Dental ImplantNCT06967090
Accuracy of Guided Implant Placement Using Artificial Intelligence Segmentation Versus Conventional Technique
A study testing Implant surgery using surgical guide in people with Dental Implant, run by Fayoum University.
Trial summary
To compare the accuracy of surgical guided implant using AI tooth segmentation of the CBCT alone without intraoral scan to fabricate the implant guide versus conventional technique by alignment the CBCT and intraoral scan to fabricate the implant guide in posterior implant. Read more about this study
- Who is it for?
- Ages 18 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Dental Implant
- What is being tested?
- Implant surgery using surgical guide
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20 participants
- Where
- No sites listed yet
- Study dates
- 1 Jun 2025to Jul 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 18 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Patients with missing posterior teeth require implant surgery.
- Patients have remaining teeth that can support the surgical guide.
- The edentulous area should involve healed bone sites at least 3 months after extraction.
- The edentulous area should have bone height of at least 10 mm from the alveolar crest to the nearest vital structure and bone width of at least 6 mm.
- Age: patient above 18 years old.
- All patients are in good health with no systemic, immunologic or debilitating diseases that could affect normal bone healing.
- All selected patients are non-smokers and non-alcoholics. Patients are free from temporomandibular disorders and abnormal (TMD) oral habits such as bruxism.
Who cannot join
- Systemic disease that may affect bone quality.
- Patients with poor oral hygiene and active periodontal diseases.
- Patient with limited mouth opening.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Accuracy of Guided Implant Placement Using Artificial Intelligence Segmentation Versus Conventional Technique: A Randomized Clinical Trial
To compare the accuracy of surgical guided implant using AI tooth segmentation of the CBCT alone without intraoral scan to fabricate the implant guide versus conventional technique by alignment the CBCT and intraoral scan to fabricate the implant guide in posterior implant.
Read the detailed description
Background:
Implant dentistry has developed rapidly all around the world in the past few decades. A revolutionary change in the field of implant dentistry has been brought forward by Artificial intelligence (AI) technology. Many advantages come from the use of guided implant surgery and virtual implant planning, including optimal surgical and prosthetic treatment plan and predictable and effective application.
Statement of the problem:
Even with over ten years of clinical and research data, as well as advancements in apparatus and technique, there are still discrepancies between planned and achieved implant placements when using conventional guided implant surgery.
Review of literature:
Conventional guided implant surgery is considered the gold standard for implant placement as it provides a higher degree of accuracy and a lower risk of complications after surgery. Conventional guided implant surgery consists of 3 key steps. The first step is obtaining a 3D model of the manually segmented CBCT and a 3D model of the intraoral scan (IOS). The second step is alignment of the 3D model of the CBCT and the IOS by Iterative Closest Point Alignment (ICP Alignment). The third step is the virtual implant planning and surgical guide design. The segmentation is needed to create a 3D surface model from a CBCT or CT. Because of this, any error or inaccuracy in the segmentation or alignment process will lower the associated quality of virtual surgical planning.
Segmentation based on AI shows promise and saves time. This revolutionary AI-driven tool allows for precise and quick segmentation of the CBCT images. Therefore, all the steps of the conventional technique to fabricate an implant surgical guide can be less sophisticated if we use the AI segmentation alone without IOS.
Using AI tooth segmentation of the CBCT to obtain a 3D model and immediately, in one step, start virtual implant planning and designing a tooth-supported surgical guide without intraoral scan can minimize the clinical workload while opening the door for possible uses regarding digital workflows.
The outcomes of this investigation may contribute to the enhancement of pre-operative planning processes, including implant positioning and bone grafting. Still, not much has been discovered about how different segmentation techniques may affect clinical practice.
According to our knowledge there is deficiency in the literature in the evaluation of the accuracy of the AI segmentation of the CBCT when used alone in surgical implant guide without the use of intraoral scan.
