Morphological Predictors for Lymph Node Metastases on Computed Tomography in Colon Cancer

Introduction/BackgroundThe aim of the study was to assess morphological predictors for lymph node metastases (Stage III disease) in colon cancer on computed tomography.Methods and materialsNinety-four patients with histology-proven colon cancer (adenocarcinoma) who underwent elective primary curative resection between the years 2012 and 2014 were included. Contrast-enhanced CT examinations were independently reviewed by two blinded observers regarding tumor location, depth of tumor invasion, and presence of lymph node metastases. Ocular presence of internal heterogeneity and presence of irregular outer border were used as morphological criteria for lymph node involvement. Protocol-based histopathology after curative surgery served as reference standard. Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values, and accuracy for each morphological criterion for prediction of stage III disease were calculated. Inter-observer agreement was compared using Kappa statistics.ResultsAccording to histopathology, 59 patients were staged as I-II disease and 35 patients were staged as stage III disease. The presence of internal heterogeneity in a lymph node on CT resulted in moderate sensitivity (66-77%) but high specificity (95-95%) for prediction of Stage III disease by both observers. The presence of irregular outer border also resulted in poor sensitivity (49-54%) but high specificity (97-97%). The combination of either internal heterogeneity and/or irregular outer border per patient resulted in a moderate sensitivity (67-77%) and high specificity (95-95%), PPV (89-96%), and NPV (84-88%). Inter-observer agreement (Cohens Kappa) was 0.72. Consensus reading for the combined criteria resulted in sensitivity and specificity of 69% and 100%, respectively.ConclusionUsing morphological criteria for lymph node metastases on CT examination in patients with colon cancer results in high specificity but moderate sensitivity in predicting stage III disease.