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作 者:陈秀峰[1] 张波[1] 杨弘鑫[1] 陈海宁[1] 沈朝勇[1] 胡建昆[1] 陈佳平[1] 陈志新[1]
机构地区:[1]四川大学华西医院胃肠外科中心,成都610041
出 处:《四川大学学报(医学版)》2013年第1期151-154,共4页Journal of Sichuan University(Medical Sciences)
基 金:四川省科技支撑计划项目(No.2010JY0019)资助
摘 要:目的评估纳米炭示踪早期胃癌(EGC)前哨淋巴结(SLN),预测胃周淋巴结转移状态的价值,探索SLN的分布情况。方法 45例EGC患者在完成开腹探查后,将1mL纳米炭混悬液分4~6个位点于肿瘤周围经浆膜下注射,将最先黑染的淋巴结确认为SLN,术后将SLN和清扫的各组淋巴结送病理组织学检查,计算其预测价值。结果 45例EGC患者中有43例染色成功,检出率为95.6%,总共检出SLN 53枚,平均(1.23±0.53)枚/例。43例染色成功的患者中有11例(25.6%)患者发生淋巴结转移,有3例(7.0%)患者出现假阴性,其预测胃周区域淋巴结转移状态的准确性及敏感性分别为93.0%和72.7%,假阴性率及阴性预测值则分别为27.3%及91.4%。在36例胃窦癌患者中,有23例(63.9%)患者检出的SLN位于第3组。黏膜内癌与黏膜下癌两组比较,肿瘤长径(P=0.042)和淋巴结转移率(P=0.001)两方面的差异有统计学意义,但这两组中的准确性和敏感性差异无统计学意义(P>0.05)。结论纳米炭示踪EGC的SLN,染色率、准确性和敏感性高,可以较为准确地预测胃周淋巴结的转移状态。Objective 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. Methods Forty five patients with EGC, who uriderwent surgical treatment, were enrolled. At the completion of exploratory laparotomy, 1 mL solution of carbon nanopartieles 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. Results Carbon nanopartieles 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 submueous cancer group in the diameter of tumor (P% 0. 042) and the rate of lymph node metastasis (P%O. 001). There were no significant differences between the two groups in the accuracy and sensitivity (P〈0. 05). In 36 cases of gastric cancer patients, 23 SLN positive cases (63.9%) were detected in third group. Conclusions 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.
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