WO2005104944A1

WO2005104944A1 - Method of assessment of airway variability in airway hyperresponsiveness

Info

Publication number: WO2005104944A1
Application number: PCT/CA2005/000664
Authority: WO
Inventors: Geoffrey N. Maksym; Carolyn A. Lall
Original assignee: Dalhousie University
Priority date: 2004-05-04
Filing date: 2005-05-03
Publication date: 2005-11-10
Also published as: JP2007536026A; CA2565625A1; CN1972631A; AU2005237191A1; CN1972631B; US8172765B2; US20050247307A1; EP1742572A1; EP1742572A4; NZ551074A

Abstract

The invention relates to a method of assessing airway variability in airway responsiveness or asthma by measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing either a single or a plurality of input frequencies during a plurality of respiratory cycles of a patient; calculating the statistical variability of the Rrs fçr the patient; and, correlating the statistical variability of the Rrs of the patient to a standard curve to quantify the degree of asthma of the patient. The invention also enables the effectiveness of a bronchoactive agent to be measured.

Description

METHOD OF ASSESSMENT OF AIRWAY VARIABILITY IN AIRWAY HYPERRESPONSIVENESS

FIELD OF THE INVENTION The invention relates to a method of assessing airway variability in airway responsiveness or asthma by measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing either a single or a plurality of input frequencies during a plurality of respiratory cycles of a patient; calculating the statistical variability of the Rrs for the patient; and, correlating the statistical variability of the Rrs of the patient to a standard curve to quantify the degree of asthma of the patient. The invention also enables the effectiveness of a bronchoactive agent to be measured.

BACKGROUND OF THE INVENTION Asthma is a disease affecting 100 - 150 million people worldwide with deaths from asthma reaching 180 000 annually [']. Asthma affects all age groups but often starts in childhood and is the most common chronic childhood disease affecting 6.3 million children worldwide ["]. Asthma is also more prevalent in the developing world with the incidence in children increasing by approximately 75% every 10 years in the United States ['"]. However currently there is no easy accepted non-invasive method of measuring pulmonary function in children under the age of 6. , The standard measure of lung function used in older children and adults is spirometry, a learned manoeuvre that depends on the active cooperation of the subject, therefore it does not produce reliable and reproducible results in young children (<6 yr). Techniques used in infants are not suitable over the age of one year, and usually require sedation [^1V,^V]. The forced oscillation technique offers a non invasive method of assessing lung mechanics that requires only passive patient cooperation [^V1,^V11]. FOT can also be applied in adults, and is also useful when spirometry is difficult, unpractical or infeasible, for example in the assessment of the elderly, paralysed and unconscious as well as in sleep studies and with mechanically ventilated patients. The forced oscillation technique was first introduced in 1956 by Dubois and colleagues [^v ] as a method of characterizing respiratory mechanics. In this technique, low-amplitude pressure oscillations are applied at the patient's airway opening during spontaneous breathing, the mechanical properties of the patient's respiratory system are derived from the pressure and flow signals recorded at the airway opening. Respiratory system impedance (Zrs) is a ratio of the Fourier transforms of pressure and flow, where the real and imaginary parts of Zrs are the resistance (Rrs) and reactance (Xrs) of the respiratory system. These mechanical properties of the respiratory system are indicative of airway obstruction. FOT has been shown to provide reproducible Rrs values at fixed frequencies as a function of sex, age and height in children [^1X]. Mean Rrs has been found to provide reproducible and reliable results in healthy children, asthmatic children and children with cystic fibrosis. These results are concordant with forced expiratory volume in 1 second (FEVi) measures in the children who were able to perform FEV1 ™ " ™]. FOT studies in adults have shown that mean Rrs and mean respiratory system reactance (Xrs) provide an indicator of airway caliber and can distinguish between asthma, chronic bronchitis and emphysema [^XV,^XV1,^XV11]. Airway hyperresponsiveness is the exaggerated airway narrowing which occurs in response to airway challenge with a wide variety of pharmacological agonists and non- specific irritants such as cold, dry air and oxidant gases [^xvm]. One standard measurement of airway hyperresponsiveness is performed by delivering methacholine or histamine to inhibit deep inhalations and increase airway hyperresponsiveness in increasing doses and measuring FEVi after each dose. Asthma is indicated by a smaller concentration that elicits a measured decrease in FEVi indicating a greater reactivity of the airways [^X1X,^XX]. More recently, increased variation in airway resistance, standard deviation of Rrs measured by FOT in adults, has been shown to ,be a useful measure of airway smooth muscle reactivity and thus bronchial hyperresponsiveness [^XX1]. Airflow limitation in bronchial hyperresponsiveness is largely determined by airway smooth muscle constriction. Airway diameters have been shown to be constantly changing within a breathing cycle and over short periods of time [^XX11]. This leads to a respiratory system resistance that also varies over a breathing cycle, which can be reduced by deep inhalation [^XX111]. Lack of significant bronchodilation or bronchoprotection due to deep inhalation may contribute to the variability in airway calibre that characterizes asthma [^XX1V ₅ ^XXV].

