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Hemodialysis vascular access stenosis detection using auditory spectro-temporal features of phonoangiography

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Abstract

For end-stage renal disease patients undergoing hemodialysis, thrombosis caused by stenosis hinders the long-term use of vascular access. However, traditional spectral bruit analysis techniques for detecting the severity of vascular access stenosis are not robust. Accordingly, the present study proposes an automated method for mimicking a trained practitioner in performing the auscultation process. In the proposed approach, the bruit obtained using a standard phonoangiographic method is transformed into the time–frequency domain, and two spectro-temporal features, namely the auditory spectrum flux and the auditory spectral centroid, are then extracted. The distributions of the two features are analyzed using a multivariate Gaussian distribution (MGD) model. Finally, the distribution parameters of the MGD model are used to detect the presence (or otherwise) of vascular access stenosis. The validity of the proposed approach is investigated using the phonoangiography signals obtained from 16 hemodialysis patients with straight arteriovenous grafts over the upper arm region. The results show that the MGD covariance matrix coefficient of the auditory spectral centroid feature yields an accuracy of 83.87 % in detecting significant vascular access stenosis. Thus, the proposed method has significant potential for the applications of vascular access stenosis detection.

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Acknowledgments

This study was supported by the National Cheng Kung University Hospital (protocol No. NCKUH-10305001) and in part of the National Science Council of the Republic of China under Grant No. NSC 100-2221-E-006-248-MY3. The institutional review board of National Cheng Kung University Hospital approved this study and the IRB No. ER-99-186. We are grateful to Sheng-Hsiang Lin and Jia-Ling Wu for providing the statistical consulting services from the Biostatistics Consulting Center, National Cheng Kung University Hospital.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan, ROC

    Po-Hsun Sung, Ling-Sheng Jang & Jhing-Fa Wang

  2. Department of Surgery, National Cheng Kung University Hospital, No. 138, Sheng Li Road, Tainan City, 704, Taiwan, ROC

    Chung-Dann Kan

  3. Department of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan, ROC

    Wei-Ling Chen

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  1. Po-Hsun Sung
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  2. Chung-Dann Kan
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  4. Ling-Sheng Jang
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Correspondence to Po-Hsun Sung or Ling-Sheng Jang.

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Sung, PH., Kan, CD., Chen, WL. et al. Hemodialysis vascular access stenosis detection using auditory spectro-temporal features of phonoangiography. Med Biol Eng Comput 53, 393–403 (2015). https://doi.org/10.1007/s11517-014-1241-z

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  • DOI: https://doi.org/10.1007/s11517-014-1241-z

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