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J Appl Physiol 104: 253-261, 2008. First published October 25, 2007; doi:10.1152/japplphysiol.00737.2007
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INNOVATIVE METHODOLOGY

Unrestrained video-assisted plethysmography: a noninvasive method for assessment of lung mechanical function in small animals

Jason H. T. Bates, John Thompson-Figueroa, Lennart K. A. Lundblad, and Charles G. Irvin

Vermont Lung Center, University of Vermont College of Medicine, Burlington, Vermont

Submitted 10 July 2007 ; accepted in final form 21 October 2007


   ABSTRACT
TOP
 ABSTRACT
METHODS AND RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
The assessment of lung mechanical function in small animals, particularly mice, is essential for investigations into the pathophysiology of pulmonary disease. The most accurate and specific methods for making this assessment are highly invasive and so provide data of questionable relevance to normality. By contrast, present noninvasive methods based on unrestrained plethysmography have no direct link to the mechanical properties of the lung. There is thus a need for a completely noninvasive method for determining lung mechanical function in small animals. In the present study, we demonstrate an extension of unrestrained plethysmography in which changes in lung volume are estimated via orthogonal video imaging of the thorax. These estimates are combined with the pressure swings recorded as mice breathe inside a heated and humidified chamber to yield an estimate of specific airway resistance (sRaw). We used this new technique, which we term "unrestrained video-assisted plethysmography" (UVAP), to measure sRaw in 11 BALB/c mice exposed to aerosols of saline, methacholine, and albuterol and obtained mean values of 0.71, 1.23 and 1.10 cmH2O·s, respectively. Mean breathing frequency was 4.3, 3.4, and 3.6 breaths/s, respectively, while the corresponding mean tidal volumes were 0.36, 0.44 and 0.37 ml, respectively. We conclude that UVAP, a noninvasive method, is able to provide usefully accurate estimates of sRaw and breathing pattern parameters in mice.

specific airway resistance; mice; tidal volume; breathing frequency; bronchoconstriction

THE ASSESSMENT OF LUNG mechanical function in small animals, particularly mice, is important for many investigations into the pathophysiology of pulmonary disease. Currently, the most accurate and specific method for making this assessment involves applying forced oscillations in flow to the lungs of a tracheostomized animal under anesthesia (5). This provides the mechanical input impedance of the lungs, from which parameters characterizing the conducting airways and the lung periphery can be derived (3, 10, 12, 25). However, the highly invasive nature of this approach means that it can generally only be applied during a single episode of anesthesia, after which the animals must be euthanized. Furthermore, the data it provides are not reflective of normal physiological conditions (5). As an alternative, many researchers have employed the noninvasive method of unrestrained plethysmography to measure a quantity known as the enhanced pause (Penh). However, Penh is an empirical parameter reflective of the pattern of breathing (11) and has a variable relationship to the mechanical properties of the lung (1, 21), so it cannot be taken as a reliable indicator of mechanical lung function (4). An attractive compromise between precision and noninvasiveness is the use of double-chamber plethysmography to measure transfer impedance in conscious mice (13). Even here, however, the animals must be confined inside a narrow tube so that nose and body flows can be measured separately in each of the two chambers. Such constraint could significantly affect the breathing pattern and the configuration of the airways.

We have shown previously (17) that it is possible, in principle, to estimate mechanical lung function in a completely noninvasive fashion with unrestrained plethysmography, which involves placing a conscious animal inside a closed chamber while the pressure in the chamber is measured. As the animal breathes, the chamber pressure fluctuates because the change in lung volume is not always precisely equal to the volume of air inspired from the box. This effect arises as a result of two distinct physical processes: 1) compressive changes in thoracic gas volume are produced by the respiratory musculature as it generates the pressure gradients necessary to drive gas along the resistive airways, and 2) inspired air from the chamber expands as it is heated and humidified in the lungs (1, 20). We have shown that the component of box pressure produced by gas conditioning can be eliminated by heating and humidifying the air in the box to match the conditions inside the lungs (17). The remaining swings in box pressure are then due to thoracic gas compression and so have a direct relationship to specific airway resistance (sRaw). However, these residual pressure swings are also influenced by tidal volume (VT), which can be markedly altered by interventions that affect lung function (1, 4, 17). Thus, if reliable measures of mechanical lung function are to be obtained via unrestrained plethysmography, the changes in lung volume that take place during breathing must also be measured (17).

In this paper we describe an extension of unrestrained plethysmography in which changes in lung volume are estimated via orthogonal video imaging of the thorax while mice are sealed inside a heated and humidified chamber. We demonstrate that this technique, which we term "unrestrained video-assisted plethysmography" (UVAP), permits the noninvasive estimation of sRaw.


