Spring 2016 Diagnostics Section Bulletin

Spring 2016 Diagnostics Section Bulletin

Jeffrey M. Haynes, RRT, RPFT

Pulmonary Function Laboratory
St. Joseph Hospital
Nashua, NH
Work Email: jhaynes@sjhnh.org
Home Email: jhaynes3@comcast.net

Katrina Hynes, BAS, RRT, RPFT
Mayo Clinic Pulmonary Evaluation Laboratory
Rochester, MN 55905
(507) 284-4545

Former Chair
Matthew J O’Brien, RRT, RPFT
Pulmonary Diagnostic Lab
University of Wisconsin Hospital and Clinics
600 Highland Ave Room E5/520
Madison, WI 53792-5772
(608) 263-7001
Fax: (608) 263-7002

Technologist’s Notes: Is FEF25-75% a Meaningful Value in Adults?

Jeffrey M. Haynes, RRT, RPFT, FAARC

When I was a student way too many years ago, I was taught that the FEF25-75% was an important value to follow because it could reveal “small airways disease” and therefore indicate early COPD.

In a recently published editorial Dr. Paul Enright wrote: “The holy grail of pulmonary physiologists during my lifetime has been a test that will reliably detect early chronic airway obstruction (CAO). The most common example of a disease that starts in the silent zone of small airways is COPD due to cigarette smoking.”1

Unfortunately, that search must continue. One of the central problems with FEF25-75% is its wide range of normality. For example, the lower limit of normal (LLN) for adults falls to 40% of the predicted value by age 60.2 Quanjer et al. recently showed that FEF25-75% as an isolated defect (<LLN while FVC, FEV1, and FEV1/FVC ≥LLN) occurs in only 2.75% of cases.2


  1. Enright PL. Counterpoint: should oscillometry be used to screen for airway disease? No. Chest 2015;148(5):1135-1137.
  2. Quanjer PH, Weiner DJ, Pretto JJ, Brazzale DJ, Boros PW. Measurement of FEF25-75% and FEF75% does not contribute to clinical decision making. Eur Respir J 2014;43(4):1051-1058.

2015 Specialty Practitioner of the Year: Matt O’Brien, MS, RRT, RPFT

Katrina Hynes, BS, RRT, RPFT


Matt O’Brien, MS, RRT, RPFT, was named the 2015 Diagnostics Section Specialty Practitioner of the Year at the 61st AARC International Respiratory Convention & Exhibition held November 7-10 in Tampa, FL. Matt is the manager of the pulmonary diagnostic lab at the University of Wisconsin Hospital and Clinics in Madison.

Matt served as the Diagnostics Section chair from 2012-2014. He has authored peer-reviewed research and regularly speaks at local and national conferences. The Diagnostics Section is fortunate to have Matt as an active member. Congratulations to Matt on a well-deserved honor!

Impulse Oscillometry: Another Tool in the Pulmonary Function Technologist’s Toolbox

Dan Alamillo, BS, RRT-NPS, CPFT
UCSF Benioff Children’s Hospital Oakland,
Oakland, CA

The forced oscillation technique (FOT) was first described by Dubois and colleagues more than 60 years ago. FOT was billed as a noninvasive technique that “superimposed pressure fluctuations on the airway over a subject’s normal, quiet, tidal breathing.”1

Since then impulse oscillometry (IOS), one type of FOT, has shown considerable promise in both research and pulmonary function labs. IOS works by generating pulses of air at varying frequencies, which propagate through the airways where the kinetic energy from the forward pulses is reflected back to the IOS based on the resistance (forward energy) and reactance (reflected energy) of those airways. These opposite characteristics are collectively called “impedance” and generate frequency dependent curves that can be visually analyzed to “recognize changes in shape and magnitude and distinguish healthy respiratory function from its diseased state.” 2

Before beginning a discussion on the data derived from the impedance measurements, it would be apropos to have an understanding of those pulses of air that generate the data from an IOS study. A look at the velocity profiles of those air pulses at different frequencies should accomplish this goal rather nicely.

