Diagnostic Accuracy of Artificial Intelligence, CBCT, and Clinical Examination in Detecting Number of Root Canals in Conventional and Retreated Maxillary and Mandibular Molars

November 28, 2024 updated by: Misr International University
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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Enrollment (Actual)

212

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Egypt
      • Cairo, Egypt, 00202
        • Misr International University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

Yes

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: CBCT, Clinical using DOM
Comparing the three methods for the detection of the number of canals of maxillary and mandibular molars
Diagnostic test: Artificial Intelligence
The number of canals detected by AI

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The number of canals detected
Time Frame: 1 day
The number of canals detected clinically using DOM, CBCT and by AI
1 day

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Canal Morphology
Time Frame: 1 day
Canal morphology for successful and failed cases
1 day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Misr International University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 20, 2023

Primary Completion (Actual)

January 20, 2024

Study Completion (Actual)

February 20, 2024

Study Registration Dates

First Submitted

November 21, 2024

First Submitted That Met QC Criteria

November 28, 2024

First Posted (Estimated)

December 2, 2024

Study Record Updates

Last Update Posted (Estimated)

December 2, 2024

Last Update Submitted That Met QC Criteria

November 28, 2024

Last Verified

October 1, 2024

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • MIU-IRB-2425-008

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

will be shared after publishing the paper

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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