Clinical Trial Validation of Automated Segmentation and Scoring of Pulmonary Cysts in Thoracic CT Scans
Aneesha Baral,
Simone Lee,
Farah Hussaini,
Brianna Matthew,
Alfredo Lebron,
Muyang Wang,
Li-Yueh Hsu,
Joel Moss,
Han Wen
Affiliations
Aneesha Baral
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Simone Lee
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Farah Hussaini
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Brianna Matthew
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Alfredo Lebron
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Muyang Wang
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Li-Yueh Hsu
Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA
Joel Moss
Pulmonary Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
Han Wen
Laboratory of Imaging Physics, Biochemistry and Biophysics Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
In cystic lung diseases such as lymphangioleiomyomatosis (LAM), a CT-based cyst score that measures the percentage of the lung volume occupied by cysts is a common index of the cyst burden in the lungs. Although the current semi-automatic measurement of the cyst score is well established, it is susceptible to human operator variabilities. We recently developed a fully automatic method incorporating adaptive features in place of manual adjustments. In this clinical study, the automatic method is validated against the standard method in several aspects. These include the agreement between the cyst scores of the two methods, the agreement of each method with independent tests of pulmonary function, and the temporal consistency of the measurements in the consecutive visits of the same patients. We found that the automatic method agreed with the standard method as well as the agreement between two trained operators running the same standard method; both methods obtained the same level of correlation with laboratory pulmonary function tests; the automated method had better temporal consistency than the standard method (p < 0.0001). The study indicates that the automatic method could replace the standard method and provide better consistency in assessing the extent of cystic changes in the lungs of patients.
