Accuracy of Artificial Intelligence Technology in Detecting Periapical Lesions in Human Teeth.

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

100 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-12-06

Study Completion Date

2025-12-21

Brief Summary

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Aims to evaluate the accuracy of using Artificial intelligence software in detecting the presence of periapical lesion compared to CBCT imaging.

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Detailed Description

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In this research, patients referred to endodontic department in the university will undergo clinical examination (percussion, palpation) tests. These will be recorded. Then the patient will undergo a periapical radiograph to detect the presence of periapical lesion. Patients with periapical lesions will then undergo a cone beam computed tomography and this scan will be uploaded into the Artificial intelligence software to detect the accuracy of the software in detecting the presence of the periapical lesion. Any patient with a periapical lesion in need of root canal treatment will undergo the treatment.

Conditions

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Periapical Lesion

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

SEQUENTIAL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Investigators

Study Groups

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cone beam computed tomography

detecting radiolucent periapical lesions using cone beam computed tomography

Group Type ACTIVE_COMPARATOR

Cone beam computed tomography

Intervention Type OTHER

Cone beam computed tomography scans to detect the presence of periapical lesion by specialized investigators.

artificial intelligence software

Cone beam CT scan will be uploaded to artificial intelligence software to ensure that the software will detect radiolucent periapical lesion compared to Cone beam CT scans.

Group Type ACTIVE_COMPARATOR

artificial intelligence software

Intervention Type OTHER

artificial intelligence software that aids in diagnosis in dentistry

Interventions

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Cone beam computed tomography

Cone beam computed tomography scans to detect the presence of periapical lesion by specialized investigators.

Intervention Type OTHER

artificial intelligence software

artificial intelligence software that aids in diagnosis in dentistry

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

1. All patients must be medically free from any systemic disease that can affect root canal treatment.
2. 18 to 50 years old patients with permanent teeth presenting with periapical pathosis.
3. No sex predilection.
4. All patients must have good oral hygiene.
5. Restorable teeth
6. Positive patient's acceptance for participating in the study.
7. Patients able to sign informed consent

Exclusion Criteria

1. Patients above 50 years or patients below 18 years.
2. Patients with very poor oral hygiene.
3. Pregnant women after taking detailed history and pregnancy test must be in the first visit.
4. Psychologically disturbed patients.

Teeth that have:

* Periodontally affected with grade 2 or 3 mobility.
* Not restorable teeth.
* Abnormal anatomy and calcified canals

Minimum Eligible Age

18 Years

Maximum Eligible Age

50 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes