Registration AccuracyNCT06273332
Assessment of the Artifical Intelligence Assisted Registration Versus Conventional Point Based Registration on Cone Beam-computed Tomography (CBCT) With Heavy Metal Artifacts
A study testing AI-assisted registration and Point-based registration in people with Registration Accuracy, run by Ain Shams University at 1 site in Egypt.
Trial summary
Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure. Read more about this study
- Who is it for?
- Ages 15 years and olderHealthy volunteers can take part
- Conditions the study is for
- Registration Accuracy
- What is being tested?
- AI-assisted registration and Point-based registration
- Type of treatment
- Pill or oral medicine
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 16 participants
- Where
- 1 siteEgypt
- Study dates
- 20 Dec 2023to 25 Feb 2024
- Phase
- Interventional
- 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 15 years and older
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- CBCT scans for either the maxilla or mandible or both and intraoral scans or manual impressions with metal restorations.
Who cannot join
- Scans without metal restorations.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Assessment of the AI-assisted Registration Versus Conventional Point-based Registration on CBCTs With Heavy Metal Artifacts
Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure.
Read the detailed description
CBCT images and intraoral scans will be screened following specific eligibility criteria. 16 CBCT images and intraoral scans that will meet the inclusion criteria will undergo manual segmentation via 3D medical image processing software. Afterward, point-based registration and AI-assisted registration will be performed by a single operator using specialized implant planning software. Then, the registration accuracy will be examined by measuring the distances between the three-dimensional models of CBCT data and intraoral scans. Also, the duration required for registration will be calibrated and recorded by a stopwatch.
- Conditions
- Registration Accuracy
- Being tested
- AI-assisted registration, Point-based registration
- Keywords
- Point-based registration, AI registration, Accuracy, Digital implant planning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-assisted registrationOther
We will use artificial intelligence to register 3d model on intra-oral scan
Point-based registrationOther
We will use five references points or more to perform model registration
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted registration | Experimental | 3D model registration will be carried out using artificial intelligence Receives: Other: AI-assisted registration |
| Point-based registration | Active comparator | 3D model registration will be carried out using point-based approach Receives: Other: Point-based registration |
What is being measured
The primary outcome is the main question the study is designed to answer.
Registration accuracy
Distance between registered 3d model and CBCT in millimeters
Measured: immediately after the procedure
Secondary outcomes (1)
Duration for registration
time taken for registration procedure
Measured: During the procedure
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Feb 2024
- Study start20 Dec 2023
- Primary completion20 Jan 2024
- Study completion25 Feb 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Registration AccuracyStudies of the same condition, open and under way.
- More trials run by Ain Shams UniversityThe sponsor's other registered studies.
- 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 16 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ain Shams University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Nehal Ibrahim Ahmed Shobair, Ain Shams University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06273332
- Sponsor's protocol ID
- AI surgery protocol
- Status last verified
- Feb 2024
- First submitted
- 5 Feb 2024
- Last updated
- 22 Feb 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: no data will be shared
Study at a glance
From the registry record, last updated by the sponsor on 22 Feb 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessment of the AI-assisted Registration Versus Conventional Point-based Registration on CBCTs With Heavy Metal Artifacts
- ClinicalTrials.gov ID
- NCT06273332
- Acronym / sponsor ID
- AI surgery protocol
- Conditions
- Registration Accuracy
- Keywords
- Point-based registration, AI registration, Accuracy, Digital implant planning
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 16 participants (estimated)
- Lead sponsor
- Ain Shams UniversityUniversity, hospital or other
- Study start
- 20 Dec 2023 (actual)
- Primary completion
- 20 Jan 2024 (actual)
- Study completion
- 25 Feb 2024 (estimated)
- First posted
- 22 Feb 2024 (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.
Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure.
Detailed description
CBCT images and intraoral scans will be screened following specific eligibility criteria. 16 CBCT images and intraoral scans that will meet the inclusion criteria will undergo manual segmentation via 3D medical image processing software. Afterward, point-based registration and AI-assisted registration will be performed by a single operator using specialized implant planning software. Then, the registration accuracy will be examined by measuring the distances between the three-dimensional models of CBCT data and intraoral scans. Also, the duration required for registration will be calibrated and recorded by a stopwatch.
Study design
- Primary purpose
- Other
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted registration | Experimental | Other: AI-assisted registration3D model registration will be carried out using artificial intelligence |
| Point-based registration | Active comparator | Other: Point-based registration3D model registration will be carried out using point-based approach |
Who may qualify
- Ages
- 15 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- CBCT scans for either the maxilla or mandible or both and intraoral scans or manual impressions with metal restorations.
Key exclusion criteria (1 listed)
- Scans without metal restorations.
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 |
|---|---|---|
| AI-assisted registrationWe will use artificial intelligence to register 3d model on intra-oral scan | Other | AI-assisted registration |
| Point-based registrationWe will use five references points or more to perform model registration | Other | Point-based registration |
Primary outcome
Registration accuracy
Time frame: immediately after the procedure
Distance between registered 3d model and CBCT in millimeters
1 secondary outcome
Duration for registration
Time frame: During the procedure
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Feb 2024.
- Individual participant dataSharing planned: No. no data will be shared
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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?
A study testing AI-assisted registration and Point-based registration in people with Registration Accuracy, run by Ain Shams University at 1 site in Egypt.
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 1 inclusion and 1 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: status not confirmed, as of the sponsor's last update on 22 Feb 2024. 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 Egypt. 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?
Results are not available in the source record.
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?
Registration accuracy (time frame: immediately after the procedure). 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 22 Feb 2024.