Ultrasound-based Pulse Wave Velocity Evaluation in Mice

Summary

Arterial stiffness represents a key factor in cardiovascular disease and pulse wave velocity (PWV) can be considered as a surrogate index for arterial stiffness. This protocol describes an image processing algorithm for calculating PWV in mice based on ultrasound image processing that is applicable at different arterial sites.

Abstract

Arterial stiffness can be evaluated by calculating pulse wave velocity (PWV), i.e., the speed with which the pulse wave travels in a conduit vessel. This parameter is being increasingly investigated in small rodent models in which it is used for assessing alterations in vascular function related to particular genotypes/treatments or for characterizing cardiovascular disease progression. This protocol describes an image processing algorithm which leads to non-invasive arterial PWV measurement in mice using ultrasound (US) images only. The proposed technique has been used to assess abdominal aorta PWV in mice and evaluate its age-associated changes.

Abdominal aorta US scans are obtained from mice under gaseous anesthesia using a specific US device equipped with high-frequency US probes. B-mode and Pulse-Wave Doppler (PW-Doppler) images are analyzed in order to obtain diameter and mean velocity instantaneous values, respectively. For this purpose, edge detection and contour tracking techniques are employed. The single-beat mean diameter and velocity waveforms are time aligned and combined in order to achieve the diameter-velocity (lnD-V) loop. PWV values are obtained from the slope of the linear part of the loop, which corresponds to the early systolic phase.

With the present approach, anatomical and functional information about the mouse abdominal aorta can be non-invasively achieved. Requiring the processing of US images only, it may represent a useful tool for the non-invasive characterization of different arterial sites in the mouse in terms of elastic properties. The application of the present technique can be easily extended to other vascular districts, such as the carotid artery, thus providing the possibility to obtain a multi-site arterial stiffness assessment.

Introduction

Mouse models are increasingly employed for the investigation of cardiovascular disease (CVD) and particularly used in longitudinal studies which allow the characterization of different phases of disease development¹. Elastic properties of large arteries are related to different pathological conditions; from a technical point of view, arterial stiffness can be assessed by measuring pulse wave velocity (PWV), which represents the speed with which the pulse wave travels in a conduit vessel². Because of its clinical significance, it is increasingly measured even in preclinical small animal models³.

Different techniques are available for assessing PWV in mice. Invasive approaches are based on the use of catheter-tip pressure transducers. PWV is assessed by acquiring pressure signals at two different arterial sites and dividing the distance between the two measurement sites by the time shift between the signals⁴. The main disadvantage related to these kinds of techniques is that they require animal sacrifice for the evaluation of the distance between the two measurement sites and, thus, cannot be used in longitudinal studies. To overcome this limitation, non-invasive approaches, based on different imaging techniques, have been developed. Previous studies have reported PWV assessments in mice obtained by applying the transit time method on velocity-encoded magnetic resonance imaging data⁵ and Pulsed-Doppler signals⁶. However, the PWV value obtained with these methods is a regional evaluation of arterial stiffness. In fact, it represents an average value, accounting for different arteries in terms of size and elastic properties. In addition, these kinds of evaluations require the assessment of the distance between the two measurements sites which is a source of error that could influence the final result.

PWV can be assessed using the diameter-velocity (lnD-V) loop⁷. This method is based on the simultaneous evaluation of diameter and flow velocity values in a selected vessel. According to this approach, the lnD-V loop is obtained by plotting natural logarithm diameter values vs mean velocity values and PWV is estimated by calculating the slope of the linear part of the obtained loop corresponding to the early systolic phase. With regard to the practical implementation of this method, previous works have already reported results about its application in an in vitro set-up system⁷ and its use for the assessment of both carotid and femoral PWV in humans⁸.

The principal aim of the present study is to provide a detailed description of an image processing algorithm that provides a non-invasive arterial PWV measurement in mice using US images only. The proposed approach allows the evaluation of local arterial stiffness by means of the processing of both B-mode and Pulsed-Wave Doppler (PW-Doppler) images and can be applied on arteries of key importance, such as the abdominal aorta.

Protocol

Animal experiments were performed in accordance with the European Directive (2010/63/UE) and the Italian law (D.Lvo 26/2014), and it followed principles of laboratory animal care. The Local Ethical Approval Panel approved the study.

1. Imaging Procedure

1. Place the mouse in an anesthesia induction chamber filled with 2.5% isoflurane in 1 L/min pure oxygen. Verify the depth of anesthesia by unresponsiveness to toe pinch.
2. Place the animal on a temperature controlled board in a supine position. Moisten the animal's eyes with eye salve, in order to avoid them running dry. Supply anesthetic gas flow (1.5% isoflurane) by placing the mouse's nose in the dedicated nose cone. If necessary, adjust the percentage of isoflurane from case to case, depending on the animal under study. Fix the board temperature at 40 °C.
3. Coat the four limbs of the animal with conductive paste and tape them on the ECG electrodes embedded in the board. Measure body temperature with a rectal probe lubricated with petroleum jelly. Check that all the physiological measurements (ECG and respiration signal as well as temperature) are correctly acquired and displayed.
4. Remove hair chemically from the abdomen with depilatory cream and coat it with acoustic coupling gel.
5. Place the (13-24 MHz) US probe in the mechanical arm.
6. Fix the US probe parallel to the animal and adjust its position in order to obtain longitudinal images of the abdominal aorta with the region of interest located in the focal zone.
7. Collect anatomical information.
   1. Click on the button allowing the high frame rate ECG-gated acquisition⁹, choose a frame rate acquisition equal to 700 fps and start the acquisition. Note: In this way anatomical images of the vessel related to a single cardiac cycle can be acquired.
8. Collect flow velocity information.
   1. Using the same scan projection, click on the PW-Doppler button, place the sample volume in the centre of the vessel and acquire images ensuring that the cine loop is not shorter than 3 s. Obtain these data maintaining the angle correction as small as possible, adjusting it from case to case on the basis of the US projection obtained.
9. Remove the animal from the temperature controlled board and wait for complete recovery.
   NOTE: In our experience this takes about 10 min. Do not leave and animal unattended until it has regained sufficient consciousness to maintain sternal recumbency.

