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Automated angular measurement for puncture angle using a computer-aided method in ultrasound-guided peripheral insertion

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Abstract

Ultrasound guidance has become the gold standard for obtaining vascular access. Angle information, which indicates the entry angle of the needle into the vein, is required to ensure puncture success. Although various image processing-based methods, such as deep learning, have recently been applied to improve needle visibility, these methods have limitations, in that the puncture angle to the target organ is not measured. We aim to detect the target vessel and puncture needle and to derive the puncture angle by combining deep learning and conventional image processing methods such as the Hough transform. Median cubital vein US images were obtained from 20 healthy volunteers, and images of simulated blood vessels and needles were obtained during the puncture of a simulated blood vessel in four phantoms. The U-Net architecture was used to segment images of blood vessels and needles, and various image processing methods were employed to automatically measure angles. The experimental results indicated that the mean dice coefficients of median cubital veins, simulated blood vessels, and needles were 0.826, 0.931, and 0.773, respectively. The quantitative results of angular measurement showed good agreement between the expert and automatic measurements of the puncture angle with 0.847 correlations. Our findings indicate that the proposed method achieves extremely high segmentation accuracy and automated angular measurements. The proposed method reduces the variability and time required in manual angle measurements and presents the possibility where the operator can concentrate on delicate techniques related to the direction of the needle.

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Acknowledgements

The authors would especially like to express their gratitude to Editage for language editing.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. School of Radiological Technology, Gunma Prefectural College of Health Sciences, Maebashi, Japan

    Haruyuki Watanabe, Yuina Ezawa, Norio Hayashi, Toshihiro Ogura & Masayuki Shimosegawa

  2. Department of Radiology, Cardiovascular Hospital of Central Japan, Shibukawa, Japan

    Hironori Fukuda

  3. Faculty of Informatics, The University of Fukuchiyama, Fukuchiyama, Japan

    Eri Matsuyama

  4. Graduate School of Health Sciences, Niigata University, Niigata, Japan

    Yohan Kondo

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  1. Haruyuki Watanabe
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  8. Masayuki Shimosegawa
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Contributions

All authors contributed to the study conception and design. Haruyuki Watanabe, Hironori Fukuda, and Yuina Ezawa conceived the main ideas, designed the study, and provided full access to all data. Eri Matsuyama, Yohan Kondo, and Norio Hayashi discussed the results and drafted the manuscript. Toshihiro Ogura and Masayuki Shimosegawa drafted the manuscript. All the authors have reviewed the manuscript.

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Correspondence to Haruyuki Watanabe.

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This study was conducted in accordance with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Gunma Prefectural College of Health Sciences (September 21, 2022; 2022-11).

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Watanabe, H., Fukuda, H., Ezawa, Y. et al. Automated angular measurement for puncture angle using a computer-aided method in ultrasound-guided peripheral insertion. Phys Eng Sci Med (2024). https://doi.org/10.1007/s13246-024-01397-x

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