Although the IOS unit generates pulses of air at multiple frequencies, those traveling at 5 and 20 Hertz allow the clinician the best look at what is going on in the patient’s airways. Pulses of air traveling at 5 Hertz (R5) have relatively little kinetic energy propelling them forward. As a result, these pulses can penetrate deep into the airways and generate data regarding the resistance to airflow of the entire airway.

Conversely, pulses of air traveling at 20 Hertz (R20) travel with a significantly higher kinetic energy and only end up penetrating the larger airways, thus rendering information regarding the resistance to airflow of the large airways. Data regarding the small airways can be inferred via the percent difference between the resistance to airflow of the entire airway (R5) and that of the large airway (R20). This differential is called the R5-R20 difference and is calculated by the IOS processor through the equation (R5-R20)/R5 x 100.




Figure 1: A depiction of the level of airway penetration due to the differing velocity profiles of air pulses at 5 and 20 Hertz and the derivation of the R5-R20 % difference.

It is from these frequency-dependent curves that data regarding the relative health of the airways can be ascertained. The data derived from an IOS study are as follows:

  • Resistance (R) [cmH2O/L/sec] is the force required to move air through the airways and is comprised of inertance (the force required to overcome inertia) and elastance (the force required to overcome the stiffness of the lung, chest wall, and tissues). (See Figure 2)The resistance to airflow will start at its highest pressure/volume point at the lower frequencies and then decrease as the frequency spectrum increases in a linear pattern. This response to changing frequencies is known as frequency dependence. In cases of distal obstruction, the curve will still exhibit frequency dependence but all of the resistance values will be significantly elevated.The same is true in cases of proximal obstructive physiology; the resistance values will all be significantly elevated, but the curve will now exhibit frequency independence, or no response to changing frequencies, thus maintaining an almost constant resistance value. In cases of a restrictive lung disease, the resistance curve will mimic that of the normal curve.
  • Reactance (X) [cmH2O/L/sec] refers to the elastic properties of the lung, including the lung’s ability to absorb energy (capacitance). (See Figure 2)A healthy lung will exhibit frequency dependence, but will start with a negative value due to the lung’s ability to passively distend at the lower frequencies (lower kinetic energy) but gradually increase with rising frequencies until the reactance value becomes positive.In cases of distal obstruction, the reactance curve will exhibit similar characteristics, such as frequency dependence and a gradual increase in reactance from the negative (at the lower frequencies) to the positive (at the higher frequencies). However the entire curve will have shifted to the left of normal due to the increased capacitance of these “floppy” lungs.A proximal obstructive physiology will yield reactance curves that are similar to a normal curve, whereas the restrictive lung disease will yield a reactance curve that is similar to that of the distal obstructive physiology.
  • Reactance at 5 Hz (X5) [cmH2O/L/sec] is the degree by which the lung passively distends at the lower frequency without reflecting any kinetic energy. (See Figure 3)
  • Resonant Frequency (FRES) [Hz} is the point at which the lung tissue transitions from passive distention to active stretch in response to the force of the pressure wave. It is the point where X is equal to zero. (See Figure 3)
  • Area of Reactance (AX) [cmH2O/L] is the area under the curve generated from X5 until you reach the FRES. (See Figure 3)

Figure 2 (Right): The different resistance and reactance curves based on the underlying pulmonary disease physiology. (From reference 3 with permission.)



Figure 3: The reactance curve showing the area of reactance (AX) and the resonant frequency (FRES).

Author’s Note: In the next issue, we’ll take a closer look at obtaining the data and interpretative strategies.


  1. Dubois AB, Brody AW, Lewis DH, Burgess BF, Jr. Oscillation mechanics of lungs and chest in man. J Appl Physiol 1956;8:587-594.
  1. Meraz EG1, Nazeran H, Ramos CD, Nava P, Diong B, Goldman MD, Goldman, CA. Analysis of impulse oscillometric measures of lung function and respiratory system model parameters in small airway-impaired and healthy children over a 2-year period. Biomed Eng Online 2011;Mar. 25;10:21. http://biomedical-engineering-online.com/content/10/1/21
  2. Komarow HD, Myles IA, Uzzaman A, Metcalfe DD. Impulse oscillometry in the evaluation of diseases of the airways in children. Ann Allergy Asthma Immunol 2011;106:191-199.

