Publication in Orthodontics & Craniofacial Research on 3D Predict Software

We're excited to share a newly published scientific article in Orthodontics & Craniofacial Research, conducted by Dr. Eser Tüfekçi, Dr. Caroline K. Carrico, Dr. Christina B. Gordon, and Dr. Steven J. Lindauer from the Department of Orthodontics at Virginia Commonwealth University (VCU).

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This study highlights how advanced CBCT analysis and AI-driven treatment planning can significantly improve outcomes in orthodontic and implantology cases, showcasing the benefits of a root- and bone-based approach to deliver more precise, predictable, and patient-centered treatment.

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Highlights from the Publication

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  • Enhanced Precision: CBCT-driven treatment planning offers detailed insights into root positions, alveolar bone structure, and jaw anatomy, paving the way for more accurate tooth movement, implant site creation, or tooth uprighting.
  • AI-powered Planning: The software automates complex calculations, enabling clinicians to streamline workflows and focus on patient care. It supports creating space for implants, uprighting teeth, and aligning roots for improved parallelism.
  • Evidence-based Research: Data was gathered from treatments performed using deep CBCT analysis software developed by 3D Predict, reinforcing the real-world applicability of these findings.

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Why It Matters

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While the publication does not mention specific brand names, it is noteworthy that the advanced CBCT analysis software and techniques used for the clinical cases were developed by 3D Predict.

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We believe this milestone reaffirms the transformative role of our technology in reshaping orthodontic and implantology practices.

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Read the Full Publication‍

‍Access the open-source article here: Deep CBCT Analysis & AI-driven Orthodontic Treatment Research