Accuracy of Artificial Intelligence Technology in Detecting Number of Root Canals in Human Mandibular First Molars Obturated and Indicated for Retreatment: Diagnostic Accuracy Experimental Study

NCT06325163 | Completed

• 1 other identifier: MIU-IRB-2223-219
• Study Type: interventional
• Target: 35
• Locations: 1 country
• Sites: 1

Brief Summary

evaluate the accuracy of new AI technology for detecting root canals in mandibular first molars retreatment cases in comparison to dentist clinical access cavity and CBCT imaging.

Conditions

Missed Canals

Outcome Measures

Primary Outcomes (1)

• Number of canals

  the numbers of canals in mandibular molars indicated for retreatment will be measured using CBCT, clinical under dental operating microscope, and using AI software

  The day of the procedure

Secondary Outcomes (1)

• linear morphological variations in failed cases

  Following the CBCT stage, an average of one week

Study Arms (1)

A single arm consisting of 3 stages

EXPERIMENTAL

This study will include 3 stages: 1. CBCT examination stage: In this stage, CBCT scanning will be done and examined by by 2 blinded endodontists and the number of canals identified will be recorded 2. Clinical Stage: This is a clinical stage where patients will be randomly distributed upon 6 Practitioners using randomization software (Microsoft Office Excel). Practitioners will then proceed with the pretreatment procedures under dental operating microscope 3. Artificial intelligence stage: The carrying out of this stage will be solely undertaken by the principal investigator. The CBCT images will be uploaded to convolutional neural network software (CNN) that uses a deep learning algorithm and CBCT segmentation. The software will then record the number of canals it found

Diagnostic Test: CBCT; Diagnostic Test: clinical examination under dental operating microscope; Diagnostic Test: canal detection AI software (diagnocat)

Interventions

CBCT DIAGNOSTIC_TEST

Mandibular molar indicated for retreatment will be scanned using limited field of view CBCT to examine the number of canals

A single arm consisting of 3 stages

clinical examination under dental operating microscope DIAGNOSTIC_TEST

the number of canals will be examined by an a randomly assigned operator following gutta percha removal under dental operating microscope

A single arm consisting of 3 stages

canal detection AI software (diagnocat) DIAGNOSTIC_TEST

software used to analyze CBCT images and report the number of canals

A single arm consisting of 3 stages

Eligibility Criteria

• Age: 18 Years - 40 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• Males and females.
• Patients aged 18 to 40 years
• Repairable permanent first molars in the lower jaw, with a closed apex, which required non-surgical retreatment.
• One or more of the following signs and symptoms: Spontaneous pain, Pain on biting, Sinus tract, Radiolucency related to one or more roots.

You may not qualify if:

• Patients with lower first molars which are deemed non restorable, or have large perforations, external resorption, or vertical root fracture,
• Pregnant women
• Immunocompromised patients.

Sponsors & Collaborators

• Misr International University: lead

Study Sites (1)

Misr International University

Cairo, Egypt

Location

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SEQUENTIAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principle investigator

Study Record Dates

• First Submitted: December 26, 2023
• First Posted: March 22, 2024
• Study Start: January 25, 2023
• Primary Completion: October 2, 2023
• Study Completion: October 10, 2023
• Last Updated: March 22, 2024

Record last verified: 2024-03

Locations

EG (1)