Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Aug 24, 2022; 13(8): 702-711
Published online Aug 24, 2022. doi: 10.5306/wjco.v13.i8.702
Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
Marios Papadakis, Alexandros Paschos, Andreas S Papazoglou, Andreas Manios, Hubert Zirngibl, Georgios Manios, Dimitra Koumaki
Marios Papadakis, Hubert Zirngibl, Department of Surgery II, University of Witten-Herdecke, Wuppertal 42283, Germany
Alexandros Paschos, Department of Dermatology, Helios St. Elisabeth Hospital Oberhausen, Oberhausen 46045, Germany
Andreas S Papazoglou, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
Andreas Manios, Department of Surgical Oncology, University Hospital of Heraklion, Heraklion 71110, Greece
Georgios Manios, Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia 35131, Greece
Dimitra Koumaki, Department of Dermatology, University Hospital of Heraklion, Heraklion 71110, Greece
Author contributions: Papadakis M designed the research, performed the research, analyzed the data and wrote the paper; Paschos A participated in the data collection; Papazoglou A analyzed the data, Manios A contributed a new software used for the study; Zirngibl H contributed literature sources; Manios G analyzed the data; Koumaki D designed the research, performed the research, analyzed the data and wrote the paper; All authors reviewed and approved the final manuscript.
Institutional review board statement: The study was approved from the Ethics Committee of University Witten/Herdecke and was performed in accordance with institutional guidelines. Written informed consent was waived for retrospective study participation.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All authors declare no conflicts of interest.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Marios Papadakis, MD, MSc, PhD, Research Scientist, Surgeon, Department of Surgery II, University of Witten-Herdecke, Heusnerstrasse 40, Wuppertal 42283, Germany.
Received: February 28, 2022
Peer-review started: February 28, 2022
First decision: May 31, 2022
Revised: June 24, 2022
Accepted: July 26, 2022
Article in press: July 26, 2022
Published online: August 24, 2022

Delays in sentinel lymph node (SLN) biopsy may affect the positivity of non-SLNs. For these reasons, effort is being directed at obtaining reliable information regarding SLN positivity prior to surgical excision. However, the existing tools, e.g., dermoscopy, do not recognize statistically significant predictive criteria for SLN positivity in melanomas.


To investigate the possible association of computer-assisted objectively obtained color, color texture, sharpness and geometry variables with SLN positivity.


We retrospectively reviewed and analyzed the computerized medical records of all patients diagnosed with cutaneous melanoma in a tertiary hospital in Germany during a 3-year period. The study included patients with histologically confirmed melanomas with Breslow > 0.75 mm who underwent lesion excision and SLN biopsy during the study period and who had clinical images shot with a digital camera and a handheld ruler aligned beside the lesion.


Ninety-nine patients with an equal number of lesions met the inclusion criteria and were included in the analysis. Overall mean (± standard deviation) age was 66 (15) years. The study group consisted of 20 patients with tumor-positive SLN (SLN+) biopsy, who were compared to 79 patients with tumor-negative SLN biopsy specimen (control group). The two groups differed significantly in terms of age (61 years vs 68 years) and histological subtype, with the SLN+ patients being younger and presenting more often with nodular or secondary nodular tumors (P < 0.05). The study group patients showed significantly higher eccentricity (i.e. distance between color and geometrical midpoint) as well as higher sharpness (i.e. these lesions were more discrete from the surrounding normal skin, P < 0.05). Regarding color variables, SLN+ patients demonstrated higher range in all four color intensities (gray, red, green, blue) and significantly higher skewness in three color intensities (gray, red, blue), P < 0.05. Color texture variables, i.e. lacunarity, were comparable in both groups.


SLN+ patients demonstrated significantly higher eccentricity, higher sharpness, higher range in all four color intensities (gray, red, green, blue) and significantly higher skewness in three color intensities (gray, red, blue). Further prospective studies are needed to better understand the effectiveness of clinical image processing in SLN+ melanoma patients.

Keywords: Melanoma, Skin cancer, Image processing, Sentinel lymph node, Presurgical

Core Tip: Computer-aided image analysis can facilitate prediction of sentinel lymph-node positivity. Several color, sharpness and geometry parameters can predict positive lymph node occurrence, while color texture cannot determine sentinel lymph node positivity.