JOURNALOF
Vol. 39, No.
APPLIED PHYSIOLOGY 2, August 1975. Printed
A modified
in U.S.A.
measurement
forced oscillation
during normal
D. C. STiiNESCU, Cardiopulmonary
of respiratory
R. FESLER,
Laboratory,
Universite’
breathing
C. VERITER, Catholipe
A. FRANS,
de Louvain,
ST~NESCU, D. C., R. FESLER, C. VERITER, A. FRANS, AND L. BRASSEUR. A modzj?ed measurement of respiratory resistance by forced oscillation during normal breathing. J. Appl. Physiol. 39(2) : 305-3 11. 1975.-We have modified the measurement of the resistance of the respiratory system, Rrs, by the forced oscillation technique and we have developed equipment to automatically compute Rrs. Flow rate and mouth pressure are treated by selective averaging filters that remove the interference of the subject’s respiratory flow on the imposed oscillations. The filtered mean Rrs represents a weighted ensemble average computed over both inspiration and expiration. This method avoids aberrant Rrs values, decreases the variability, and yields an unbiased mean Rrs. Rrs may be measured during slow or rapid spontaneous breathing, in normals and in obstructive patients, over a range of 3-9 Hz. A good reproducibility of Rrs at several days’ interval was demonstrated. Frequency dependence of Rrs was found in patients with obstructive lung disease but not in healthy nonsmokers. lung
mechanics;
chronic
obstructive
lung
resistance by
Cliniques
AND
L. BRASSEUR
Universitaires
St. Pierre,
Louvain,
Belgium
chronic obstructive lung disease than in normal subjects, at a low (3 Hz) than at a high frequency (9 Hz) of forced oscillations, and when rate of breathing was increased. Important changes of Rrs, from one oscillation to another, are recorded (during expiration and inspiration also) and selection of a given Rrs value becomes an arbitrary matter. The high variability was not the only problem encountered. Obvious spurious values of Rrs (either infinite or negative) were frequently observed in the circumstances quoted above. An increased variability of Rrs and aberrant Rrs values (at 3 Hz) were observed by Hyatt et al. (10) also (see Fig. 6 in (10)). To obtain accurate data of Rrs, these authors recommended that the breathing rate of subjects should be slow. A decrease in the breathing rate is however not always easy to impose and a method of measuring Rrs in the absence of any restriction upon the pattern and breathing rate would be suitable. Goldman et al. (7) had also observed marked changes in Rrs, mainly during expiration and less frequently during inspiration. They also noted that “aberrant breaths should not be measured.” These authors attributed the artifacts to transient changes in the upper airway resistance. In an earlier study we examined the glottis orifice during quiet breathing (17) and changes in the size of the glottis aperture were indeed present, but not of sufficient magnitude to explain the important changes in Rrs. Obviously this was a qualitative observation and changes in the pharynx and larynx may also be involved. However, we do not believe that upper airways changes are the main factor explaining the marked variability of the flow resistance measured with the forced oscillation technique. We attribute the increased variability of Rrs to a distortion of the imposed oscillatory flow by the subject’s flow rate. This became critical when respiratory flow is changing rapidly and at an increased rate of breathing. Hyatt et al. (10) also suggested that harmonics of nonnegligible amplitude in the subject’s flow pattern may interfere with the applied oscillatory flow. We thought therefore that measurement of Rrs from the imposed oscillations in the absence of interference with the respiratory flow of the subject will improve the accuracy of the measurement of Rrs and decrease its variability. This was achieved by average filtering of both flow rate and oral pressure signals. In this communication we describe the equipment used to measure Rrs and we present comparative data of the variability of filtered and unfiltered Rrs (i.e., with the method of Hyatt et al. (10)). We also present data on the reproducibility of Rrs and measurements of Rrs at different frequencies of the imposed oscillation, in normal subjects and patients with chronic obstructive lung disease.
disease
DUBOIS AND HIS COLLEAGUES (2) were the first to estimate the resistance of the respiratory system, Rrs, with the method of forced oscillation. Several modifications of the original technique have been subsequently reported (5, 7, 8, 15). The advantage of this technique is that it does not require a body plethysmograph or swallowing of an esophageal balloon and little cooperation of the subject is asked. Fisher et al. (5) have measured Rrs at end expiration during prolonged apnea. Previously, Mead (11) had demonstrated that Rrs could also be measured during normal breathing. More recently, Goldman et al. (7) h ave described a simplified method for computing Rrs during spontaneous breathing. Assuming a linear behavior of the respiratory system, these authors showed that Rrs can be measured by relating flow rate, at points of zero volume acceleration, to the corresponding oral pressure changes. At these instants, inertial impedance is zero and since points of zero volume acceleration occur at the same volume, there are no pressure differences related to elastic impedance either. Therefore, the pressure difference between two successive instants of zero volume acceleration must be determined only by the flow resistance of the respiratory system. Rrs is computed by relating the changes in pressure between these two points to the amplitude of the flow rate. The authors also showed that principles underlying their method are valid during a constant respiratory flow rate, but also when flow is changing from breath to breath. Using this approach, Hyatt et al. (10) have developed equipment which automatically computes Rrs. Initially, we duplicated the equipment of Hyatt et al. (10) and we intended to use it for routine purposes. However, soon after its introduction we were disappointed by the marked intraindividual variability of Rrs. The variability was higher in patients with
EQUIPMENT
AND
METHODS
Since at first we used the method of Hyatt et al. (10) for measuring Rrs, the apparatus we built for inducing oscillation had several features in common with that described by these authors. Oscillating airflows were applied at the mouth using a 15-in loudspeaker (Lansing Sound Inc.) driven by a sine-wave function generator (Philips model PM 5160) and power amplifier (Philips model PM 5 175). The loudspeaker was mounted in an enclosure 305
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STANESCU
306
9
”
+
COMB FILTER
..
’ 6
DERIVATIVE CIRCUIT
-
SAMPLE and HOLD (max VI
>
OPERATIONAL AMPLIFIER X1
r
v
, -
.I
*
SAMPLE and HOLD (mln 91
4>.
ZERO COMPARATOR
*
1 SUMMATION CIRCUIT
+
w
START
SUBTRACTION
1 -
CIRCUIT
, t
4) -.
t-
AL.
