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  • Title: Hyperpolarized 3He magnetic resonance imaging ventilation defects in asthma: relationship to airway mechanics.
    Author: Leary D, Svenningsen S, Guo F, Bhatawadekar S, Parraga G, Maksym GN.
    Journal: Physiol Rep; 2016 Apr; 4(7):. PubMed ID: 27053294.
    Abstract:
    In patients with asthma, magnetic resonance imaging (MRI) provides direct measurements of regional ventilation heterogeneity, the etiology of which is not well-understood, nor is the relationship of ventilation abnormalities with lung mechanics. In addition, respiratory resistance and reactance are often abnormal in asthmatics and the frequency dependence of respiratory resistance is thought to reflect ventilation heterogeneity. We acquiredMRIventilation defect maps, forced expiratory volume in one-second (FEV1), and airways resistance (Raw) measurements, and used a computational airway model to explore the relationship of ventilation defect percent (VDP) with simulated measurements of respiratory system resistance (Rrs) and reactance (Xrs).MRIventilation defect maps were experimentally acquired in 25 asthmatics before, during, and after methacholine challenge and these were nonrigidly coregistered to the airway tree model. Using the model coregistered to ventilation defect maps, we narrowed proximal (9th) and distal (14th) generation airways that were spatially related to theMRIventilation defects. The relationships forVDPwith Raw measured using plethysmography (r = 0.79), and model predictions of Rrs>14(r = 0.91,P < 0.0001) and Rrs>9(r = 0.88,P < 0.0001) were significantly stronger (P = 0.005;P = 0.03, respectively) than withFEV1(r = -0.68,P = 0.0001). The slopes for the relationship ofVDPwith simulated lung mechanics measurements were different (P < 0.0001); among these, the slope for theVDP-Xrs0.2relationship was largest, suggesting thatVDPwas dominated by peripheral airway heterogeneity in these patients. In conclusion, as a first step toward understanding potential links between lung mechanics and ventilation defects, impedance predictions were made using a computational airway tree model with simulated constriction of airways related to ventilation defects measured in mild-moderate asthmatics.
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