Quantitative assessment for pneumoconiosis severity diagnosis using 3D CT images

Pneumoconiosis is an occupational respiratory illness that occur by inhaling dust to the lungs. 240,000 participants are screened for diagnosis of pneumoconiosis every year in Japan. Radiograph is used for staging of severity rate in pneumoconiosis worldwide. CT imaging is useful for the differentiation of requirements for industrial accident approval because it can detect small lesions in comparison with radiograph. In this paper, we extracted lung nodules from 3D pneumoconiosis CT images by two manual processes and automatic process, and created a database of pneumoconiosis CT images. We used the database to analyze, compare, and evaluate visual diagnostic results of radiographs and quantitative assessment (number, size and volume) of lung nodules. This method was applied to twenty pneumoconiosis patients. Initial results showed that the proposed method can assess severity rate in pneumoconiosis quantitatively. This study demonstrates effectiveness on diagnosis and prognosis of pneumoconiosis in CT screening.