   METHODS AND RESULTS
TOP
 ABSTRACT
 METHODS AND RESULTS
DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 
Theory.   When an animal breathes spontaneously inside a closed chamber of volume Vb, the chamber pressure relative to atmospheric pressure, Pb(t), varies according to (see APPENDIX)

Formula 1(1)
where V(t) is lung volume relative to functional residual capacity (FRC), V·(t) is flow into the lungs, Tb is chamber temperature, Sb is the vapor pressure of water in the chamber, Raw is airway resistance, and Va is the volume of the entire animal. The first term of the right-hand side of Eq. 1 accounts for the increase in volume of inspired gas due to heating and humidification in the lungs, while the second term accounts for compressive volume changes in the lungs caused by the respiratory muscles acting to drive flow along the airways (Boyle's law). When the air in the chamber is conditioned to body temperature and humidity, the first term is zero. If we further assume that V(t) is small compared with FRC, FRC is small compared with Vb, Pb(t) is small compared with atmospheric pressure, and Va is small compared with Vb, then we can integrate Eq. 1 over the duration of inspiration, TI, to obtain the approximate relationship

Formula 2(2)
where we have made the adjustment to the right-hand side suggested by Lai-Fook and Lai (15) of approximating mean lung volume as (FRC + VT/2) rather than simply FRC. Previously, we showed (17) that the left-hand side of Eq. 2 agrees well with our original formulation of the right-hand side calculated with independent measurements of Raw, FRC, and VT. Here we generalize Eq. 2 to include the integral of Pb(t) over any portion of the respiratory cycle by noting that the product of Raw and (FRC + VT/2) is the average value of specific airway resistance, sRaw, throughout inspiration. We can therefore say that

Formula 3(3)
Equation 3 embodies our new method of noninvasive lung function measurement, and shows that sRaw can be obtained by regressing the time integral of Pb(t) against V(t) and then multiplying the slope of the relationship by Vb. This could be done in a completely noninvasive fashion if we had an independent means of noninvasively measuring V(t).

Before proceeding to the practicalities of measuring V(t), however, we need to ask whether significant errors are introduced into the evaluation of sRaw as a result of the various assumptions made in reducing Eq. 1 to Eq. 3. To address this question, we performed a sensitivity analysis by calculating Pb(t) from Eq. 1 under conditions typical for a mouse. Equation 1 is quadratic in Pb(t), so to calculate Pb(t) explicitly we had to solve this quadratic and select the physically meaningful of its two roots, which is

Formula 4(4)
where

Formula 4

Formula 5(5)
We then calculated Pb(t) with Eqs. 4 and 5 by making V(t) sinusoidal with a peak-peak amplitude of 0.2 ml and a frequency of 5 Hz, which is similar to the breathing pattern of a normal mouse. The various constants in Eq. 5 were assigned values as follows. Vb was set to match the 270-ml volume of our experimental chamber (see below), and Va was set to 20 ml to represent a typical 20-g mouse. FRC was set to 0.4 ml, a typical value for a normal BALB/c mouse (17, 18). Tb and Sb were set to correspond to saturated body temperature (BTPS) conditions, as pertain inside the lungs. A typical baseline value for Raw in an anesthetized, tracheostomized 20-g mouse is 0.25 cmH2O·s·ml–1 (17, 18, 23), but this does not include the resistance of the nose and larynx. Inclusion of these additional structures would be expected to increase total Raw by severalfold (8). We therefore used a value for Raw of 1.0 cmH2O·s·ml–1 in Eq. 5, giving a value for sRaw of 0.4 cmH2O·s.

Figure 1 shows a plot of the resulting time integral of Pb(t) vs. V(t), which is very close to linear with little looping. The mean slope of this relationship, obtained by linear regression, is 0.0020 cmH2O·s·ml–1, which by Eq. 3 is equal to the ratio of sRaw to Vb. This provides a value for sRaw of 0.40 cmH2O·s, which to two significant figures is the same value as used to generate the simulated data. We would further expect the assumptions used in deriving Eq. 3 to become increasingly less important as sRaw becomes elevated above baseline, such as occurs during bronchoconstriction. The above analysis thus indicates that the various assumptions made in deriving Eq. 3 have no important effect on the estimations of sRaw it provides.


Figure 1
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  		Fig. 1. Integrated chamber pressure [Pb(t)] vs. lung volume change obtained from Eq. 2 driven by Eq. 1. When the chamber gas is properly conditioned to match body temperature and humidity, the relationship is almost linear, with minimal looping (bullet). When the chamber gas conditioning is imperfect (2°C below body temperature and 5 mmHg below fully saturated), the relationship is elliptical ({circ}).

