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A segmentation algorithm to isolate areas of ventilation from hyperpolarized helium-3 magnetic resonance imaging (HP  3 He MRI) is described. The algorithm was tested with HP  3 He 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 (FEV 1 ) ( 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.

computational and mathematical methods in medicine

Semiautomatic Segmentation of Ventilated Airspaces in Healthy and Asthmatic Subjects Using Hyperpolarized<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mtext>He</mml:mtext></mml:math>MRI

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