SUMMARY OF THE INVENTION In accordance with the invention, there is provided a method of assessment of airway variability in airway responsiveness or asthma comprising the steps of measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing either a single or a plurality of input frequencies during a plurality of respiratory cycles of a patient; calculating the statistical variability of the Rrs for the patient; and, correlating the statistical variability of the Rrs of the patient to a standard curve to quantify the degree of airway responsiveness or asthma of the patient. In accordance with an alternate embodiment, the invention also provides a method of determining the effectiveness of a pharmacological agonist or antagonist comprising the steps of: measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing either a single or a plurality of input frequencies during a plurality of respiratory cycles of a patient; measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing a plurality of input frequencies during a plurality of respiratory cycles of a patient having been administered pharmacological agonist or antagonist; calculating the statistical variability of the Rrs for the patient for each of the first two steps; and, comparing the statistical variability of the Rrs to determine the effectiveness of the pharmacological agonist or antagonist. In accordance with another embodiment, the invention provides a method of determining the effectiveness of a pharmacological agonist or antagonist on altering airway diameter variability comprising the steps of: measuring the variation of reactance (Xrs) by a forced oscillation technique utilizing a plurality of input frequencies during a plurality of respiratory cycles of a patient both pre- and post-administration of a pharmacological agonist or antagonist; calculating the Xrs for the patient for each of the pre- and post-administration steps; and, comparing Xrs to determine the effectiveness of the pharmacological agonist or antagonist. A method for determining baseline values of variations of resistance (Rrs), variations in reactance (Xrs) and standard deviation of resistance (SDRrs) and the changes in these values in response to bronchoactive agents comprising the steps of: measuring and storing closed impedance (Zc); measuring and storing open impedance (Zo) measuring and compensating baseline subject impedance Zm(t) over several cycles to determine Zrs(t); measuring and comparing Rrs, Xrs and variations in Rrs and Xrs; administering a bronchoactive agent to a patient; measuring post drug impedance Zm_p and compensating to determine Zrs_p; calculating post-drug and pre-drug Rrs, Xrs and variation in Rrs and Xrs; comparing post-drug and pre-drug values of Rrs, Xrs and variations in Rrs and Xrs to standard values to determine if the Rrs, Xrs and variation in Xrs and Rrs are normal or abnormal. BRIEF DESCRIPTION OF THE DRAWINGS The invention is described with reference to the following drawings wherein: Figure 1 is a schematic diagram of a test protocol, where FO is a forced oscillation measurement, and BD is administration of a pharmacological agonist or antagonist; Figure 2 are two plots with the top panel showing FOT Rrs over time calculated once per second at 4 and 34 Hz in an asthmatic child and the bottom panel showing FOT median Rrs and median Xrs over frequency in an asthmatic child calculated from 180 seconds; Figure 3 are plots showing percent predicted FEVI vs. median Rrs and FEVI vs. standard deviation of Rrs from asthmatic children at low, middle and high frequencies before (diamonds) and after (squares) bronchodilator, with one diamond and one square from each subject; Figure 4 are three plots of standard deviation of Rrs vs. median Rrs at low, middle and high frequencies pre (diamonds) and post (squares) bronchodilator from each asthmatic child; Figure 5 is a plot of the coefficient of variation of Rrs vs. frequency in all asthmatic subjects where each line is from a different subject; Figure 6 is a plot of the simulated effect of noise on Rrs values; Figure 7 is a plot of median Rrs in asthmatic and control children; Figure 8 is a plot of the baseline standard deviation of Rrs in asthmatic and control children; Figure 9 is a plot of the median Rrs in control children before and after administration of bronchrodilator or sham saline dose; Figure 10 is a plot of the standard deviation of Rrs in control children vs. frequency before and after administration of a bronchodilator or sham saline dose; Figure 11 is a plot of coherence calculated between pressure (circles) and flow (crosses) signals from two different representative subjects at the oscillation frequencies; Figure 12 is a representative example of magnitudes of fast Fourier transformed pressure and flow signals vs. frequency showing the oscillation frequencies used (4, 10, 14, 22, 26, 34 Hz) and breathing noise at low frequencies; Figure 13 is a representative plot of signal to noise ratios computed from data in Figure 12 vs. frequency for pressure signal (circles) and flow signals (squares) for each oscillation frequency; Figure 14 is a plot of percent predicted FEVI versus median Xrs from children with asthma pre (diamonds) and post bronchodilator (squares) at low, mid and high frequencies; Figure 15 is a plot of median Xrs pre- and post- bronchodilator in asthmatic children versus frequency; Figure 16 is a plot showing a comparison of FEV1%, median Rrs, SDRrs and median Xrs in response to BD, with error bars showing standard error; Figure 17 is a plot of the relationship between SDRrs and Xrs before bronchodilator (diamonds) and post bronchodilator (squares) in children with asthma; Figure 18 is a plot of the relationship between % change in SDRrs with bronchodilator and change in Xrs with bronchodilator in children with asthma. Figure 19 is a flow chart of a method to determine baseline Rrs, Xrs and SDRs and the changes in these values in response to bronchoactive agents; and, Figure 20 is a flow chart of a method to determine baseline values of Rrs, Xrs and SDRs, and changes in these values in response to bronchoactive agents.

