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DOI:10.2214/AJR.07.3334
AJR 2009; 192:1037-1044
© American Roentgen Ray Society


Original Research

Automated Algorithm for Quantifying the Extent of Cystic Change on Volumetric Chest CT: Initial Results in Lymphangioleiomyomatosis

Vincent J. Schmithorst1, Talissa A. Altes2,3, Lisa R. Young4,5, David N. Franz6, John J. Bissler7, Francis X. McCormack5, Bernard J. Dardzinski1,8 and Alan S. Brody1

1 Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
2 Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA.
3 Present address: Department of Radiology, University of Virginia, Box 800170, Chalottesville, VA 22908.
4 Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH.
5 Division of Pulmonary and Critical Care Medicine, University of Cincinnati, Cincinnati, OH.
6 Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
7 Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH.
8 Present address: Merck and Co., Inc., Whitehouse Station, NJ.

OBJECTIVE. The purpose of our study was to develop a new method for quantifying the severity of cystic lung disease using chest CT and to evaluate this method in patients with lymphangioleiomyomatosis (LAM).

SUBJECTS AND METHODS. Eighteen patients with LAM (all women; mean age, 43.6 years) underwent chest CT and pulmonary function testing including diffusing capacity for carbon monoxide (DLCO). All patients were at their clinical baseline on the day of imaging. Standard quantitative CT metrics including the percentage of the lung volume < –910 HU and the 15th percentile of Hounsfield units were computed from the histogram of lung voxels. A new histogram analysis method was developed to compute the cyst volume and the volume of the remaining lung by segmenting the entire lung attenuation histogram into two underlying distributions, one from the cysts and the other from the remaining lung tissue.

RESULTS. The mean ± SD for quantitative lung metrics was 21% ± 16% for percentage < –910 HU, –915 ± 47 HU for 15th percentile of Hounsfield units, and 19% ± 13% for cyst volume. The correlation between pulmonary function tests and CT metrics was strongest for the percentage of cyst volume for all pulmonary function testing indexes, with correlations between forced expiratory volume in 1 second (FEV1) percentage predicted and the CT metrics of r = –0.52, r = 0.50, and r = –0.86 for the percentage of lung < –910 HU, the 15th percentile of Hounsfield units, and the percentage of cyst volume, respectively.

CONCLUSION. A new method for quantifying cyst volume as a percentage of total lung volume using chest CT correlates with pulmonary function parameters in patients with LAM and may have utility in the assessment of disease severity and progression of cystic lung diseases.

Keywords: chest CT • cystic lung disease • lymphangioleiomyomatosis (LAM) • quantitative CT


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