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

NCT07459036 | Not Yet Recruiting DMC

• 1 other identifier: 5-9-23
• Study Type: interventional
• Target: 80
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Dental Implant; Immediate Implant; Guided Bone Regeneration

Outcome Measures

Primary Outcomes (1)

• Immediate implant feasability

  Proportion of sites with successful immediate implant placement with primary stability at the index surgery (feasible vs not feasible).

  During the implant surgery-intra operative after flap elevation

Secondary Outcomes (1)

• Planning time (minutes)

  Preoperative before the surgery

Study Arms (2)

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

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

Procedure: Manual CBCT segmentation

Interventions

AI assisted CBCt DEVICE

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.

AI assisted CBCT

Manual CBCT segmentation PROCEDURE

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

Manual CBCT segmented

Eligibility Criteria

• Age: 18 Years - 99 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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).

You may not qualify if:

• 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).

Sponsors & Collaborators

• Shalash Dental education: lead

Study Sites (1)

Shalash Implant education

Cairo, Egypt

Location

Study Officials

• Mahmoud Shalash, PhD

  Shalash Implant education

  STUDY DIRECTOR

Central Study Contacts

Mihad Ibrahim, M.Sc

CONTACT

00201008551124; mihad.farouk@hotmail.com

Mahmoud Shalash, PhD

CONTACT

00201006151498; Dr_shalash@yahoo.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical researcher

Study Record Dates

• First Submitted: March 1, 2026
• First Posted: March 9, 2026
• Study Start: March 3, 2026
• Primary Completion: April 2, 2026
• Study Completion: May 2, 2026
• Last Updated: March 9, 2026

Record last verified: 2026-03

Locations

EG (1)