Comparative Study Between Artificial Intelligence-Assisted/Computer-Guided Versus Conventional Ridge Splitting Utilizing Electromagnetic Mallet for Reconstruction of Horizontal Ridge Defects: A Randomized Controlled Clinical Study

Status: Recruiting
Location: See location...
Intervention Type: Procedure
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY

The current trial aims to assess the efficacy of utilizing the electromagnetic mallet either by AI-assisted digital workflow or by the conventional freehand approach for reconstruction of horizontal ridge defects utilizing the ridge-split and expansion technique.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 40
Healthy Volunteers: t
View:

• The target population with inadequate bone volume for implant placement due to width insufficiency of maxillary anterior alveolar ridges.

• Age ranges from 18 to 40 years of both sexes.

• Absence of any complicating systemic condition that may contraindicate surgical procedures and implant placement.

• Adequate oral hygiene.

• Eligible participants should present good general health and agree to random assignment to any of the two parallel study groups.

• Participants had a minimum 3-month post-extraction healing period and a horizontal defect in the maxillary esthetic zone with at least a bone width of 3 mm.

Locations
Other Locations
Egypt
Faculty of Dentistry, Periodontology Department
RECRUITING
Kafr Ash Shaykh
Contact Information
Primary
Asmaa Hamdy Elgarawany, Lecturer
asmaahady@gmail.com
+201229460097
Time Frame
Start Date: 2024-08-27
Estimated Completion Date: 2026-03
Participants
Target number of participants: 22
Treatments
Experimental: Freehand spit
conventional ridge splitting with conventional simultaneous implant placement
Experimental: computer-guided split
computer-guided ridge splitting assisted by artificial intelligence with simultaneous computer-guided implant placement.
Related Therapeutic Areas
Sponsors
Leads: Kafrelsheikh University

This content was sourced from clinicaltrials.gov