A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary AdenocarcinomaCui, X., Heuvelmans, M. A., Fan, S., Han, D., Zheng, S., Du, Y., Zhao, Y., Sidorenkov, G., Groen, H. J. M., Dorrius, M. D., Oudkerk, M., de Bock, G. H., Vliegenthart, R. & Ye, Z., Jul-2020, In : Clinical lung cancer. 21, 4, p. 314-+ 16 p.
Research output: Contribution to journal › Article › Academic › peer-review
It is essential to identify the subsolid nodules subtype preoperatively to select the optimal treatment algorithm. We developed and validated an imaging reporting system using a classification and regression tree model that based on computed tomography imaging characteristics (291 cases in training group, 146 cases in testing group). The model showed high sensitivity and accuracy of classification. Our model can help clinicians to make follow-up recommendations or decisions for surgery for clinical patients with a subsolid nodule.
|Number of pages||16|
|Journal||Clinical lung cancer|
|Early online date||6-Feb-2020|
|Publication status||Published - Jul-2020|
- Decision trees, Diagnosis, Lung, Solitary pulmonary nodule, X-ray computed tomography, GROUND-GLASS OPACITY, MINIMALLY INVASIVE ADENOCARCINOMA, DECISION TREE, LUNG, CT, CLASSIFICATION, DIAGNOSIS, RESECTION, SECTION, CANCER