Robotic blue-dye sentinel lymph node detection for endometrial cancer - Factors predicting successful mapping

Area of Science:

• Gynecologic Oncology
• Surgical Pathology
• Minimally Invasive Surgery

Background:

• Sentinel lymph node (SLN) mapping is increasingly adopted for endometrial cancer staging.
• Accurate SLN identification is crucial for appropriate treatment planning.

Purpose of the Study:

• To evaluate the initial experience with a robotic blue-dye SLN mapping algorithm in endometrial cancer.
• To identify factors influencing the success rate of SLN mapping.

Main Methods:

• Analysis of data from 74 patients undergoing robotic-assisted surgery for endometrial cancer with attempted SLN mapping (Jan 2012-Dec 2014).
• Inclusion of patient demographics, SLN allocation, operative times, and pathology results.
• Assessment of SLN detection rates and influencing factors via univariate and multivariate analyses.

Main Results:

• Overall SLN detection rate was 62.1%, improving from 50% to 84.6% after 30 cases.
• Methylene blue dye showed higher detection rates (74.3%) compared to patent blue dye (52.3%).
• High body mass index (BMI), lymph-vascular space invasion (LVSI), and lower surgeon experience (fewer cases) were associated with failed mapping.

Conclusions:

• Surgeon experience, patient BMI, and the presence of LVSI are significant factors affecting SLN mapping success in endometrial cancer.
• Further investigation into these factors is warranted for optimizing SLN mapping protocols.