rate is differentiated and instants of zero volume acceleration identified by a zero comparator circuit. At each instant of zero volume acceleration two pulses are generated which sample and hold simultaneous values of 7j’, and PaoF. The difference between two successive values of PaoF (corresponding to maximal and minimal flow) provided by a subtraction circuit, defines APaoF. Similarly A%$ is provided by another subtraction circuit. A division circuit computes Rrs as APao,/AX$ ratio. This value is displayed on a front-panel digital voltmeter and an analog output is provided for recording. Two resistance values are computed for each cycle of the applied oscillations, that is, at an imposed frequency of 3 Hz, six values of Rrs are generated each second. A separate circuit computes the mean value of Rrs from 100 successive individual data. In fact it is a summation circuit, the mean value being obtained by moving the decimal point two places to the left. This mean Rrs is also recorded on a digital display. A push button starts the measurement of the mean Rrs. For convenience, the displayed Rrs is in actual units (cmHzO/l per s). The output of the carrier amplifiers was calibrated in such a way that a given pressure and flow rate unit correspond to a given voltage. For routine puposes we calibrated the equipment with a resistor constructed from a bundle of fine capillary tubes fixed together. The measurement of Rrs is done with the subject in a seated position, the cheeks being pressed by the subject’s hands. The person is asked to breathe as usual. We allow about l-2 min before starting the measurement of Rrs. Subjects become accustomed to the equipment and they reach a steady-state breathing pattern during this period. Three to four mean values of Rrs are usually recorded at a frequency of 3, 6, and 9 Hz. Afterward the subject performs a maximal inspiration to define the functional residual capacity with respect to total lung capacity. To validate our system we measured the Rrs of three known linear resistors (with a resistance of 1.6, 6.4, and 11.9 cmH20/1 per s, respectively) at different flow rates, between 3 and 9 Hz. An accurate measurement of the resistance was obtained and, as expected, no change in the resistance at different frequencies was observed. The accuracy of the division circuit in computing Rrs was tested by measuring a known added resistance. Thereafter, the gain of the amplifiers (of the flow or pressure signals) was changed. We found an excellent agreement between the new computed Rrs and its predicted value. Previously with the method of Hyatt et al. (10) we found intra-
made of 0.5in Plexiglas (15.5 x 15.5 x 7 in). The subject breathed into an 1 l-in length of tubing (ID 1 in) connecting the mouthpiece to the Plexiglas enclosure. Airflow was measured by a Fleisch no. 3 pneumotachograph and a Statham (PM 15) differential transducer. Mouth pressure with respect to atmosphere was measured by another differential pressure transducer (Sanborn, model 270). Both signals were amplified (Hewlett-Packard 8805 B carrier amplifiers). Three tubes in series (15 in long, 2.3 in ID; 24 in, 1.6 in; 34 in, 1.2 in) connected the Plexiglas enclosure to atmosphere. This tubing provided a low impedance to the subject’s breathing and a relatively high one to the forcing oscillations. To prevent accumulation of carbon dioxide in the system, a constant bias flow (0.3 l/s) entered through the impedance tubing and was pulled through a lateral opening in the respiratory tubing. The block diagram of the electrical network to compute Rrs is shown in Fig. 1. To avoid noise the amplified flow and pressure signals are passed through two low-pass filters (first order, cutoff frequency at - 3 dB 16 Hz). The filtered signals are afterwards treated by two comb filters (14). We chose this type of filter since it has a narrow bandwidth at low frequencies and the bandwidth is easily adjustable. The filter has also an unusually high Q at very low frequencies and the Q is substantially less sensitive to changes in filter element values, in contrast to large variations in the Q of active filters. The diagram of the comb filter is presented in Fig. 2 and a more detailed description of its operation is given in the APPENDIX. However some information has to be given now. First, the filter introduces a lag between the input and the output signals. To avoid phase shifts between flow rate and oral pressure, both signals were passed through two identical comb filters. The lag is due to the time constant of the filter. We used in our measurements a time constant of about 1 s. The predicted bandwidth of the filter, for this time constant, is 0.4 Hz at - 3dB. This bandwidth is narrow enough to remove the fundamental and harmonics of important amplitude of the subject’s breathing. Second, the output signal represents weighted ensemble averages of previous successive input signals. Rapid variations in the amplitude of the input signals are in this way leveled out. We will refer to these PaoF). Output for recording is output signals as filtered (%$; provided for these as well as for unfiltered v and Pao signals. 0, and PaoF are thereafter amplified by a factor of 4. This makes detection of zero volume acceleration instants more accurate and improves the operation of the division circuit (see below). Flow
-
ET
SAMPLE HOLD Pa0
and
To rtcordtr
A
SUBTRACTION
Pa0 to
f Pa0
t recorder
FIG.
1. Block
to
diagram
of the electrical
rtcordtr
network
for computing
respiratory
resistance,
Rrs.
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RESPIRATORY
RESISTANCE
307 415v
from GENERATOR
SN 7442 N
BAX16 2N3703
r
Pa0 from
high pass filters
2. Electrical
FIG.
to low pass f i kers
diagram
of the
comb
filter.
High-pass
filters
(left
side
of diagram)
and
low-pass
filters
(right
side)
are
components of
comb filter. individual
coefficients
of variation
of Rrs
(the
standard
deviation
of the Rrs
was tested
at 3 days’
interval
(at the same
hour
in the
divided by the mean, expressed in percentage) during quiet breathing, ranging from 40 to 1ZOO/& The present method of
morning) in 9 of the 12 healthy subjects. Rrs averaged 1.98 =t 0.43 cmHzO/l per s the 1st day and 2.04 rt 0.50 cmHaO/l per s
measuring
3 days
Rrs
drastically
reduced
the
variability
of this
index.
later.
The
difference
is statistically
not
significant
as as-
To illustrate this improvement we compared the variability of Rrs with the two methods in one normal subject (Fig. 3) and in two patients with chronic obstructive lung diseases. The oscillographic tracing in one of these patients is shown in Fig. 4. Flow rate (filtered and unfiltered), mouth pressure (filtered and unfiltered), and filtered Rrs were simultaneously recorded versus time (Brush model 480 recorder). Unfiltered Rrs was computed by hand from the recorder tracing, by locating instances of zero volume acceleration and by dividing APao by AV. The manual
sessed by the paired t-test. Rate and pattern of breathing were chosen freely by the subjects each time. In patients there was a decrease of the average Rrs at 9 Hz (6.6 ZJZ3.0 cmHzO/l per s) with respect to the value at 3 Hz (7.8 & 3.8 cmHzO/l per s). The decrease is statistically significant (P < 0.05). However, 5 of the 15 patients had similar Rrs values at 3 and 9 Hz (Table 2). The average intraindividual coefficient of variation of Rrs for all patients was 9.1 * 3.6y0. The coefficient of variation was somewhat smaller in obstructive patients than in
method
healthy
of computation
of Rrs
is less accurate
than
the
electrical
one, but no systematic error is introduced. To mord. both filtered and unfiltered Rrs simultaneously we should have duplicated most
of the electrical
circuits
of our equipment.
The
coefficient
of
variation was calculated from 140 consecutive individual Rrs. Filtered Rr was measured in 12 healthy nonsmoking subjects (mean
age 34.0
=t: 6.6 yr)
and
in
15 patients
(mean
age 51.4
rt=
19.7 yr) with chronic obstructive lung diseases (avg FE&, o/VC ratio 50.9 & 8.9aj0) at a frequency of the imposed oscillations of 3 and 9 Hz. RESULTS
Mean Rrs in 12 normal subjects at 3 Hz was 2.2 =t 0.5 cmHzO/l per s. It averaged 2.2 of= 0.5 cmHsO/l per s at 9 Hz (Table 1). In 10 of the above mentioned subjects the intraindividual coefficient of variation ranged between 5.9 and 24y0 (mean 12.0 &Z 6.1 yO). In two other subjects however, the coefficient of variation was much higher (38 and 41 y0 respectively). The reproducibility
persons
since
average
Rrs was higher
in the former
group.
In seven patients Rrs was measured at two flow rates of the imposed oscillation (at a frequency of 6 Hz). The Rrs at an average amplitude
of the flow
oscillations
of 0.15
& 0.03
l/s was 7.1 of= 1.6
cmH20/1 per s, whereas it averaged 6.9 =f= 1.4 cmH20/1 per s at a flow rate of 0.3 of= 0.08 l/s. The difference in Rrs was statistically not significant (paired t-test). In a normal subject, unfiltered Rrs was 2.9 & 1.2 cmH20/1 per s (coefficient of variation 42.0y0) while the filtered Rrs averaged 2.5 -4 0.4 (coefficient of variation 16.Ooj,) (Fig. 3). In two obstructive patients unfiltered resistance averaged 7.9 & 7.8 and 30.6 & 24.6 cmH20/1 per s. The corresponding coefficients of variation were 99.0 and 80.3oj,, respectively. Filtered Rrs was 5.0 k 0.3 (coefficient of variation 6.0%) and 14.1 =t 1.5 cmHQO/l per s (coefficient of variation 10.9 %), respectively. Aberrant Rrs values were not’ included in the calculation of the coefficient of variation. No aberrant Rrs were observed with the present method
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STANESCU
ET
AL.
1. Physical data and Rrs at 3 and 9 Hz in normal subjects
TABLE
UNFILTERED
Mean
Subj
Age, yl
VH vc SC DD CJ HL HE FP FA DP VR BT
33 32 43 33 43 43 35 28 38 26 25 28
f
SD
34 f
Ht,
cm
182 184 167 181 172 181 178 171 176 176 170 183 6.6
Wrs)
3Hz
9Hz
3.1 2.1 2.7 2.2 1.9 1.4 2.2 1.8 2.2 2.3 2.9 1.5
3.1 2.0 2.8 2.0 1.8 1.3 2.5 1.8 2.1 2.5 2.9 1.8
177 rt 6
2.2
i
0.5
2.2
f
0.5
FILTERED
TABLE 2. Physical data, FEVJVC ratio and R(rs) at 3 and 9 Hz in patients with chronic obstructive lung disease UNFILTERED
RI PV DV CA GM CK GE JA AM MF MM FL LJ CL ME
FILTERED
UNFILTERED
Rh) cm H,O/L
Sex
Patient
Pa0 cm Hz0
/set
M M M F M F M M M M F F M F M
Age, yr
25 61 46 62 72 10 76 50 69 50 21 48 61 48 72
Ht,
cm
180 185 158 166 164 122 166 156 175 162 170 153 167 155 167
FEVI o/VC %
53 37 49 56 44 48 44 55 56 33 69 59 55 55 53
3Hz
RW
9Hz
7.0 4.0 7.0 4.6 8.0 17.0 3.2 12.5 4.0 12.0 7.6 5.7 10.0 9.1 5.6
4.0 3.2 6.3 4.4 6.0 11.0 2.7 10.4 4.2 13.0 7.6 5.4 8.1 8.2 4.9
7.8f3.8
6.6f3.0
FILTERED
Mean
f
SD
51f20
163f14
51f9
EXP.
