Deep Learning to Summarize Findings in Dental Panoramic Radiographs

In this work, the investigators study the application of artificial intelligence systems on dental panoramic images for dental findings. An artificial intelligence system will be learned on an publicly available panoramic image dataset, and test against the investigators' local patient cohort as external test data. The investigators hypothesize the performance would be similar, if not identical to on the public data, and that the investigators' AI system is generalizable.

Study Overview

• Status: Enrolling by invitation
• Conditions: Dental Diseases; Radiography; Dentist-Patient Relations; Digital
• Intervention / Treatment: Radiation: Dental Panoramic Radiographs

• Study Type: Observational
• Enrollment (Anticipated): 1000

Contacts and Locations

Study Locations

• Taiwan
  • Taipei, Taiwan, 100
    • National Taiwan University Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years to 100 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

all patients with panoramic image exposure and not with exclusion criteria

Description

Exclusion Criteria:

• patients under 20 or with primary teeth
• patients with non-removable metal accessory above neck, such as tongue ring, nose ring etc.
• patients with mandible or maxilla deformation

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
All patients with relevant dental findings	Radiation: Dental Panoramic Radiographs; Exposure to dental panoramic radiographs

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Area Under Curve for Receiver Operating Characteristics of Clinical Findings	The investigators use the AI model to infer whether a clinical finding (out of the six type of findings the investigators are interested in) is present in an imaging study from the test set. The result is compared against expert annotation and evaluated for receiver operating characteristics over the whole set. The area under curve will then be calculated and averaged across six type of findings to represent the overall efficacy of the model on detecting findings from panoramic images. From a scale of zero to one, zero is the worst this metric can be and one is the best.	1 day

Collaborators and Investigators

• Sponsor: National Taiwan University Hospital

Study record dates

Study Major Dates

• Study Start (Actual): May 7, 2021
• Primary Completion (Anticipated): December 1, 2021
• Study Completion (Anticipated): May 1, 2023

Study Registration Dates

• First Submitted: May 9, 2021
• First Submitted That Met QC Criteria: May 16, 2021
• First Posted (Actual): May 20, 2021

Study Record Updates

• Last Update Posted (Actual): May 20, 2021
• Last Update Submitted That Met QC Criteria: May 16, 2021
• Last Verified: May 1, 2021

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Stomatognathic Diseases
• Other Study ID Numbers: 202102018RINB

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No