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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 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 35

Last updated 2024-03-22

No results posted yet for this study

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

Interventions

DIAGNOSTIC_TEST

CBCT

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

DIAGNOSTIC_TEST

clinical examination under dental operating microscope

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

DIAGNOSTIC_TEST

canal detection AI software (diagnocat)

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

Sponsors & Collaborators

  • Misr International University

    lead OTHER

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SEQUENTIAL

Eligibility

Min Age
18 Years
Max Age
40 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-01-25
Primary Completion
2023-10-02
Completion
2023-10-10

Countries

  • Egypt

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06325163 on ClinicalTrials.gov