Nora Tgavalekos 1 Jose G. Venegas, Ph.D. 2 Kenneth Lutchen,Ph.D. 1 1 Respiratory and Physiological Systems Identification Laboratory Biomedical Engineering, Boston University 2 Massachusetts General Hospital, Anesthesia and Critical Care Positron Emission Tomography (PET) Based Image Assisted Modeling of Lung Mechanics in Asthmatics

Physiological Implications of Asthma Healthy Airway Asthmatic Airway Airway disease characterized by: airway smooth muscle hypertrophy, edema, mucous gland hypertrophy, and infiltration by eosinophils Airways are hyper-responsive to various stimuli During an asthma attack, airway smooth muscle contracts

Asymmetric Horsefield model Human Airway Tree Models Impedance of a Single Airway Airways Terminate on Alveoli with Viscoelastic Tissue

Previous Uses of Morphometric Tree Models Models suggest a relationship between the pattern of constriction and the impact on mechanical function Shapes are consistent with measured R L and E L in asthma

Advances in Airway Tree Models Kitaoka et al.(1999)

Creation 3-D Airway Trees o 1 2 Q Q Q Q ~ d n Murray described a relationship between flow rate (Q) and diameter (d) Model determines branching angles and lengths based on a space filling algorithm 11 22

Advancing 3D Models for Computation of Prediction of Function Application of arbitrary number of distinct heterogeneous patterns to specific anatomic locations throughout the tree Prediction of dynamic lung properties during heterogeneous constriction 3-D Model was advanced to incorporate a combined parallel-serial stacking algorithm which allows the following: Airway walls are non-rigid and allow for gas compression

1) Healthy Mechanical Impact of Regional Constriction Frequency Frequency Mechanics 2) Cranial-Dorsal Only: M = 50%; SD = 70% Front Ventilation % Reduction in Diameter % Distal Alveoli 3) Case 2 & Remaining with: M = 25%; SD = 35% 4) Case 3 & Remaining with: M = 25%; SD =70% Back closure baseline R L (cmH 2 O/L/S) E L (cmH 2 O/L)

Mild-Moderate Asthmatic Pre Challenge Regional Ventilation via PET Imaging EACH SLICE: Color intensity proportional to tracer washout rate calculated by integrating 32 time sequenced images Darker colors correspond to regions of low ventilation Lighter color correspond to high ventilated regions Apex Base

Regional Ventilation via PET Imaging Post Challenge EACH SLICE: Color intensity proportional to tracer washout rate calculated by integrating 32 time sequenced images Darker colors correspond to regions of low ventilation Lighter color correspond to high ventilated regions

Quantifying PET Images Baseline Post-Challenge 17%

Image Assisted Modeling Challenges Find a constriction pattern that : Creates closures primarily in the upper region of the lung with ~ 20 % of alveoli not communicating with the rest of the lung Matches subject specific R L and E L

Frequency (Hz) % Reduction in Diameter Frequency (Hz) Asthmatic #1 Post MCH: 2.56 mg/ml Image Assisted Modeling I: Constricted Asthmatic 1) Baseline 3) Case 2 & Remaining with: M = 50%; SD = 40% 2) Cranial-Dorsal Only: M = 50%; SD = 70% (d<2mm) 4) Case 2 & Remaining with: M = 50%; SD = 60% R L (cmH 2 O/L/S) E L (cmH 2 O/L) % Distal Alveoli

Conclusions An anatomically explicit airway tree model can now be used to predict R L and E L for anatomically applied patterns of constriction We now have the ability to predict structure – function on almost a personalized basis understand what range of constriction patterns are possible for different levels and degrees of asthma. This model has the potential to predict ventilation distributions in asthmatic patients

Acknowledgements Boston UniversityMass. General Hospital K. R. Lutchen, Ph.D.J. G. Venegas, Ph.D. Bela Suki, Ph.D.Scott Harris, MD. Heather Gillis, M.S. Dominick Layfield, Ph.D. Cand. Andrew Jensen, M.S. Cortney Henderson, Ph.D. Cand. Lauren Black, MS Cand. Carissa Belladrine, MS Cand. Skyler Greene &Tina Lewis, BS Cand.