Dental ImplantAINCT07459036
Artificial Intelligence-Guided Versus Manual CBCT Planning for Immediate Implant Placement
A study testing AI assisted CBCt and Manual CBCT segmentation in people with Dental Implant and Immediate Implant, run by Shalash Dental education at 1 site in Egypt.
Trial summary
This study evaluates whether artificial intelligence (AI)-based analysis of cone-beam computed tomography (CBCT) scans can support clinical decision-making for immediate dental implant placement in molar extraction sites. Read more about this study
- Who is it for?
- Ages 18 to 99 yearsHealthy volunteers can take part
- Conditions the study is for
- Dental Implant, Immediate Implant, Guided Bone Regeneration
- What is being tested?
- AI assisted CBCt and Manual CBCT segmentation
- Type of treatment
- Pill or oral medicine, Medical device, Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 80 participants
- Where
- 1 siteEgypt
- Study dates
- 3 Mar 2026to 2 May 2026
- 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 18 to 99 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Adults≥18 years are able to provide informed consent. Indicated for the extraction of a molar tooth (maxillary or mandibular) with planned implant-supported rehabilitation.
- Candidate for immediate implant placement attempt based on preoperative clinical evaluation and CBCT availability.
- Preoperative CBCT will be acquired using the study imaging protocol within a defined window (e.g., ≤4 weeks before surgery).
- Adequate oral hygiene and periodontal condition compatible with implant surgery (e.g., treated/stable periodontal status per clinician judgement).
Who cannot join
- Pregnancy or breastfeeding (due to imaging/surgical considerations).
- Uncontrolled systemic disease or medical contraindication to oral surgery/implant placement (e.g., uncontrolled diabetes, immunosuppression as judged by clinician).
- History of head and neck radiotherapy in the implant region. Use of medications associated with compromised bone healing where immediate implant placement is not advised (e.g., high-dose antiresorptives/IV bisphosphonates; you can specify per your clinic policy).
- Acute uncontrolled infection at the site requiring staged management (e.g., spreading cellulitis/abscess) or other condition precluding immediate placement per surgeon judgement.
- Need for simultaneous major augmentation that precludes immediate implant placement (e.g., extensive ridge reconstruction planned at the same surgery rather than socket-level grafting).
- Inadequate CBCT quality for segmentation/measurement (motion artifacts, incomplete field of view, or metal artifact obscuring the septum).
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Artificial Intelligence-Guided Versus Manual CBCT Planning for Immediate Implant Placement in Molar Extraction Sites: A Randomized Controlled Trial
This study evaluates whether artificial intelligence (AI)-based analysis of cone-beam computed tomography (CBCT) scans can support clinical decision-making for immediate dental implant placement in molar extraction sites.
When a molar tooth is removed, placing a dental implant immediately may reduce treatment time and preserve surrounding bone. However, immediate implant placement is not always possible and depends on the anatomy of the extraction socket, particularly the interradicular septum (the bone between the roots). CBCT imaging is routinely used to assess this anatomy before surgery. Traditionally, radiologists manually evaluate these scans. Recently, AI-based tools have been developed to automatically analyze CBCT images.
Read more
In this randomized controlled trial, patients requiring molar extraction and potential immediate implant placement will be assigned to one of two planning approaches: AI-guided CBCT assessment or conventional manual CBCT assessment. The operating surgeon will use the assigned planning report to guide treatment decisions.
The primary outcome of the study is the feasibility of immediate implant placement, defined as successful implant placement with achievement of primary stability during surgery. Secondary outcomes include surgical time, need for changes to the treatment plan, and implant stability measurements.
The goal of this study is to determine whether AI-assisted CBCT analysis performs similarly to, or improves upon, conventional manual radiologic assessment in supporting safe and effective immediate implant placement.
Read the detailed description
This study is a prospective, parallel-arm, randomized controlled clinical trial designed to evaluate the clinical impact of artificial intelligence (AI)-based CBCT analysis on decision-making for immediate implant placement in molar extraction sites.
Following eligibility confirmation and informed consent, participants requiring molar extraction with potential immediate implant placement will undergo standardized preoperative cone-beam computed tomography (CBCT) imaging. Participants will be randomly allocated in a 1:1 ratio to one of two planning workflows:
AI-guided planning arm: CBCT scans will be analyzed using a pre-specified, locked AI-based segmentation and socket assessment model. The AI system will quantify interradicular septum dimensions and generate a feasibility classification based on predefined anatomical criteria.
Manual planning arm: CBCT scans will undergo conventional manual segmentation and assessment by an experienced radiologist using the same predefined anatomical criteria for feasibility determination.
