Periapical Lesion
Conditions
Keywords
artificial intelligence, periapical lesion, CBCT
Brief summary
Aims to evaluate the accuracy of using Artificial intelligence software in detecting the presence of periapical lesion compared to CBCT imaging.
Detailed description
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.
Interventions
Cone beam computed tomography scans to detect the presence of periapical lesion by specialized investigators.
OTHERartificial intelligence software
artificial intelligence software that aids in diagnosis in dentistry
Sponsors
Future University in Egypt
Study design
Allocation
RANDOMIZED
Intervention model
SEQUENTIAL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Investigator)
Eligibility
Sex/Gender
ALL
Age
18 Years to 50 Years
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| CBCT scans | 1 year | Presence of periapical lesion on CBCT scans |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of Artificial intelligence software | 1 year | Comparing results from CBCT scans to Artificial intelligence software in detection of periapcial lesions. |
Countries
Egypt
Outcome results
None listed