DISCUSSION UNFILTERED
9 L/seC
FILTERED
UNFILTERED
Pa0 cm Hz0 FILTERED
-.0.5
I 0.: P FIG. 3. Recorder tracing from a normal subject. From top to bottom, unfiltered and filtered Rrs, flow rate, and mouth pressure, respectively. Unfiltered Rrs was calculated by hand (see text) and was drawn on the record. Note that filtered signals are delayed with respect to unfiltered ones. FI(?. 4. Recorder tracing from a patient with severe airway obstruction and obesity. Legend is the same as in Fig. 3. Black circles on tracing of unfiltered Rrs identify spurious values of respiratory resistance.
The purpose of the present modification of the measurement of Rrs by the forced oscillation technique was to separate the useful oscillatory flow, from what we considered signal, i.e., imposed breathing flow, in other words to improve “noise,” i.e., subject’s the signal-to-noise ratio. This was achieved by filtering both flow and pressure signals. In this way the influence of the subject’s respiratory flow and pressure on the imposed oscillations is removed. This modified technique represents an improvement over former methods. Measurements of Rrs can be done during spontaneous breathing,’ no restriction being imposed on the pattern or the rate of breathing of subjects. Accurate measurement of Rrs is provided over a range of frequency from 3 to 9 Hz, both in normal and in obstructive patients. Comparative measurements of Rrs with the method of Hyatt et al. (10) and this technique showed a striking decrease of the variability of Rrs with the latter method. i This method may also be used to measure Rrs during panting. However the equipment has to be modified and a loudspeaker box (8) instead of a small Plexiglas enclosure must be used to avoid loading of the loudspeaker during panting. With our equipment, the loudspeaker was displaced by the subject’s flow during panting. This resulted in a distortion of the imposed flow and pressure signals which were no longer sinusoidal.
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RESPIRATORY
309
RESISTANCE
Two factors may account for the variability of Rrs: actual changes in the caliber of upper (or lower) airways during breathing, or methodological factors. One has to distinguish, however, between the regular phasic changes in Rrs during inspiration and expiration (see Fig. 7A) and the irregular chaotic tracing, with tremendous changes in Rrs from one moment to another (Fig. 4) : both patterns would result in an increased variability of Rrs. We suggest that the first pattern reflects phasic changes in the upper airways while the latter is methodological in nature. Indeed a “chaotic” irregular record is observed whenever breathing rate is increased, frequency of the imposed oscillations is low (3 Hz), and flow resistance is high. Under these conditions oscillatory flow is distorted by the respiratory flow since frequency of breathing comes nearer to the frequency of oscillations and a low amplitude of the oscillatory flow (high resistance) renders detection of zero volume acceleration points inaccurate. One may wonder why particularly in these conditions upper airway changes intervene to disturb Rrs and not when rate of breathing is slow and oscillatory frequency is high (9 Hz). From the practical point of view, under these unfavorable conditions, important moment-tomoment changes of the unfiltered Rrs and spurious values are observed and selection of a “good” Rrs value becomes an arbitrary matter. Filtering avoids distortion of the oscillatory flow and reduces variability of respiratory resistance. It must be appreciated, however, that the decreased variability of Rrs is also due to the filtering process itself: each measured Rrs value is a weighted value of an ensemble of previous resistances. Rapid fluctuations in Rrs are in this way leveled out. The reported variability of the filtered Rrs does not reflect the actual variability of respiratory resistance but tends to underestimate it. To illustrate this, an “artificially” induced decrease in the yariability of Rrs is shown in Fig. 5 (the time constant of the filters was increased from 1 to 5 s).
Important phasic variations of filtered Rrs were observed in 2 of 12 healthy subjects during quiet breathing. This resulted in a much higher intraindividual coefficient of variation than in the rest. Rate of breathing and respiratory flow rate were comparable among subjects. The pattern of the fluctuations of Rrs during quiet breathing in these two subjects was reproducible over several months (Fig. 6), suggesting the intervention of a systematic factor. We instructed one of these subjects to breathe very shallowly and moderately fast (rate of breathing about 7O/min). Every time this was done fluctuations of filtered Rrs were drastically reduced (Fig. 78) and the coefficient of variation decreased from 37.3 to 9.1%. Contrasting with the behavior of the filtered Rrs, the coefficient of variation of the unfiltered Rrs increased twofold (from 64.6 to 123%). Previously, Vincent et al. (18) had found this maneuver useful to decrease the variability of Rrs, presumably by keeping the glottis wide open. These results are in keeping with our argumentation. Indeed, the unfiltered Rrs had an increased variability following a maneuver which must reduce its variability and which indeed results in a clear-cut decrease of the variation of the filtered Rrs. The perturbative effect of the increased rate of breathing upon unfiltered Rrs became manifest. The large fluctuations of the filtered Rrs during quiet breathing are due probably to phasic changes in the caliber of upper airways and difference between the inspiratory and expiratory resistance of these airways were previously reported (1, 4, 9, 16). From our results it also appears that the variability of filtered Rrs differs among normal subjects and large fluctuations of the respiratory resistance during quiet breathing is present only in a minority of them. It may be that imperfection of previous forced oscillation techniques has led to an overestimation of the variability of respiratory resistance during quiet breathing (13). A marked variability of the resistance distorts its mean value as well. The mean unfiltered Rrs was higher than the filtered one
Rks) FILTERED
cmH,O/L/sec
pro.
\j
5.
Respiratory
resistance in a
healthy subject computed using a time constant of comb filters of 1 s (A) and 5 s (B). Only filtered signals are shown.
FILTERED L/seC
1.0
1.0
0
0
Pa0 FILTERED
cm
Hz0
EXP 0.5 "NFlLTERED \j
0
Fxa. 6. Respiratory
resistance
with important phasic between inspiration and over a Z-mo period.
IN-05
Llsec
(fil-
tered) in one of two normal subjects fluctuations expiration,
0.3 FILTERED
0 0:
cm
Pa0 H,O
FILTERED
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STANESCU
ET
AL.
7. Recorder tracing from the subject as in Fig. 6, during quiet (A) and shallow breathing (B) (rate of breathing 9/min and 75/min, respectively). Filtered Rrs has a coefficient of variation of 37.3% in (A) and 9.1% in (B). Coefficient of variation of unfiltered Rrs (not shown on the record) increased from 64.6% during quiet breathing (A) to 123% during shallow breathing (B). FIG.