In both arms, feasibility recommendations will be based on identical, prospectively defined decision thresholds to ensure comparability between planning methods. The operating surgeon will receive only the planning report corresponding to the assigned allocation.
All surgeries will be performed according to a standardized surgical protocol. The primary outcome is intraoperative feasibility of immediate implant placement, defined as successful implant placement in the extraction socket with achievement of primary stability according to prespecified stability criteria documented in the operative record. Cases in which implant placement is not performed or is aborted due to inability to achieve adequate primary stability will be classified as non-feasible.
Secondary outcomes include operative time, need for intraoperative modification of the treatment plan, insertion torque values, and any intraoperative complications.
Outcome assessment will be performed by an independent assessor blinded to allocation. AI analysis will be conducted using a locked model without post hoc modification.
The study aims to determine whether AI-guided CBCT planning is non-inferior or superior to conventional manual CBCT assessment in supporting immediate implant placement decisions.
- Conditions
- Dental Implant, Immediate Implant, Guided Bone Regeneration
- Being tested
- AI assisted CBCt, Manual CBCT segmentation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI assisted CBCtDevice
The intervention consists of a fully automated, deep learning-based CBCT analysis pipeline designed for extraction socket segmentation and quantitative interradicular septum assessment.
The AI system utilizes a pre-trained convolutional neural network architecture to perform voxel-level segmentation of the extraction socket and surrounding alveolar structures on CBCT datasets. Following segmentation, the model automatically quantifies predefined anatomical parameters, including interradicular septum width at standardized reference levels and socket morphology classification. These measurements are generated using algorithmically defined geometric landmarks, ensuring consistent spatial reference across cases.
Feasibility for immediate implant placement is determined using a prespecified, protocol-defined decision rule applied to AI-derived quantitative parameters.
Manual CBCT segmentationProcedure or surgery
The control intervention consists of conventional radiologic evaluation of CBCT datasets using manual segmentation and operator-driven anatomical assessment.
CBCT scans will be reviewed by an experienced oral and maxillofacial radiologist using standard imaging software. Interradicular septum dimensions will be determined through manual identification of anatomical landmarks and measurement using software-based calipers at predefined reference levels. Socket morphology classification will be assigned based on visual interpretation and application of the same predefined anatomical criteria specified in the study protocol.
Feasibility for immediate implant placement will be determined by applying the protocol-defined decision thresholds to manually obtained measurements. All measurements and classifications will be documented in a structured planning report provided to the operating surgeon.
Unlike the AI-guided intervention, this workflow relies on manual landmark identification and ope
| Study group | Role | What they receive |
|---|---|---|
| AI assisted CBCT | Experimental | Participants randomized to this arm will undergo preoperative cone-beam computed tomography (CBCT) imaging as part of standard diagnostic workup for molar extraction with potential immediate implant placement.
CBCT datasets will be processed using a pre-specified, locked artificial intelligence (AI)-based segmentation and socket assessment model. The AI system will automatically segment the extraction socket anatomy, quantify interradicular septum dimensions, and generate a structured feasibility assessment according to predefined anatomical decision thresholds established in the study protocol.
A standardized AI-generated planning report, including septum measurements and feasibility classification, will be provided to the operating surgeon prior to surgery. The surgeon will use this report to guide preoperative planning and intraoperative decision-making.
Surgical procedures will be performed according to a standardized surgical protocol. Immediate implant placement will be attempte Receives: Device: AI assisted CBCt |
| Manual CBCT segmented | Active comparator | Participants randomized to this arm will undergo preoperative CBCT imaging as part of the standard diagnostic workup for molar extraction with potential immediate implant placement.
CBCT datasets will be evaluated using conventional manual segmentation and radiologic assessment performed by an experienced radiologist. Interradicular septum dimensions and socket morphology will be assessed according to predefined anatomical criteria specified in the study protocol. Feasibility for immediate implant placement will be determined using the same prospectively defined decision thresholds applied in the intervention arm.
A standardized manual planning report, including septum measurements and feasibility classification, will be provided to the operating surgeon before surgery. The surgeon will use this report to guide preoperative planning and intraoperative decision-making.
Surgical procedures will be performed according to the same standardized surgical protocol Receives: Procedure: Manual CBCT segmentation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Immediate implant feasability
Proportion of sites with successful immediate implant placement with primary stability at the index surgery (feasible vs not feasible).
Measured: During the implant surgery-intra operative after flap elevation
Secondary outcomes (1)
Planning time (minutes)
Time to generate the report (AI processing time vs manual segmentation/assessment time).
