Identifying Airways Associated with Hyper-Reactivity in Asthma: Interfacing PET imaging and Dynamic Mechanical Function with 3D Airway Models N.T. Tgavalekos 1, R.S. Harris 2, M. F. Vidal Melo 2, G. Musch 2, T. Winkler 2, J. G. Venegas 2 and K.R. Lutchen 1 1 Department of Biomedical Engineering, Boston University, Boston, MA 2 Dept. of Anesthesia and Medicine, Massachusetts General Hospital, Boston, MA GOAL It has been proposed that the primary location of heterogeneous constriction resides in the peripheral airways. Imaging studies, confirm that ventilation distribution and, hence, airway constriction in asthmatics is heterogeneous. However, imaging technology cannot probe small airways (< 1mm.) in humans. Lung Mechanics PET Imaging Figure 4: The PET imaging technique for human subjects requires a bolus of 13 NN labeled saline solution to be injected intravenously. The 13 NN allows diffuses into the alveoli. The rate at which the tracer washes out is proportional to local ventilation. Gas trapping is identified as areas where 13 NN delivered to the alveoli has not washed out during breathing Figure 3:Lung resistance (R L ) and elastance (E L ) represent the mechanical load to breathing. Experimental studies (top panel) have shown that as asthma severity worsens, the frequency dependence and mean level of R L and E L increases. Morphometric modeling studies (bottom panel) suggest that the increased frequency dependence is a result of heterogeneous broncho constriction in the peripheral airways. The overall goal is to advance a new paradigm called Image-Functional Modeling (IFM), which synthesizes patient specific structure-function measures from imaging techniques with dynamic lung mechanics into 3D computational models. We desire to identify which alterations in specific anatomic structures and locations can and cannot simultaneously alter mechanical and ventilation lung function in a manner consistent with both imaging and mechanical data. ANATOMICALLY-BASED MODELING Structure FIGURE 1: A 3D asymmetric conducting airway tree structure described by Tawhai et al is created on a personalized basis via MRI and airway tree space filling algorithms. Function PATIENT SPECIFIC METHODS FIGURE 5: Left: PET scan mask defines the lung field for each subject. Using anatomic markers such as the heart, we approximated the corresponding 3D Model-based mask (right). The mask from the model only shows the terminal airways that actually lie in the same plane as the corresponding PET image mask for that slice. PET Scan Mask3D Model-Based Mask PET: Tracer Retention3D Model: Tracer Retention Figure 6: Example subject during an asthma attack. Left reveals, in red, portions of the PET data that retained the initial tracer at the end of the washout period (ie., hypo-ventilated alveoli). Right shows (in red) the terminal airways in the corresponding model slice assumed to be un-ventilated. Figure 7: 3D Model reconstruction. Left represents healthy model with all terminal branches well ventilated. Right shows the same model, but with hypo-ventilating alveolar regions (from PET data, Fig. 6) shown in red. SUMMARY To maintain consistency with both the PET images and mechanical data, closures and constriction of airways needs to occur small airways,particularly those below the resolution of imaging methods for humans (i.e. <1mm.). Using the IFM approach we expect that patient specific models may be developed to aid in interpreting structural conditions associated with lung function impairment and evaluating the functional impact of specific disease management strategies. Figure 8: Top: The computational model is used to identify airway constriction patterns that are consistent with the measured ventilation defects shown in Figure 6 simultaneous with dynamic R and E. Bottom: Predicted specific ventilation from Case 1 and 2 vs. measured from PET Case 1: Airways 4 mm and below constricted heterogeneously so that ventilation defects are localized in the exactanatomic locations as identified in the PET image data. Simulation does not predict well the measured mechanics (top right). Case 2: Airways.6 mm and below constricted heterogeneously as in Case 1. Simulation predicts the best matchwith the measured mechanics. FIGURE 2: We model each individual airway as a compliant tube. The airway terminate onto viscoelastic alveolar tissue elements. Whole lung R L and E L can be simulated from the network combination of all pathways. Acinus ventilation distribution can also be predicted from the network analysis. Case 1Case 2 normal under Ventilation Spectrum over Ventilation Distribution IMAGE FUNCTIONAL MODELING apex base Asthmatic:Post Challenge