Related Experiment Video
Updated: Sep 27, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
Published on: May 5, 2011
Preoperative melanoma thickness determination by 20-MHz sonography and digital videomicroscopy in combination
Giovanni Pellacani1, Stefania Seidenari
1Department of Dermatology, University of Modena and Reggio Emilia, 41100 Modena, Italy.
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.
More Related Videos
10:35Multimodal Imaging and Spectroscopy Fiber-bundle Microendoscopy Platform for Non-invasive, In Vivo Tissue Analysis
Published on: October 17, 2016
09:37Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
Published on: August 18, 2022