1. [Clinical research of the sentinel lymph node in patients with early gastric cancer]
- Author
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Xiu-Feng, Chen, Bo, Zhang, Hong-Xin, Yang, Hai-Ning, Chen, Chao-Yong, Shen, Jian-Kun, Hu, Jia-Ping, Chen, and Zhi-Xin, Chen
- Subjects
Sentinel Lymph Node Biopsy ,Stomach Neoplasms ,Lymphatic Metastasis ,Abdomen ,Humans ,Lymph Nodes ,Neoplasm Staging - Abstract
To assess the value of carbon nanoparticles which mapping sentinel lymph node (SLN) and predict the status of lymph node metastasis status in the early gastric cancer (EGC), and to explore the SLN distribution.Forty five patients with EGC, who underwent surgical treatment, were enrolled. At the completion of exploratory laparotomy, 1 mL solution of carbon nanoparticles was injected subserosally in the gastric wall 4-6 sites around the primary tumor during surgery in all patients. The first stained lymph nodes were defined as the SLN. Postoperative SLN and dissection of the lymph node was sent for histopathological examination.Carbon nanoparticles were applied in 45 EGC patients for mapping SLN and 43 cases (95.6%) were observed with positive stain. 53 pieces of SLN were detected, average (1.23 +/- 0.53) pieces for one person. 11 of the 43 patients (25.6%) developed lymph node metastasis, through the SLN histopathological examination, 3 cases (7.0%) were false negative, the accuracy and sensitivity of the prediction of regional lymph node metastasis status was 93.0% and 72.7%, respectively. The false negative and negative predictive value was 27.3% and 91.4%. There were significant differences between the mucosal cancer group and submucous cancer group in the diameter of tumor (P = 0.042) and the rate of lymph node metastasis (P = 0.001). There were no significant differences between the two groups in the accuracy and sensitivity (P0.05). In 36 cases of gastric cancer patients, 23 SLN positive cases (63.9%) were detected in third group.The dyeing rate, accuracy and sensitivity of carbon nanoparticles mapping SLN for EGC were high. Carbon nanoparticles mapping SLN can more accurately predict perigastric lymph node metastasis status in patients with EGC.
- Published
- 2013