2. Post-Processing

1. Export B-mode and PW-Doppler images as DICOM files and save them on a personal computer. Transform PW-Doppler DICOM files to .tiff images.
2. Process B-mode images.
   1. Import the corresponding DICOM file using the dedicated Graphical User Interface (GUI).
   2. To initialize contours, draw a line close to the far wall of the vessel (single click for starting it and double click for ending it) and double-click close to the near wall. A line parallel to that close to the far wall will appear automatically. Apply the algorithm on a single frame by pressing the "ANALYSE" button.
   3. Check the result. If the edges have been correctly identified (i.e., the evolution of the initialized points have detected both the posterior and the anterior wall), apply the algorithm on the whole cine-loop by clicking on the "GO" button. If the edges are not correctly identified, clear them by clicking on "Clear Contour" and initialize them again by repeating point 2.2.2.
      NOTE: The algorithm is based on edge detection and contour tracking techniques and has been previously described in detail¹⁰.
   4. Obtain the final result by pressing on the "RECORD" button and save the corresponding .mat file which contains instantaneous diameter values related to a single cardiac cycle.
3. Open the GUI for the lnD-V loop implementation.
4. Click on the "VELOCITY" button in order to start PW-Doppler image processing which leads to a single-beat mean velocity curve.
   1. Identify the PW-Doppler trace and locate the line corresponding to a velocity value equal to zero by pressing the "WHITE LINE" button.
   2. Perform velocity calibration and time calibration by using the "VELOCITY" and "TIME" buttons (in the Calibration panel), respectively. Pressing on these buttons allows one to draw a line whose length corresponds to the calibration factor inserted.
   3. Manually select a ROI containing the physiological signals by using the "ROI PHYSIO" button.
   4. Manually select a ROI containing the PW-Doppler trace by pressing the "ROI SIGNAL" button.
   5. Click on the "ANALYSE" button and check if the envelope is identified. If the result is not satisfactory, change the threshold (by typing the new value in the "Velocity Threshold" editable text field) and press the "ANALYSE" button again. Tune the threshold from case to case, depending on the quality of the images. Press the "ELABORATION" button.
   6. Locate the R-peaks of the ECG signal and divide the velocity envelope signal accordingly by clicking the "UPDATE" button. Choose beats that are not corrupted by noise or located in the inspiration phase by clicking on the "CHOOSE BEATS" button. In this way, obtain a single-beat mean velocity waveform.
5. Use the Fast Fourier Transform method to interpolate the selected beats in the frequency domain and make them all composed of the same number of points, as detailed in reference¹¹. Perform this operation automatically by simply pressing the return key on the PC keyboard once the beats have been selected. If the "MEAN VELOCITY" checkbox is checked the single beat mean velocity signal is achieved by dividing the maximum velocity curve by two, hypothesizing a parabolic velocity profile¹². Press the "OK" button.
6. Click on the "DIAMETER" button. Interpolate the single-beat diameter waveform in the time domain in order to obtain a single-beat diameter signal with the same sample frequency as the single-beat velocity signal by pressing the "INTERPOLATE" button. Click on the "OK" button.
   NOTE: In order to have the single-beat diameter and mean velocity curves with the same sample frequency and the same number of data points, they are interpolated in the frequency domain.
7. Select the "Second derivative" approach as the alignment method (above the graph displaying the diameter and velocity waveforms) and click on the "UPDATE" button. The two curves will be automatically time-aligned using the second derivative method¹⁴.
8. Build the final lnD-V loop by plotting the natural logarithm of the single-beat diameter values against the single-beat mean velocity values. This is automatically done when the two waveforms are aligned. Note: The points included between the 5% and the 90% of the maximum value of the single-beat mean velocity curve are automatically located and a linear interpolation on these points is applied to evaluate the slope of the linear part of the loop.
9. Calculate PWV according to the following equation⁷
   

Results

The proposed approach has been applied to mice abdominal aorta in a previous study¹¹. The following figures show the results of the application of the described approach on real mice images. These data are from a single animal (wild type mice, 13 weeks old, strain: C57BL6, weight: 33 g) In particular, Figure 1 represents the result of the analysis of the US images. Edge detection and contour tracking techniques applied to B-mode images acquired wit...

Discussion

In this study, an image processing algorithm based on the lnD-V loop for PWV assessment in mice has been described in detail. The proposed approach is based on the processing of US images only and, thus, could represent a valid alternative to existing techniques^6,13 for the evaluation of arterial stiffness in mouse models. In fact, conversely to invasive methods⁶ which are based on the acquisition of intra-arterial pressure signals and req...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
VEVO2100	FUJIFILM VisualSonics Inc, Toronto, Canada		micro-ultrasound equipment
MS250 Ultrasound Probe	FUJIFILM VisualSonics Inc, Toronto, Canada		micro-ultrasound probe
EKV Software	FUJIFILM VisualSonics Inc, Toronto, Canada		Software
Matlab R2015a	MathWorks Inc, Natick, MA, USA		Software
Conductive Paste	Chosen by the operator		Laboratory material
Petroleum Jelly	Chosen by the operator		Laboratory material
Depilatory Cream	Chosen by the operator		Laboratory material
Acoustic Coupling Gel	Chosen by the operator		Laboratory material
Developed Matlab Software			The authors are willing to collaborate with those researchers who are interested in the software and to make the software available under their supervision