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Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment

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[Diagnostic methods for transverse problems of malocclusion].

L Chen¹, J Guo¹

¹Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan 250012, China.

Zhonghua Kou Qiang Yi Xue Za Zhi = Zhonghua Kouqiang Yixue Zazhi = Chinese Journal of Stomatology

|November 27, 2025

Summary

Diagnosing transverse discrepancies in malocclusion is key for effective orthodontic treatment. This review analyzes current diagnostic methods, digital technologies, and AI applications for better treatment consistency.

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Area of Science:

Dentistry
Orthodontics
Dental Diagnostics

Background:

Transverse discrepancy, a common issue in three-dimensional occlusal abnormalities, involves disharmony in maxillary and mandibular arch widths.
Maxillary transverse deficiency is a prevalent clinical challenge impacting orthodontic treatment planning and outcomes.

Purpose of the Study:

To systematically review and analyze the current diagnostic methods for transverse discrepancies in malocclusion.
To explore emerging digital technologies and artificial intelligence applications in diagnosing transverse problems.
To identify challenges and progress in standardizing diagnostic criteria for transverse discrepancies.

Main Methods:

Systematic literature review of diagnostic methods for transverse discrepancies.
Analysis of traditional diagnostic techniques.
Evaluation of digital technologies and artificial intelligence in orthodontics.

Main Results:

Diagnostic criteria for transverse problems lack unification, affecting treatment decisions.
Digital technologies offer new avenues for precise diagnosis.
Artificial intelligence shows potential for improving diagnostic accuracy and consistency.

Conclusions:

Standardized diagnostic criteria are needed for transverse discrepancies in malocclusion.
Integrating digital tools and AI can enhance diagnostic accuracy and treatment planning.
Further research is required to establish unified diagnostic protocols and leverage AI effectively.