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Article

Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women

1
Department of Physical Therapy and Assistive Technology, National Yang Ming Chiao Tung University, Taipei City 112304, Taiwan
2
Department of Physical Medicine & Rehabilitation, Far Eastern Memorial Hospital, New Taipei City 22000, Taiwan
*
Author to whom correspondence should be addressed.
Medicina 2026, 62(1), 181; https://doi.org/10.3390/medicina62010181
Submission received: 28 November 2025 / Revised: 29 December 2025 / Accepted: 9 January 2026 / Published: 15 January 2026
(This article belongs to the Section Cardiology)

Abstract

Background and Objectives: Endothelial dysfunction is an early indicator of cardiovascular disease and is commonly assessed using flow-mediated dilation (FMD). Although handheld ultrasound (HHUS) devices improve measurement accessibility, image analysis for conventional flow-mediated dilation (FMD) assessment remains time-consuming and highly operator-dependent. This study aimed to evaluate the between-day test–retest reliability of an AI-assisted brachial artery image analysis workflow integrating HHUS imaging with a YOLOv12 deep learning model in postmenopausal women. Materials and Methods: Seventeen postmenopausal women aged 55–70 years completed two flow-mediated dilation assessments conducted seven days apart. Brachial artery images were acquired using a standardized FMD protocol with a handheld ultrasound system. An AI-assisted image analysis workflow based on a YOLOv12 deep learning model was used to automatically measure baseline diameter (Dbase), peak diameter (Dpeak), absolute FMD (FMDabs), and relative FMD (FMD%). Between-day reliability was evaluated using intraclass correlation coefficients (ICCs), coefficients of variation (CVs), and Bland–Altman analysis. Results: Good between-day repeatability was observed for baseline and peak diameters, with ICCs of 0.81 and 0.76 and low CVs (3.26% and 3.22%), respectively. Functional vascular outcomes also demonstrated good reliability, with ICCs of 0.81 for FMDabs and 0.87 for FMD%. However, higher CVs were observed for FMDabs (17.15%) and FMD% (19.09%), indicating substantial inter-individual variability. Bland–Altman analysis showed a small mean difference for FMD% (0.34%), with no evidence of systematic bias. Conclusions: An AI-assisted HHUS image analysis workflow integrating a YOLOv12 deep learning model demonstrates acceptable between-day reliability for diameter-based and dilation-based measures of flow-mediated dilation in postmenopausal women. While variability in functional responses exists, the proposed system is feasible for research-oriented vascular assessment, providing a methodological foundation for future validation and clinical translation studies.
Keywords: YOLOv12; deep learning; flow mediated dilation; vascular endothelium; ultrasound; postmenopausal women YOLOv12; deep learning; flow mediated dilation; vascular endothelium; ultrasound; postmenopausal women

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MDPI and ACS Style

Chen, W.-D.; Kao, Y.-C.; Chiu, C.-H.; Huang, C.-C.; Tsai, M.-W. Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women. Medicina 2026, 62, 181. https://doi.org/10.3390/medicina62010181

AMA Style

Chen W-D, Kao Y-C, Chiu C-H, Huang C-C, Tsai M-W. Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women. Medicina. 2026; 62(1):181. https://doi.org/10.3390/medicina62010181

Chicago/Turabian Style

Chen, Wei-Di, Yung-Chia Kao, Chun-Hsien Chiu, Chao-Chun Huang, and Mei-Wun Tsai. 2026. "Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women" Medicina 62, no. 1: 181. https://doi.org/10.3390/medicina62010181

APA Style

Chen, W.-D., Kao, Y.-C., Chiu, C.-H., Huang, C.-C., & Tsai, M.-W. (2026). Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women. Medicina, 62(1), 181. https://doi.org/10.3390/medicina62010181

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