same
“NFILTEREO Pa0 cm H,O
and this was more evident for high Rrs values. In the example given in fig. 4 the unfiltered resistance was 30.6 cmH20/1 per s, while the filtered one was 14.1 cmH20/1 per s (the highest Rrs value observed in our group). The mean filtered Rrs is necessarily lower than the mean unfiltered Rrs. In an earlier report, ClCment and van de Woestijne (3) have shown that the arithmetic mean of a number of individual ratios would be overestimated with respect to the true value when variability of denominator and the value of the ratio are high. The mean unfiltered Rrs is indeed computed as the mean of a number of individual APjA\;r ratios. The variability of AP is very small. On the contrary, the variability of AV is very important. Since A$’ is in the denominator of the ratio, changes in A$‘, during normal breathing would lead to an overestimation of mean Rrs. Assuming a constant AP, low AX’ values will produce high Rrs values and conversely high AK’ values will generate small Rrs values, the final result being, as demonstrated by Clement and van de Woestijne (3), a displacement of the average Rrs toward a higher value. These authors also showed that the bias will be corrected for if variability of the denominator is decreased and the ratio of mean values of the variables (AP and A$‘), instead of the mean of several individual ratios is computed. This is in fact the way filtered Rrs is computed. Variability of the A%7 is diminished due to the leveling action of the filter and each individual Rrs value is a ratio of weighted (if not mean) AP and Av values. If filters with sufficiently long time constants are used, variability of AP and Av is abolished (see Fig. 5B). Usually, flow resistance is expressed as a mean value of several individual resistances measured at a given flow rate, either during inspiration or during both inspiration and expiration. This permits standardization of resistance with respect to flow. In addition, measurement of flow resistance during inspiration only is considered to better reflect the intrinsic state of airways excluding their dynamic narrowing during expiration. With the present method as it was previously stated, each computed Rrs is delayed with respect to its actual value. Therefore we cannot measure precisely Rrs at a given flow or during a selected phase of respiration and we chose to express resistance as a mean value, which represents a weighted ensemble average computed over both inspiration and expiration. This mean value does not reflect only the inspiratory intrinsic uncompressed size of the tracheobronchial tree, and this may be considered as a drawback. Measuring both expiratory and inspiratory resistance, however, may a priori permit a better separation of patients with chronic obstructive lung diseases from normal persons. In many of these
patients flow resistance is tremendously increased during expiration, due to dynamic compression of intrathoracic airways. Besides, expiration represents a larger part of the respiratory cycle in these patients than in normals. Both factors would increase the share of the expiratory resistance in the average Rrs. All Rrs values in our patients were above the values found in normal subjects, without overlapping. However, mean age of the healthy subjects and patients differed and the number of persons studied was too small to permit us to draw a firm conclusion about the higher discriminatory power of the mean Rrs. One may also object that useful information on changes of Rrs during inspiration and expiration is lost with our method. One must however appreciate that Goldman and associates (7), though suggesting that Rrs could be measured at any instant during respiration, in practice to avoid artifacts, restricted its measurement to inspiration only, at a mean respiratory flow of 0.5 I/s. Confirming a theoretical prediction of Otis et al. (12), Grimby and his co-workers (8) have demonstrated frequency dependence of resistance in patients with obstructive lung diseases. In all their patients, Rrs at 9 Hz was less than at 3 Hz. A qualitatively similar pattern was observed by us in a comparable group of patients. However, the average decrease in Rrs-from 3 to 9 Hz-was less important in our patients (85% of the value at 3 Hz, as compared with about 54%, calculated by us from the data presented in Fig. 5 by Grimby et al. (8)) and in five patients Rrs was independent of frequency. Average Rrs at 3 Hz was higher in their (about 9 cmH20/1 per s) than in our patients (7.80 cmH20/1 per s), and FEV1.o and FEVl.o/VC ratio were also higher in the former group. The difference between Grimby’s results and ours may be explained by the more severe disease in his group, hut also, by the fact that Grimby et al. measured inspiratory resistance only, while our average Rrs includes expiratory resistance. If increase of the expiratory resistance in patients is due mainly to dynamic compression of the airways, there is no reason for the expiratory resistance to decrease from 3 to 9 Hz. It may be that our method obscures frequency dependence of resistance. Measurement of Rrs at 3 Hz is to be preferred since it permits a better separation between normal persons and patients. Concerning the behavior of Rrs at different frequencies in normal subjects Grimby et al. (8) quoted unpublished results of Wohl and her colleagues (done in 5 normal subjects); the former authors stated that “frequency dependence of resistance in normal subjects is of much smaller magnitude than that in most of the patients.” More recently, frequency dependence of resistance in healthy
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RESPIRATORY
subjects was reported by Frank et al. (6). No explanation was given for this rather unexpected finding. In our normal subjects average as well as individual values of Rrs were similar at 3 and 9 Hz. Mean age of these subjects was 36 yr (range 24-43 yr). The healthy subjects studied by Frank et al. (6) ranged in age between 31 and 58 yr. We have found the present method practical and rapid: Rrs is automatically computed in less than 2-3 min. In some persons, transient closure of upper airways is a perturbing factor. It results in an important increase of Rrs, easy however to distinguish from the regular pattern of its fluctuation. By monitoring the digital display of Rrs we measure the mean value only when those important changes in Rrs are absent. APPENDIX Comb
Filter
311
RESISTANCE
(Fig.
2)
The input signals (flow rate and mouth pressure) are passed through a second-order high-pass filter, cut-off frequency 2 Hz (not shown in Fig. 2) to remove the fundamental and harmonics of the subject’s breathing. These treated signals are applied to a network consisting of an input resistor, a load resistor, and eight commutating capacitors. A clock commutator commands the successive charging of the capacitors. It is tuned to the 8th harmonic of the fundamental frequency of the signal generator. The frequency of the commutator
clock is equal to the product of the number of capacitors that have to be commutated and of the central frequency of the comb filter (at 6 Hz the frequency of the commutation is 48 Hz, i.e., 6 X 8 capacitors). The clock generator consists of a phase-locked loop (LM 565), a binary counter, and a three-bit decoder. During commutation, each capacitor is successively exposed to a portion of the input signal. If the frequency of the input signal is some submultiple of the clock frequency, the fundamental frequency and the harmonics of the input signal will pass through the filter. If the frequency of the input signal is not an exact submultiple this frequency will be rejected by the filters, since the capacitors will charge to some small voltage, near zero. The charging rate of each capacitor is determined by the RC time constant. This time constant is several times higher than the period of the clock frequency and several clock cycles are required to charge the capacitors to the average value of the input voltage. Increasing the time constant of the filter (by increasing the value of the input resistor) will require more time for charging the capacitors, i.e., an increased number of input signals are averaged. At the same time a higher time constant would also narrow the bandwidth (BW) of the filter. The BW of this filter, neglecting the loading, is dependent on the relation: BW = 1 /(xNRC), where N is the number of capacitors being commutated. The filtered output signal is a stepwise sine wave and smooth reconstruction of the signal was obtained using a thirdorder low-pass filter. A complete scheme will be supplied on request. Received
for publication
6 December
1974.
REFERENCES 1. BLIDE, R. W., H. D. KERR, AND W. S. SPICER, JR. Measurement of upper and lower airway resistance and conductance in man. J. Ap~2. Physiol. 19 : 1059-1069, 1964. 2. DuBors, A. B., A. W. BRODY, D. H. LEWIS, AND B. F. BURGESS, JR. Oscillation mechanics of lungs and chest in man. J. A$$& Physiol 8: 587-594, 1956. 3. CLEMENT, J., AND K. P. VAN DE WOESTIJNE. Resistance or conductance? Compliance or elastance? J. ApPZ. Physiol. 30: 437439, 1971. 4. FERRIS, B. G., JR., J. MEAD, AND L. H. OPIE. Partitioning of respiratory flow resistance in man. J. A/$d. Physiol. 19: 653-658, 1964. 5. FISHER, A. B., A. B. DUBOIS, AND R. W. HYDE. Evaluation of the forced oscillation technique for the determination of resistance to breathing. J. Clin. Invest. 47 : 2045-2057, 1968. 6. FRANK, N. R., J. MEAD, AND J. L. WHITTENBERGER. Comparative sensitivity of four methods for measuring changes in respiratory flow resistance in man. J. A@ Physiol. 3 1 : 934-938, 197 1. 7. GOLDMAN, M., R. J. KNUDSON, J. MEAD, N. PETERSON, J. R. SCHWABER, AND M. E. WOHL. A simplified measurement of respiratory resistance by forced oscillation. J. A/@. Physiol. 28: 113-l 16, 1970. 8. GRIMBY, G., T. TAKISHIMA, W. GRAHAM, P. MACKLEM, AND J. MEAD. Frequency dependence of flow resistance in patients with obstructive lung disease. J. Clin. Invest. 47 : 1455-1465, 1968. 9. HYATT, R. E., AND R. E. WILCOX. Extrathoracic airway resistance in man. J. ApPl. Physiol. 16 : 326-330, 196 1.
10. HYATT, R. E., I. R. ZIMMERMAN, G. M. PETERS, AND W. J. SULIJ. AppZ. VAN. Direct writeout of total respiratory resistance. Physiol. 28 : 675-678, 1970. 11. MEAD, J. Control of respiratory frequency. J. AppI. Physiol. 15 : 325-336, 1960. 12. OTIS, A. B., C. B. MCKERROW, R. A. BARTLETT, J. MEAD, M. B. MCILROY, N. J. SELVERSTONE, AND E. P. RADFORD. Mechanical factors in distribution of pulmonary ventilation. J. Appl. Physiol. 8 : 427-443, 1956. 13. PESLIN, R., T. HIXON, AND J. MEAD. Variations des resistances thoracopulmonaires au tours du cycle ventilatoire etudiees par la methode d’oscillation. Bull. Physio-Pathol. Respirat. 7 : 173186, 1971. 14. RYKEN, M. L., JR. Experimental Investigation into a Commutative filter. Tech. Publ. TP-73-7, 1973, Naval Missile Center, Point Mugu, Calif., p. l-35. 15. SOBOL, B. J. Tests of ventilatory function not requiring maximal subject effort. II. The measurement of total respiratory impedance. Am. Rev. Respirat. Diseases 97 : 868-879, 1968. 16. SPANN, R. W., AND R. E. HYATT. Factors affecting upper airway resistance in conscious man. J. A&?l. Physiol. 3 1 : 708-7 12, 1971. 17. STANESCU, D. C., J. PATT~JN, J. CLEMENT, AND K. P. VAN DE WOESTIJNE. Glottis opening and airway resistance. J. A&p/. Physiol. 32 : 460-466, 1972. 18. VINCENT, N. J., R. KNUDSON, D. E. LEITH, P. T. MACKLEM, AND J. MEAD. Factors influencing pulmonary resistance. J. Appk Physiol. 29 : 236-243, 1970.