DETAILED DESCRIPTION OF THE INVENTION In accordance with the invention, a patient study was performed in order to measure the statistical variation in the respiratory system resistance (Rrs) by a forced oscillation technique (FOT). The study provided a measure of baseline bronchial activity and thus airway smooth muscle activity in terms of optimal frequency of measurement, sensitivity in distinguishing between asthmatic and control children and a measure of bronchodilator (BD) effect in asthmatics which also enabled distinguishing between asthmatic and control children. The study also measured the reactance of the patient to determine changes in airway stiffness and degree of airway closure caused by changes in airway smooth muscle activity, in terms of optimal frequency of measurement, sensitivity in distinguishing between asthmatic and control children and a measure of bronchodilator (BD) effect in asthmatics, which also enabled distinguishing between asthmatic and control children.

Experimental The study measured, by FOT, the median Rrs, standard deviation of Rrs (SDRrs) and Xrs at several frequencies between 4 and 34 Hz of a) asthmatic children and b) non- asthmatic children using spirometry performed both pre- and post- bronchodilator. Hypothesis: Children with asthma have a greater value of both median Rrs and standard deviation of Rrs compared to control children and both may be negatively correlated with FEVi measurements. Bronchodilator administration reduces median Rrs and standard deviation of Rrs. Bronchodilator administration increases Xrs. Protocol: Forty four physician-diagnosed asthmatic children between the ages of 7 and 13 were measured. The test protocol followed for each child is shown in Figure 1. Approximately thirty control children in the same age group with no history of respiratory problems were also measured. Half of the control children were given a placebo instead of a bronchodilator. Flow-volume curves were recorded with a portable, pneumotachograph-based spirometer (PrestoFlash, Burdick, Inc., Milton, WI) to determine FEVi and FEF₂₅.₇so_o This spirometer was calibrated daily with a volumetric syringe. Acceptance of flow volume curves was according to international criteria "Standardization of Spirometry, 1994

