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

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.

The prototype device for non-invasive diagnosis of arteriovenous fistula condition using machine learning methods

“…However, the doctors with experience can recognize the stenosis sound pattern even in the noisy environments. Therefore, we are going to expand the device menu and add some further options with possibility to assess AVF condition with the use of different methods, like wavelet transform 20 , 21 or others proposed in the literature for detecting hemodynamically significant vascular access stenosis 9 , 22 , 23 .…”

“…while using contrast) and require the use of expensive apparatus, hence, they are rather impractical for an initial screening in hemodialysis centres. Therefore, uncomplicated but effective ways of assessing the condition of the fistula are still being sought 9 .…”

Bruit-enhancing phonoangiogram filter using sub-band autoregressive linear predictive coding

“…Frames are recombined using a 25% overlap-add frame smoother to produce 2 time-domain outputs, X BEF [ n ] and E BEF [ n ]. X BEF [ n ] is the bruit-enhanced version of the original PAG and is a clearer recording which can be analyzed using frequency-domain or data clustering methods [5,6]. In this work, we analyze the properties of E BEF [ n ], which is the modeled time-domain envelope of the bruit signal.…”

“…PAGs can be parametrically analyzed to quantity vascular access function [5–6]. One promising parameter derived from E BEF [ n ] is the RMS sub-band velocity SBV RMS , i.e., time-derivative of E BEF [ n ]: SBVRMS=∑(EBEF[n]−EBEF[n−1])2 Note that (5) only uses the modeled SB-FDLP envelope and not the enhanced PAG X BEF [ n ].…”

“…PAGs contain a unique acoustic spectrum that correlates strongly with degree of stenosis ( DOS ) [5] and their interpretation can be automated [6]. Previous studies have recorded and analyzed pathological PAGs, on patients with known access dysfunction, and have relied on imaging to localize the PAG recording site [5,6]. In this context, PAG analysis is of limited value when a patient has already received an intervention and clinical imaging is available.…”