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Please note that you are viewing an archived section from 2020 and some content may be unavailable. To unlock all content for 2020, please visit the archives.

Abstract: PO1330

Relationship of Vascular Access Flow and Stenosis Detected by Frequency Domain Analysis of Videos Taken with a Smartphone

Session Information

  • Vascular Access
    October 22, 2020 | Location: On-Demand
    Abstract Time: 10:00 AM - 12:00 PM

Category: Dialysis

  • 704 Dialysis: Vascular Access

Authors

  • Zhu, Fansan, Renal Research Institute, New York, New York, United States
  • Wang, Lin-Chun, Renal Research Institute, New York, New York, United States
  • Cherif, Alhaji, Renal Research Institute, New York, New York, United States
  • Maheshwari, Vaibhav, Renal Research Institute, New York, New York, United States
  • Thwin, Ohnmar, Renal Research Institute, New York, New York, United States
  • Tisdale, Lela, Renal Research Institute, New York, New York, United States
  • Tao, Xia, Renal Research Institute, New York, New York, United States
  • Paneque Galuzio, Paulo, Renal Research Institute, New York, New York, United States
  • Shtaynberg, Norbert, AzuraVascular Care, New York, New York, United States
  • Preddie, Dean C., AzuraVascular Care, New York, New York, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

We developed a video image processing (VIP) technique with frequency domain analysis to assess arteriovenous fistula (AVF) blood flow. This study aimed to investigate the relationship of heart rate and access blood flow rate (Qa) represented by the frequency signals at maximum (FMax, Hz) and minimum (FMin, Hz) of magnitude in frequency domain analysis.

Methods

We employed VIP pre- and post-endovascular interventions in 90 hemodialysis patients (age 63.3 ± 14.3, 41 females, weight 78.6 ± 21.5 kg),. FMax and FMin pre- and post-intervention were recorded. ΔF was defined as FMin - FMax for each video. Qa was measured pre- and post-intervention by HVT100 endovascular flowmeter (Transonic Systems Inc., Ithaca, NY, USA). The degree of stenosis (%) was quantitated by angiography. Heart rate (HR, beats/min) was expressed as a frequency (FHR, Hz).

Results

The pre- and post-intervention differences between FMax and FHR were 1.14±0.74 Hz and 1.38±1.44 Hz, respectively. ΔF was associated with Qa pre- (Fig 1(a)) and post-intervention (Fig1(b)). ΔF increased most when Qa increased from pre-intervention range of 300 to 600 ml/min to post-intervention 600 to 900 ml/min. Fig 1(c) shows the relationship between % stenosis and the change in ΔF between pre- and post-intervention. The difference between FMax and FHR was associated with % stenosis pre-intervention (Fig. 1(d)).

Conclusion

The relationship between FMax and FHR suggests that the signal of FMax represents an important hemodynamic component of Qa. ΔF may be used as an index to predict low levels of stenosis. The use of frequency domain analysis from video image data provides a contact-free method to ascertain Qa and to indirectly indicate the degree of stenosis. Further study is needed to standardize the quality of video and streamline the methodology.