 
To test how sensitive the estimates of sRaw are to imperfect gas conditioning within the plethysmograph chamber, we simulated Pb(t) by using Eqs. 4 and 5 with chamber temperature set to 2°C less than body temperature and chamber humidity set to 5 mmHg less than fully saturated at 35°C. The result is an elliptical plot of the integral of Pb(t) vs. volume, which in Fig. 1 gives the visual impression of having a steeper slope than the flatter one obtained under BTPS conditions. However, because of the nonuniform distribution of data points around this ellipse, the slope of the regression line through it still gives a value for sRaw that is within 1% of its correct value. These results this indicate that accurate estimation of sRaw based on Eq. 3 should be feasible even when the air in the plethysmograph chamber is not precisely conditioned to match the air inside the lungs, which might occur, for example, if body temperature were to change from normal.

Apparatus development and calibration.   We constructed a cuboidal plethysmograph chamber with two clear orthogonal sides through which the mouse can be visualized, while the remaining sides incorporate a water jacket to allow for controlled heating of the air inside the chamber (Fig. 2). A stream of air was passed over a flask of hot water and then directed into the chamber to maintain humidity. The air was shut off only during those brief periods when the chamber was sealed to make measurements. A piezoresistive pressure transducer and associated signal conditioner (ATD05 and SC-24, Scireq, Montreal, QC, Canada) monitor Pb(t), which is low-pass filtered at 30 Hz with a 6-pole Bessel filter before digitization with a 12-bit analog-digital converter. A pair of 1-megapixel black-and-white charge-coupled device video cameras (A202k, Basler Vision Technologies, Exton, PA) are mounted in orthogonal viewing positions, each directed at one of the clear sides of the plethysmograph chamber. The cameras are distanced so as to have their viewing areas completely filled by each of the 50-mm x 50-mm chamber walls, giving a linear spatial resolution at the chamber walls of ~50/1,000 = 0.05 mm. The plethysmograph and the two cameras are mounted on an optical breadboard so they can be precisely aligned with respect to each other. To provide good contrast between the video image of the mouse and the background, the outside walls of the chamber opposite each viewing wall are lined with an electroluminescent panel (Proto-Kut, BKL, King of Prussia, PA) cut to the appropriate shape and excited by a small current oscillating at 400 Hz to provide uniform illumination behind the animal. Images can be acquired continuously in 1-s epochs at 24 frames/s with an IMAQ frame grabber controlled by Labview software (National Instruments, Austin, TX). Image analysis is performed with custom software assembled with Vision Builder (National Instruments).


Figure 2
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  		Fig. 2. Schematic of the plethysmograph used to implement unrestrained video-assisted plethysmography (UVAP) in spontaneously breathing mice. A pressure transducer in the wall of the plethysmograph chamber measured Pb(t). The two video cameras measured body silhouettes from which lung volume [V(t)] was calculated.

 
The resolution limit with which this system can detect changes in thoracic volume is estimated as follows. The worst-case scenario is to consider resolving the volume change of a spherical body, because a sphere is the most efficient way of storing a given change in volume with minimal change in linear dimension. A typical mouse weighs 20 g, which gives a total body volume of 20 ml assuming a density of 1 g/ml. A sphere of 20 ml has a circular silhouette of area 891 mm2. If this sphere increases by 0.2 ml, a typical VT of a mouse, its silhouette area increases to 895 mm2, an increase of 4 mm2. Because there are 106 pixels in the entire viewing area of 50 mm x 50 mm = 2,500 mm2, 4 mm2 occupies 1,600 pixels. Any other shape of body (including that of a mouse) will give a greater number of pixels for the same change in volume. Each pixel thus represents <0.1% of the area change due to a normal tidal breath.

We calibrated the video volume estimation system by imaging the finger of a latex glove as it was inflated and deflated by 1 ml in increments of 0.2 ml. The glove finger, syringe, and all connecting tubing were filled with water, instead of air, to prevent gas compression from reducing the reference volume increments. The volume of the finger was estimated from each pair of orthogonal video images as follows. First, at each point along the long axis of the glove finger, the corresponding horizontal and vertical dimensions of the finger were multiplied together and then scaled by {pi}/4 to yield an estimate of the cross-sectional area of the finger at that point (this assumes an elliptical cross section). All such cross sections were then summed and the result multiplied by the pixel width to yield an estimate of the total finger volume. Figure 3A shows the estimated volume changes of the glove finger plotted against the volumes of water injected by the syringe. The two agree to within ~6%.


