title: Semiautomatic segmentation of longitudinal computed tomography images in a rat model of lung injury by surfactant depletion.
abstract: Quantitative analysis of computed tomography (CT) is essential to the study of acute lung injury. However, quantitative CT is made difficult by poor lung aeration, which complicates the critical step of image segmentation. To overcome this obstacle, this study sought to develop and validate a semiautomated, multilandmark, registration-based scheme for lung segmentation that is effective in conditions of poor aeration. Expiratory and inspiratory CT images were obtained in rats (n = 8) with surfactant depletion of incremental severity to mimic worsening aeration. Trained operators manually delineated the images to provide a comparative landmark. Semiautomatic segmentation originated from a single, previously segmented reference image obtained at healthy baseline. Deformable registration of the target images (after surfactant depletion) was performed using the symmetric diffeomorphic transformation model with B-spline regularization. Registration used multiple landmarks (i.e., rib cage, spine, and lung parenchyma) to minimize the effect of poor aeration. Then target images were automatically segmented by applying the calculated transformation function to the reference image contour. Semiautomatically and manually segmented contours proved to be highly similar in all aeration conditions, including those characterized by more severe surfactant depletion and expiration. The Dice similarity coefficient was over 0.9 in most conditions, confirming high agreement, irrespective of poor aeration. Furthermore, CT density-based measurements of gas volume, tissue mass, and lung aeration distribution were minimally affected by the method of segmentation. Moving forward, multilandmark registration has the potential to streamline quantitative CT analysis by enabling semiautomatic image segmentation of lungs with a broad range of injury severity.
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Yi
authors: Y
authors: Xin
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Gang
authors: G
authors: Song
authors: Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, Pennsylvania; and rahim.rizi@uphs.upenn.edu.
authors: Maurizio
authors: M
authors: Cereda
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Stephen
authors: S
authors: Kadlecek
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Hooman
authors: H
authors: Hamedani
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Yunqing
authors: Y
authors: Jiang
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Jennia
authors: J
authors: Rajaei
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Justin
authors: J
authors: Clapp
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Harrilla
authors: H
authors: Profka
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Natalie
authors: N
authors: Meeder
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Jue
authors: J
authors: Wu
authors: Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia.
authors: Nicholas J
authors: NJ
authors: Tustison
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: James C
authors: JC
authors: Gee
authors: Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania;
authors: Rahim R
authors: RR
authors: Rizi
mesh_terms: D000818:Animals; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008168:Lung / Q000000981:diagnostic imaging; D055370:Lung Injury / Q000139:chemically induced / Q000000981:diagnostic imaging* / Q000473:pathology*; D008297:Male; D051381:Rats; D017207:Rats, Sprague-Dawley; D013501:Surface-Active Agents / Q000009:adverse effects*; D014057:Tomography, X-Ray Computed / Q000379:methods
chemical_list: D013501:Surface-Active Agents
keywords: ARDS; computed tomography; image analysis; image registration; semiautomatic segmentation
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