- Conditions
- Dental Implant
- Being tested
- Implant surgery using surgical guide
- Keywords
- AI in guided dental implant
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Implant surgery using surgical guideDevice
Dental implant surgical guides are customized device used to position dental implants to ensure that the implant is placed in the most ideal location, angulation and depth into the bone.
| Study group | Role | What they receive |
|---|---|---|
| Study group: | Active comparator | Will use surgical guided implant using AI tooth segmentation of the CBCT alone without intraoral scan to fabricate the implant guide. Receives: Device: Implant surgery using surgical guide |
| Control group: | Active comparator | Will use surgical guided implant using conventional technique and intraoral scan to fabricate the implant guide. Receives: Device: Implant surgery using surgical guide |
What is being measured
The primary outcome is the main question the study is designed to answer.
The accuracy of the placed implants
The accuracy of the placed implants by measurements of the following:
Horizontal platform deviation, (Measuring unit in millimeter) corresponding to the horizontal distance between the virtually planned and actually placed implant platforms.
Measured: one week after surgery
Horizontal apex deviation, (Measuring unit in millimeter)
corresponding to the horizontal distance between the virtually planned and placed implant apices.
Measured: one week after surgery
Angular deviation, (Measuring unit in degree)
corresponding to the angle between the virtually planned and placed implant axes.
Measured: one week after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 May 2025
- Study start1 Jun 2025 (estimated)
- Primary completionJun 2026 (estimated)
- Study completionJul 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (13)Papers the sponsor has linked to this study.
- Other trials for Dental ImplantStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Fayoum University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Dina Emad Rabie, Fayoum University
- Investigators
- Haytham Ahmed Salah Al-Mahalawy, Phd, Study chair, Head of the Department of Oral & Maxillofacial Surgery Faculty of Dentistry Fayoum UniversityNourhan Mohamed Abdelmoneim, Phd, Study chair, Lecturer of Oral & Maxillofacial Surgery Faculty of Dentistry Fayoum University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06967090
- Sponsor's protocol ID
- AI in Guided implant surgery
- Status last verified
- May 2025
- First submitted
- 1 May 2025
- Last updated
- 13 May 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
On SW, Cho SW, Park SY, Yi SM, Park IY, Byun SH, Kim JC, Yang BE. Advancements in computer-assisted orthognathic surgery: A comprehensive review and clinical application in South Korea. J Dent. 2024 Jul;146:105061. doi: 10.1016/j.jdent.2024.105061. Epub 2024 May 9.
PubMed 38729289Altalhi AM, Alharbi FS, Alhodaithy MA, Almarshedy BS, Al-Saaib MY, Al Jfshar RM, Aljohani AS, Alshareef AH, Muhayya M, Al-Harbi NH. The Impact of Artificial Intelligence on Dental Implantology: A Narrative Review. Cureus. 2023 Oct 30;15(10):e47941. doi: 10.7759/cureus.47941. eCollection 2023 Oct.
PubMed 38034167Schubert O, Schweiger J, Stimmelmayr M, Nold E, Guth JF. Digital implant planning and guided implant surgery - workflow and reliability. Br Dent J. 2019 Jan 25;226(2):101-108. doi: 10.1038/sj.bdj.2019.44.
PubMed 30679852Mahardawi B, Jiaranuchart S, Arunjaroensuk S, Dhanesuan K, Mattheos N, Pimkhaokham A. The Accuracy of Dental Implant Placement With Different Methods of Computer-Assisted Implant Surgery: A Network Meta-Analysis of Clinical Studies. Clin Oral Implants Res. 2025 Jan;36(1):1-16. doi: 10.1111/clr.14357. Epub 2024 Sep 10.
PubMed 39254507Aghaloo T, Hadaya D, Schoenbaum TR, Pratt L, Favagehi M. Guided and Navigation Implant Surgery: A Systematic Review. Int J Oral Maxillofac Implants. 2023 May-Jun;38(suppl):7-15. doi: 10.11607/jomi.10465.
PubMed 37436945Ulbrich M, Van den Bosch V, Bonsch A, Gruber LJ, Ooms M, Melchior C, Motmaen I, Wilpert C, Rashad A, Kuhlen TW, Holzle F, Puladi B. Advantages of a Training Course for Surgical Planning in Virtual Reality for Oral and Maxillofacial Surgery: Crossover Study. JMIR Serious Games. 2023 Jan 19;11:e40541. doi: 10.2196/40541.