Update. American Thoracic Society. Am J Respir Crit Care Med 152:1107-1136, 1995." Percent predicted values were calculated based on reference values for this age group "Knudson, et al. The maximal expiratory flow-volume curve. Normal standards, variability, and effects of age. Am Rev. Respir Dis. 113:587-600, 1976. Each forced oscillation (FO) measurement was made using a custom FOT device constructed at Dalhousie University. The FOT device included pressure and flow transducers upon a breathing tube and a system for generating low-amplitude pressure oscillations (approximately ±1 cm H₂O) at multiple frequencies ranging from 4-34 Hz. The signal driving the pressure oscillations was composed of frequency components at 4, 6, 10, 14, 22, 26 and 34 Hz within a one second oscillation period that was continuously repeated. While different oscillation period durations could be chosen depending on the oscillation frequencies, as long as the oscillation period was an integer multiple of the inverse of all oscillation frequencies, one second was used in all cases. Each patient was asked to breathe through the breathing tube for three recording periods of one minute duration with nose clips on and with their cheeks supported. Between each of the one minute recording periods were provided breaks of approximately 10 seconds during which patients could swallow if needed. Pressure and flow data were collected at 700 Hz using a data acquisition system. For each second of the FO measurement median Rrs, standard deviation of Rrs, median Xrs and standard deviation of Xrs were measured at 4, 6, 10, 14, 22, 26 and 34 Hz. A bias fan provided approximately 12L/min of fresh air through long stiff walled flexible tubes and the subject breathed through a mouthpiece and filter. The impedance of the patient's respiratory system (Zrs) is derived from pressure and flow signals according to the formulae:

2, - ?M1 (1) V ( f ) „ ZcZm ZoZc ...

Zrs (2) Zc - Zm Zo + Zc where P(f) and V(f) are the Fourier transforms of pressure and flow respectively of one or more oscillation periods; Zc and Zo are calibrated impedances obtained with the FOT device system closed (Zc) and open to the atmosphere (Zo), Zm is a time series of the measured impedance. Equation (1) and (2) are applied for each repeated oscillation period, forming a time series of Zm and Zrs with lengths equal to the number of oscillation periods. If multiple oscillation periods of pressure and flow are used in the Fourier transforms of Equation (1), the length of Zm and Zrs correspondingly decreases by that multiple. Zc and Zo are typically calculated from recordings of up to 1 minute or until coherences > 0.95 are achieved. The correction of Zm by the system impedances compensates for resistive and reactive losses within the measuring device and any filter at the patient attachment as described in "Schuessler TF and Bates JH. A computer- controlled research ventilator for small animals: design and evaluation. IEEE Trans Biomed Eng 42: 860-866, 1995." Successful application of the method required that measurement of Zrs be calculated including compensation for the impedance of the device (including any tubing or filters between the device and the patient). The impedance of the device is a significant amount of the measured Zrs and should be removed from Zm to accurately determine Zrs.

This was performed by providing an oscillatory pressure signal producing an oscillatory flow signal (consisting of either a single frequency or a range of frequencies as described above), and recording a measurement of impedance (Zm) with no patient at the device opening (ie. the open impedance or Zo), and another measurement of impedance but with the patient attachment closed by a stopper so that there are no leaks (ie. the closed impedance or Zc). After obtaining Zo and Zc with good coherence (> 0.95) patient Zrs and thus Rrs and Xrs can then be accurately calculated from Equations 1 and 2 above, when the Zm is recorded from a patient. Zrs is thus calculated from Zm, Zc and Zo forming a time series usually up to 180 points in length calculated once per oscillation period (1 second) from the three concatenated one minute recording periods, and cycles with inadequate coherence or signal to noise ratio are removed. Rrs and Xrs (Figure 2) are the real and imaginary parts of Zrs respectively. Rrs, Xrs and variation in Rrs were analyzed at different frequencies in asthmatic children and control children before and after a BD performed both pre- and post-spirometry. This allowed median Rrs, variation in Rrs and median Xrs calculated from the time series of Zrs to be examined over the frequency range 4-34 Hz, the effect of a BD on mechanical properties of the respiratory system of asthmatic and non-asthmatic children to be evaluated, the difference in mechanical properties of the respiratory system in control and asthmatic patients to be determined and the effectiveness and sensitivity of spirometry, median FOT Rrs, standard deviation of FOT Rrs, and median FOT Xrs to be evaluated.

Results: Asthmatics (Table 1) were physician diagnosed and most were taking regular anti- inflammatory medication.

