Accuracy of Artificial Intelligence Technology in Detecting Periapical Lesions in Human Teeth. (AI)
Accuracy of Artificial Intelligence Technology in Detecting Periapical Lesions in Human Teeth. Diagnostic Accuracy Experimental Study.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
-
Cairo, Egypt
- Future University in Egypt
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- All patients must be medically free from any systemic disease that can affect root canal treatment.
- 18 to 50 years old patients with permanent teeth presenting with periapical pathosis.
- No sex predilection.
- All patients must have good oral hygiene.
- Restorable teeth
- Positive patient's acceptance for participating in the study.
- Patients able to sign informed consent
Exclusion Criteria:
- Patients above 50 years or patients below 18 years.
- Patients with very poor oral hygiene.
- Pregnant women after taking detailed history and pregnancy test must be in the first visit.
- Psychologically disturbed patients.
Teeth that have:
- Periodontally affected with grade 2 or 3 mobility.
- Not restorable teeth.
- Abnormal anatomy and calcified canals
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Sequential Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Active Comparator: cone beam computed tomography
detecting radiolucent periapical lesions using cone beam computed tomography
|
Cone beam computed tomography scans to detect the presence of periapical lesion by specialized investigators.
|
|
Active Comparator: 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.
|
artificial intelligence software that aids in diagnosis in dentistry
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
CBCT scans
Time Frame: 1 year
|
Presence of periapical lesion on CBCT scans
|
1 year
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of Artificial intelligence software
Time Frame: 1 year
|
Comparing results from CBCT scans to Artificial intelligence software in detection of periapcial lesions.
|
1 year
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- (52)/11-2024
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- ICF
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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