Digital analysis and quantitative assessment of the cervical surface with dysplasia
| Autor: | Aleshkin Va, A. D. Dushkin, T. G. Grishacheva, S.S. Afanasiev, Yu.V. Nesvizhsky, M. S. Afanasiev, A Yu Mironov, O.Y. Borisova, Alexander Karaulov, A M Zatevalov |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Colposcopy
Mild Dysplasia medicine.medical_specialty 030219 obstetrics & reproductive medicine medicine.diagnostic_test business.industry Biochemistry (medical) Digital analysis Physical examination General Medicine medicine.disease female genital diseases and pregnancy complications 03 medical and health sciences Medical Laboratory Technology 0302 clinical medicine Dysplasia 030220 oncology & carcinogenesis Cervical surface Quantitative assessment medicine Radiology business Moderate Dysplasia |
| Zdroj: | Russian Clinical Laboratory Diagnostics. 66:417-421 |
| ISSN: | 2412-1320 0869-2084 |
| DOI: | 10.51620/0869-2084-2021-66-7-417-421 |
| Popis: | The investigation aims - a quantitative assessment of cervical surface changes with digital analysis and computer technologies in dysplasia. Colposcopy was made in 90 women from 21 to 52 years (avr. age 33,9±8,13 y.o.) with mild epithelial dysplasia (CIN1), moderate dysplasia (CIN2), severe dysplasia (CIN3). The algorithm detected indicators which provide the cervical dysplasia classification on pre cytological and pre molecular-genetic patients investigations. The outcome of an algorithm was the identification of the cervix surface condition severity by an objective quantification. The cervical dysplasia type (CIN) was classified as IndGV values. The mild dysplasia (CIN1) had IndGV=8,5, moderate dysplasia (CIN2) - IndGV=13, severe dysplasia (CIN3) - IndGV=15,6. The cervical affected surface area (IndInt) equalled 0,17 in CIN1, 0,19 in CIN2, 0,22 in CIN3. A change severity has a direct relation with a grey color value. It demonstrates quantify classification in digital analysis. The algorithm is used in real-time mode and no requires considerable material outlays. This makes it possible to use an algorithm after clinical examination and predict patient management. |
| Databáze: | OpenAIRE |
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