Related Experiment Video
Updated: Jun 27, 2025
09:10
Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
Published on: July 12, 2022
2.9K
Tooth-size discrepancy: a clinical necessity
19 allée Jeanne Guillon, 35000 Rennes, France
L' Orthodontie Francaise
|May 3, 2024
Summary
Dento-dental disharmony (DDD) is often discovered late due to diagnostic challenges. Early detection using indices and AI can improve treatment outcomes.
Area of Science:
- Dentistry
- Orthodontics
- Dental Morphology
Context:
- Dento-dental disharmony (DDD) is frequently diagnosed at the conclusion of orthodontic treatment, leading to patient dissatisfaction.
- Clinical examination alone often fails to detect DDD due to masking compensatory mechanisms, particularly when co-occurring with other dental anomalies.
Purpose:
- To highlight the challenges in diagnosing dento-dental disharmony (DDD) during orthodontic treatment.
- To introduce diagnostic aids, such as the Bolton index and pre-treatment models, for identifying DDD.
- To explore the potential of artificial intelligence in the systematic diagnosis of DDD.
Summary:
- This study addresses the late discovery of dento-dental disharmony (DDD), a common cause of treatment disappointment.
- It emphasizes that DDD is difficult to diagnose clinically due to compensatory mechanisms and associated dysmorphoses.
- The use of indices like Bolton's on pre-treatment models is crucial for diagnosis and prognosis, while adapting dental volumes can resolve DDD.
Impact:
- Improved diagnostic accuracy for dento-dental disharmony (DDD) can prevent treatment failures.
- The integration of AI in dental diagnostics promises more systematic and earlier detection of DDD.
- Proactive identification and management of DDD will enhance patient satisfaction and orthodontic treatment success.
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