Cargando…

Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma

BACKGROUND: 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 statistical...

Descripción completa

Detalles Bibliográficos
Autores principales: Papadakis, Marios, Paschos, Alexandros, Papazoglou, Andreas S, Manios, Andreas, Zirngibl, Hubert, Manios, Georgios, Koumaki, Dimitra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476607/
https://www.ncbi.nlm.nih.gov/pubmed/36160464
http://dx.doi.org/10.5306/wjco.v13.i8.702
_version_ 1784790175829721088
author Papadakis, Marios
Paschos, Alexandros
Papazoglou, Andreas S
Manios, Andreas
Zirngibl, Hubert
Manios, Georgios
Koumaki, Dimitra
author_facet Papadakis, Marios
Paschos, Alexandros
Papazoglou, Andreas S
Manios, Andreas
Zirngibl, Hubert
Manios, Georgios
Koumaki, Dimitra
author_sort Papadakis, Marios
collection PubMed
description BACKGROUND: 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. AIM: To investigate the possible association of computer-assisted objectively obtained color, color texture, sharpness and geometry variables with SLN positivity. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
format Online
Article
Text
id pubmed-9476607
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Baishideng Publishing Group Inc
record_format MEDLINE/PubMed
spelling pubmed-94766072022-09-23 Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma Papadakis, Marios Paschos, Alexandros Papazoglou, Andreas S Manios, Andreas Zirngibl, Hubert Manios, Georgios Koumaki, Dimitra World J Clin Oncol Retrospective Study BACKGROUND: 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. AIM: To investigate the possible association of computer-assisted objectively obtained color, color texture, sharpness and geometry variables with SLN positivity. METHODS: 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. RESULTS: 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. CONCLUSION: 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. Baishideng Publishing Group Inc 2022-08-24 2022-08-24 /pmc/articles/PMC9476607/ /pubmed/36160464 http://dx.doi.org/10.5306/wjco.v13.i8.702 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/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.
spellingShingle Retrospective Study
Papadakis, Marios
Paschos, Alexandros
Papazoglou, Andreas S
Manios, Andreas
Zirngibl, Hubert
Manios, Georgios
Koumaki, Dimitra
Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title_full Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title_fullStr Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title_full_unstemmed Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title_short Computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
title_sort computer-aided clinical image analysis as a predictor of sentinel lymph node positivity in cutaneous melanoma
topic Retrospective Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476607/
https://www.ncbi.nlm.nih.gov/pubmed/36160464
http://dx.doi.org/10.5306/wjco.v13.i8.702
work_keys_str_mv AT papadakismarios computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT paschosalexandros computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT papazoglouandreass computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT maniosandreas computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT zirngiblhubert computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT maniosgeorgios computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma
AT koumakidimitra computeraidedclinicalimageanalysisasapredictorofsentinellymphnodepositivityincutaneousmelanoma