Biomedicines (Mar 2020)

The Lymphoscintigraphic Study of Unpredictable Head and Neck Cutaneous Melanoma Lymphatic Drainage

  • Valentina Lavelli,
  • Cristina Ferrari,
  • Giulia Santo,
  • Corinna Altini,
  • Andrea Ballini,
  • Angela Sardaro,
  • Margherita Fanelli,
  • Antonio Rosario Pisani,
  • Anna Giulia Nappi,
  • Giuseppe Giudice,
  • Giuseppe Rubini

DOI
https://doi.org/10.3390/biomedicines8040070
Journal volume & issue
Vol. 8, no. 4
p. 70

Abstract

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Head and neck cutaneous melanoma (HNCM) does not always follow standard lymphatic drainage; typical expected lymphatic pathways are associated with unexpected ones. The aim of this study was to investigate the relation between the primary HNCM sites and all possible lymphatic drainage pathways by lymphoscintigraphy with a special focus on the unexpected sentinel lymph node (SLNs) detection. We retrospectively analyzed 67 patients (46 M, 21 F; mean age 63 years) who underwent lymphoscintigraphy from January 2004 to November 2018. 99mTc-serum albumin was injected intra-dermally at the dose of 18–37 MBq in 0.2–0.4 mL. All patients underwent dynamic and static image acquisition. For all patients, the relation between the expected and unexpected SLNs was performed using the “Sidney Melanoma Unit Database” as our reference. The relation was performed also according to the primary HNCM localization. Cohens’ kappa was calculated. In 61/67 (91%) of patients, SLNs were detected only in predictable sites, while in six/67 (9%), unexpected SLNs were revealed. In all patients, the agreement proportion was 91% (95% confidence interval CI 0.8–0.96) and Cohen’s K was 0.11 (95% CI 0–0.43). Regarding the primary melanoma sites, the nasolabial field HNCM showed the highest rate of concordance (K = 0.60; 95%, CI 0.32–0.89) while the preauricular region HNCM revealed the highest rate of discordance with the clinically predictable drainage. The HNCM lymphatic drainage is extremely variable in regard to both the sites and the number of involved SLNs. The lymphoscintigraphic study is highly recommended to identify all possible SLNs in order to perform an accurate staging for all patients and to avoid missing unexpected SLNs.

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