Artificial intelligence assisted discrimination between pulmonary tuberculous nodules and solid lung cancer nodules

The differential diagnosis between pulmonary tuberculous nodules and solid lung cancer nodules is difficult and easy to be misdiagnosed in clinic. The data of clinic and image features of Chest CT with 70 cases of non-calcified pulmonary tuberculous nodules and 198 cases of solid lung cancer nodules confirmed by pathology in the Department of Thoracic Surgery or Respiratory and Critical Care Medicine, the First Affiliated Hospital of Chongqing Medical University from January to September 2020 were collected retrospectively. The characteristics of clinical and chest CT were compared between pulmonary tuberculous nodules and solid lung cancer nodules. The sensitivity, specificity, accuracy and negative predictive value in the two groups were compared between Artificial Intelligence assisted diagnosis system and manual image reading. The results found that the mean age, past tumor history, family history of tumor, CT image features of nodules includes mean diameter, short burr, blood vessel crossing in the pulmonary tuberculous nodules group were lower than those in the solid lung cancer group (p < 0.05). In 35 cases of pulmonary tuberculous nodules group and 63 cases of solid lung cancer nodules group with Dicom format thin-slice chest CT, the sensitivity of AI-assisted diagnosis was 98.98 %. The diagnosis specificity, accuracy and negative predictive value in the AI group (80.61 %, 92.06 %, 60.00 %) were much higher than these in the intermediate respiratory physicians (62.24 %, 76.19 %, 37.14 %, p = 0.004, 0.015, 0.044) respectively, and there was no significant difference between AI and senior radiologists. There are many similarities in clinical and CT image features between pulmonary tuberculous nodules and solid lung cancer nodules. The ability of AI-assisted diagnosis system is better than that of intermediate physicians, reaching the diagnostic level of senior physicians, which is conducive to homogenization and improvement of the differential diagnosis ability of physicians.