Quantitative and Semi-quantitative Methods for Assessing the Degree of Methylene Blue Staining in Sentinel Lymph Nodes in Dogs Academic Article uri icon

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abstract

  • Background: To develop a digital algorithm for quantitative assessment of surface methylene blue staining in whole lymph nodes and validate a semi-quantitative visual scoring method for patient-side use.Methods: Lymph nodes from canine patients with spontaneous tumors undergoing sentinel lymph node mapping were prospectively assessed ex vivo and photographed. Using an open-source computer-based imaging software, an algorithm was developed for quantification of staining based on a signal-to-background ratio. Next, two blinded observers evaluated images and assigned a semi-quantitative visual score based on surface staining (0—no blue stain, 1−1–50% stained, and 2−51–100% stained) and those results were compared to the established quantitative standard.Results: Forty-three lymph nodes were included. Image analysis successfully quantified blue staining and differentiated from normal lymph node tissue in all cases. Agreement between observers using the Kappa coefficient demonstrated strong agreement (k = 0.8581, p < 0.0001) between semi-quantitative visual scoring and image analysis. There was substantial interobserver and intraobserver agreement for the scoring system (k = 0.7340, p < 0.0001 and k = 0.8983, p < 0.0001, respectively).Conclusion: A digital algorithm using an open-source software was simple and straightforward to use for quantification of blue staining. The use of a semi-quantitative visual scoring system shows promise for a simple, objective, repeatable assessment of methylene blue staining at the time of surgery. This study demonstrates reliable and repeatable methods for blue staining quantification thereby providing a novel and objective reporting mechanism in scientific research involving sentinel lymph node mapping.

authors

  • Ram, Ann S
  • Matuszewska, Kathy
  • Petrik, James
  • Singh, Ameet
  • Oblak, Michelle L

publication date

  • January 2021