<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=875423625897521&amp;ev=PageView&amp;noscript=1">
Customer Login


Hear more from our team:

Questions from the Field III - Client Questions

By Cole McLarty30 Mar 2021

In part one and two of this recurring series, I reviewed some common questions I have encountered during lab visits over the past 11 years. These questions were somewhat general – touching on broader topics that would be asked from experts and newcomers alike. In this installment, I will be reviewing specific client questions related to our ADV500 Pressure-Volume Loop system and as a result, this blog is best suited to our clients directly. In an effort to keep the content approachable for all readers, I will reference technical notes to help explain topics that are out of the scope of description in this brief blog:

What is “Phase” and what numbers should I expect in my animals?

Unlike a classic conductance system which outputs two signals – pressure and conductance (sometimes called Relative Volume Units or “RVU’s) – our more modern admittance system outputs four signals – pressure and conductance (exactly like a classic system) along with “phase” and absolute ventricular volume. That absolute volume of course is what makes our equipment most unique and why we continue to grow in this market, however it is the “phase” signal that does the heavy lifting, allowing for the accurate calculation of volume.

Heart with PV Catheter - Blood v Muscle ContributionIn the most basic sense “phase” is the total muscle contribution to the overall electric signal we collect from the heart (see our technical note for a reminder of how PV technologies work). As many of you will be aware, one of the main confounding factors in collecting quality PV loops is the fact that the emitted electrical signal from the catheter penetrates both the blood and the muscle. The blood is what we want, however the muscle is always present in varying proportion depending on several factors – catheter position, location in the cardiac cycle, presence of heart disease, etc. Our technology looks at the input current and output voltage, monitoring it many times through a single heartbeat, and reports the synchrony of the two signals. As you can see in Figure #1 below, the input current and output voltage are not the same, they are out of “phase” by a measurable degree – this is where the name comes from. Our equipment monitors the degree of phase throughout the entire experiment, the more phase, the more muscle present in the electrical field generated by the catheter.

Phase Shift Theory

Figure #1 – Comparison between the input current and output voltage collected from a PV catheter – the delta between these two signals is called “phase.” The more out of phase, the more muscle present in the total signal.

Why is this helpful? There are a few reasons:

  1. Knowing the muscle contribution to the total conductance signal gives us the ability to subtract this contribution during an experiment, removing the need for a saline bolus calibration.
  2. It also allows us to process the data live, giving a true-ventricular volume during the experiment.
  3. It allows us to steer the catheter into optimal position, which is perhaps one of the most important fringe benefits of phase. A known challenge with PV catheterizations, especially in rodents, is the strict requirement to place the catheter in the center of the animal’s ventricle. However, imaging modalities are uncommon in these applications and when using a closed chest approach, you cannot see the catheter’s position. Using phase, a surgeon can simply aim to minimize the total reported phase, because the middle of the heart places the catheter as far away from the myocardium as possible. This also allows for the monitoring and normalization of position between animals – a rarely talked about confounding variable in PV science.
  4. Most importantly, in our opinion, is the fact that having a live representation of muscle contribution allows us to track and remove the increase of muscle contribution to the total conductance signal seen during an occlusion. Occlusions are, of course, the one thing that PV loops do uniquely well; however the increase in muscle contribution through the occlusion ramp is a variable that conductance systems simply cannot account for. With the phase signal, we track and remove the increased muscle contributions, making your occlusion trends more accurate.

What phase values should you expect in your animal models? This is a great question, and we give our clients’ the following general guidelines based on body weight:

  1. 15-1000g : ~3-7 degrees
  2. 1Kg-8Kg : 2-5 degrees
  3. 8Kg-60Kg : 1-4 degrees
  4. 60Kg+ : 0.5-3 degrees

How to cope with a breathing artifact in your data

Before we jump into this topic, there are several schools of thought here. As with my previous blogs, I want to address practical issues in the lab while leaving the science debate to the experts. However, sometimes that is impossible because the advice that we give directly effects physiology and in so doing, we are making a scientific choice. We are informed by the trending scientific mores, so our suggestions do change with changing trends. With this said, let us jump in.

A “breathing artifact” is the physiological result of changing pressures in the chest. It effects various measurements, but for PV loops we are looking at how it effects pressure and volume in the heart. For a PV loop, breathing artifacts most dramatically effect the isovolumic contraction phase of the cardiac cycle. They manifest as dramatic changes in the end diastolic (ED) and maximum volume calculated, sometimes changing as much as 40% from minimum to maximum effect. As you can see in Figure 2, there is a big different between data that has a breathing artifact and a data set that does not.

