Artificial Intelligence-Guided Versus Manual CBCT Planning for Immediate Implant Placement (AI)

Shalash Dental education

Status: Not yet enrolling

Conditions: Immediate Implant; Guided Bone Regeneration; Dental Implant

Treatments: Procedure: Manual CBCT segmentation; Device: AI assisted CBCt

Study type: Interventional

Funder types: Other

Identifiers

NCT07459036

5-9-23

Details and patient eligibility

About

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.

Full 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.

Enrollment: 80 estimated patients

Sex: All

Ages: 18 to 99 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• 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).

Exclusion criteria

• 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 design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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80 participants in 2 patient groups

AI assisted CBCT

Experimental group

Description:

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

Treatment:

Device: AI assisted CBCt

Manual CBCT segmented

Active Comparator group

Description:

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

Treatment:

Procedure: Manual CBCT segmentation