A. Dushkin, M. Afanasiev, S. S. Afanasiev, T. Grishacheva, A. Karaulov
{"title":"利用 ImageJ 软件估算宫颈临床图像的数字化方法","authors":"A. Dushkin, M. Afanasiev, S. S. Afanasiev, T. Grishacheva, A. Karaulov","doi":"10.17816/dd626768","DOIUrl":null,"url":null,"abstract":"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. \nAIM: The study aimed at demonstrating the capabilities of digital analysis of cervical images based on ImageJ software [1]. \nMATERIALS 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. \nRESULSTS: Statistical significance was observed in the increase of MinGV (p=0.035), MaxGV (p0.001) 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. \nCONCLUSIONS: 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.","PeriodicalId":34831,"journal":{"name":"Digital Diagnostics","volume":"77 s340","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital approach to estimate clinical images of the cervix with ImageJ software\",\"authors\":\"A. Dushkin, M. Afanasiev, S. S. Afanasiev, T. Grishacheva, A. Karaulov\",\"doi\":\"10.17816/dd626768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. \\nAIM: The study aimed at demonstrating the capabilities of digital analysis of cervical images based on ImageJ software [1]. \\nMATERIALS 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. \\nRESULSTS: Statistical significance was observed in the increase of MinGV (p=0.035), MaxGV (p0.001) 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. \\nCONCLUSIONS: 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.\",\"PeriodicalId\":34831,\"journal\":{\"name\":\"Digital Diagnostics\",\"volume\":\"77 s340\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital Diagnostics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17816/dd626768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Diagnostics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17816/dd626768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital approach to estimate clinical images of the cervix with ImageJ software
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 (p0.001) 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.