Fundamental study for optical transillumination imaging of arteriovenous fistula

Hideaki Kamiyama, Masataka Kitama, Hisae Odagiri-Shimizu, Masaji Yamashita, Yohichiro Kojima, Koichi Shimizu

Research output: Contribution to journalArticlepeer-review

Abstract

An arteriovenous (AV) fistula is commonly constructed in patients who need dialysis treatment. Daily monitoring of the AV fistula is crucially important to maintain its correct function. We developed a new technique using a safe and simple instrument for noninvasive monitoring of the AV fistula. Using this technique, we can observe and analyze the blood vessel condition using transillumination imaging with near-infrared (NIR) light. For an AV fistula in the forearm, we illuminate NIR light from both sides of the arm. Then the transillumination image is captured using a camera placed above the forearm. An imaging system was developed to validate the proposed technique. It was tested with model phantoms that simulate the blood vessels of the human adult forearm. Severe blurring of the image caused by strong scattering in the interstitial tissue can be eliminated by deconvolution with a point spread function of the blur. This process clarified the blood vessel image and facilitated measurement of its inner diameter. After confirming the accuracy of the system, we attempted measurement of localized stenosis. Results show that we can detect stenotic portions as small as 2 mm in diameter and 2 mm in length. The detectability of non-coaxial stenosis was also confirmed. These results verified the feasibility and applicability of the proposed technique for non-invasive daily monitoring of AV fistulae.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalAdvanced Biomedical Engineering
Volume10
DOIs
Publication statusPublished - 2021

Keywords

  • AV fistula
  • NIR light
  • Noninvasive
  • PSF deconvolution
  • Transillumination imaging

ASJC Scopus subject areas

  • Biotechnology
  • Biomaterials
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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