PubMed 36656632Marei HF, Abdel-Hady A, Al-Khalifa K, Al-Mahalawy H. Influence of surgeon experience on the accuracy of implant placement via a partially computer-guided surgical protocol. Int J Oral Maxillofac Implants. 2019 September/October;34(5):1177-1183. doi: 10.11607/jomi.7480. Epub 2019 Apr 1.
PubMed 30934035Khaohoen A, Powcharoen W, Sornsuwan T, Chaijareenont P, Rungsiyakull C, Rungsiyakull P. Accuracy of implant placement with computer-aided static, dynamic, and robot-assisted surgery: a systematic review and meta-analysis of clinical trials. BMC Oral Health. 2024 Mar 21;24(1):359. doi: 10.1186/s12903-024-04033-y.
PubMed 38509530Custodio ALN, Chrcanovic BR, Cameron A, Bakr M, Reher P. Accuracy evaluation of 3D-printed guide-assisted flapless micro-osteoperforations in the anterior mandible. Int J Comput Dent. 2022 Nov 25;25(4):387-396. doi: 10.3290/j.ijcd.b2599841.
PubMed 35072427Li Y, Lyu J, Cao X, Zhou Y, Tan J, Liu X. Accuracy of a calibration method based on cone beam computed tomography and intraoral scanner data registration for robot-assisted implant placement: An in vitro study. J Prosthet Dent. 2024 Dec;132(6):1309.e1-1309.e9. doi: 10.1016/j.prosdent.2024.08.009. Epub 2024 Sep 7.
PubMed 39245604Minnema J, Ernst A, van Eijnatten M, Pauwels R, Forouzanfar T, Batenburg KJ, Wolff J. A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery. Dentomaxillofac Radiol. 2022 Sep 1;51(7):20210437. doi: 10.1259/dmfr.20210437. Epub 2022 May 23.
PubMed 35532946Lahoud P, Diels S, Niclaes L, Van Aelst S, Willems H, Van Gerven A, Quirynen M, Jacobs R. Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT. J Dent. 2022 Jan;116:103891. doi: 10.1016/j.jdent.2021.103891. Epub 2021 Nov 13.
PubMed 34780873Shaheen E, Leite A, Alqahtani KA, Smolders A, Van Gerven A, Willems H, Jacobs R. A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation study. J Dent. 2021 Dec;115:103865. doi: 10.1016/j.jdent.2021.103865. Epub 2021 Oct 26.
PubMed 34710545
Study at a glance
From the registry record, last updated by the sponsor on 13 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Accuracy of Guided Implant Placement Using Artificial Intelligence Segmentation Versus Conventional Technique: A Randomized Clinical Trial
- ClinicalTrials.gov ID
- NCT06967090
- Acronym / sponsor ID
- AI in Guided implant surgery
- Conditions
- Dental Implant
- Keywords
- AI in guided dental implant
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- Fayoum UniversityUniversity, hospital or other
- Study start
- 1 Jun 2025 (estimated)
- Primary completion
- Jun 2026 (estimated)
- Study completion
- Jul 2026 (estimated)
- First posted
- 13 May 2025 (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.
To compare the accuracy of surgical guided implant using AI tooth segmentation of the CBCT alone without intraoral scan to fabricate the implant guide versus conventional technique by alignment the CBCT and intraoral scan to fabricate the implant guide in posterior implant.
Detailed description
Background:
Implant dentistry has developed rapidly all around the world in the past few decades. A revolutionary change in the field of implant dentistry has been brought forward by Artificial intelligence (AI) technology. Many advantages come from the use of guided implant surgery and virtual implant planning, including optimal surgical and prosthetic treatment plan and predictable and effective application.
Statement of the problem:
Even with over ten years of clinical and research data, as well as advancements in apparatus and technique, there are still discrepancies between planned and achieved implant placements when using conventional guided implant surgery.
