Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

PURPOSE: The eighth edition of the TNM classification of malignant tumors for the first time includes an official staging system for thymic epithelial tumors (TETs) recognized by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Staging is critical for the management of TETs, and determining stage accurately from imaging has the potential to improve clinical outcomes. We examine preoperative computed tomography (CT) characteristics of TETs associated with AJCC/UICC pathologic TNM stage.

MATERIALS AND

METHODS

In this retrospective study, patients were included if they met all the following criteria: (1) diagnosis of TET, (2) had primary curative intent surgery performed at Stanford University, and (3) had available preoperative CT imaging for review. Tumor pathology was staged according to the eighth edition TNM classification. Fifteen CT scan features were examined from each patient case according to the International Thymic Malignancy Interest Group standard report terms in a blinded manner. A Lasso-regularized multivariate model was used to produce a weighted scoring system predictive of pathologic TNM stage.

RESULTS

Examining the 54 patients included, the following CT characteristics were associated with higher pathologic TNM stage when using the following scoring system: elevated hemidiaphragm (score of 6), vascular endoluminal invasion (score of 6), pleural nodule (score of 2), lobulated contour (score of 2), and heterogeneous internal density (score of 1). Area under the receiver operating characteristic curve was 0.76.

CONCLUSIONS

TETs with clearly invasive or metastatic features seen on CT are associated with having higher AJCC/UICC pathologic TNM stage, as expected. However, features of lobulated contour and heterogeneous internal density are also associated with higher stage disease. These findings need to be validated in an independent cohort.