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Visualizing Lymph Node Structure and Cellular Localization using Ex-Vivo Confocal Microscopy
Published on: August 9, 2019
Re-fixation in a lymph node revealing solution is a powerful method for identifying lymph nodes in colorectal
1Department of Pathology, Faculty Hospital Královské Vinohrady and Third Medical Faculty, Charles University, Prague, Czech Republic. alexandr.svec@stees.nhs.uk
Summary
A novel lymph node revealing solution (LRS) significantly increases the number of detected lymph nodes (LN) in colorectal resection specimens. This method improves staging accuracy for colorectal cancer by revealing more than 12 LNs in most pT2 and pT3 adenocarcinomas.
Area of Science:
- Surgical Pathology
- Oncology
- Histopathology
Background:
- Accurate lymph node (LN) staging is crucial for colorectal cancer prognosis and treatment.
- Conventional methods may underestimate the total number of LNs in resection specimens.
Purpose of the Study:
- To evaluate the efficacy of a lymph node revealing solution (LRS) in increasing LN yield from colorectal resection specimens.
- To determine if LRS improves the detection rate of LNs in pT2 and pT3 colorectal adenocarcinomas.
Main Methods:
- Rectosigmoid carcinoma specimens (pT2&3 and ypT2&3) were divided into a study group (fixed in LRS) and a control group (routine examination).
- The LRS comprised ethanol, diethyl ether, glacial acetic acid, and formalin.
- The number of revealed LNs was compared between the groups using Student's t-test.
Main Results:
- The study group yielded an average of 14.7 LNs per specimen, compared to 5.9 in the control group.
- This difference was statistically significant (P = 0.05).
- LRS enabled the detection of over 12 LNs in the majority of stage pT2 and pT3 adenocarcinomas.
Conclusions:
- The use of LRS significantly enhances the number of lymph nodes identified in colorectal resection specimens.
- LRS is a valuable tool for improving the accuracy of lymph node staging in colorectal cancer.
- This method facilitates the detection of a higher number of LNs, aiding in more precise tumor classification.
