Dentomaxillofacial RadiologyNCT06022731
Artificial Intelligence Evaluation of Fillings
An observational study of Dentomaxillofacial Radiology, run by Eskisehir Osmangazi University at 1 site in Turkey (Türkiye).
Trial summary
The goal of this Non-Interventional Clinical Research is to detect the prevalence and distribution of filling and overhanging filling without the need for additional bitewing radiographs using panoramic images, based on a deep CNN (Convolutional Neural Network) architecture trained through supervised learning. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Dentomaxillofacial Radiology
- What is being tested?
- Panoramic Radiography
- How many people
- 4,323 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Jan 2022to 1 Mar 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
Study population: These datasets were obtained from the images of the patients who applied to ESOGU Dentistry Faculty, Dentomaxillofacial Radiology clinic for various dental purposes.
Who may be able to join
- Images of individuals in the permanent dentition period
- Artifact-free images in the examination region
- Individuals with a history of restorative dental treatment
Who cannot join
- Images of individuals in mixed dentition
- Radiographic images obtained by incorrect positioning of the patient or containing artifacts
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Eskişehir Osmangazi University
Eskişehir, 26200
About this study
Official title: A Yolo-V5 Approaches to Evaluation of Filling and Overhanging Filling: An Artificial Intelligence Study
The goal of this Non-Interventional Clinical Research is to detect the prevalence and distribution of filling and overhanging filling without the need for additional bitewing radiographs using panoramic images, based on a deep CNN (Convolutional Neural Network) architecture trained through supervised learning.
In this study, retrospectively obtained radiographs were used in the development of artificial intelligence models for relevant situations. These datasets were obtained from the images of the patients who applied to ESOGU (Eskişehir Osmangazi University) Dentistry Faculty, Dentomaxillofacial Radiology clinic for various dental purposes. Eskisehir Osmangazi University Non-Interventional Clinical Research Ethics Board (decision date and decision number: 04.10.2022/22) approved the study protocol. The principles of the Helsinki Declaration were followed in the study.
- Conditions
- Dentomaxillofacial Radiology
- Being tested
- Panoramic Radiography
- Keywords
- dental filling, dentistry, deep learning,
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Panoramic RadiographyDiagnostic test
this retrospective study includes analysis of radiographs previously taken from patients for various purposes
| Study group | Role | What they receive |
|---|---|---|
| Filling | Not described Receives: Diagnostic Test: Panoramic Radiography | |
| Overhanging Filling | Not described Receives: Diagnostic Test: Panoramic Radiography |
What is being measured
The primary outcome is the main question the study is designed to answer.
The success of artificial intelligence models for filling and overhanging filling
It is obtained by calculating the sensitivity, precision, and F1 scores values for filling and overhanging filling.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Sep 2023
- Study start1 Jan 2022
- Primary completion1 Jan 2023
- Study completion1 Mar 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Dentomaxillofacial RadiologyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Retrospective
- Enrolment
- 4,323 participants (actual)
Sponsor and investigators
- Lead sponsor
- Eskisehir Osmangazi University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Elif Bilgir, Eskisehir Osmangazi University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06022731
- Sponsor's protocol ID
- Retrospective
- Status last verified
- Aug 2023
- First submitted
- 8 Aug 2023
- Last updated
- 5 Sep 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The investigators plan to publish the findings obtained as a result of the study in internationally journals and share this information within the publication.
Study at a glance
From the registry record, last updated by the sponsor on 5 Sep 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Yolo-V5 Approaches to Evaluation of Filling and Overhanging Filling: An Artificial Intelligence Study
- ClinicalTrials.gov ID
- NCT06022731
- Acronym / sponsor ID
- Retrospective
- Conditions
- Dentomaxillofacial Radiology
- Keywords
- dental filling, dentistry, deep learning,
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 4,323 participants (actual)
- Lead sponsor
- Eskisehir Osmangazi UniversityUniversity, hospital or other
- Study start
- 1 Jan 2022 (actual)
- Primary completion
- 1 Jan 2023 (actual)
- Study completion
- 1 Mar 2023 (actual)
- First posted
- 5 Sep 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this Non-Interventional Clinical Research is to detect the prevalence and distribution of filling and overhanging filling without the need for additional bitewing radiographs using panoramic images, based on a deep CNN (Convolutional Neural Network) architecture trained through supervised learning.
In this study, retrospectively obtained radiographs were used in the development of artificial intelligence models for relevant situations. These datasets were obtained from the images of the patients who applied to ESOGU (Eskişehir Osmangazi University) Dentistry Faculty, Dentomaxillofacial Radiology clinic for various dental purposes. Eskisehir Osmangazi University Non-Interventional Clinical Research Ethics Board (decision date and decision number: 04.10.2022/22) approved the study protocol. The principles of the Helsinki Declaration were followed in the study.
Study design
- Observational model
- Case only
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Filling | – | Diagnostic Test: Panoramic Radiography |
| Overhanging Filling | – | Diagnostic Test: Panoramic Radiography |
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- These datasets were obtained from the images of the patients who applied to ESOGU Dentistry Faculty, Dentomaxillofacial Radiology clinic for various dental purposes.
Key inclusion criteria (3 listed)
- Images of individuals in the permanent dentition period
- Artifact-free images in the examination region
- Individuals with a history of restorative dental treatment
Key exclusion criteria (2 listed)
- Images of individuals in mixed dentition
- Radiographic images obtained by incorrect positioning of the patient or containing artifacts
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Panoramic Radiographythis retrospective study includes analysis of radiographs previously taken from patients for various purposes | Diagnostic test | Filling, Overhanging Filling |
Primary outcome
The success of artificial intelligence models for filling and overhanging filling
Time frame: 1 year
It is obtained by calculating the sensitivity, precision, and F1 scores values for filling and overhanging filling.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Sep 2023.
- Individual participant dataSharing planned: Yes. The investigators plan to publish the findings obtained as a result of the study in internationally journals and share this information within the publication.
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Dentomaxillofacial Radiology, run by Eskisehir Osmangazi University at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Sep 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The success of artificial intelligence models for filling and overhanging filling (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Sep 2023.