Complete fully automatic segmentation and 3-dimensional measurement of mediastinal lymph nodes for a new response evaluationcriteria for solid tumors

We aimed to automatically detect and segment mediastinal lymph nodes, and to establish an objective method and reliable new response evaluation criteria to monitor the effectiveness of cancer treatment. The image processing techniques were applied and developed 3D measurement of the mediastinal lymph nodes based on automatic settings when segmenting the lymph node image. A repeatable and consistent lymph node evaluation system was created based on such features as the position of occurrence, grayness, and number of serial sections of lymph nodes. A total of 200 lymph node samples from Tri-Service General Hospital, Taiwan, were examined for statistical analysis. The proposed approach used weighted k-nearest neighbors for classification, achieving superior results with an accuracy and specificity of 97.5% and 99.4%, respectively. The volume of the lymph nodes was used as the reference index for tumor invasiveness evaluation. The error in the lymph node volume was 1.71% according to the verification results. Receiver operating characteristic (ROC) curves for each analysis were constructed and the area under the curve (AUC) was calculated with histopathology diagnosis as outcome for determining the optimal volume threshold of benign and malignant lymph nodes. It was observed that the lymph node volume was highly correlated with tumor invasion (p-value was less than 0.05). The experiment showed that the volume for the area under the ROC curve was 0.90 of tumor invasion evaluation. The lymph node volume was most effective in predicting tumor invasiveness, with the value 798.53 mm3used as the standard for judging benignity and malignancy.