Table 1: Summary of asthmatic patient population

In the asthmatic cohort median Rrs was negatively correlated with FEVi , with correlation coefficients of 0.561, 0.546 and 0.563 at low, middle and high frequency oscillations where low frequency includes average measurements at 4 and 6 Hz, middle frequency includes average of 10 and 14Hz and high frequency includes average of 22, 26 and 34 Hz (Figure 3, left panels, diamonds). Thirty eight of the forty children did not show clinically significant changes in FEVi or Rrs values after bronchodilator administration (p > 0.05). This is most likely because most were taking regular anti-inflammatory medication. Median increase in FEVi was 3.5 + 0.7% and decrease in Rrs was 16.9 + 2.8%, 14.2+ 2.1% and 5.4± 1.3% at low, middle and high frequencies seen as a slight upward and leftward shift from baseline to post bronchodilator values in the left panels of Figure 3 and in Figure 4 where diamonds are baseline values from each subject and squares are post-bronchodilator values from each subject. However, standard deviation of Rrs significantly decreased after bronchodilator administration by 40.1 + 5.8%, 36.0 + 6.5% and 56.2 + 2.1% (p<0.05) at low, middle and high frequencies seen as a slight upward and large leftward shift from baseline (diamonds) to post-bronchodilator values (squares) in the right panels of Figure 3 and downward shift from baseline (diamonds) to post-bronchodilator values (squares) in Figure 4. The coefficient of variation of Rrs measurements decreased as the frequency increased. This may be due to contamination of the signals by low frequency noise introduced by breathing (Figure 5). A simulated system was created to determine the effects of adding different types of noise to the measurements. Adding Gaussian noise increased the standard deviation of Rrs by a constant (Figure 6). However, adding noise similar to the type of noise introduced by breathing during measurements, that follows a 1 /frequency curve, caused the calculated Rrs values to have higher standard deviation at low frequencies (Figure 6). This was similar to the pattern of standard deviation of Rrs seen in the actual measurements (Figure 5). This indicates that measurements below 20Hz are more likely to be affected by breathing and may be less reliable than those measured at higher frequencies. In conclusion, bronchodilator administration only slightly decreased median resistance and FEVi in asthma but significantly reduced variability in airway resistance. Thus, measurement of Rrs by FOT at frequencies not affected by breathing noise (typically above 10 Hz) may provide a useful measure of airway smooth muscle activity by measuring variations in Rrs not detected by traditional lung function measurements such as spirometry in children with asthma. This would also be useful in adults as it does not require a learned manoeuvre. In addition, it was also found that Xrs, particularly measured at higher frequencies is a sensitive measure of bronchodilator effect as shown in Figures 14-18. More specifically, Figure 14 shows the percent predicted FEVI versus median Xrs from children pre- (diamonds) and post-bronchodilator (squares) at low, mid and high frequencies. Figure 15 shows median reactance pre- and post- bronchodilator in asthmatic children versus frequency. Figure 16 is a comparison of FEV1%, median Rrs, standard deviation of resistance

(SDRrs) and median Xrs in response to BD. This shows that SDRrs and median Xrs are more sensitive measures of bronchodilator effect than either FEVI or Median Rrs, in children with asthma aged 6-9. Figure 17 shows the relationship between SDRrs and Xrs before bronchodilator (diamonds) and post bronchodilator (squares) in children with asthma. Each point represents the Xrs and SDRrs from an individual and shows there is a moderate dependency between Xrs and SDRrs either before or after bronchodilator, such that those with high SDRrs also have low Xrs. Thus, measures of Xrs and SDRrs can be used in combination for diagnosing and monitoring asthma. Figure 18 shows the relationship between % change in SDRrs with bronchodilator and change in Xrs with bronchodilator in children with asthma. Each point represents the Xrs and SDRrs from an individual. It is apparent that a decrease in SDRrs is usually found with an increase in Xrs (especially at mid frequencies). Thus these measures could be used together to determine the efficacy of a particular bronchodilator.

Control Data with Placebo The control data with half taking a placebo instead of a bronchodilator was collected. The control data with half taking a bronchodilator was collected. The controls (Table 2) were all children with no history of respiratory illness.

