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A Supporting Platform for Semi-Automatic Hyoid Bone Tracking and Parameter Extraction from Videofluoroscopic Images for the Diagnosis of Dysphagia Patients

Dysphagia volume 32, pages 315–326 (2017)Cite this article

Abstract

Conventional kinematic analysis of videofluoroscopic (VF) swallowing image, most popular for dysphagia diagnosis, requires time-consuming and repetitive manual extraction of diagnostic information from multiple images representing one swallowing period, which results in a heavy work load for clinicians and excessive hospital visits for patients to receive counseling and prescriptions. In this study, a software platform was developed that can assist in the VF diagnosis of dysphagia by automatically extracting a two-dimensional moving trajectory of the hyoid bone as well as 11 temporal and kinematic parameters. Fifty VF swallowing videos containing both non-mandible-overlapped and mandible-overlapped cases from eight patients with dysphagia of various etiologies and 19 videos from ten healthy controls were utilized for performance verification. Percent errors of hyoid bone tracking were 1.7 ± 2.1% for non-overlapped images and 4.2 ± 4.8% for overlapped images. Correlation coefficients between manually extracted and automatically extracted moving trajectories of the hyoid bone were 0.986 ± 0.017 (X-axis) and 0.992 ± 0.006 (Y-axis) for non-overlapped images, and 0.988 ± 0.009 (X-axis) and 0.991 ± 0.006 (Y-axis) for overlapped images. Based on the experimental results, we believe that the proposed platform has the potential to improve the satisfaction of both clinicians and patients with dysphagia.

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Acknowledgements

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1004622 and NRF-2015R1D1A1A01058652).

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    Authors and Affiliations

    1. Department of Biomedical Engineering, Hanyang University, Seoul, 04763, Korea

      Jun Chang Lee, Kyoung Won Nam, Dong Pyo Jang & In Young Kim

    2. Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul, 13620, Korea

      Nam Jong Paik & Ju Seok Ryu

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    1. Jun Chang Lee
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    Correspondence to In Young Kim.

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    Jun Chang Lee and Kyoung Won Nam contributed equally to this paper and should therefore be regarded as equivalent first authors.

    In Young Kim and Ju Seok Ryu contributed equally to this paper and should therefore be regarded as equivalent corresponding authors.

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    Lee, J.C., Nam, K.W., Jang, D.P. et al. A Supporting Platform for Semi-Automatic Hyoid Bone Tracking and Parameter Extraction from Videofluoroscopic Images for the Diagnosis of Dysphagia Patients. Dysphagia 32, 315–326 (2017). https://doi.org/10.1007/s00455-016-9759-x

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    • DOI: https://doi.org/10.1007/s00455-016-9759-x

    Keywords

    • Dysphagia
    • Videofluoroscopic
    • Hyoid bone
    • Diagnosis
    • Deglutition
    • Deglutition disorders