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  11. Optimizing The Sensitivity Of A Pelvic Sentinel Node Algorithm Requires A Hybrid Algorithm Combining Indocyanine Green Based Mapping And The Removal Of Non-mapped Nodes At Defined Anatomic Positions.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Optimizing The Sensitivity Of A Pelvic Sentinel Node Algorithm Requires A Hybrid Algorithm Combining Indocyanine Green Based Mapping And The Removal Of Non-mapped Nodes At Defined Anatomic Positions.

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

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Optimizing the Sensitivity of a Pelvic Sentinel Node Algorithm Requires a Hybrid Algorithm Combining Indocyanine Green Based Mapping and the Removal of Non-Mapped Nodes at Defined Anatomic Positions.

Michele Bollino1,2, Barbara Geppert1,2, Petur Reynisson1,2

  • 1Division of Gynaecologic Oncologic Surgery, Department of Obstetrics and Gynaecology, Skåne University Hospital Lund, 22185 Lund, Sweden.

Cancers
|September 28, 2024

View abstract on PubMed

Summary
This summary is machine-generated.
Keywords:
endometrial cancerhybrid algorithmpelvic sentinel node

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In endometrial cancer surgery, even if sentinel lymph nodes (SLNs) are detected elsewhere, removing nodes from typical obturator and interiliac positions is crucial. This helps avoid missing isolated metastases in 4.3% of node-positive cases.

Area of Science:

  • Gynecologic Oncology
  • Surgical Pathology
  • Medical Imaging

Background:

  • Sentinel lymph node (SLN) mapping is essential for staging endometrial cancer (EC).
  • Indocyanine green (ICG) is a common tracer for SLN detection.
  • Non-mapped nodes in typical pelvic areas may harbor undetected metastases.

Purpose of the Study:

  • To determine the incidence of non-mapped isolated metastatic pelvic lymph nodes in specific anatomical locations.
  • To evaluate the effectiveness of an anatomically based SLN algorithm in endometrial cancer.
  • To identify potential gaps in metastasis detection using ICG mapping alone.

Main Methods:

  • Prospective study of women with EC undergoing robotic surgery and SLN detection (June 2019-Jan 2024).
  • Utilized an anatomically based algorithm with ICG tracer.
  • Nodes in "typical positions" (obturator/interiliac) were removed and analyzed if not mapped by ICG.

    • Main Results:

    • 180 of 620 women (29%) had non-mapped obturator or interiliac areas.
    • 114 women (18.4%) were node-positive.
    • Five women (4.3%) had isolated metastases in non-mapped "SLN anatomy" nodes.

    Conclusions:

    • Anatomically defined nodes should be removed if mapping fails in typical pelvic areas, even if other nodes are mapped.
    • This approach is necessary to prevent missing isolated nodal metastases in a subset of endometrial cancer patients.
    • Optimizing SLN algorithms can improve detection rates and staging accuracy in EC.