Table 2: Summary of the control patient population

Median Rrs was negatively correlated with FEVi, with correlation coefficients of 0.531, 0.555, and 0.436 at low, middle and high frequency oscillations. There was not a significant change in FEVi with placebo administration with an average increase of 1.3 ± 0.13% increase. There also was no significant change in median Rrs and standard deviation of Rrs with placebo administration. There was not a significant difference (7.62%, p > 0.05) in baseline FEVi measured in controls and asthmatic children. Median resistance of asthmatics was significantly (p < 0.05) higher than controls at frequencies equal to or lower than 26Hz with a percent difference of 28.9% and 31.1% at 4 and 6Hz respectively (Figure 7). This shows that Median Rrs measured at 4 or 6Hz is approximately 4 times more sensitive than FEVi as an indicator of asthma in children. Standard deviation of Rrs was 88.65% higher in asthmatics compared to controls at 4Hz but not significantly different (p > 0.05) at the other frequencies measured (Figure 8). Since we believe low frequency measurements were contaminated by noise this may indicate that noise was greater in the asthmatics. There was a slight change in median Rrs with bronchodilator administration in control children at low frequencies less than 14 Hz but not at higher frequencies (Figure

9)- There was no significant change in standard deviation of Rrs with either placebo or bronchodilator administration in control children at any frequency (Figure 10). As shown in Figure 16, there is no significant difference found with BD in control subjects. Thus, a decrease in variation of resistance by FOT at frequencies not affected by breathing noise that occur with a bronchodilator may provide a useful measure of elevated airway smooth muscle activity that occurs in asthma. Figure 11 is a plot of coherence between pressure (circles) and flow signals (crosses), Figure 12 is a plot of the Fourier transformed pressure and flow signals and, Figure 13 is a plot of the signal to noise ratios for pressure (circles) and for flow (crosses) for each oscillation frequency. Signal to noise was calculated in the frequency domain for each oscillation frequency using as a measure of the noise amplitude the noise present in the frequencies adjacent to the oscillation frequencies. Signals were considered to be valid if their coherence was greater than 0.9, and also inferred that the high signal to noise ratios of greater than 20 indicated good signal quality. With reference to Figure 19, a method is described for determining baseline values of Rrs, Xrs and SDRs and the changes in these values in response to bronchoactive agents. In this embodiment, at step 1, closed impedance Zc is measured and stored. At step 2, open impedance Zo is measured and stored. At step 3, the baseline subject impedance Zm(t) over several cycles is measured and compensated over several cycles to determine Zrs(t). At step 4, Rrs, Xrs and variations in Rrs and Xrs are measured and if desired are compared (step 10) to standard values to compute % predicted to determine if the Rrs, Xrs and variation in Xrs and Rrs are normal or abnormal. At step 5, a bronchoactive agent may be administered to the patient. At step 6, the post drug impedance Zm_p is measured and compensated to determine Zrs_p. At step 7, Rrs, Xrs and variation in Rrs and Xrs are calculated. At step 8, post-drug and pre-drug values of Rrs, Xrs and variations in Rrs and Xrs are measured. Optionally, if the drug dose is increased or repeated at step 9, steps 6-8 are repeated. With reference to Figure 20, an alternate method is described for determining baseline values of Rrs, Xrs and SDRs and the changes in these values in response to bronchoactive agents. In this method at step 20, closed impedance Zc is measured until coherence and signal to noise ratio at each frequency is acceptable and stored. At step 21, open impedance Zo is measured until coherence and signal to noise ratio is acceptable and stored. At step 22, the baseline subject impedance Zm(t) is measure and Zm at each frequency is calculated once per period of the perturbation waveform. At step 23, Zm is compensated with Zo and Zc to compute baseline Zrs. At step 24, periods of Zrs are removed for which coherence and/or signal to noise ratio was low. At step 25, Rrs, Xrs and variation in the Rrs and Xrs are calculated and if desired are compared (step 31) to standard values to compute % predicted to determine if normal or abnormal. At step 26, a bronchoactive agent may be administered. At step 27, post drug impedance Zm_p is measured and compensated to determine Zrs_p. At step 28, Rrs, Xrs and variations in Rrs and Xrs are calculated. At step 29, baseline values of Rrs, Xrs and variations in Rrs and Xrs are compared to post-drug values. At step 30, if increasing or repeating the drug dose, the increased drug dose is administered and steps 27-29 are repeated.