Figure 3
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  		Fig. 3. A: measured volume of a water-filled latex glove finger determined from orthogonal silhouettes under the assumption of an elliptical cross section vs. volume delivered to the finger from a calibrated syringe. Graph shows triplicate measurements made during both inflation (lines with positive slope) and deflation (lines with negative slope) of the finger. B: similar measurements made in a dead, tracheostomized, supine mouse inflated and deflated with saline in 0.05-ml steps.

 
Figure 3B shows similar measurements made in a dead mouse placed supine and inflated and deflated twice with 1.5 ml saline in 0.05-ml steps. The middle portions of the plots have slopes close to 1, indicating that the volume changes estimated by the video imaging system are close to the true volume changes. At low lung volumes the video measurements underestimate the true changes, but here the chest wall of the animal may have been slightly concave so that increases in lung volume would not have registered in the silhouettes of the thorax. However, the low end of the lung volume range shown in Fig. 3B is likely below that of a spontaneously breathing mouse, which actively maintains an elevated functional residual capacity. At the high end of the volume scale in Fig. 3B the slopes of the curves also flatten out somewhat, but again these volumes are likely significantly outside the range normally encountered in a living mouse. Thus, although we cannot be sure from this experiment, we suggest that a spontaneously breathing mouse will operate in the middle portion of the curves shown in Fig. 3B. Also, the various respiratory muscles in a conscious animal operate in a coordinated fashion during spontaneous breathing. This would further tend to maintain the thorax in a concave configuration, so changes in lung volume should be reflected in corresponding changes in vertical and horizontal silhouette areas.

We determined the phase matching between measurements of Pb(t) and the video-based calculations of changes in volume, V(t). The glove finger was inflated and deflated dynamically at a frequency of several hertz while Pb(t) and V(t) were sampled at 25 Hz. The maximum in the cross-correlation of Pb(t) and V(t) occurred at a lag of 20 ms, presumably due to the delay of the Bessel filter applied to Pb(t). This delay is about half the data sampling interval and so was ignored.

Animal validation experiments.   All animal procedures were approved by the Animal Care and Use Committee of the University of Vermont.

Eleven normal female BALB/c mice (19–21 g, 8–10 wk of age) were placed in an exposure chamber into which an aerosol of saline was directed for 1 min. The animals were then transferred to the heated (37°C) and fully humidified plethysmograph chamber. We waited for 5–10 min until the animals were sitting quietly and orientated more or less with the long axis of the chamber (i.e., the same as the long axis of the glove finger described above) before collecting data. We then recorded 12 epochs of Pb(t) and V(t), each of 1-s duration, in each mouse such that the respiratory variations in Pb(t) were clearly discernible. Next, the mice were transferred back to the exposure chamber, where they were free to move around and breathe in an aerosol of methacholine (50 mg/ml) for 1 min. They were then immediately transferred back to the UVAP chamber, and an additional 12 recordings of Pb(t) and V(t) were made. Finally, the animals were exposed to an aerosol of albuterol (5 mg/ml, Warrick Pharmaceuticals, Reno, NV) in the same way, and a further 12 recordings were made.

We also studied an additional three mice under baseline conditions as described above and then repeated the experiments 2 and 5 days later, to assess the within-animal variation in measurements over time.

Data analysis.   The data were analyzed in 1-s epochs. The calculation of mouse body volume was performed as for the glove finger described above. That is, the horizontal and vertical video images were converted into binary images with a grayscale threshold value based on the background illumination (Fig. 4). The horizontal and vertical dimensions of the images of the body were automatically determined at each point along the nose-tail axis with custom-designed software. Corresponding dimensions were then multiplied together and the result scaled by {pi}/4 to provide an elliptical cross section. Finally, the cross sections were multiplied by the pixel width to provide a slice volume, and all slices along the nose-tail axis were added together to give an estimate of V(t). This procedure was performed at each of the 25 equally spaced time points in the 1-s data epoch.


Figure 4
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  		Fig. 4. Examples of thresholded video images of a mouse inside the plethysmograph chamber viewed from the side (left) and from above (right). The dimensions of the images at corresponding axial (nose-tail) locations are used to construct an elliptical body cross section. These cross sections are integrated axially to yield an estimate of total body volume.

 
sRaw was calculated from each pair of Pb(t) and V(t) signals as follows. First, we removed any baseline trends in each Pb(t) and V(t) by fitting a straight line to each signal and then subtracting the line from the original signal. Pb(t) was then integrated with respect to t (using trapezoidal integration), and the baseline of the resulting signal was again characterized by a straight line and subtracted. Next, the processed and integrated Pb(t) was regressed against the processed V(t), and the slope of the relationship was determined. Finally, the slope was multiplied by the volume of the plethysmograph chamber (270 ml) to provide sRaw as per Eq. 3.

