Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Validation of the 2025 ESGO/ESTRO/ESP postoperative risk stratification system in endometrial cancer: A same-cohort comparison with the 2020 molecular classification.

Gynecologic oncology·2026
Same author

Comparative prognostic performance of FIGO 2023 staging system and the 2025 ESGO-ESTRO-ESP risk classification in endometrial cancer.

Obstetrics & gynecology science·2026
Same author

Enhanced surgical efficiency with the next-generation da Vinci 5 system compared with da Vinci Xi: a retrospective cohort study in total laparoscopic hysterectomy.

Journal of robotic surgery·2026
Same author

Prognostic significance of psoas muscle index at diagnosis in cervical cancer progression.

Journal of gynecologic oncology·2026
Same author

Diagnostic accuracy of the droplet digital PCR POLE mutation test in endometrial cancer: comparison with Sanger sequencing and NGS.

Journal of gynecologic oncology·2026
Same author

Enhanced ovarian cancer diagnosis using deep learning on pelvic ultrasound with integrated clinical data: retrospective multicenter study.

Journal of gynecologic oncology·2026

Related Experiment Video

Updated: Dec 29, 2025

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
05:52

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy

Published on: August 19, 2021

12.7K

Learning curve for sentinel lymph node mapping in gynecologic malignancies.

Seongmin Kim1,2, Ki Jin Ryu2, Kyung Jin Min2

  • 1Gynecologic Oncology Center, Department of Obstetrics and Gynecology, CHA University Ilsan Medical Center, Goyang-si, Gyeonggi-do, Republic of Korea.

Journal of Surgical Oncology
|January 30, 2020
PubMed
Summary

Robot-assisted surgery for gynecologic cancers requires at least 27 cases to achieve proficiency in sentinel lymph node (SLN) detection. This learning curve may impact surgical quality, necessitating further investigation into disease outcomes.

Keywords:
cervical cancerendometrial cancerlearning curvesentinel lymph node

More Related Videos

Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology
06:37

Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology

Published on: October 20, 2010

23.7K
The Application of 1% Methylene Blue Dye As a Single Technique in Breast Cancer Sentinel Node Biopsy
07:51

The Application of 1% Methylene Blue Dye As a Single Technique in Breast Cancer Sentinel Node Biopsy

Published on: June 1, 2019

21.0K

Related Experiment Videos

Last Updated: Dec 29, 2025

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
05:52

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy

Published on: August 19, 2021

12.7K
Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology
06:37

Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology

Published on: October 20, 2010

23.7K
The Application of 1% Methylene Blue Dye As a Single Technique in Breast Cancer Sentinel Node Biopsy
07:51

The Application of 1% Methylene Blue Dye As a Single Technique in Breast Cancer Sentinel Node Biopsy

Published on: June 1, 2019

21.0K

Area of Science:

  • Gynecologic Oncology
  • Surgical Oncology
  • Minimally Invasive Surgery

Background:

  • Limited data exists on the learning curve for sentinel lymph node (SLN) detection in gynecologic malignancies.
  • Robot-assisted laparoscopic surgery is increasingly utilized for endometrial and cervical cancer treatment.

Purpose of the Study:

  • To investigate the learning curve for SLN detection during robot-assisted laparoscopic surgery in patients with endometrial and cervical carcinomas.
  • To determine the number of cases required to achieve proficiency in SLN mapping.

Main Methods:

  • Retrospective analysis of patients with cervical or endometrial cancer undergoing SLN mapping with indocyanine green.
  • Learning curve assessment using cumulative detection rates and the cumulative sum (CUSUM) method for a single surgeon.
  • Analysis of SLN detection rates in right, left, and bilateral pelvic regions.

Main Results:

  • Overall SLN mapping success rates were 81.25% (right), 77.50% (left), and 66.25% (bilateral).
  • Cumulative detection rates showed initial variability before stabilizing.
  • The CUSUM method indicated proficiency in mapping right, left, and bilateral SLNs after 27-28 cases.

Conclusions:

  • A minimum of 27 cases are necessary for achieving proficiency in SLN mapping for gynecologic cancer surgery.
  • The identified learning period may influence surgical quality.
  • Further research is needed to establish the impact of this learning curve on patient outcomes.