Measured: Preoperative before the surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Mar 2026
- Study start3 Mar 2026
- Primary completion2 Apr 2026
- Study completion2 May 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- 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
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 80 participants (actual)
Sponsor and investigators
- Lead sponsor
- Shalash Dental education
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Mihad Ibrahim, Shalash Dental education
- Investigators
- Mahmoud Shalash, PhD, Study director, Shalash Implant education
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07459036
- Sponsor's protocol ID
- 5-9-23
- Acronym
- AI
- Status last verified
- Mar 2026
- First submitted
- 1 Mar 2026
- Last updated
- 30 Sep 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 30 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-Guided Versus Manual CBCT Planning for Immediate Implant Placement in Molar Extraction Sites: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07459036
- Acronym / sponsor ID
- AI / 5-9-23
- Conditions
- Dental Implant, Immediate Implant, Guided Bone Regeneration
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 80 participants (actual)
- Lead sponsor
- Shalash Dental educationUniversity, hospital or other
- Study start
- 3 Mar 2026 (actual)
- Primary completion
- 2 Apr 2026 (actual)
- Study completion
- 2 May 2026 (actual)
- First posted
- 9 Mar 2026 (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.
This study evaluates whether artificial intelligence (AI)-based analysis of cone-beam computed tomography (CBCT) scans can support clinical decision-making for immediate dental implant placement in molar extraction sites.
When a molar tooth is removed, placing a dental implant immediately may reduce treatment time and preserve surrounding bone. However, immediate implant placement is not always possible and depends on the anatomy of the extraction socket, particularly the interradicular septum (the bone between the roots). CBCT imaging is routinely used to assess this anatomy before surgery. Traditionally, radiologists manually evaluate these scans. Recently, AI-based tools have been developed to automatically analyze CBCT images.
In this randomized controlled trial, patients requiring molar extraction and potential immediate implant placement will be assigned to one of two planning approaches: AI-guided CBCT assessment or conventional manual CBCT assessment. The operating surgeon will use the assigned planning report to guide treatment decisions.
The primary outcome of the study is the feasibility of immediate implant placement, defined as successful implant placement with achievement of primary stability during surgery. Secondary outcomes include surgical time, need for changes to the treatment plan, and implant stability measurements.
The goal of this study is to determine whether AI-assisted CBCT analysis performs similarly to, or improves upon, conventional manual radiologic assessment in supporting safe and effective immediate implant placement.
Detailed description
This study is a prospective, parallel-arm, randomized controlled clinical trial designed to evaluate the clinical impact of artificial intelligence (AI)-based CBCT analysis on decision-making for immediate implant placement in molar extraction sites.
Following eligibility confirmation and informed consent, participants requiring molar extraction with potential immediate implant placement will undergo standardized preoperative cone-beam computed tomography (CBCT) imaging. Participants will be randomly allocated in a 1:1 ratio to one of two planning workflows:
AI-guided planning arm: CBCT scans will be analyzed using a pre-specified, locked AI-based segmentation and socket assessment model. The AI system will quantify interradicular septum dimensions and generate a feasibility classification based on predefined anatomical criteria.
Manual planning arm: CBCT scans will undergo conventional manual segmentation and assessment by an experienced radiologist using the same predefined anatomical criteria for feasibility determination.
In both arms, feasibility recommendations will be based on identical, prospectively defined decision thresholds to ensure comparability between planning methods. The operating surgeon will receive only the planning report corresponding to the assigned allocation.
All surgeries will be performed according to a standardized surgical protocol. The primary outcome is intraoperative feasibility of immediate implant placement, defined as successful implant placement in the extraction socket with achievement of primary stability according to prespecified stability criteria documented in the operative record. Cases in which implant placement is not performed or is aborted due to inability to achieve adequate primary stability will be classified as non-feasible.
Secondary outcomes include operative time, need for intraoperative modification of the treatment plan, insertion torque values, and any intraoperative complications.
Outcome assessment will be performed by an independent assessor blinded to allocation. AI analysis will be conducted using a locked model without post hoc modification.
