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OpenTrials
Completed

NCT Number: NCT06666907

Artificial Intelligence in Smile Designing

The study aims to assess the accuracy and patient satisfaction of smile designs based on artificial intelligence versus conventional DSD.

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Key information

Age range

18 year–30 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Faculty of Dentistry

Cairo, 11553, Egypt

About this study

Advances in digital technology are transforming dental esthetic treatments, particularly through the use of Digital Smile Design (DSD) software. These programs enable dentists to create personalized, natural-looking smile designs, improving both treatment planning and patient satisfaction. Initially, tools like PowerPoint and Photoshop were used for smile design, but modern DSD programs allow dentists to work with high-resolution 3D models to design smiles that align with facial features.

Digital smile design (DSD) technology allows dentists to create and preview new smile designs before treatment, aiding in detailed planning and clear communication with patients. This process consists of three main steps: (1) capturing digital images or videos to assess the patient's current smile, (2) analyzing these images to identify aesthetic needs, and (3) using digital tools to simulate the planned changes. Although these digital tools have greatly improved patient experience, they can be challenging to adopt in routine practice due to the required time, skill, and cost. However, this procedure could be time consuming and subjective to the dentist's skills and expertise.

To address this, artificial intelligence (AI) has been integrated into smile design software, automating tasks like facial analysis, image alignment, and smile design simulation. Accessible through apps or cloud-based platforms, AI software supports a variety of tasks, including identifying anatomical landmarks, adjusting images, and conducting live treatment simulations. DSD's integration with artificial intelligence (AI) offers further advancements, promising rapid, automated esthetic evaluations and smile designs Although AI-powered smile design tools are becoming popular in dental practices, some concerns exist that these tools may be used more for marketing purposes than for identifying genuine patient needs.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients with esthetic problems that require digital smile design.
  • Patient's age ranging from 19-30
  • Good oral hygiene.
  • Patients who have stable occlusion.

Exclusion criteria

  • Poor oral hygiene.
  • Patients with high caries or high plaque index.
  • Patients with periodontal problems.
  • Heavy bruxism habit or presence of any parafunctional habits.
  • Pregnant or lactating women.
  • Participating in another trial.

Treatment and study plan

Smilefy

Device

AI based DSD

EXOCAD

Device

Conventional DSD software

Primary outcomes

  1. Accuracy

    Time frame: immediately after the procedure

    Mean difference between the two designs measured in millimeters (mm) using geomagic control software.

Secondary outcomes

  1. Patient satisfaction

    Time frame: immediately after the procedure

    Visual analogue scale (VAS) from 0 to 10 (0 is the least satisfaction, 10 is the maximum satisfaction)

Sponsors and collaborators

Lead sponsor

Cairo University

Other

Registry information

Official study title

Accuracy of Artificial Intelligence Compared to Conventional Methods in Digital Smile Designing

Important dates

Study start
2024
Primary completion
2025
Study completion
2025
First posted
Oct 31, 2024
Registry last updated
Jun 11, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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