Digital approach to estimate clinical images of the cervix with ImageJ software

A. Dushkin, M. Afanasiev, S. S. Afanasiev, T. Grishacheva, A. Karaulov
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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. 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.
利用 ImageJ 软件估算宫颈临床图像的数字化方法
背景:目视检查和阴道镜检查是评估宫颈的主观方法。目前,大多数阴道镜都配备了数字传输和记录宫颈图像的功能,以及用于图像处理的现代软件。为了对癌前病变(SIL+)和宫颈癌进行客观评估、预防发展和风险评估,必须使用现代图像处理方法。目的:本研究旨在展示基于 ImageJ 软件[1]的宫颈图像数字分析能力。材料与方法:在扩张阴道镜检查过程中,共获得 500 张席勒试验阴道镜图像。使用 ImageJ 软件进行数字分析,该软件采用最小(MinGV)和最大(MaxGV)灰色像素值(0-255)以及病变表面积(%Area)作为参数。根据细胞学检查结果将图像分为 4 组:健康供体(n=19;3.8%)、轻度鳞状细胞上皮内病变(n=113;22.6%)、重度鳞状细胞上皮内病变(n=327;65.4%)和浸润性宫颈癌(n=41;8.2%)。在谷歌 Colab 环境中使用 Python 编程语言包对获得的数据进行了数学和统计分析。采用 Kruskal-Wallis 标准对三组或更多组之间的定量指标进行比较,采用 Dunn 标准和 Holm 校正进行后验比较。结果:从轻度(88/141/31)到重度(83/142/32)鳞状细胞上皮内病变和宫颈癌(88/162/36)的 MinGV(p=0.035)、MaxGV(p0.001)和%Area(p=0.022)的增加具有统计学意义。数字阴道镜检查获得了评估宫颈表面病变程度的客观参数。宫颈表面的数字化分析可帮助临床专家确定进一步的治疗策略,包括瘢痕切除或切开活检及随后的形态学检查。结论:对阴道镜图像进行数字分析有可能减少对宫颈状况的主观评估,提高与妇科医生初次会面的效率,并有助于选择患者进行细胞学检查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
44
审稿时长
5 weeks
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