Figure 4. (A) a mild responder, (B) a moderate responder, and (C) a severe responder. The top panels display the arterial blood gas measurements which were taken periodically. The middle and bottom panels display the dynamic R and E estimates

1
Tracking Severity and Distribution of Lung
Disease During Mechanical Ventilation Application
s to Bronchoconstriction and Respiratory Distress
Syndrome C. Bellardine1, E.P. Ingenito2, A.
Hoffman3, F. Lopez4, W. Sanborn4, and K.R.
Lutchen1 1Biomedical Engineering, Boston
University, Boston, MA, 2Pulmonary Division,
Brigham and Women's Hospital, Boston, MA, 3Tufts
Veterinary School of Medicine, N. Grafton, MA,
4Puritan Bennett/Tyco Healthcare, Pleasanton, CA
INTRODUCTION
RESULTS I (Figure 3 Bronchoconstriction)
RESULTS III (Figure 5 Correlations)

• Mechanical ventilation is required when a
  patient cannot generate sufficient pressures to
  maintain ventilation. The lungs ability to
  generate these pressures is governed primarily by
  the elastic recoil and the resistance of the
  respiratory system (E and R).
• With lung disease, R and E become elevated and
  increasingly more frequency dependent. The R and
  E from 0.1 to 8 Hz reflect the level and pattern
  of lung disease 1 and these data would aid in
  evaluating the efficacy of mechanical
  ventilation. Modern clinical ventilators apply
  simple flow waveforms containing energy primarily
  at one frequency. Therefore, the frequency
  dependence of R and E cannot be tracked.
• We have recently invented new broadband
  ventilation patterns known as Enhanced Ventilator
  Waveforms (EVWs) which contain discrete
  frequencies (from 0.1 to 8 Hz) blended to provide
  a tidal breath followed by a passive exhalation
  2 (Fig 1). In principle, these waveforms allow
  for estimation of R and E from 0.1 to 8 Hz during
  ventilation.

Figure 1. EVW flow and volume are plotted vs.
time. Note the enhanced frequency content in the
inspiratory flow waveform and also the passive
expiratory sections.

• Figure 5. Correlation between decrease in
  arterial PaO2 levels and increases in
  heterogeneity (A) and airway closure (B). Within
  both bronchoconstriction (blue) and RDS (red)
  models, data revealed a range of constriction
  conditions. The degree of heterogeneity and
  airway closures quantified from EVW data was
  strongly correlated with significant drops in O2.
  Both increased heterogeneity and airway closures
  are consistent with a substantial degradation of
  ventilation distrubution.

(A)
(B)
(C)
Figure 3. (A) a mild responder, (B) a moderate
responder, and (C) a severe responder. The top
panels display the arterial blood gas
measurements which were taken periodically. The
middle and bottom panels display the dynamic R
and E estimates calculated from the EVW. Data
corresponding to baseline, initial response,
final response, and albuterol is shown. With
increased severity of response, the R and E are
elevated at all frequencies. The severe
responder shows significant evidence of airway
closure (elevated E at 0.2 Hz) and heterogeneous
constriction (more frequency dependence). This
should impact ventilation distribution. In fact,
oxygen levels are extremely depressed and carbon
dioxide levels are elevated.
GOAL
SUMMARY
To advance the delivery of an EVW for routine
clinical ventilation and evaluate whether the
frequency dependence of R and E provide insight
on degradation of lung gas exchange function.

• In all sheep the EVW sustains ventilation
  similarly to conventional ventilation but the EVW
  permitted insight on the level and distribution
  of lung disease.
• Data during bronchoconstriction revealed a range
  of constriction conditions from mild and
  homogeneous to severe and heterogeneous with
  airway closures. Often there was lack of
  complete improvement in R and E with albuterol or
  recruitment maneuvers. This was consistent with
  a pattern of airway closures that would not
  reopen.
• In the ARDS lung injury model, the EVW revealed
  the progression of the disease and showed that
  the extent of the defects in ventilation were
  consistent with the heterogeneity of constriction
  and airway closure.
• Detailed analysis of all data (Figure 5)
  indicated that the degradation in PaO2 (gas
  exchange) was highly correlated with features of
  dynamic R and E associated with functional airway
  closures and heterogeneities. Both features
  would imply degradation in ventilation
  distribution leading to poor ventilation-perfusion
  matching.
• We conclude that the EVW is a viable new
  ventilation method that can simultaneously
  provide clinically unique information regarding
  the mean level and heterogeneity of lung
  constriction. The degree of heterogeneity
  directly reflects the mechanical requirements of
  breathing and potential ventilation-perfusion
  mismatches. This unique information could be the
  basis to of more knowledgeable and effective
  clinician intervention with regards to treatment
  and ventilator weaning strategies.

METHODS
RESULTS II (Figure 4 RDS Model)

• The EVW was applied in 5 sheep before and after
  a bronchial challenge.
• Measured arterial O2 and CO2. EVW processed to
  obtain dynamic inspiratory R and E vs. frequency.
• PROTOCOL
• Stabilize sheep on conventional ventilation for
  15 minutes
• Collect baseline dynamic R and E measurements
• Deliver nebulized carbochol (16mg/ml for 2
  minutes). Monitor response through blood gas and
  R and E.
• Deliver albuterol MDI. Obtain final R and E
  estimates.
• The EVW was then applied in the same 5 sheep
  before and during an oleic acid lung injury model
  of ARDS and blood gases were once again tracked
  along with lung mechanics.

Figure 2. The EVW was implemented in a prototype
of the NPB840 (Puritan Bennett/Tyco Healthcare)
ventilator shown above.
DATA ANALYSIS

• The flow and pressure at the airway opening were
  measured (Qao and Pao, respectively). The
  inspiratory segments of the pressure and flow
  data were then isolated and fit to a
  trigonometric Fourier Series using the technique
  previously described by Kaczka 2.
• The corresponding low frequency components of R
  and E were recalculated to adjust for transient
  artifacts. The Qao and Pao were low pass filtered
  to isolate the low frequency components and fit
  to the following equation using a standard linear
  regression. Low frequency R and E were then
  re-estimated.

REFERENCES
(A)
(B)
(C)

• Lutchen, K.R. and B. Suki. Understanding
  pulmonary mechancis using the forced oscillation
  technique. Bioengineering Approaches to
  Pulmonary Physiology and Medicine. 1996.
• Kaczka, D.W., E. Ingenito, and K.R. Lutchen. A
  technique to determine inspiratory impedance
  during mechanical ventilation Implications for
  flow limited patients. Annals of Biomedical
  Engineering. 27 340-355, 1999.

Figure 4. (A) a mild responder, (B) a moderate
responder, and (C) a severe responder. The top
panels display the arterial blood gas
measurements which were taken periodically. The
middle and bottom panels display the dynamic R
and E estimates calculated from the EVW. With
increased severity of RDS, there were increased
airway closures, increased heterogeneity or
frequency dependence of both R and E, and
elevated R and E values at all frequencies.
Also, with increased severity, note the
depression of oxygen levels and increase of
carbon dioxide levels.