Preoperative melanoma thickness determination by 20-MHz sonography and digital videomicroscopy in combination

Arch Dermatol. 2003 Mar;139(3):293-8. doi: 10.1001/archderm.139.3.293.

Abstract

Objective: To identify accurately thick melanomas preoperatively by means of a combined approach based on sonography and clinical-videomicroscopic evaluation.

Design: Ultrasonographic thickness measurement, obtained by means of a 20-MHz B-scanner, and identification of clinical and videomicroscopic variables useful in distinguishing between thick and thin melanomas were performed on a training set of 40 melanomas. An algorithm based on echographic, clinical, and videomicroscopic criteria was constructed to develop a method for preoperative evaluation of melanoma thickness and was validated on a test set of 48 melanomas.

Setting: University medical department.

Patients: Eighty-eight patients affected by primary cutaneous melanoma.

Main outcome measures: Sensitivity and specificity of the algorithm, with the use of sonographic, clinical, and videomicroscopic data, in thick melanoma identification.

Results: Echographic thickness was calculated for each lesion. On the training set, 2 clinical and 7 videomicroscopic features were identified for distinction between thick and thin melanomas: nonpalpability, central pigment network, central brown globules, and blotches were characteristic of thin melanomas; clinical regression, localized peripheral pigment network, veil, grayish polygonal areas, and blood vessels were characteristic of thick ones. A coefficient was attributed to each variable and a score was obtained for each lesion. The algorithm, developed for preoperative thickness prediction, was validated on the test set, enabling the distinction of thick melanomas with an 86.7% sensitivity and a 100% specificity.

Conclusion: The correct classification of all thin melanomas as such renders this approach suitable in clinical practice.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Image Processing, Computer-Assisted / standards*
  • Melanoma / diagnostic imaging
  • Melanoma / pathology*
  • Melanoma / surgery
  • Microscopy, Video / methods
  • Microscopy, Video / standards
  • Preoperative Care
  • Sensitivity and Specificity
  • Skin Neoplasms / diagnostic imaging
  • Skin Neoplasms / pathology*
  • Skin Neoplasms / surgery
  • Ultrasonography / methods
  • Ultrasonography / standards