Cargando…
Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma
OBJECTIVE: Computerized clinical image analysis is shown to improve diagnostic accuracy for cutaneous melanoma but its effectiveness in preoperative assessment of melanoma thickness has not been studied. The aim of this study, is to explore how melanoma thickness correlates with computer-assisted ob...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201878/ https://www.ncbi.nlm.nih.gov/pubmed/34127072 http://dx.doi.org/10.1186/s13104-021-05650-4 |
_version_ | 1783707883443060736 |
---|---|
author | Papadakis, Marios Paschos, Alexandros Manios, Andreas Lehmann, Percy Manios, Georgios Zirngibl, Hubert |
author_facet | Papadakis, Marios Paschos, Alexandros Manios, Andreas Lehmann, Percy Manios, Georgios Zirngibl, Hubert |
author_sort | Papadakis, Marios |
collection | PubMed |
description | OBJECTIVE: Computerized clinical image analysis is shown to improve diagnostic accuracy for cutaneous melanoma but its effectiveness in preoperative assessment of melanoma thickness has not been studied. The aim of this study, is to explore how melanoma thickness correlates with computer-assisted objectively obtained color and geometric variables. All patients diagnosed with cutaneous melanoma with available clinical images prior to tumor excision were included in the study. All images underwent digital processing with an automated non-commercial software. The software provided measurements for geometrical variables, i.e., overall lesion surface, maximum diameter, perimeter, circularity, eccentricity, mean radius, as well as for color variables, i.e., range, standard deviation, coefficient of variation and skewness in the red, green, and blue color space. RESULTS: One hundred fifty-six lesions were included in the final analysis. The mean tumor thickness was 1.84 mm (range 0.2–25). Melanoma thickness was strongly correlated with overall surface area, maximum diameter, perimeter and mean lesion radius. Thickness was moderately correlated with eccentricity, green color and blue color. We conclude that geometrical and color parameters, as objectively extracted by computer-aided clinical image processing, may correlate with tumor thickness in patients with cutaneous melanoma. However, these correlations are not strong enough to reliably predict tumor thickness. |
format | Online Article Text |
id | pubmed-8201878 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82018782021-06-16 Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma Papadakis, Marios Paschos, Alexandros Manios, Andreas Lehmann, Percy Manios, Georgios Zirngibl, Hubert BMC Res Notes Research Note OBJECTIVE: Computerized clinical image analysis is shown to improve diagnostic accuracy for cutaneous melanoma but its effectiveness in preoperative assessment of melanoma thickness has not been studied. The aim of this study, is to explore how melanoma thickness correlates with computer-assisted objectively obtained color and geometric variables. All patients diagnosed with cutaneous melanoma with available clinical images prior to tumor excision were included in the study. All images underwent digital processing with an automated non-commercial software. The software provided measurements for geometrical variables, i.e., overall lesion surface, maximum diameter, perimeter, circularity, eccentricity, mean radius, as well as for color variables, i.e., range, standard deviation, coefficient of variation and skewness in the red, green, and blue color space. RESULTS: One hundred fifty-six lesions were included in the final analysis. The mean tumor thickness was 1.84 mm (range 0.2–25). Melanoma thickness was strongly correlated with overall surface area, maximum diameter, perimeter and mean lesion radius. Thickness was moderately correlated with eccentricity, green color and blue color. We conclude that geometrical and color parameters, as objectively extracted by computer-aided clinical image processing, may correlate with tumor thickness in patients with cutaneous melanoma. However, these correlations are not strong enough to reliably predict tumor thickness. BioMed Central 2021-06-14 /pmc/articles/PMC8201878/ /pubmed/34127072 http://dx.doi.org/10.1186/s13104-021-05650-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Note Papadakis, Marios Paschos, Alexandros Manios, Andreas Lehmann, Percy Manios, Georgios Zirngibl, Hubert Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title | Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title_full | Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title_fullStr | Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title_full_unstemmed | Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title_short | Computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
title_sort | computer-aided clinical image analysis for non-invasive assessment of tumor thickness in cutaneous melanoma |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201878/ https://www.ncbi.nlm.nih.gov/pubmed/34127072 http://dx.doi.org/10.1186/s13104-021-05650-4 |
work_keys_str_mv | AT papadakismarios computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma AT paschosalexandros computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma AT maniosandreas computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma AT lehmannpercy computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma AT maniosgeorgios computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma AT zirngiblhubert computeraidedclinicalimageanalysisfornoninvasiveassessmentoftumorthicknessincutaneousmelanoma |