Orthodontics in 2025: Evidence Based Clinical Practice

This is the definitive guide to practicing orthodontics in the modern era. This book is a complete roadmap to the evidence-based clinical practice of 2025. It re-examines the core of the specialty, from diagnosis to finishing. You'll learn the new patient exam, integrating 3D imaging and systemic health. We dive deep into the biology of tooth movement, including the latest on epigenetics. The text covers advanced biomechanics and how to create truly personalized treatment plans using AI and Finite Element Analysis. It details managing growing patients, covering Class II and Class III correction with modern functional appliances and skeletal anchorage. You'll master the debate between extraction and non-extraction with a profile-driven approach. We explore interceptive treatment in the mixed dentition, including the use of clear aligners in children. The book provides a masterclass in the fully digital workflow, from intraoral scanning to in-house 3D printing of appliances. It offers a critical, science-backed review of clear aligner therapy and techniques for accelerating treatment. Finally, it expands your role into interdisciplinary care, focusing on airway-focused orthodontics and integrated planning for orthognathic surgery.

What makes this book different is its synthesis of what's new and what's essential. Other texts might show you a single new technique or rehash old principles. Orthodontics in 2025 connects the dots. It doesn't just tell you what AI-powered diagnostics or Mini-implant Assisted Rapid Palatal Expansion (MARPE) are; it shows you how they fit into a seamless clinical workflow. It moves beyond isolated chapters on biomechanics or growth, demonstrating how a deep understanding of biology, informed by computational power, leads to a new standard of personalized, predictive, and patient-centered care. This book isn't just a collection of facts; it's a new framework for thinking about and practicing orthodontics at the highest level.

Disclaimer: The author of this work is not affiliated, associated, authorized, endorsed by, or in any way officially connected with the University of Pennsylvania, New York University (NYU), Saint Louis University (SLU), Jefferson Health, Columbia University, University of Illinois Chicago (UIC), the University of Michigan, Seton Hill University, or the University of the Pacific. All institutional and company names are used for identification and descriptive purposes only, under the principle of nominative fair use. This is an independently produced publication.