Review of literature:
Conventional guided implant surgery is considered the gold standard for implant placement as it provides a higher degree of accuracy and a lower risk of complications after surgery. Conventional guided implant surgery consists of 3 key steps. The first step is obtaining a 3D model of the manually segmented CBCT and a 3D model of the intraoral scan (IOS). The second step is alignment of the 3D model of the CBCT and the IOS by Iterative Closest Point Alignment (ICP Alignment). The third step is the virtual implant planning and surgical guide design. The segmentation is needed to create a 3D surface model from a CBCT or CT. Because of this, any error or inaccuracy in the segmentation or alignment process will lower the associated quality of virtual surgical planning.
Segmentation based on AI shows promise and saves time. This revolutionary AI-driven tool allows for precise and quick segmentation of the CBCT images. Therefore, all the steps of the conventional technique to fabricate an implant surgical guide can be less sophisticated if we use the AI segmentation alone without IOS.
Using AI tooth segmentation of the CBCT to obtain a 3D model and immediately, in one step, start virtual implant planning and designing a tooth-supported surgical guide without intraoral scan can minimize the clinical workload while opening the door for possible uses regarding digital workflows.
The outcomes of this investigation may contribute to the enhancement of pre-operative planning processes, including implant positioning and bone grafting. Still, not much has been discovered about how different segmentation techniques may affect clinical practice.
According to our knowledge there is deficiency in the literature in the evaluation of the accuracy of the AI segmentation of the CBCT when used alone in surgical implant guide without the use of intraoral scan.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Study group: | Active comparator | Device: Implant surgery using surgical guideWill use surgical guided implant using AI tooth segmentation of the CBCT alone without intraoral scan to fabricate the implant guide. |
| Control group: | Active comparator | Device: Implant surgery using surgical guideWill use surgical guided implant using conventional technique and intraoral scan to fabricate the implant guide. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- Patients with missing posterior teeth require implant surgery.
- Patients have remaining teeth that can support the surgical guide.
- The edentulous area should involve healed bone sites at least 3 months after extraction.
- The edentulous area should have bone height of at least 10 mm from the alveolar crest to the nearest vital structure and bone width of at least 6 mm.
- Age: patient above 18 years old.
Key exclusion criteria (3 listed)
- Systemic disease that may affect bone quality.
- Patients with poor oral hygiene and active periodontal diseases.
- Patient with limited mouth opening.
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 |
|---|---|---|
| Implant surgery using surgical guideDental implant surgical guides are customized device used to position dental implants to ensure that the implant is placed in the most ideal location, angulation and depth into the bone. | Device | Control group:, Study group: |
Primary outcome
The accuracy of the placed implants
Time frame: one week after surgery
The accuracy of the placed implants by measurements of the following: Horizontal platform deviation, (Measuring unit in millimeter) corresponding to the horizontal distance between the virtually planned and actually placed implant platforms.
Horizontal apex deviation, (Measuring unit in millimeter)
Time frame: one week after surgery
corresponding to the horizontal distance between the virtually planned and placed implant apices.
Angular deviation, (Measuring unit in degree)
Time frame: one week after surgery
corresponding to the angle between the virtually planned and placed implant axes.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 May 2025.
- Background: PubMed 38729289On SW, Cho SW, Park SY, Yi SM, Park IY, Byun SH, Kim JC, Yang BE. Advancements in computer-assisted orthognathic surgery: A comprehensive review and clinical application in South Korea. J Dent. 2024 Jul;146:105061. doi: 10.1016/j.jdent.2024.105061. Epub 2024 May 9.
- Background: PubMed 38034167Altalhi AM, Alharbi FS, Alhodaithy MA, Almarshedy BS, Al-Saaib MY, Al Jfshar RM, Aljohani AS, Alshareef AH, Muhayya M, Al-Harbi NH. The Impact of Artificial Intelligence on Dental Implantology: A Narrative Review. Cureus. 2023 Oct 30;15(10):e47941. doi: 10.7759/cureus.47941. eCollection 2023 Oct.
- Background: PubMed 30679852Schubert O, Schweiger J, Stimmelmayr M, Nold E, Guth JF. Digital implant planning and guided implant surgery - workflow and reliability. Br Dent J. 2019 Jan 25;226(2):101-108. doi: 10.1038/sj.bdj.2019.44.
