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AI Model for Cervical Cancer Detection From Colposcopy Images

NCT06644248 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2024-10-16

No results posted yet for this study

Summary

Cervical cancer is a significant health issue, particularly in low-income countries, where late diagnosis and limited access to screenings contribute to high mortality rates. This study aims to develop and evaluate an artificial intelligence (AI) model to analyze colposcopic images for detecting cervical cancer more accurately and efficiently. Colposcopy, a procedure used to examine the cervix for signs of cancer, relies heavily on doctors' expertise, leading to inconsistent results. The current gold standard, colposcopy-directed biopsy, is invasive and can cause complications. The hypothesis is that an AI model can outperform traditional methods in identifying cervical abnormalities, providing a reliable and scalable solution for early detection, especially in underserved areas. By automating the analysis process, the AI model aims to reduce reliance on trained personnel, making cervical cancer screening more accessible and improving early diagnosis and treatment outcomes. The study will create a diverse dataset of colposcopy images from various sources and develop the AI model. The model's performance will be validated in clinical settings, assessing its accuracy in classifying cancer stages and identifying transformation zones. The impact on early detection, patient outcomes, and model usability will be evaluated, as well as its generalizability across different healthcare environments. The goal is to enhance the accuracy and efficiency of cervical cancer screening, ultimately reducing mortality rates and improving patient care.

Conditions

  • Uterine Cervical Neoplasms

Interventions

DIAGNOSTIC_TEST

Colposcopy

The intervention involves the use of colposcopy, a diagnostic procedure to visually examine the cervix using a colposcope. The procedure includes the application of saline, acetic acid, and iodine solutions to enhance the visualization of cervical tissues and identify abnormalities. The dosage form includes applying these solutions directly to the cervical area. The frequency of the intervention is typically a single session per patient, with the duration of the procedure lasting approximately 10-15 minutes. This study aims to utilize an AI model to analyze the colposcopic images obtained during the procedure to improve the accuracy and efficiency of cervical cancer detection.

Sponsors & Collaborators

  • Bangladesh University of Engineering and Technology

    lead OTHER

Principal Investigators

  • Taufiq Hasan, Taufiq · Department of Biomedical Engineering, BUET, Dhaka - 1205.

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-01-11
Primary Completion
2025-01-11
Completion
2025-02-11

Countries

  • Bangladesh

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06644248 on ClinicalTrials.gov