We also recorded the coefficient of determination (CD) of the regression between the integral of Pb(t) and V(t). CD provides a measure of the linearity of the relationship and can take a value anywhere between 0 and 1. The theory outlined above predicts that CD should have a value of 1.0. This was never actually the case, of course, because of measurement noise and other factors not taken into account by the theory. In fact, CD varied from close to zero to more than 0.9 between the different measurements, in large part because of variations in animal movement and posture during the recording of the data. Also, in ~6% of the recordings we obtained negative values for sRaw. Such values are physically meaningless and were associated in the great majority of cases with CD values well below 0.1, again likely indicating excessive animal movement. Figure 5A shows an example of good-quality data from one of the mice in which the breath-by-breath variations in both Pb(t) and V(t) are clearly defined. When these two signals are processed as described above and the time integral of Pb(t) is regressed against V(t), the result is a tight correlation with a CD value of 0.777. Figure 5B shows a poorer-quality pair of Pb(t) and V(t) signals in which the breathing variations apparent in Pb(t) are less clearly evident in V(t), probably as a result of animal movement. The data in Fig. 5, A and B, were collected in the same mouse under the same (saline exposure) conditions.


Figure 5
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  		Fig. 5. Examples of UVAP data analysis. A, left: examples of good-quality Pb and volume (V) data. Little movement artifact is apparent in V. These signals had their linear trends removed, and then Pb was integrated with respect to time and the linear trend was removed from the result. Right: trend- corrected integrated Pb regressed against trend-corrected V. The 2 signals are highly correlated, with a coefficient of determination (CD) of 0.777. B: example of a poorer-quality data set, with movement artifact and noise apparent in V, from the same mouse under the same conditions. The integral of Pb is much less well correlated with V in this case, with a CD of 0.063.

 
So that we did not have to make an arbitrary decision as to which values of CD were high enough to make their corresponding sRaw values acceptable, the final value of sRaw was calculated from the CD-weighted mean of the 12 individual measurements made for each animal under each of the three exposure conditions, using the formula

Formula 6(6)
The corresponding standard deviation (SD) for sRaw was determined as

Formula 7(7)
We used corresponding formulas to calculate CD-weighted values for VT and breathing frequency for each animal under each experimental condition. Because the individual breaths in each 1-s V(t) signal were sometimes difficult to discern, VT was calculated as the total excursion in each V(t) signal after trend removal. The individual estimates of breathing frequency were calculated from the position of the peak in the power spectrum of each Pb(t) signal [the respiratory variations in Pb(t) were invariably clearer and less corrupted by animal movement than were those in V(t), as is evident in Fig. 5].

We used unpaired t-tests to compare mean values of sRaw, VT, and breathing frequency obtained with Eq. 6 after exposure to methacholine or albuterol to those obtained after exposure to saline.

The means and standard errors of sRaw for all 11 animals studied after exposure to saline, methacholine, and albuterol are shown in Fig. 6. Also shown in Fig. 6 are the corresponding values of VT and breathing frequency. The individual values of sRaw and their SDs for each mouse, calculated with Eqs. 6 and 7, respectively, are listed in Table 1. The coefficients of variation of sRaw for the saline, methacholine, and albuterol exposures are 68%, 41%, and 62%, respectively. The coefficients of variation of sRaw for the three mice in which longitudinal measurements were made on three different days were similar at 49 ± 15% (mean ± SD). Thus the within-animal variation in the UVAP measurement of sRaw is similar to the between-animal variation, indicating that most of the variation in the measurements is methodological rather than biological.


Figure 6
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  		Fig. 6. Estimates of breathing pattern parameters [tidal volume (top) and frequency (middle)] and specific airway resistance (sRaw; bottom) obtained with UVAP in 11 mice after exposure to aerosols of saline, methacholine, and albuterol. *Significant difference from saline value (paired t-test, P < 0.05).

 

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  		Table 1. Individual values of sRaw for each of the animals averaged in Fig. 6

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS AND RESULTS
 DISCUSSION
APPENDIX
 GRANTS
 REFERENCES
 
There is currently a pressing need for a truly noninvasive method for assessing lung function in mice, for example, when large numbers of animals must be screened or when destructive testing of valuable transgenic mice is unacceptable. The purpose of the present study was to develop such a method by extending unrestrained plethysmography through the simultaneous measurement of changes in lung volume. From a theoretical point of view, the various approximations made in deriving the equation for the method (Eq. 3) do not pose any significant limitations on its potential accuracy (Fig. 1). From a practical point of the view, the crux of our new method, UVAP, is to complement the measurement of Pb(t) with the simultaneous measurement of V(t) by using a pair of orthogonal video cameras. Our approach assumes that we can get sufficiently accurate estimates of changes in lung volume from pairs of orthogonal silhouettes by assuming an elliptical body cross section. While this is certainly defendable in the case of a glove finger (Fig. 3A), it may be less so in the case of the irregularities in thoracic shape of a spontaneously breathing mouse. Nevertheless, we were able to obtain good estimates of changes in lung volume throughout the middle range of volumes in a dead mouse, which is irregularly shaped and covered in fur (Fig. 3B). Thus, provided the chest wall remains reasonably convex, its volume changes should be reflected with sufficient accuracy by the changes in area of its vertical and horizontal silhouettes.