['] http://www.who.int/mediacentre/factsheets/fs206/en/

["] http://www.lungusa.org/asthma/ascpedfac99.html

['"]http://www.getasthmahelp.org/quickfacts.asp

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Claims

1. A method of assessment of airway variability in airway responsiveness or asthma comprising the steps of: measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing either a single or a plurality of input frequencies during a plurality of respiratory cycles of a patient; calculating the statistical variability of the Rrs for the patient; and, correlating the statistical variability of the Rrs of the patient to a standard curve to quantify the degree of asthma of the patient.

2. A method as in claim 1 wherein calculating the statistical variability of the Rrs is a calculation of any one of or a combination of standard deviation or high/low Rrs measurements.

3. A method of determining the effectiveness of a pharmacological agonist or antagonist on altering airway diameter variability comprising the steps of: measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing a plurality of input frequencies during a plurality of respiratory cycles of a patient; measuring the variation of resistance (Rrs) by a forced oscillation technique utilizing a plurality of input frequencies during a plurality of respiratory cycles of a patient having been administered a pharmacological agonist or antagonist; calculating the statistical variability of the Rrs for the patient for each of the first two steps; and, comparing the statistical variability of the Rrs to determine the effectiveness of the pharmacological agonist or antagonist.

4. A method as in claim 3 wherein the pharmacological agonist or antagonist is a bronchodilator.

A method as in claim 3 wherein the pharmacological agonist or antagonist is a bronchoconstrictor.

6. A method of determining the effectiveness of a pharmacological agonist or antagonist on altering airway diameter variability comprising the steps of: measuring the variation of reactance (Xrs) by a forced oscillation technique utilizing a plurality of input frequencies during a plurality of respiratory cycles of a patient both pre- and post-administration of a pharmacological agonist or antagonist; calculating the Xrs for the patient for each of the pre- and post-administration steps; and, comparing Xrs to determine the effectiveness of the pharmacological agonist or antagonist.

7. A method as in claim 6 wherem the pharmacological agonist or antagonist is a bronchodilator.

8. A method as in claim 6 wherein the pharmacological agonist or antagonist is a bronchoconstrictor.

9. A method as in claim 6 where the impedance of the measuring device is removed by a compensation algorithm.

10. A method as in claim 6 wherein the effectiveness of a pharmacological agonist or antagonist is determined by a comparison of any one of or a combination of standard deviation of Rrs or high/low Rrs measurements or Xrs measurements between pre- and post- pharmacological agonist or antagonist administration in a patient.

11. A method as in claim 1 further comprising the steps of determining the noise level and the signal to noise ratio contributing to the assessment of airway resistance variability for each oscillation frequency of the pressure oscillations, including: obtaining the coherence of the pressure with flow signals; obtaining a Fourier transform of multiple cycles of pressure and a Fourier transform of multiple cycles of flow; obtaining the absolute value of the pressure and flow signals at each frequency of oscillation; obtaining the average of the absolute values of the pressure and flow signals for a region of frequencies adjacent to the oscillation frequencies not including any oscillation frequencies that the signal to noise ratio for either pressure or flow is the ratio of the signal, determined as the magnitude of the pressure or flow at the oscillation frequency, divided by the noise, determined as the magnitude of the pressure or flow in a region of frequencies adjacent to the oscillation frequency not including any oscillation frequency.

12. A method for determining baseline values of variations of resistance (Rrs), variations in reactance (Xrs) and standard deviation of resistance (SDRrs) and the changes in these values in response to bronchoactive agents comprising the steps of: a. measuring and storing closed impedance (Zc); b. measuring and storing open impedance (Zo) c. Measuring and compensating baseline subject impedance Zm(t) over several cycles to determine Zrs(t); d. Measuring and comparing Rrs, Xrs and variations in Rrs and Xrs; e. Administering a bronchoactive agent to a patient; f. Measuring post drug impedance Zmp and compensating to determine Zrsp; g. calculating post-drug and pre-drug Rrs, Xrs and variation in Rrs and Xrs; h. comparing post-drug and pre-drug values of Rrs, Xrs and variations in Rrs and Xrs to standard values to determine if the Rrs, Xrs and variation in Xrs and Rrs are normal or abnormal.