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Vol. 39, No.
APPLIED PHYSIOLOGY 2, August 1975. Printed
A modified
in U.S.A.
measurement
forced oscillation
during normal
D. C. STiiNESCU, Cardiopulmonary
of respiratory
R. FESLER,
Laboratory,
Universite’
breathing
C. VERITER, Catholipe
A. FRANS,
de Louvain,
ST~NESCU, D. C., R. FESLER, C. VERITER, A. FRANS, AND L. BRASSEUR. A modzj?ed measurement of respiratory resistance by forced oscillation during normal breathing. J. Appl. Physiol. 39(2) : 305-3 11. 1975.-We have modified the measurement of the resistance of the respiratory system, Rrs, by the forced oscillation technique and we have developed equipment to automatically compute Rrs. Flow rate and mouth pressure are treated by selective averaging filters that remove the interference of the subject’s respiratory flow on the imposed oscillations. The filtered mean Rrs represents a weighted ensemble average computed over both inspiration and expiration. This method avoids aberrant Rrs values, decreases the variability, and yields an unbiased mean Rrs. Rrs may be measured during slow or rapid spontaneous breathing, in normals and in obstructive patients, over a range of 3-9 Hz. A good reproducibility of Rrs at several days’ interval was demonstrated. Frequency dependence of Rrs was found in patients with obstructive lung disease but not in healthy nonsmokers. lung
mechanics;
chronic
obstructive
lung
resistance by
Cliniques
AND
L. BRASSEUR
Universitaires
St. Pierre,
Louvain,
Belgium
chronic obstructive lung disease than in normal subjects, at a low (3 Hz) than at a high frequency (9 Hz) of forced oscillations, and when rate of breathing was increased. Important changes of Rrs, from one oscillation to another, are recorded (during expiration and inspiration also) and selection of a given Rrs value becomes an arbitrary matter. The high variability was not the only problem encountered. Obvious spurious values of Rrs (either infinite or negative) were frequently observed in the circumstances quoted above. An increased variability of Rrs and aberrant Rrs values (at 3 Hz) were observed by Hyatt et al. (10) also (see Fig. 6 in (10)). To obtain accurate data of Rrs, these authors recommended that the breathing rate of subjects should be slow. A decrease in the breathing rate is however not always easy to impose and a method of measuring Rrs in the absence of any restriction upon the pattern and breathing rate would be suitable. Goldman et al. (7) had also observed marked changes in Rrs, mainly during expiration and less frequently during inspiration. They also noted that “aberrant breaths should not be measured.” These authors attributed the artifacts to transient changes in the upper airway resistance. In an earlier study we examined the glottis orifice during quiet breathing (17) and changes in the size of the glottis aperture were indeed present, but not of sufficient magnitude to explain the important changes in Rrs. Obviously this was a qualitative observation and changes in the pharynx and larynx may also be involved. However, we do not believe that upper airways changes are the main factor explaining the marked variability of the flow resistance measured with the forced oscillation technique. We attribute the increased variability of Rrs to a distortion of the imposed oscillatory flow by the subject’s flow rate. This became critical when respiratory flow is changing rapidly and at an increased rate of breathing. Hyatt et al. (10) also suggested that harmonics of nonnegligible amplitude in the subject’s flow pattern may interfere with the applied oscillatory flow. We thought therefore that measurement of Rrs from the imposed oscillations in the absence of interference with the respiratory flow of the subject will improve the accuracy of the measurement of Rrs and decrease its variability. This was achieved by average filtering of both flow rate and oral pressure signals. In this communication we describe the equipment used to measure Rrs and we present comparative data of the variability of filtered and unfiltered Rrs (i.e., with the method of Hyatt et al. (10)). We also present data on the reproducibility of Rrs and measurements of Rrs at different frequencies of the imposed oscillation, in normal subjects and patients with chronic obstructive lung disease.
disease
DUBOIS AND HIS COLLEAGUES (2) were the first to estimate the resistance of the respiratory system, Rrs, with the method of forced oscillation. Several modifications of the original technique have been subsequently reported (5, 7, 8, 15). The advantage of this technique is that it does not require a body plethysmograph or swallowing of an esophageal balloon and little cooperation of the subject is asked. Fisher et al. (5) have measured Rrs at end expiration during prolonged apnea. Previously, Mead (11) had demonstrated that Rrs could also be measured during normal breathing. More recently, Goldman et al. (7) h ave described a simplified method for computing Rrs during spontaneous breathing. Assuming a linear behavior of the respiratory system, these authors showed that Rrs can be measured by relating flow rate, at points of zero volume acceleration, to the corresponding oral pressure changes. At these instants, inertial impedance is zero and since points of zero volume acceleration occur at the same volume, there are no pressure differences related to elastic impedance either. Therefore, the pressure difference between two successive instants of zero volume acceleration must be determined only by the flow resistance of the respiratory system. Rrs is computed by relating the changes in pressure between these two points to the amplitude of the flow rate. The authors also showed that principles underlying their method are valid during a constant respiratory flow rate, but also when flow is changing from breath to breath. Using this approach, Hyatt et al. (10) have developed equipment which automatically computes Rrs. Initially, we duplicated the equipment of Hyatt et al. (10) and we intended to use it for routine purposes. However, soon after its introduction we were disappointed by the marked intraindividual variability of Rrs. The variability was higher in patients with
EQUIPMENT
AND
METHODS
Since at first we used the method of Hyatt et al. (10) for measuring Rrs, the apparatus we built for inducing oscillation had several features in common with that described by these authors. Oscillating airflows were applied at the mouth using a 15-in loudspeaker (Lansing Sound Inc.) driven by a sine-wave function generator (Philips model PM 5160) and power amplifier (Philips model PM 5 175). The loudspeaker was mounted in an enclosure 305
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STANESCU
306
9
”
+
COMB FILTER
..
’ 6
DERIVATIVE CIRCUIT
-
SAMPLE and HOLD (max VI
>
OPERATIONAL AMPLIFIER X1
r
v
, -
.I
*
SAMPLE and HOLD (mln 91
4>.
ZERO COMPARATOR
*
1 SUMMATION CIRCUIT
+
w
START
SUBTRACTION
1 -
CIRCUIT
, t
4) -.
t-
AL.
