Characterization Of Atopy And Asthma Severity Levels In Children In Orange County, CA

Asthma is a heterogeneous and complex condition characterized by chronic airway inflammation, which may be clinically stratified into three main phenotypes: type 2 (T2) low, T2-high allergic, and T2-high non-allergic asthma. This real-world study investigated whether phenotyping patients with asthma using non-invasive parameters could be feasible to characterize the T2-low and T2-high asthma phenotypes in clinical practice. This cross-sectional observational study involved asthmatic outpatients (n = 503) referring to the Severe Asthma Centre of the San Luigi Gonzaga University Hospital. Participants were stratified according to the patterns of T2 inflammation and atopic sensitization. Among outpatients, 98 (19.5%) patients had T2-low asthma, 127 (25.2%) T2-high non-allergic, and 278 (55.3%) had T2-high allergic phenotype. In comparison to T2-low, allergic patients were younger (OR 0.945, p < 0.001) and thinner (OR 0.913, p < 0.001), had lower smoke exposure (OR 0.975, p < 0.001) and RV/TLC% (OR 0.950, p < 0.001), higher prevalence of asthma severity grade 5 (OR 2.236, p < 0.05), more frequent rhinitis (OR 3.491, p < 0.001) and chronic rhinosinusitis with (OR 2.650, p < 0.001) or without (OR 1.919, p < 0.05) nasal polyps, but less common arterial hypertension (OR 0.331, p < 0.001). T2-high non-allergic patients had intermediate characteristics. Non-invasive phenotyping of asthmatic patients is possible in clinical practice. Identifying characteristics in the three main asthma phenotypes could pave the way for further investigations on useful biomarkers for precision medicine.

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Semiautomatic Segmentation of Ventilated Airspaces in Healthy and Asthmatic Subjects Using HyperpolarizedHeMRI

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/624683 ◽

2013 ◽

Vol 2013 ◽

pp. 1-9 ◽

Cited By ~ 5

Author(s):

J. K. Lui ◽

A. S. LaPrad ◽

H. Parameswaran ◽

Y. Sun ◽

M. S. Albert ◽

...

Keyword(s):

Respiratory Diseases ◽

Vital Capacity ◽

Asthma Severity ◽

Forced Expiratory Volume ◽

Quantitative Characterization ◽

Hyperpolarized Helium ◽

Semiautomatic Segmentation ◽

Significant Difference ◽

Highly Correlated

A segmentation algorithm to isolate areas of ventilation from hyperpolarized helium-3 magnetic resonance imaging (HP3He MRI) is described. The algorithm was tested with HP3He MRI data from four healthy and six asthmatic subjects. Ventilated lung volume (VLV) measured using our semiautomated technique was compared to that obtained from manual outlining of ventilated lung regions and to standard spirometric measurements. VLVs from both approaches were highly correlated (R=0.99;P<0.0001) with a mean difference of 3.8 mL and 95% agreement indices of −30.8 mL and 38.4 mL. There was no significant difference between the VLVs obtained through the semiautomatic approach and the manual approach. A Dice coefficient which quantified the intersection of the two datasets was calculated and ranged from 0.95 to 0.97 with a mean of 0.96 ± 0.01 (mean ± SD). VLVs obtained through the semiautomatic algorithm were also highly correlated with measurements of forced expiratory volume in one second (FEV1) (R=0.82;P=0.0035) and forced vital capacity (FVC) (R=0.95;P<0.0001). The technique may open new pathways toward advancing more quantitative characterization of ventilation for routine clinical assessment for asthma severity as well as a number of other respiratory diseases.

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