- Background: PubMed 39254507Mahardawi B, Jiaranuchart S, Arunjaroensuk S, Dhanesuan K, Mattheos N, Pimkhaokham A. The Accuracy of Dental Implant Placement With Different Methods of Computer-Assisted Implant Surgery: A Network Meta-Analysis of Clinical Studies. Clin Oral Implants Res. 2025 Jan;36(1):1-16. doi: 10.1111/clr.14357. Epub 2024 Sep 10.
- Background: PubMed 37436945Aghaloo T, Hadaya D, Schoenbaum TR, Pratt L, Favagehi M. Guided and Navigation Implant Surgery: A Systematic Review. Int J Oral Maxillofac Implants. 2023 May-Jun;38(suppl):7-15. doi: 10.11607/jomi.10465.
- Background: PubMed 36656632Ulbrich M, Van den Bosch V, Bonsch A, Gruber LJ, Ooms M, Melchior C, Motmaen I, Wilpert C, Rashad A, Kuhlen TW, Holzle F, Puladi B. Advantages of a Training Course for Surgical Planning in Virtual Reality for Oral and Maxillofacial Surgery: Crossover Study. JMIR Serious Games. 2023 Jan 19;11:e40541. doi: 10.2196/40541.
- Background: PubMed 30934035Marei HF, Abdel-Hady A, Al-Khalifa K, Al-Mahalawy H. Influence of surgeon experience on the accuracy of implant placement via a partially computer-guided surgical protocol. Int J Oral Maxillofac Implants. 2019 September/October;34(5):1177-1183. doi: 10.11607/jomi.7480. Epub 2019 Apr 1.
- Background: PubMed 38509530Khaohoen A, Powcharoen W, Sornsuwan T, Chaijareenont P, Rungsiyakull C, Rungsiyakull P. Accuracy of implant placement with computer-aided static, dynamic, and robot-assisted surgery: a systematic review and meta-analysis of clinical trials. BMC Oral Health. 2024 Mar 21;24(1):359. doi: 10.1186/s12903-024-04033-y.
- Background: PubMed 35072427Custodio ALN, Chrcanovic BR, Cameron A, Bakr M, Reher P. Accuracy evaluation of 3D-printed guide-assisted flapless micro-osteoperforations in the anterior mandible. Int J Comput Dent. 2022 Nov 25;25(4):387-396. doi: 10.3290/j.ijcd.b2599841.
- Background: PubMed 39245604Li Y, Lyu J, Cao X, Zhou Y, Tan J, Liu X. Accuracy of a calibration method based on cone beam computed tomography and intraoral scanner data registration for robot-assisted implant placement: An in vitro study. J Prosthet Dent. 2024 Dec;132(6):1309.e1-1309.e9. doi: 10.1016/j.prosdent.2024.08.009. Epub 2024 Sep 7.
- Background: PubMed 35532946Minnema J, Ernst A, van Eijnatten M, Pauwels R, Forouzanfar T, Batenburg KJ, Wolff J. A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery. Dentomaxillofac Radiol. 2022 Sep 1;51(7):20210437. doi: 10.1259/dmfr.20210437. Epub 2022 May 23.
- Background: PubMed 34780873Lahoud P, Diels S, Niclaes L, Van Aelst S, Willems H, Van Gerven A, Quirynen M, Jacobs R. Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT. J Dent. 2022 Jan;116:103891. doi: 10.1016/j.jdent.2021.103891. Epub 2021 Nov 13.
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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.
Haytham Ahmed Salah Al-Mahalawy, Phd study chair
Head of the Department of Oral & Maxillofacial Surgery Faculty of Dentistry Fayoum University
Nourhan Mohamed Abdelmoneim, Phd study chair
Lecturer of Oral & Maxillofacial Surgery Faculty of Dentistry Fayoum University
Questions about this trial
What is this clinical trial studying?
A study testing Implant surgery using surgical guide in people with Dental Implant, run by Fayoum University.
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 7 inclusion and 3 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: opening soon, as of the sponsor's last update on 13 May 2025. Status can change between updates, so confirm with the study contact before making plans.
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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Dina Emad Rabie, Bachelor's (00201104790329, de1279@fayoum.edu.eg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The accuracy of the placed implants (time frame: one week after surgery). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06967090, which also lists 13 linked publications.
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 13 May 2025.