Automatic identification of metastatic lymph nodes in OCT images

摘要

Lymphatic metastasis is a main pathway of dissemination of malignancies. The diagnosis of metastasis in lymph nodescan help stage cancer or help the surgeons make intraoperative decisions. In addition, lymph nodes are more easilyconfused with other neck tissues during thyroid surgery. Therefore, identification of lymph nodes is very important. Upto now, the gold standard for identification of metastatic lymph nodes is still histological examination, which can only beperformed ex vivo and needs a long time. Optical coherence tomography (OCT) is a non-invasive, high-resolutionimaging technology that is capable of detecting microstructures in bio-tissues in real time. In this study, we demonstrateda method to identify metastatic lymph nodes automatically by intraoperative OCT imaging. With a home-made sweptsource OCT system, we obtained OCT images of different resected neck tissues, including lymph nodes with andwithout metastasis, thyroid, parathyroid, fat and muscle, from 28 patients undertaking thyroidectomy. The automaticidentification algorithm was based on texture analysis and back-propagation artificial neural network (BP-ANN). 66texture features of OCT images were extracted and 14 were selected and used for automatic identification experiments.The trained BP-ANN has an excellent performance in identifying OCT images of lymph nodes with the sensitivity of98.9 % and specificity of 98.8 %. The accuracy of lymphatic metastasis diagnosis is 90.1 %.