In principle, we would obtain better volume estimates by using multiple cameras to obtain more than two silhouettes, because this would allow us to characterize the body as a more irregular object. An alternative approach would be to place markers on the thorax and use multiple cameras to track them in three dimensions. Saumarez (22) employed this approach in humans by illuminating the thorax with planes of light. Optoelectronic plethysmography (2) achieves the same end by tracking multiple markers attached to the thorax. These systems, while no doubt more accurate than the biplanar approach we used, are considerably more complicated to implement and would probably be difficult to scale down to the size of a mouse. We therefore decided to settle for reduced accuracy in return for greater practicability. Of course, one might ask why not make the system even simpler and use only a single silhouette? Indeed, Lai-Fook et al. (14) estimated lung volume from a single planar image obtained by X-raying the thorax. This has the advantage, compared with our video method, of allowing one to define the borders of the lung independently of the rest of the thorax, which would compensate at least in part for the measurement of only a single degree of freedom in thoracic movement. However, X-ray imaging also has significant practical disadvantages compared with the video-based procedure we employed in the present study. In particular, the X-ray system used by Lai-Fook et al. (14) was not able to collect images rapidly throughout a single breath, and the segmentation of the lung from the chest wall in each image had to be done manually by tracing the lung border. Their system therefore would be extremely difficult to automate and does not lend itself to routine laboratory use.

Another factor that likely impinges on the accuracy of our volume estimates is the orientation of the animal in the chamber. We attempted to collect data only when the mouse was sitting facing along the long axis of the chamber, as in Fig. 4, but this condition was never perfectly met. It is possible that better accuracy would be obtained if the animals were corralled so as to face in this direction, but this begins to get away from the condition of complete lack of constraint that we wanted to achieve. The fur of the mouse might also add an element of variability, although the animals became quite wet when they were exposed to aerosols for airway challenge, which caused their fur to become matted down.

In any case, the key question that arises is whether our video volume estimation system has the necessary accuracy and sensitivity to provide useful physiological measurements in mice. Of course, given the noninvasive nature of UVAP, we do not expect the estimates of sRaw it provides to be as accurate as those provided by a highly invasive method (5). Nevertheless, UVAP must still estimate changes in sRaw to a useful degree of accuracy, and this translates essentially into the question of how accurately the two orthogonal video cameras can estimate V(t) (Fig. 2). In the case of the glove finger, which had a smooth surface and a cross section that was close to elliptical, we obtained accurate estimates of changes in volume (Fig. 3). We would expect somewhat less accurate estimates for an irregularly shaped object such as a mouse thorax. The fundamental problem we face in validating our volume estimates, however, is that there is no good way to accurately and independently measure V(t) in conscious and unrestrained mice, so we have no good basis for comparison. Of course, we can ask whether the estimates are physiologically reasonable. Our mean value for VT of 0.38 (Fig. 6) ml is somewhat higher than the value of 0.28 ml reported for awake mice by Vinegar et al. (24), but this may have been due to an increased minute ventilation induced by our animals being in a warm and humid environment. Also, the values of VT that we report here were determined by the peak-to-peak excursions in 1-s volume records that typically contained 4 or 5 individual breaths (see Fig. 5). Although we removed the linear trends from these records before determining VT in this way, variations in the mean volume of each breath could have resulted in the peak-to-peak variation in the volume records being significantly larger than the mean VT for each breath.

This brings up another of the vagaries of working with conscious animals. We ostensibly exposed each animal to the same dose of methacholine and albuterol by placing them in a chamber containing a known aerosol concentration of either drug. However, we relied on the animals to control the exposure through their own choice of breathing pattern, which was significantly affected by the exposures they received (Fig. 6). We thus cannot be sure that different animals did not receive different exposures to the lungs by adopting different breathing strategies. Nor do we have any idea how much of the drugs they actually received, unlike the situation in mechanically ventilated animals, when we are in complete control of how much aerosol actually reaches the lungs. In the conscious mice of the present study we also do not know how much of the inhaled methacholine may have been deposited in the nose without ever reaching the lungs. Deposition in the nose may also explain why we only found a doubling in sRaw even though the concentration of methacholine we used (50 mg/ml) was high compared with those we have used in the past in tracheostomized, ventilated animals (3, 25). The situation is not entirely clear in this regard, however, because it has been reported in guinea pigs (9) that smooth muscle agonists and relaxants have much less effect on nasal resistance than on pulmonary resistance, whereas in rats methacholine has been shown to affect both upper and lower airway resistances (8).