rate is differentiated and instants of zero volume acceleration identified by a zero comparator circuit. At each instant of zero volume acceleration two pulses are generated which sample and hold simultaneous values of 7j’, and PaoF. The difference between two successive values of PaoF (corresponding to maximal and minimal flow) provided by a subtraction circuit, defines APaoF. Similarly A%$ is provided by another subtraction circuit. A division circuit computes Rrs as APao,/AX$ ratio. This value is displayed on a front-panel digital voltmeter and an analog output is provided for recording. Two resistance values are computed for each cycle of the applied oscillations, that is, at an imposed frequency of 3 Hz, six values of Rrs are generated each second. A separate circuit computes the mean value of Rrs from 100 successive individual data. In fact it is a summation circuit, the mean value being obtained by moving the decimal point two places to the left. This mean Rrs is also recorded on a digital display. A push button starts the measurement of the mean Rrs. For convenience, the displayed Rrs is in actual units (cmHzO/l per s). The output of the carrier amplifiers was calibrated in such a way that a given pressure and flow rate unit correspond to a given voltage. For routine puposes we calibrated the equipment with a resistor constructed from a bundle of fine capillary tubes fixed together. The measurement of Rrs is done with the subject in a seated position, the cheeks being pressed by the subject’s hands. The person is asked to breathe as usual. We allow about l-2 min before starting the measurement of Rrs. Subjects become accustomed to the equipment and they reach a steady-state breathing pattern during this period. Three to four mean values of Rrs are usually recorded at a frequency of 3, 6, and 9 Hz. Afterward the subject performs a maximal inspiration to define the functional residual capacity with respect to total lung capacity. To validate our system we measured the Rrs of three known linear resistors (with a resistance of 1.6, 6.4, and 11.9 cmH20/1 per s, respectively) at different flow rates, between 3 and 9 Hz. An accurate measurement of the resistance was obtained and, as expected, no change in the resistance at different frequencies was observed. The accuracy of the division circuit in computing Rrs was tested by measuring a known added resistance. Thereafter, the gain of the amplifiers (of the flow or pressure signals) was changed. We found an excellent agreement between the new computed Rrs and its predicted value. Previously with the method of Hyatt et al. (10) we found intra-
made of 0.5in Plexiglas (15.5 x 15.5 x 7 in). The subject breathed into an 1 l-in length of tubing (ID 1 in) connecting the mouthpiece to the Plexiglas enclosure. Airflow was measured by a Fleisch no. 3 pneumotachograph and a Statham (PM 15) differential transducer. Mouth pressure with respect to atmosphere was measured by another differential pressure transducer (Sanborn, model 270). Both signals were amplified (Hewlett-Packard 8805 B carrier amplifiers). Three tubes in series (15 in long, 2.3 in ID; 24 in, 1.6 in; 34 in, 1.2 in) connected the Plexiglas enclosure to atmosphere. This tubing provided a low impedance to the subject’s breathing and a relatively high one to the forcing oscillations. To prevent accumulation of carbon dioxide in the system, a constant bias flow (0.3 l/s) entered through the impedance tubing and was pulled through a lateral opening in the respiratory tubing. The block diagram of the electrical network to compute Rrs is shown in Fig. 1. To avoid noise the amplified flow and pressure signals are passed through two low-pass filters (first order, cutoff frequency at - 3 dB 16 Hz). The filtered signals are afterwards treated by two comb filters (14). We chose this type of filter since it has a narrow bandwidth at low frequencies and the bandwidth is easily adjustable. The filter has also an unusually high Q at very low frequencies and the Q is substantially less sensitive to changes in filter element values, in contrast to large variations in the Q of active filters. The diagram of the comb filter is presented in Fig. 2 and a more detailed description of its operation is given in the APPENDIX. However some information has to be given now. First, the filter introduces a lag between the input and the output signals. To avoid phase shifts between flow rate and oral pressure, both signals were passed through two identical comb filters. The lag is due to the time constant of the filter. We used in our measurements a time constant of about 1 s. The predicted bandwidth of the filter, for this time constant, is 0.4 Hz at - 3dB. This bandwidth is narrow enough to remove the fundamental and harmonics of important amplitude of the subject’s breathing. Second, the output signal represents weighted ensemble averages of previous successive input signals. Rapid variations in the amplitude of the input signals are in this way leveled out. We will refer to these PaoF). Output for recording is output signals as filtered (%$; provided for these as well as for unfiltered v and Pao signals. 0, and PaoF are thereafter amplified by a factor of 4. This makes detection of zero volume acceleration instants more accurate and improves the operation of the division circuit (see below). Flow
-
ET
SAMPLE HOLD Pa0
and
To rtcordtr
A
SUBTRACTION
Pa0 to
f Pa0
t recorder
FIG.
1. Block
to
diagram
of the electrical
rtcordtr
network
for computing
respiratory
resistance,
Rrs.
Downloaded from www.physiology.org/journal/jappl by ${individualUser.givenNames} ${individualUser.surname} (129.237.035.237) on January 19, 2019.
RESPIRATORY
RESISTANCE
307 415v
from GENERATOR
SN 7442 N
BAX16 2N3703
r
Pa0 from
high pass filters
2. Electrical
FIG.
to low pass f i kers
diagram
of the
comb
filter.
High-pass
filters
(left
side
of diagram)
and
low-pass
filters
(right
side)
are
components of
comb filter. individual
coefficients
of variation
of Rrs
(the
standard
deviation
of the Rrs
was tested
at 3 days’
interval
(at the same
hour
in the
divided by the mean, expressed in percentage) during quiet breathing, ranging from 40 to 1ZOO/& The present method of
morning) in 9 of the 12 healthy subjects. Rrs averaged 1.98 =t 0.43 cmHzO/l per s the 1st day and 2.04 rt 0.50 cmHaO/l per s
measuring
3 days
Rrs
drastically
reduced
the
variability
of this
index.
later.
The
difference
is statistically
not
significant
as as-
To illustrate this improvement we compared the variability of Rrs with the two methods in one normal subject (Fig. 3) and in two patients with chronic obstructive lung diseases. The oscillographic tracing in one of these patients is shown in Fig. 4. Flow rate (filtered and unfiltered), mouth pressure (filtered and unfiltered), and filtered Rrs were simultaneously recorded versus time (Brush model 480 recorder). Unfiltered Rrs was computed by hand from the recorder tracing, by locating instances of zero volume acceleration and by dividing APao by AV. The manual
sessed by the paired t-test. Rate and pattern of breathing were chosen freely by the subjects each time. In patients there was a decrease of the average Rrs at 9 Hz (6.6 ZJZ3.0 cmHzO/l per s) with respect to the value at 3 Hz (7.8 & 3.8 cmHzO/l per s). The decrease is statistically significant (P < 0.05). However, 5 of the 15 patients had similar Rrs values at 3 and 9 Hz (Table 2). The average intraindividual coefficient of variation of Rrs for all patients was 9.1 * 3.6y0. The coefficient of variation was somewhat smaller in obstructive patients than in
method
healthy
of computation
of Rrs
is less accurate
than
the
electrical
one, but no systematic error is introduced. To mord. both filtered and unfiltered Rrs simultaneously we should have duplicated most
of the electrical
circuits
of our equipment.
The
coefficient
of
variation was calculated from 140 consecutive individual Rrs. Filtered Rr was measured in 12 healthy nonsmoking subjects (mean
age 34.0
=t: 6.6 yr)
and
in
15 patients
(mean
age 51.4
rt=
19.7 yr) with chronic obstructive lung diseases (avg FE&, o/VC ratio 50.9 & 8.9aj0) at a frequency of the imposed oscillations of 3 and 9 Hz. RESULTS
Mean Rrs in 12 normal subjects at 3 Hz was 2.2 =t 0.5 cmHzO/l per s. It averaged 2.2 of= 0.5 cmHsO/l per s at 9 Hz (Table 1). In 10 of the above mentioned subjects the intraindividual coefficient of variation ranged between 5.9 and 24y0 (mean 12.0 &Z 6.1 yO). In two other subjects however, the coefficient of variation was much higher (38 and 41 y0 respectively). The reproducibility
persons
since
average
Rrs was higher
in the former
group.
In seven patients Rrs was measured at two flow rates of the imposed oscillation (at a frequency of 6 Hz). The Rrs at an average amplitude
of the flow
oscillations
of 0.15
& 0.03
l/s was 7.1 of= 1.6
cmH20/1 per s, whereas it averaged 6.9 =f= 1.4 cmH20/1 per s at a flow rate of 0.3 of= 0.08 l/s. The difference in Rrs was statistically not significant (paired t-test). In a normal subject, unfiltered Rrs was 2.9 & 1.2 cmH20/1 per s (coefficient of variation 42.0y0) while the filtered Rrs averaged 2.5 -4 0.4 (coefficient of variation 16.Ooj,) (Fig. 3). In two obstructive patients unfiltered resistance averaged 7.9 & 7.8 and 30.6 & 24.6 cmH20/1 per s. The corresponding coefficients of variation were 99.0 and 80.3oj,, respectively. Filtered Rrs was 5.0 k 0.3 (coefficient of variation 6.0%) and 14.1 =t 1.5 cmHQO/l per s (coefficient of variation 10.9 %), respectively. Aberrant Rrs values were not’ included in the calculation of the coefficient of variation. No aberrant Rrs were observed with the present method
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STANESCU
ET
AL.