Back to Basics: How to Calculate Spirometry Values Without a Computer

Jeffrey M. Haynes, RRT, RPFT, FAARC

Many years ago when I sat for the NBRC RPFT exam, candidates were handed a test booklet and a ruler. You had to bring your own #2 pencil. There were no computers or Internet, and you had to wait 4-6 weeks to find out if you passed the exam.

Younger readers may be wondering why candidates would need a ruler to take a PFT exam. As a candidate you were expected to be able to calculate values like FVC, FEV1, FEF25-75%, and even back extrapolated volume from a volume-time curve. No computer, no calculator.

Calculating spirometry values by hand is actually pretty easy and I believe that this is a great exercise for those learning how to perform and interpret PFTs. In the example below, I calculated spirometry values by hand and compared my calculations against the computer.


The first task was to calculate the volume (vertical) and time (horizontal) scales in millimeters. On this graph 1 liter is 22 mm, so there is 0.045 L per mm. One second is 15 mm. The volume-time curve in this example is reported at BTPS, so there is no need to adjust volumes to BTPS.


I measured a distance of 60 mm from the bottom of the horizontal axis to the highest point of exhaled volume (green line). Since we’ve determined that volume changes 0.045 L per mm, 60 mm x 0.045 = 2.70 L. The computer generated FVC was 2.71 L. I was off by .25 mm, if you believe computers.


To calculate FEV1 simply follow the vertical line at 1 second (or draw one) up until it intersects the exhaled volume line (green line). Measure the distance from the horizontal line to the point of intersection. I measured 33 mm from the horizontal line to the point of intersection. Since we’ve determined that volume changes 0.045 L per mm, 33 mm x 0.045 = 1.48 L. The computer got it right this time (!): 1.48 L.


FEF25-75% is the forced expiratory flow in the middle half of the FVC. To calculate the FEF25-75%, we need to divide the volume exhaled in the middle half of the FVC by the time required to exhale that volume.

First, multiply the FVC by .25 and .75. In this example, the FVC25% (2.70 x .25) is .67 L and the FVC75% (2.70 x .75) is 2.02 L. The volume change between these points is 1.35 L (2.02 -.67).

Next we need to measure the time lapse between .67 exhaled to 2.02 exhaled. Divide .67 L by 0.045 to determine the vertical distance of FVC25%: .67/0.045 = 14.9, rounded up to 15 mm. Measure 15 mm up the vertical axis, then draw a horizontal line until it intersects the green exhaled volume line; this is .67 L. Do the same for FVC75%: 2.02/0.045 = 44.9, rounded up to 45 mm. Measure 45 mm up the vertical axis, then draw a horizontal line until it intersects the green exhaled volume line; this is 2.02 L.

Now draw vertical lines down from both points until they intersect the horizontal axis. Measure the distance between these vertical lines. In the example above, there is 34 mm between the .67 L and 2.02 L. Since 1 second is 15 mm, 34 mm is divided by 15 mm to calculate the time between .67 L and 2.02 L: 34/15 = 2.27 seconds.

Flow is volume change/time, so 1.35 L/2.27 seconds gives us an FEF25-75% of .59 L/second. The computer calculated an FEF25-75% of .61 L/second.

Take home message

While it is not likely that we’ll ever need to calculate spirometry values by hand, this is a great exercise for students and trainees to better understand where spirometry values come from.

Spirometer Calibration Checks and Biologic Control Testing: Not Just for PFT Labs Anymore

Jeffrey M. Haynes, RRT, RPFT, FAARC

Recently, I was asked to provide spirometry training for nurses in a physician practice. After a couple hours of classroom training it was time to do some hands-on testing. Job #1 was to verify that the office calibration syringe was producing 3L per stroke. The office syringe was tested on a PFT lab spirometer: perfect 3.0 liters (see below).


