Literature DB >> 23643002

[Application of carbon nanoparticles in the laparoscopic sentinel lymph node detection in patients with cervical cancer].

Kai-jiang Liu1, Xin-wei Lv, Qing Liu, Na-na Han, Ming-fang Ru, Juan Wang, Pei-quan Li, Wen-yu Shao.   

Abstract

OBJECTIVE: To explore the role of laparoscopic sentinel lymph node(SLN) detection with carbon nanoparticles tracer in cervical carcinoma.
METHODS: Totally 21 patients with confirmed early cervical cancer were enrolled in this study.Before laparoscopic extended hysterectomy and pelvic lymphadenoetomy(and para-aortic lymphadenoectomy) , they were injected with carbon nanoparticles suspension injection tracer from cervical neck before surgery. The black-staining lymph nodes were cut as SLN under the laparoscope for routine pathological examination.
RESULTS: Of these 21 patients, at least one SLN was successfully detected in 20 patients(95.24%) , and a total of 158 SLNs were detected.The conventional pathology results suggested that 5 patients(23.81%) had positive lymph nodes(n=16, including 14 in 4 patients) . The new approach showed a sensitivity of 80.0%(4/5) , accuracy of 100.0%(20/20) , and negative predictive value of 100.0%(16/16) for SLN detection.
CONCLUSION: Laparoscopic SLN detection with carbon nanoparticles tracer is a relative safe and sensitive method for in cervical carcinoma.

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Mesh:

Year:  2013        PMID: 23643002     DOI: 10.3881/j.issn.1000-503X.2013.02.005

Source DB:  PubMed          Journal:  Zhongguo Yi Xue Ke Xue Yuan Xue Bao        ISSN: 1000-503X


  2 in total

1.  Meta-Analysis of the Diagnostic Value of Tracer Staining Technology Based on Nanocarbon Suspension in Sentinel Lymph Node Biopsy of Breast Cancer.

Authors:  Luhua Xia; Le Chong; Zinan Lu; Xinhua Wang; Zhanfei Dong; Yanping Zhao; Cheng Chang; Gang Sun
Journal:  Comput Math Methods Med       Date:  2022-05-12       Impact factor: 2.809

2.  Application of carbon nanoparticles in laparoscopic sentinel lymph node detection in patients with early-stage cervical cancer.

Authors:  Yan Lu; Jin-Ying Wei; De-Sheng Yao; Zhong-Mian Pan; Yao Yao
Journal:  PLoS One       Date:  2017-09-05       Impact factor: 3.240

  2 in total

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