandro Gentilin1,2, Alice Gasparini3, Enrico Tam3
1Université Marie et Louis Pasteur, SINERGIES, Besançon, France.
Introduction:
Artery flow-mediated dilation (FMD) is a non-invasive method for assessing vascular endothelial function and cardiovascular disease risk. Flow-mediated dilation is calculated as the percentage increase in arterial diameter following a post-ischemic increase in blood flow through ultrasound analysis. Manual extraction of flow-mediated dilation scores is time-consuming, operator-dependent, and prone to variability. Automated software solutions for processing ultrasound data could enhance efficiency, accuracy, standardisation, and scalability for clinical and research applications, especially when distributed as free, open-source tools accessible even to non-coders. However, no current software tools reporting these features are available for automatic flow-mediated dilation extraction.
Methods:
We developed aFMD Master, a free, open-source software tool with an intuitive graphical interface designed for non-coders. The software is compatible with most of the videos from different ultrasound scanners, extracts arterial diameters, and outputs PDF reports and Excel datasheets with flow-mediated dilation scores. Validation was conducted by comparing software outputs with manually obtained data from 115 participants, using scatter plots, Bland-Altman analysis, and other appropriate statistical metrics.
Results:
Strong correlation between the software and manual methods was obtained (R² = 0.97, p < 0.01). The Bland-Altman analysis showed minimal bias (-0.0015%), with 95% limits of agreement between -0.28% and 0.28%. The software showed high accuracy, minimal bias, and low variability, with negligible impact of errors, reflecting strong precision, consistency, and reliability.
Conclusions:
Validation showed excellent agreement with manual analysis, confirming accuracy, low bias, and consistency. The aFMD Master offers an accessible and reliable solution for automated flow-mediated dilation analysis, showcasing significant potential for research and clinical applications.
