Detecting carotid stenosis from skin vibrations using Laser Doppler Vibrometry – An in vitro proof-of-concept

Figures

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  Fig 1. Patient-specific model. (A) CTA images of the carotid bifurcation from a 75 year old male were processed by Iannaccone et al.[20] in order to obtain a patient-specific model of the plaque-free stenosed vessel. The compliant (B) and stiff (C) models used for the hydraulic tests replicate the geometry of the patient-specific common carotid artery (CCA), external carotid artery (ECA), and internal carotid artery (ICA) where the 76% area stenosis (circled) is located.

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  Fig 2. The assembled loop. (A) The model was secured to an optical table in order to minimize the influence of external movements. (B) In this layout of the test rig, the flow is depicted as a blue line where the arrow represents the direction of the flow. The thinner red, orange and green lines represent the signal acquisition wires of the LDV, pressure probes and flow probes, respectively. This set-up was used for both the compliant and stiff models.

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  Fig 3. Time traces for the compliant (upper panels) and stiff (bottom panels) models obtained at 1D with low (left panels) and high (right panels) QCCA. The horizontal dashed line shows the mean QCCA.

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  Fig 4. Workflow of the signal processing. (A) The spectrum of the no-flow pressure signals was subtracted from the spectrum of each flow recording to obtain the normalized spectrum, (B) its integral, based on the trapezoidal method and (C) the sum of the integrals in 50 Hz-wide frequency ranges, (D) the same post processing was applied to all available recordings.

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  Fig 5. Spectrograms of the pressure and LDV at the ICA for the compliant (upper panels) and stiff (bottom panels) models obtained at 1D with low (left panels) and high (right panels) QCCA.

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  Fig 6. Normalized spectra of pressure (left panel) and LDV (right panel) signals, for multiple QICA in the 0–500 Hz range.

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  Fig 7. The F coefficient of Freq.QICA, resulting from the regression analysis of all available signals, showed that the sensitivity of LDV and pressure have a similar trend and that their sensitivity is the highest in the 50–150 Hz range.

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  Fig 8. Estimated Marginal Means (EMMs). (A) The stiff model lead to higher EMMs for both the integrals of normalized spectra of pressure and LDV in the ICA (PICA and LDVICA, respectively). (B) The EMMs decreased while moving further downstream from the stenosis for the pressure, and this trend was not as marked for the LDV where the 4D signal was above the 1D level.