The study aims to determine whether AI-guided CBCT planning is non-inferior or superior to conventional manual CBCT assessment in supporting immediate implant placement decisions.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI assisted CBCT | Experimental | Device: AI assisted CBCtParticipants randomized to this arm will undergo preoperative cone-beam computed tomography (CBCT) imaging as part of standard diagnostic workup for molar extraction with potential immediate implant placement. CBCT datasets will be processed using a pre-specified, locked artificial intelligence (AI)-based segmentation and socket assessment model. The AI system will automatically segment the extraction socket anatomy, quantify interradicular septum dimensions, and generate a structured feasibility assessment according to predefined anatomical decision thresholds established in the study protocol. A standardized AI-generated planning report, including septum measurements and feasibility classification, will be provided to the operating surgeon prior to surgery. The surgeon will use this report to guide preoperative planning and intraoperative decision-making. Surgical procedures will be performed according to a standardized surgical protocol. Immediate implant placement will be attempte |
| Manual CBCT segmented | Active comparator | Procedure: Manual CBCT segmentationParticipants randomized to this arm will undergo preoperative CBCT imaging as part of the standard diagnostic workup for molar extraction with potential immediate implant placement. CBCT datasets will be evaluated using conventional manual segmentation and radiologic assessment performed by an experienced radiologist. Interradicular septum dimensions and socket morphology will be assessed according to predefined anatomical criteria specified in the study protocol. Feasibility for immediate implant placement will be determined using the same prospectively defined decision thresholds applied in the intervention arm. A standardized manual planning report, including septum measurements and feasibility classification, will be provided to the operating surgeon before surgery. The surgeon will use this report to guide preoperative planning and intraoperative decision-making. Surgical procedures will be performed according to the same standardized surgical protocol |
Who may qualify
- Ages
- 18 to 99 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Adults≥18 years are able to provide informed consent. Indicated for the extraction of a molar tooth (maxillary or mandibular) with planned implant-supported rehabilitation.
- Candidate for immediate implant placement attempt based on preoperative clinical evaluation and CBCT availability.
- Preoperative CBCT will be acquired using the study imaging protocol within a defined window (e.g., ≤4 weeks before surgery).
- Adequate oral hygiene and periodontal condition compatible with implant surgery (e.g., treated/stable periodontal status per clinician judgement).
Key exclusion criteria (6 listed)
- Pregnancy or breastfeeding (due to imaging/surgical considerations).
- Uncontrolled systemic disease or medical contraindication to oral surgery/implant placement (e.g., uncontrolled diabetes, immunosuppression as judged by clinician).
- History of head and neck radiotherapy in the implant region. Use of medications associated with compromised bone healing where immediate implant placement is not advised (e.g., high-dose antiresorptives/IV bisphosphonates; you can specify per your clinic policy).
- Acute uncontrolled infection at the site requiring staged management (e.g., spreading cellulitis/abscess) or other condition precluding immediate placement per surgeon judgement.
- Need for simultaneous major augmentation that precludes immediate implant placement (e.g., extensive ridge reconstruction planned at the same surgery rather than socket-level grafting).
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 CBCtThe intervention consists of a fully automated, deep learning-based CBCT analysis pipeline designed for extraction socket segmentation and quantitative interradicular septum assessment. The AI system utilizes a pre-trained convolutional neural network architecture to perform voxel-level segmentation of the extraction socket and surrounding alveolar structures on CBCT datasets. Following segmentation, the model automatically quantifies predefined anatomical parameters, including interradicular septum width at standardized reference levels and socket morphology classification. These measurements are generated using algorithmically defined geometric landmarks, ensuring consistent spatial reference across cases. Feasibility for immediate implant placement is determined using a prespecified, protocol-defined decision rule applied to AI-derived quantitative parameters. | Device | AI assisted CBCT |
| Manual CBCT segmentationThe control intervention consists of conventional radiologic evaluation of CBCT datasets using manual segmentation and operator-driven anatomical assessment. CBCT scans will be reviewed by an experienced oral and maxillofacial radiologist using standard imaging software. Interradicular septum dimensions will be determined through manual identification of anatomical landmarks and measurement using software-based calipers at predefined reference levels. Socket morphology classification will be assigned based on visual interpretation and application of the same predefined anatomical criteria specified in the study protocol. Feasibility for immediate implant placement will be determined by applying the protocol-defined decision thresholds to manually obtained measurements. All measurements and classifications will be documented in a structured planning report provided to the operating surgeon. Unlike the AI-guided intervention, this workflow relies on manual landmark identification and ope | Procedure or surgery | Manual CBCT segmented |
Primary outcome
Immediate implant feasability
Time frame: During the implant surgery-intra operative after flap elevation
Proportion of sites with successful immediate implant placement with primary stability at the index surgery (feasible vs not feasible).
1 secondary outcome
Planning time (minutes)
Time frame: Preoperative before the surgery
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 30 Sep 2026.
- Individual participant dataSharing planned: Undecided
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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.
Mahmoud Shalash, PhD study director
Shalash Implant education
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 CBCt and Manual CBCT segmentation in people with Dental Implant and Immediate Implant, run by Shalash Dental education 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 4 inclusion and 6 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 30 Sep 2026. 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?
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?
Immediate implant feasability (time frame: During the implant surgery-intra operative after flap elevation). 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 30 Sep 2026.