---
title: Development and Evaluation of an Artificial Intelligence Tool for Colposcopy Assistance
nct_id: NCT06208319
overall_status: UNKNOWN
sponsor: Assistance Publique - Hôpitaux de Paris
study_type: OBSERVATIONAL
primary_condition: Cervical Cancer
canonical_url: "https://parkinsonspathways.com/agent/trials/NCT06208319.md"
clinicaltrials_gov: "https://clinicaltrials.gov/study/NCT06208319"
ct_last_update_post_date: 2024-02-01
last_seen_at: "2026-05-12T06:30:23.214Z"
source: ClinicalTrials.gov (mirrored, no enrichment)
---
# Development and Evaluation of an Artificial Intelligence Tool for Colposcopy Assistance

**NCT ID:** [NCT06208319](https://clinicaltrials.gov/study/NCT06208319)

## Key Facts

- **Status:** UNKNOWN
- **Study Type:** OBSERVATIONAL
- **Target Enrollment:** 1000
- **Lead Sponsor:** Assistance Publique - Hôpitaux de Paris
- **Collaborators:** Sorbonne University
- **Conditions:** Cervical Cancer, HSIL, LSIL, Cervical Ectropion
- **Start Date:** 2024-03-01
- **Completion Date:** 2024-10-31
- **CT.gov Last Update:** 2024-02-01

## Brief Summary

Project aiming to develop an algorithm to help the interpretation of colposcopy images, then to evaluate the effectiveness of this algorithm by using it on new cases and comparing the results obtained to the impression of expert clinicians

## Detailed Description

Due to the increase in the number of colposcopies following changes in recommendations regarding cervical cancer screening, the investigators wondered about the benefit of assistance provided by the computer tool. Several teams have already developed algorithms to aid in the interpretation of colposcopy, but the studies were carried out in countries that do not have the colposcopic expertise of French practitioners, and no algorithm has has demonstrated its effectiveness to our knowledge, the different results being inhomogeneous. The investigators therefore wanted to develop an algorithm to aid colposcopy based on clinical cases carried out by practitioners considered experts, then evaluate its effectiveness.

The investigators manually collect data concerning adult patients who underwent colposcopy by an expert doctor at La Pitié-Salpêtrière between September 1, 2022 and December 31, 2023, for whom the photographs of the colposcopic examination (without staining, after acid acetic and after Lugol) are available and usable and for which the clinical context is known. If a biopsy has been performed, the histological result is considered the gold standard. If this is not the case (normal and satisfactory colposcopy), the investigators consider by default that the histology is normal. The investigators excluded all patients for whom photographs were of poor quality or unavailable.

Development of the algorithm with the help of a computer science student, aiming to answer the following 2 questions:

* assumed histological result
* localization of the targeted biopsy if necessary

Evaluation of the algorithm: use of the algorithm for new cases, then comparison of the results obtained with the response given by expert clinicians (reading of images by 2 colposcopists). The aim will be to highlight the non-inferiority of the algorithm.

## Eligibility

- **Minimum age:** 18 Years
- **Sex:** FEMALE
- **Healthy Volunteers:** No

```
Inclusion Criteria:

1. Adult patients who underwent colposcopy with directed biopsies at La Pitié-Salpêtrière between September 1, 2022 and December 31, 2023
2. Known clinical context (why the patient underwent colposcopy)
3. Histological results of cervical biopsies (+/- conization or even hysterectomy) known
4. Images available (photographs of the cervix without preparation, after application of acetic acid and after application of lugol)
5. Informed of the study and not opposing the use of their data

Exclusion Criteria:

* Patients who do not speak French
```

## Interventions

- **data collection** (OTHER) — data collection from the patient's medical record. The data will be that of routine care, with no procedures added by the research.

## Primary Outcomes

- **Development of an algorithm to help interpret colposcopy images** _(time frame: 4 month after inclusion)_ — Creation of an imaging database with correlation to clinical and histological data, using data from care at the Pitié-Salpêtrière Hospital. A hundred cases will be selected for the study from the hundreds available in the department.

Annotation of colposcopy photos according to the recommendations of the French Society of Colposcopy and Cervico Vaginal Pathology (SFCPCV), then correlation with histological data.

Development of an algorithm for recognizing and analyzing colposcopy photos, with the help of a computer science student, using the analyzed data.

## Secondary Outcomes

- **Evaluate the effectiveness of this algorithm** _(time frame: 4 month after inclusion)_

## Recent Field Changes (last 30 days)

- `eligibility.sex` — added _(2026-05-12)_
- `eligibility.minAge` — added _(2026-05-12)_
- `status.overallStatus` — added _(2026-05-12)_
- `status.primaryCompletionDate` — added _(2026-05-12)_
- `status.completionDate` — added _(2026-05-12)_
- `status.lastUpdatePostDate` — added _(2026-05-12)_
- `design.enrollmentCount` — added _(2026-05-12)_
- `eligibility.criteria` — added _(2026-05-12)_
- `outcomes.primary` — added _(2026-05-12)_
- `outcomes.secondary` — added _(2026-05-12)_
- `armsInterventions.interventions` — added _(2026-05-12)_
- `sponsor.lead` — added _(2026-05-12)_
- `sponsor.collaborators` — added _(2026-05-12)_
- `results.hasResults` — added _(2026-05-12)_

---

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*Source data (authoritative): https://clinicaltrials.gov/study/NCT06208319*  
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