The next task was to verify the calibration of the aging office spirometers:

Office spirometer 3L calibration verification

ATS/ERS Standard: 3L +/- 3.5% (2.9-3.1)

Spirometer #1

Measured volume: 3.08 L, 2.7% error, passed (barely)

Spirometer #2

Measured volume: 3.14 L, 4.6% error, failed

Biologic control with office spirometers

As a biologic control for the PFT lab I was interested to see what my numbers would be on these spirometers. I performed testing on both spirometers then repeated testing on the PFT lab spirometer.


FVC and FEV1 were outside of my biologic control range (mean +/- 2 SD). Interestingly, while the calibration verifications were above the expected value, the FVC and FEV1 were below the expected biologic control values.

The Levey-Jennings plots below show the poor performance of the office spirometers.

diag_winter_2016_fig7 diag_winter_2016_fig8

OS = Office Spirometer


Spirometry testing, whether in a physician’s office or a PFT lab, should follow recommended quality assurance programs. While the current ATS/ERS spirometry guidelines do not make recommendations regarding biologic control testing for spirometry, they should.

As shown in this case, office spirometer #1 passed calibration verification but produced values outside of the expected range for a biologic control subject. The FVC and FEV1 from the office spirometers would not have fallen within inter-effort variability standards (150 ml) when compared to the PFT lab spirometer.

In response to these findings the office spirometers were immediately taken out of service. If one of the physicians in this practice compared office spirometry values to previously measured values in the PFT lab, he might wrongly conclude that the patient’s condition had deteriorated.

An Out-of-Control Biologic Control

Jeffrey M. Haynes, RRT, RPFT, FAARC

Biologic control testing of total lung capacity (TLC) via plethysmography indicated an out-of-control condition. The TLC was > 2 standard deviations above the mean value for the biologic control subject (see below).


Inspection of the closed shutter breathing plot of mouth pressure (y) vs. box pressure (x) showed a tight slope line without artifact.


Inspection of the appartus revealled that the MIP/MEP pinhole adaptor had been left in place. This resulted in a spuriously low mouth (alveolar) pressure, which caused the overestimation of TLC.




Repeated biologic control testing with the MIP/MEP adaptor removed produced expected values.



Accurate mouth (alveolar) pressure measurements are critically important during plethysmography testing. An underestimation of mouth pressure during closed-shutter breathing results in a flatter mouth pressure vs. box pressure slope. The mouth pressure vs. box pressure slope is represented by a numerical value, which is at the core of the thoracic gas volume calculation.


Examples of closed shutter breathing tangents: dashed line, rise < run, 30º angle, tangent value: .58; solid line, rise = run, 45º angle, tangent value: 1; dotted line, rise > run, 60º angel, tangent value: 1.7.



VTG = thoracic gas volume

PB = Atmospheric pressure in cm H2O

PH2O = pressure of water vapor

λ = tangent

K= box volume displaced by body surface area

As shown below, if the tangent value is 1 the VTG is 3,452 ml.


If everything stays the same but the tangent value changes to .58 because of an underestimation of mouth pressure, the VTG becomes 5,954 ml.


Teaching Point: Learn from my mistake (yes, it was me). Be sure to remove the MIP/MEP adaptor before measuring lung volumes!

2015 Bulletin Authors: A Note of Appreciation

Jeffrey M. Haynes, RRT, RPFT, FAARC, and Katrina Hynes, MHA, RRT, RPFT

We would like to extend a note of appreciation to all of the Diagnostics Section members who wrote articles for the Bulletin in 2015. Your willingness to donate your time and share your expertise with your colleagues is a testament to your professionalism.

Thank you!

Jason Blonshine, RRT, CPFT

Richard Johnston, CPFT

Denise Maginnis, RRT-NPS, RPFT, RDCS

Matt O’Brien, MS, RRT, RPFT

Balamurugan Panneerselvam, BS, CPFT, RPSGT

Martin Rohrer, BS, RRT, CPFT

Ralph Stumbo, RRT, CPFT

Jennifer Weltz Horpedahl, RRT-NPS, RPFT, AE-C

Ann Wilson, BS, RRT, RPFT

We also want to acknowledge the invaluable assistance and patience of AARC writer Debbie Bunch. Thank you Debbie!

Section Connection

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Next Bulletin deadline: Fall Issue: August 1.