1. Physical data and Rrs at 3 and 9 Hz in normal subjects
TABLE
UNFILTERED
Mean
Subj
Age, yl
VH vc SC DD CJ HL HE FP FA DP VR BT
33 32 43 33 43 43 35 28 38 26 25 28
f
SD
34 f
Ht,
cm
182 184 167 181 172 181 178 171 176 176 170 183 6.6
Wrs)
3Hz
9Hz
3.1 2.1 2.7 2.2 1.9 1.4 2.2 1.8 2.2 2.3 2.9 1.5
3.1 2.0 2.8 2.0 1.8 1.3 2.5 1.8 2.1 2.5 2.9 1.8
177 rt 6
2.2
i
0.5
2.2
f
0.5
FILTERED
TABLE 2. Physical data, FEVJVC ratio and R(rs) at 3 and 9 Hz in patients with chronic obstructive lung disease UNFILTERED
RI PV DV CA GM CK GE JA AM MF MM FL LJ CL ME
FILTERED
UNFILTERED
Rh) cm H,O/L
Sex
Patient
Pa0 cm Hz0
/set
M M M F M F M M M M F F M F M
Age, yr
25 61 46 62 72 10 76 50 69 50 21 48 61 48 72
Ht,
cm
180 185 158 166 164 122 166 156 175 162 170 153 167 155 167
FEVI o/VC %
53 37 49 56 44 48 44 55 56 33 69 59 55 55 53
3Hz
RW
9Hz
7.0 4.0 7.0 4.6 8.0 17.0 3.2 12.5 4.0 12.0 7.6 5.7 10.0 9.1 5.6
4.0 3.2 6.3 4.4 6.0 11.0 2.7 10.4 4.2 13.0 7.6 5.4 8.1 8.2 4.9
7.8f3.8
6.6f3.0
FILTERED
Mean
f
SD
51f20
163f14
51f9
EXP.
DISCUSSION UNFILTERED
9 L/seC
FILTERED
UNFILTERED
Pa0 cm Hz0 FILTERED
-.0.5
I 0.: P FIG. 3. Recorder tracing from a normal subject. From top to bottom, unfiltered and filtered Rrs, flow rate, and mouth pressure, respectively. Unfiltered Rrs was calculated by hand (see text) and was drawn on the record. Note that filtered signals are delayed with respect to unfiltered ones. FI(?. 4. Recorder tracing from a patient with severe airway obstruction and obesity. Legend is the same as in Fig. 3. Black circles on tracing of unfiltered Rrs identify spurious values of respiratory resistance.
The purpose of the present modification of the measurement of Rrs by the forced oscillation technique was to separate the useful oscillatory flow, from what we considered signal, i.e., imposed breathing flow, in other words to improve “noise,” i.e., subject’s the signal-to-noise ratio. This was achieved by filtering both flow and pressure signals. In this way the influence of the subject’s respiratory flow and pressure on the imposed oscillations is removed. This modified technique represents an improvement over former methods. Measurements of Rrs can be done during spontaneous breathing,’ no restriction being imposed on the pattern or the rate of breathing of subjects. Accurate measurement of Rrs is provided over a range of frequency from 3 to 9 Hz, both in normal and in obstructive patients. Comparative measurements of Rrs with the method of Hyatt et al. (10) and this technique showed a striking decrease of the variability of Rrs with the latter method. i This method may also be used to measure Rrs during panting. However the equipment has to be modified and a loudspeaker box (8) instead of a small Plexiglas enclosure must be used to avoid loading of the loudspeaker during panting. With our equipment, the loudspeaker was displaced by the subject’s flow during panting. This resulted in a distortion of the imposed flow and pressure signals which were no longer sinusoidal.
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RESPIRATORY
309
RESISTANCE
Two factors may account for the variability of Rrs: actual changes in the caliber of upper (or lower) airways during breathing, or methodological factors. One has to distinguish, however, between the regular phasic changes in Rrs during inspiration and expiration (see Fig. 7A) and the irregular chaotic tracing, with tremendous changes in Rrs from one moment to another (Fig. 4) : both patterns would result in an increased variability of Rrs. We suggest that the first pattern reflects phasic changes in the upper airways while the latter is methodological in nature. Indeed a “chaotic” irregular record is observed whenever breathing rate is increased, frequency of the imposed oscillations is low (3 Hz), and flow resistance is high. Under these conditions oscillatory flow is distorted by the respiratory flow since frequency of breathing comes nearer to the frequency of oscillations and a low amplitude of the oscillatory flow (high resistance) renders detection of zero volume acceleration points inaccurate. One may wonder why particularly in these conditions upper airway changes intervene to disturb Rrs and not when rate of breathing is slow and oscillatory frequency is high (9 Hz). From the practical point of view, under these unfavorable conditions, important moment-tomoment changes of the unfiltered Rrs and spurious values are observed and selection of a “good” Rrs value becomes an arbitrary matter. Filtering avoids distortion of the oscillatory flow and reduces variability of respiratory resistance. It must be appreciated, however, that the decreased variability of Rrs is also due to the filtering process itself: each measured Rrs value is a weighted value of an ensemble of previous resistances. Rapid fluctuations in Rrs are in this way leveled out. The reported variability of the filtered Rrs does not reflect the actual variability of respiratory resistance but tends to underestimate it. To illustrate this, an “artificially” induced decrease in the yariability of Rrs is shown in Fig. 5 (the time constant of the filters was increased from 1 to 5 s).
Important phasic variations of filtered Rrs were observed in 2 of 12 healthy subjects during quiet breathing. This resulted in a much higher intraindividual coefficient of variation than in the rest. Rate of breathing and respiratory flow rate were comparable among subjects. The pattern of the fluctuations of Rrs during quiet breathing in these two subjects was reproducible over several months (Fig. 6), suggesting the intervention of a systematic factor. We instructed one of these subjects to breathe very shallowly and moderately fast (rate of breathing about 7O/min). Every time this was done fluctuations of filtered Rrs were drastically reduced (Fig. 78) and the coefficient of variation decreased from 37.3 to 9.1%. Contrasting with the behavior of the filtered Rrs, the coefficient of variation of the unfiltered Rrs increased twofold (from 64.6 to 123%). Previously, Vincent et al. (18) had found this maneuver useful to decrease the variability of Rrs, presumably by keeping the glottis wide open. These results are in keeping with our argumentation. Indeed, the unfiltered Rrs had an increased variability following a maneuver which must reduce its variability and which indeed results in a clear-cut decrease of the variation of the filtered Rrs. The perturbative effect of the increased rate of breathing upon unfiltered Rrs became manifest. The large fluctuations of the filtered Rrs during quiet breathing are due probably to phasic changes in the caliber of upper airways and difference between the inspiratory and expiratory resistance of these airways were previously reported (1, 4, 9, 16). From our results it also appears that the variability of filtered Rrs differs among normal subjects and large fluctuations of the respiratory resistance during quiet breathing is present only in a minority of them. It may be that imperfection of previous forced oscillation techniques has led to an overestimation of the variability of respiratory resistance during quiet breathing (13). A marked variability of the resistance distorts its mean value as well. The mean unfiltered Rrs was higher than the filtered one
Rks) FILTERED
cmH,O/L/sec
pro.
\j
5.
Respiratory
resistance in a
healthy subject computed using a time constant of comb filters of 1 s (A) and 5 s (B). Only filtered signals are shown.
FILTERED L/seC
1.0
1.0
0
0
Pa0 FILTERED
cm
Hz0
EXP 0.5 "NFlLTERED \j
0
Fxa. 6. Respiratory
resistance
with important phasic between inspiration and over a Z-mo period.
IN-05
Llsec
(fil-
tered) in one of two normal subjects fluctuations expiration,
0.3 FILTERED
0 0:
cm
Pa0 H,O
FILTERED
Downloaded from www.physiology.org/journal/jappl by ${individualUser.givenNames} ${individualUser.surname} (129.237.035.237) on January 19, 2019.
STANESCU
ET
AL.
