Detecting Number of Root Canal of Human Mandibular Second Molar
Conditions
Brief summary
to detect the Accuracy of Artificial Intelligence Technology in Detecting Number of Root Canal of Human Mandibular Second Molar: Diagnostic Accuracy Experimental Study.
Interventions
PROCEDUREAI
Detection of all canals in patients indicated for root canal therapy in lower second molars by Artificial Intelligence Dental operating microscope and CBCT
PROCEDURECBCT
CBCT scans performed to all participants, will be randomly distributed upon postgraduate students using randomization software
Sponsors
Future University in Egypt
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
DOUBLE (Subject, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to 40 Years
Healthy volunteers
Yes
Inclusion criteria
\- A- Inclusion criteria: 1. Patients must be medically free from any systemic disease that can affect root canal treatment. 2. Age range of the patients should be 18-40 with permanent mandibular second molars indicated for root canal treatment. 3. No sex predilection. 4. Patients must have good oral hygiene. 5. restorable teeth. 6. Positive patients acceptance for participating in the study. 7. Patients able to sign informed consent. B-
Exclusion criteria
1. Lower second molars which are non-restorable, having large perforations, external root resorption, vertical root fracture, internal root resorption, grade 2/3 mobility, previous successful/non-successful root canal treatment 2. Pregnant women after taking detailed history and pregnancy test must be in the first visit. 3. Psychologically disturbed patients. Teeth that have: • Periodontally affected with grade 2 or 3 mobility. 12 • Not restorable teeth. • Abnormal anatomy and calcified canals. • Previous root canal treatment.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Number of root canals detected | within one year | Detected by AI software |
Countries
Egypt
Outcome results
None listed