This uncertainty carries over to the estimation of sRaw itself, where again we must resort to considerations of physiological reasonableness in the absence of independent measurements against which to validate our measurements. Nevertheless, the results from a recent study using restrained plethysmography in mice provide a convenient basis for comparison. Lofgren et al. (16) restrained conscious animals so that respiratory flow could be measured independently of chamber pressure and found a baseline value for sRaw in BALB/c mice of 0.63 (SE 0.05) cmH2O·s. This value is encompassed by the range defined by the SE for sRaw (0.71 ± 0.15 cmH2O·s) that we found in the present study (Fig. 6). Lofgren et al. (16) also exposed their mice to aerosols of methacholine and found increased value of sRaw (up to ~2.5 cmH2O·s) that were substantially greater than those we found in the present study (Fig. 6). However, this could easily be explained by the fact that they measured the response to methacholine much sooner after exposure than we did, because our animals had to be transferred from the exposure chamber back to the plethysmograph before measurement.

To convert our UVAP measurements of sRaw into Raw itself, we have to multiply the former by mean lung volume. We will assume this volume to be 0.4 ml based on our previous measurements of FRC in BALB/c mice at a lung inflation pressure of 3 cmH2O (7, 17, 18). This gives a mean value for Raw in our mice under baseline (saline exposure) conditions of 1.78 cmH2O·s·ml–1. We previously measured Raw with the forced oscillation and alveolar capsule techniques in anesthetized, paralyzed, tracheostomized mice and found it to be in the range 0.25–0.30 cmH2O·s·ml–1 when the lungs are ventilated against a positive end-expiratory pressure of 3 cmH2O. However, these previous measurements of Raw correspond to only the resistance of the airway tree beginning at a point just above the main carina, distal to the end of the tracheal cannula connecting the lungs to a mechanical ventilator. The value of Raw calculated for the conscious mice of the present study includes the resistances of most of the trachea, the larynx, the pharynx, and the nose. Furthermore, we do not know what mean lung volumes the animals were breathing at, making comparison to the invasive measurements of Raw even more problematic. Nevertheless, spontaneously breathing anesthetized rats have been shown to have an upper airway resistance about fourfold that of the lower airways (8). Furthermore, conscious mice maintain FRC dynamically, possibly through the use of laryngeal braking during expiration (24), which would further increase airway resistance proximal to the trachea. Our estimate of 1.78 cmH2O·s·ml–1 for total Raw in conscious mice, being six- to sevenfold greater than the values found in tracheally cannulated animals, is thus physiologically perfectly reasonable. It is also very close to the value of 1.9 cmH2O·s·ml–1 predicted by Lai-Fook and Lai (15) for conscious mice based on their measurements of variations in Pb(t) corrected for gas conditioning effects. These investigators attempted to estimate Raw by measuring Pb(t) both at room temperature and at body temperature and then eliminating the contribution to Pb(t) from gas conditioning. When they used X-ray images of the thorax to estimate lung volume (14), they obtained a mean value for Raw in unconstricted mice of 2.0 cmH2O·s·ml–1, which is comparable to that which we estimated above. They also obtained a mean value for VT of 0.33 ml, which again is comparable to our estimates (Fig. 6).

We found that the slope and CD of the relationship between integrated Pb(t) and V(t) (Fig. 5) was quite variable from one measurement to the next under identical experimental conditions, even thought we tried to record the signals only when the mice were relatively still. This reflects a fundamental problem of working with conscious mice: the breathing pattern, and indeed behavior in general, are not controlled. Also, although we only made UVAP measurements of sRaw when the animals appeared to be sitting quietly in the chamber, we were not able to ensure that they assumed either the same orientation with respect to the chamber axes or the same posture from one measurement to the next. These factors are likely to be significant sources of variability and necessitate the averaging of multiple measurements to reduce the effects of noise. In the present study, we averaged 12 measurements per animal per experimental condition and further employed the strategy of weighting the different measurements according to the level of correlation between the time integral of Pb(t) and V(t) (Fig. 5). This allowed us to detect a statistically significant near-doubling of sRaw after methacholine exposure and its subsequent reversal toward baseline with albuterol (Fig. 6). Even greater discriminatory power in sRaw would be obtained by averaging a larger number of individual measurements per study condition. This would, of course, increase the experimental time commensurately. On the other hand, once a mouse is established inside the UVAP chamber, multiple 1-s measurements of Pb(t) and V(t) can be made in a relatively short time. A probably more significant time limitation on UVAP is how long it takes for an animal to settle down and stop moving about inside the chamber before signal recording can begin. The mice used in the present experiments were naive to the procedure, and we let them acclimatize to the chamber under each exposure condition for 5–10 min before making 12 acceptable measurements, which took up to an additional 5 min, but this might improve with training because mice will become acclimatized to being in confined spaces (13). One of the potential advantages of UVAP over more invasive methods for assessing lung function is that it can be used repeatedly to follow changes in sRaw in individual animals over long periods of time. Repeat measurements made, for example, each day might lead to the animals becoming more comfortable with the procedure, thereby allowing UVAP to proceed more quickly each time it is employed.

