Number of Root Canals
Conditions
Keywords
CBCT, AI
Brief summary
The study compares the effectiveness of Artificial Intelligence (AI), CBCT, and clinical examination in detecting root canals in upper first, upper second, and lower first molars. Results show AI detects more molars with three or four canals in conventional treatment cases and retreatment cases.
Detailed description
Introduction: Accurate root canal detection is crucial for successful endodontic treatment, particularly in complex molar cases. Conventional methods, such as clinical examination and cone-beam computed tomography (CBCT), have their limitations, as high radiation exposure. Recent advancements in Artificial Intelligence (AI) have shown promise in improving diagnostic accuracy. This study aims to compare the effectiveness of AI, CBCT, and clinical examination using a dental operating microscope (DOM) in detecting root canals in upper first, upper second, and lower first molars, in both conventional and retreatment cases. Methods: CBCT scans from 210 patients requiring non-surgical root canal therapy or re-treatment were selected. The scans were analyzed using three detection methods: clinical examination via DOM, interpretation by two experienced endodontists using CBCT, and an AI convolutional neural network (CNN) software (Diagnocat). The detected number of root canals was recorded and compared across the three methods.
Interventions
DIAGNOSTIC_TESTArtificial Intelligence
The number of canals detected by AI
Sponsors
Misr International University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 40 Years
Healthy volunteers
Yes
Inclusion criteria
* Male and female patients who were capable of providing informed consent * Age between 18 to 40 years old. * A restorable tooth.
Exclusion criteria
* Patients that underwent vital pulp therapies. * Patients with calcifications in pulp space. * Open apex/immature roots. * Teeth restored by full coverage crowns. * Pregnant women by taking adequate history from patient and pregnancy test that was done in the first visit
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The number of canals detected | 1 day | The number of canals detected clinically using DOM, CBCT and by AI |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Canal Morphology | 1 day | Canal morphology for successful and failed cases |
Countries
Egypt
Outcome results
None listed