7. Recorder tracing from the subject as in Fig. 6, during quiet (A) and shallow breathing (B) (rate of breathing 9/min and 75/min, respectively). Filtered Rrs has a coefficient of variation of 37.3% in (A) and 9.1% in (B). Coefficient of variation of unfiltered Rrs (not shown on the record) increased from 64.6% during quiet breathing (A) to 123% during shallow breathing (B). FIG.
same
“NFILTEREO Pa0 cm H,O
and this was more evident for high Rrs values. In the example given in fig. 4 the unfiltered resistance was 30.6 cmH20/1 per s, while the filtered one was 14.1 cmH20/1 per s (the highest Rrs value observed in our group). The mean filtered Rrs is necessarily lower than the mean unfiltered Rrs. In an earlier report, ClCment and van de Woestijne (3) have shown that the arithmetic mean of a number of individual ratios would be overestimated with respect to the true value when variability of denominator and the value of the ratio are high. The mean unfiltered Rrs is indeed computed as the mean of a number of individual APjA\;r ratios. The variability of AP is very small. On the contrary, the variability of AV is very important. Since A$’ is in the denominator of the ratio, changes in A$‘, during normal breathing would lead to an overestimation of mean Rrs. Assuming a constant AP, low AX’ values will produce high Rrs values and conversely high AK’ values will generate small Rrs values, the final result being, as demonstrated by Clement and van de Woestijne (3), a displacement of the average Rrs toward a higher value. These authors also showed that the bias will be corrected for if variability of the denominator is decreased and the ratio of mean values of the variables (AP and A$‘), instead of the mean of several individual ratios is computed. This is in fact the way filtered Rrs is computed. Variability of the A%7 is diminished due to the leveling action of the filter and each individual Rrs value is a ratio of weighted (if not mean) AP and Av values. If filters with sufficiently long time constants are used, variability of AP and Av is abolished (see Fig. 5B). Usually, flow resistance is expressed as a mean value of several individual resistances measured at a given flow rate, either during inspiration or during both inspiration and expiration. This permits standardization of resistance with respect to flow. In addition, measurement of flow resistance during inspiration only is considered to better reflect the intrinsic state of airways excluding their dynamic narrowing during expiration. With the present method as it was previously stated, each computed Rrs is delayed with respect to its actual value. Therefore we cannot measure precisely Rrs at a given flow or during a selected phase of respiration and we chose to express resistance as a mean value, which represents a weighted ensemble average computed over both inspiration and expiration. This mean value does not reflect only the inspiratory intrinsic uncompressed size of the tracheobronchial tree, and this may be considered as a drawback. Measuring both expiratory and inspiratory resistance, however, may a priori permit a better separation of patients with chronic obstructive lung diseases from normal persons. In many of these
patients flow resistance is tremendously increased during expiration, due to dynamic compression of intrathoracic airways. Besides, expiration represents a larger part of the respiratory cycle in these patients than in normals. Both factors would increase the share of the expiratory resistance in the average Rrs. All Rrs values in our patients were above the values found in normal subjects, without overlapping. However, mean age of the healthy subjects and patients differed and the number of persons studied was too small to permit us to draw a firm conclusion about the higher discriminatory power of the mean Rrs. One may also object that useful information on changes of Rrs during inspiration and expiration is lost with our method. One must however appreciate that Goldman and associates (7), though suggesting that Rrs could be measured at any instant during respiration, in practice to avoid artifacts, restricted its measurement to inspiration only, at a mean respiratory flow of 0.5 I/s. Confirming a theoretical prediction of Otis et al. (12), Grimby and his co-workers (8) have demonstrated frequency dependence of resistance in patients with obstructive lung diseases. In all their patients, Rrs at 9 Hz was less than at 3 Hz. A qualitatively similar pattern was observed by us in a comparable group of patients. However, the average decrease in Rrs-from 3 to 9 Hz-was less important in our patients (85% of the value at 3 Hz, as compared with about 54%, calculated by us from the data presented in Fig. 5 by Grimby et al. (8)) and in five patients Rrs was independent of frequency. Average Rrs at 3 Hz was higher in their (about 9 cmH20/1 per s) than in our patients (7.80 cmH20/1 per s), and FEV1.o and FEVl.o/VC ratio were also higher in the former group. The difference between Grimby’s results and ours may be explained by the more severe disease in his group, hut also, by the fact that Grimby et al. measured inspiratory resistance only, while our average Rrs includes expiratory resistance. If increase of the expiratory resistance in patients is due mainly to dynamic compression of the airways, there is no reason for the expiratory resistance to decrease from 3 to 9 Hz. It may be that our method obscures frequency dependence of resistance. Measurement of Rrs at 3 Hz is to be preferred since it permits a better separation between normal persons and patients. Concerning the behavior of Rrs at different frequencies in normal subjects Grimby et al. (8) quoted unpublished results of Wohl and her colleagues (done in 5 normal subjects); the former authors stated that “frequency dependence of resistance in normal subjects is of much smaller magnitude than that in most of the patients.” More recently, frequency dependence of resistance in healthy
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RESPIRATORY
subjects was reported by Frank et al. (6). No explanation was given for this rather unexpected finding. In our normal subjects average as well as individual values of Rrs were similar at 3 and 9 Hz. Mean age of these subjects was 36 yr (range 24-43 yr). The healthy subjects studied by Frank et al. (6) ranged in age between 31 and 58 yr. We have found the present method practical and rapid: Rrs is automatically computed in less than 2-3 min. In some persons, transient closure of upper airways is a perturbing factor. It results in an important increase of Rrs, easy however to distinguish from the regular pattern of its fluctuation. By monitoring the digital display of Rrs we measure the mean value only when those important changes in Rrs are absent. APPENDIX Comb
Filter
311
RESISTANCE
(Fig.
2)
The input signals (flow rate and mouth pressure) are passed through a second-order high-pass filter, cut-off frequency 2 Hz (not shown in Fig. 2) to remove the fundamental and harmonics of the subject’s breathing. These treated signals are applied to a network consisting of an input resistor, a load resistor, and eight commutating capacitors. A clock commutator commands the successive charging of the capacitors. It is tuned to the 8th harmonic of the fundamental frequency of the signal generator. The frequency of the commutator
clock is equal to the product of the number of capacitors that have to be commutated and of the central frequency of the comb filter (at 6 Hz the frequency of the commutation is 48 Hz, i.e., 6 X 8 capacitors). The clock generator consists of a phase-locked loop (LM 565), a binary counter, and a three-bit decoder. During commutation, each capacitor is successively exposed to a portion of the input signal. If the frequency of the input signal is some submultiple of the clock frequency, the fundamental frequency and the harmonics of the input signal will pass through the filter. If the frequency of the input signal is not an exact submultiple this frequency will be rejected by the filters, since the capacitors will charge to some small voltage, near zero. The charging rate of each capacitor is determined by the RC time constant. This time constant is several times higher than the period of the clock frequency and several clock cycles are required to charge the capacitors to the average value of the input voltage. Increasing the time constant of the filter (by increasing the value of the input resistor) will require more time for charging the capacitors, i.e., an increased number of input signals are averaged. At the same time a higher time constant would also narrow the bandwidth (BW) of the filter. The BW of this filter, neglecting the loading, is dependent on the relation: BW = 1 /(xNRC), where N is the number of capacitors being commutated. The filtered output signal is a stepwise sine wave and smooth reconstruction of the signal was obtained using a thirdorder low-pass filter. A complete scheme will be supplied on request. Received
for publication
6 December
1974.
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10. HYATT, R. E., I. R. ZIMMERMAN, G. M. PETERS, AND W. J. SULIJ. AppZ. VAN. Direct writeout of total respiratory resistance. Physiol. 28 : 675-678, 1970. 11. MEAD, J. Control of respiratory frequency. J. AppI. Physiol. 15 : 325-336, 1960. 12. OTIS, A. B., C. B. MCKERROW, R. A. BARTLETT, J. MEAD, M. B. MCILROY, N. J. SELVERSTONE, AND E. P. RADFORD. Mechanical factors in distribution of pulmonary ventilation. J. Appl. Physiol. 8 : 427-443, 1956. 13. PESLIN, R., T. HIXON, AND J. MEAD. Variations des resistances thoracopulmonaires au tours du cycle ventilatoire etudiees par la methode d’oscillation. Bull. Physio-Pathol. Respirat. 7 : 173186, 1971. 14. RYKEN, M. L., JR. Experimental Investigation into a Commutative filter. Tech. Publ. TP-73-7, 1973, Naval Missile Center, Point Mugu, Calif., p. l-35. 15. SOBOL, B. J. Tests of ventilatory function not requiring maximal subject effort. II. The measurement of total respiratory impedance. Am. Rev. Respirat. Diseases 97 : 868-879, 1968. 16. SPANN, R. W., AND R. E. HYATT. Factors affecting upper airway resistance in conscious man. J. A&?l. Physiol. 3 1 : 708-7 12, 1971. 17. STANESCU, D. C., J. PATT~JN, J. CLEMENT, AND K. P. VAN DE WOESTIJNE. Glottis opening and airway resistance. J. A&p/. Physiol. 32 : 460-466, 1972. 18. VINCENT, N. J., R. KNUDSON, D. E. LEITH, P. T. MACKLEM, AND J. MEAD. Factors influencing pulmonary resistance. J. Appk Physiol. 29 : 236-243, 1970.
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