Enviar artigo por via de e-mail Digital approach to estimate clinical images of the cervix with ImageJ software
- Autores: Dushkin A.D.1, Afanasiev M.S.2, Afanasiev S.S.3, Grishacheva T.G.4, Karaulov A.V.2
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Afiliações:
- Moscow City Oncology Hospital No 62
- The First Sechenov Moscow State Medical University
- G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology
- Academician I.P. Pavlov First St. Petersburg State Medical University
- Edição: Volume 5, Nº 1S (2024)
- Páginas: 18-20
- Seção: Articles by YOUNG SCIENTISTS
- ##submission.dateSubmitted##: 12.02.2024
- ##submission.dateAccepted##: 07.03.2024
- ##submission.datePublished##: 03.07.2024
- URL: https://jdigitaldiagnostics.com/DD/article/view/626768
- DOI: https://doi.org/10.17816/DD626768
- ID: 626768
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Resumo
BACKGROUND: Visual inspection and colposcopy are subjective methods of cervical evaluation. Currently, the majority of colposcopes are equipped with the capacity to digitally transmit and record cervical images, in addition to modern software for image processing. For the objective assessment, prevention of development, and risk assessment of precancerous changes (SIL+) and cervical cancer, it is essential to use modern methods of image processing.
AIM: The study aimed at demonstrating the capabilities of digital analysis of cervical images based on ImageJ software [1].
MATERIALS AND METHODS: A total of 500 colposcopic images of the Schiller test were obtained during dilated colposcopy. Digital analysis was performed using ImageJ software, which employed minimum (MinGV) and maximum (MaxGV) gray pixel values (0–255) and lesion surface area (%Area) as parameters. The images were divided into 4 groups according to the cytologic examination performed: healthy donors (n=19; 3.8%), mild grade squamous cell intraepithelial lesion (n=113; 22.6%), severe grade squamous cell intraepithelial lesion (n=327; 65.4%), and invasive cervical cancer (n=41; 8.2%). Mathematical and statistical analysis of the obtained data was performed using Python programming language packages in the Google Colab environment. Comparisons of quantitative measures between three or more groups were conducted using the Kruskal-Wallis criterion and posteriori comparisons by Dunn’s criterion with Holm’s correction.
RESULSTS: Statistical significance was observed in the increase of MinGV (p=0.035), MaxGV (p<0.001) and %Area (p=0.022) from the mild (88/141/31) to the severe (83/142/32) degree of squamous cell intraepithelial lesion and cervical cancer (88/162/36). Objective parameters for the assessment of the degree of cervical surface lesions during digital colposcopy were obtained. Digital analysis of the cervical surface may assist the clinical specialist in determining further management strategies, including scarification or incisional biopsy with subsequent morphological examination.
CONCLUSIONS: The application of digital analysis to colposcopic images has the potential to reduce the subjective assessment of cervical condition, enhance the efficiency of the initial appointment with a gynecologist, and facilitate the selection of patients for cytologic examination.
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Texto integral
BACKGROUND: Visual inspection and colposcopy are subjective methods of cervical evaluation. Currently, the majority of colposcopes are equipped with the capacity to digitally transmit and record cervical images, in addition to modern software for image processing. For the objective assessment, prevention of development, and risk assessment of precancerous changes (SIL+) and cervical cancer, it is essential to use modern methods of image processing.
AIM: The study aimed at demonstrating the capabilities of digital analysis of cervical images based on ImageJ software [1].
MATERIALS AND METHODS: A total of 500 colposcopic images of the Schiller test were obtained during dilated colposcopy. Digital analysis was performed using ImageJ software, which employed minimum (MinGV) and maximum (MaxGV) gray pixel values (0–255) and lesion surface area (%Area) as parameters. The images were divided into 4 groups according to the cytologic examination performed: healthy donors (n=19; 3.8%), mild grade squamous cell intraepithelial lesion (n=113; 22.6%), severe grade squamous cell intraepithelial lesion (n=327; 65.4%), and invasive cervical cancer (n=41; 8.2%). Mathematical and statistical analysis of the obtained data was performed using Python programming language packages in the Google Colab environment. Comparisons of quantitative measures between three or more groups were conducted using the Kruskal-Wallis criterion and posteriori comparisons by Dunn’s criterion with Holm’s correction.
RESULSTS: Statistical significance was observed in the increase of MinGV (p=0.035), MaxGV (p<0.001) and %Area (p=0.022) from the mild (88/141/31) to the severe (83/142/32) degree of squamous cell intraepithelial lesion and cervical cancer (88/162/36). Objective parameters for the assessment of the degree of cervical surface lesions during digital colposcopy were obtained. Digital analysis of the cervical surface may assist the clinical specialist in determining further management strategies, including scarification or incisional biopsy with subsequent morphological examination.
CONCLUSIONS: The application of digital analysis to colposcopic images has the potential to reduce the subjective assessment of cervical condition, enhance the efficiency of the initial appointment with a gynecologist, and facilitate the selection of patients for cytologic examination.
Sobre autores
Alexander Dushkin
Moscow City Oncology Hospital No 62
Autor responsável pela correspondência
Email: alex@drdushkin.ru
ORCID ID: 0000-0002-8013-5276
Código SPIN: 3857-0010
Rússia, Moscow region, Istra village
Maxim Afanasiev
The First Sechenov Moscow State Medical University
Email: maxim.afanasyev78@gmail.com
ORCID ID: 0000-0002-5860-4152
Código SPIN: 5137-1449
Rússia, Moscow
Stanislav Afanasiev
G.N. Gabrichevsky Research Institute for Epidemiology and Microbiology
Email: afanasievss409.4@bk.ru
ORCID ID: 0000-0001-6497-1795
Rússia, Moscow
Tatyana Grishacheva
Academician I.P. Pavlov First St. Petersburg State Medical University
Email: grishatanchik82@gmail.com
ORCID ID: 0000-0002-9515-914X
Código SPIN: 4170-4253
Rússia, Saint Petersburg
Alexander Karaulov
The First Sechenov Moscow State Medical University
Email: karaulov_a_v@staff.sechenov.ru
ORCID ID: 0000-0002-1930-5424
Código SPIN: 4122-5565
Rússia, Moscow
Bibliografia
- Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nature Methods. 2012;9(7):671–675. doi: 10.1038/nmeth.2089
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