In conclusion, we have developed an extension of unrestrained plethysmography, UVAP, that combines measurements of Pb(t) with orthogonal video measurements of V(t) to provide a measure of sRaw in mice. These values of sRaw are somewhat variable, principally because of the noise introduced by animal movement, so it is necessary to average multiple measurements obtained under each set of experimental conditions. Collection of Pb(t) and V(t) signals must also be limited to periods during which the animal is resting quietly inside the plethysmograph chamber. Despite these limitations, however, UVAP has the advantage of being solidly grounded in the first-principles theory of lung mechanics, in marked contradistinction to the quantity known as Penh, which is still widely and inappropriately used (19, 20). We have also shown that the values of sRaw provided by UVAP in normal mice under baseline conditions, after challenge with a smooth muscle agonist, and again after administration of a smooth muscle relaxant are physiologically reasonable in terms of both their relative and absolute magnitudes. The goal of the present study was to establish proof of concept for the UVAP method. A significant amount of engineering development work remains to be done if it is to serve as a practical laboratory tool. Nevertheless, we conclude that UVAP has the potential to serve as a truly noninvasive method for assessing lung mechanical function in conscious mice. We suggest that UVAP may have particular application in situations requiring repeated screening of valuable animal models of lung disease. Finally, although we have focused on the application of UVAP to mice, in principle it can be used in larger animals and humans. Indeed, scaling the technique up in size may reduce some of the technical problems associated with accurately determining lung volume from video silhouettes. In particular, UVAP may be particularly suited to studying lung function in human infants in whom the application of conventional lung function methods is problematic.


   APPENDIX
TOP
 ABSTRACT
 METHODS AND RESULTS
 DISCUSSION
 APPENDIX
GRANTS
 REFERENCES
 
We consider an animal breathing spontaneously inside a closed chamber of volume Vb (17). Let a volume V(t) of gas be inspired into the lungs, starting from FRC. The inspired gas becomes saturated with water vapor (vapor pressure Sb) and is heated to body temperature (Tb in °C), causing the inspired V(t) to increase in volume by an amount

Formula A1(A1)
where 47 is the vapor pressure (in mmHg) of water in saturated air at body temperature and 760 is atmospheric pressure. When gas flow [V·(t)] is nonzero, lung gas volume [VA(t)] is further changed as it is compressed and decompressed in response to changes in alveolar pressure according to Boyle's law. The alveolar pressure [PA(t)] is

Formula A2(A2)
Therefore, the volume of gas in the lungs that occurs with both gas conditioning and compression is

Formula A3(A3)
By contrast, if neither gas conditioning nor compression takes place, then the lung volume would simply be [FRC + V(t)]. Thus the amount by which the gas inside the box, but outside the animal, becomes compressed is equal to the difference between Eq. A3 and [FRC + V(t)]. This difference is

Formula A4(A4)
The volume of gas in the box around the animal, before compression or decompression of thoracic gas, is Vb – Va – FRC – V(t), where Va is the volume of the animal's body excluding the volume of gas in the lungs. This volume of gas becomes compressed by the amount given in Eq. A4, so invoking Boyle's law we arrive at the expression for Pb(t) given by Eq. 1.


   GRANTS
TOP
 ABSTRACT
 METHODS AND RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
REFERENCES
 
The authors acknowledge the financial support of National Institutes of Health grants NCRR-P20-RR-15557 and R01-HL-62743.


   FOOTNOTES
 

Address for reprint requests and other correspondence: J. H. T. Bates, 149 Beaumont Ave., Burlington, VT 05405-0075 (e-mail: jason.h.bates{at}uvm.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 METHODS AND RESULTS
 DISCUSSION
 APPENDIX
 GRANTS
 REFERENCES
 

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