Aside from effecting the look of the loop, why are they a problem? The effect of a breathing artifact is to dramatically change your ED location, which in turn changes your stroke volume, ejection fraction, cardiac output and several other measurements. This then leaves the researcher to cope with analyzing variable data trends and then normalizing this approach between animals.

Breathing artifact vs none

Figure #2 – Comparison between a significant breathing artifact (A) and no breathing artifact (B) in a mouse model.

With the above in mind, what do we suggest?

  1. For most applications, we suggest proper ventilation of the subject – “proper” being the operative word. In many situations, the ventilator present in the lab is old, passing down from previous users. These older vents do not always have both pressure and volume control and sometimes the delivery of the air itself does not match what it states to be providing. In these cases, a breathing artifact can be artificially induced, and gasping can occur. Even with newer ventilators, air leaks, improper rates, pressure, or volume can induce the same. Therefore, the starting point is always to ensure that your equipment is operating to the manufacturing specification, that your surgical approach does not allow leaking around the mouth or trachea and that your intubation line isn’t overly long. Finally, it is also very important to check the gas mixtures themselves. It is not uncommon for a lack of O2 delivery to be the culprit – try increasing your O2 delivered if in doubt.
  2. Assuming the ventilator is working well, you will still likely see a breathing artifact in many cases, especially in rodents. In these cases, we suggest considering a side-breath or “vent off,” which transiently turns off the ventilator and stops breathing of the subject. This removes the breathing artifact in most cases and is part of our suggested data collection protocol that I will cover below.
  3. If a ventilation is not possible, or if you believe that breathing artifacts should be included into the data set, you will approach the problem using your software. Within the software platform of your choosing, you should see the option to select the average loop within a series of loops. This would then show you the average loop statistically and you can follow this same analysis trend for all cohort animals.

How to minimize electrical noise in your PV loop data

PV loop catheters have both emission and receiving electrodes and along with other factors, they are subject to collecting electric noise from the environment. Below is a list of common sources and potential solutions:

  1. 60 cycle noise. This type of noise comes form the outlets in the lab, the lights and really any other electrical device that is drawing power from the main lines. To address this, you can first try plugging the PV box into a different outlet, ideally a medical grade outlet or power conditioner. However, if the noise is coming from the environment, this will not solve your issue. In most circumstances, we would simply suggest that you apply a digital, low-pass filter with a cut off frequency around 50-60Hz. The process for doing this will different based on your data acquisition system.
  2. Noise from a secondary technology. This type of noise will typically show as a massive, high frequency noise in both the magnitude and phase signal (as well as volume) – note, the pressure signal is essentially impervious to noise unless damaged, so you should not ever see noise there. If you see noise in your volume, phase or magnitude signals, you will want to start systematically unplugging – not just turning off – different things in the lab. Most of the time however, the culprit in small animals is either the heating pad itself, or most commonly the rectal probe is not grounded. In large animal models, it usually is also the heating pad or rectal probe, less commonly it is the surgical table. These types of issues are usually resolved by grounding the responsible system correctly.

What data collection protocol do you suggest for PV loop data?

Like other questions above, this too is a bit loaded – your needs and scientific goals will be different from others. However, PV loop data collection typically has the same overall needs – collecting physiologically relevant data that is reproducible. To help streamline this in labs that we train, we suggest:

  1. For baseline data – this would be load-dependent data such has dp/dt, cardiac output, ejection fraction, stroke volume, etc. – we suggest taking 3 data collections periods of roughly 10 seconds and average them. In practice, this is frequently paired with a vent-off (covered above) but can also be done without ventilation. The goal being that you take 3 snap shots of representative data from the same animal and then average them. This averaged data would be used to compare between animals.
  2. For occlusion data – this would be load-independent data such as ESPVR, EDPVR, PRSW, etc. – you would again average 3 complete occlusion trends within the same animal and then compare the average data between animals.

Importantly, studies that look at medical devices – such as LVADs – or drug dosing protocols, may choose to analyze their data in different ways to this. Commonly, they will look at different LVAD cycle speeds or do a dosing protocol looking at 30-minutes sections of data. Most approaches are equally valid, the key being that you want to do the same thing with each subject.

As this series continues in our next installment, I will cover questions not yet tackled such as “how to optimize a catheter’s life span” and “what exactly is a baseline scan.” Please check back for more content or plan to be in touch with me through email, cole.mclarty@transonic.com. I hope that you found this blog useful, and I look forward to speaking with you again in the next one. Cheers!