How AI ‐Driven Root and Bone Predictions Can Assist Clear Aligner Treatment Planning

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Autori principali: Eser Tüfekçi, Caroline K. Carrico, Christina B. Gordon, Steven J. Lindauer
Natura: Artículo Open Access
Pubblicazione: Wiley 2025
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author Eser Tüfekçi
Caroline K. Carrico
Christina B. Gordon
Steven J. Lindauer
author_facet Eser Tüfekçi
Caroline K. Carrico
Christina B. Gordon
Steven J. Lindauer
Eser Tüfekçi
Caroline K. Carrico
Christina B. Gordon
Steven J. Lindauer
collection Wiley Open Access
contents How AI ‐Driven Root and Bone Predictions Can Assist Clear Aligner Treatment Planning Eser Tüfekçi Caroline K. Carrico Christina B. Gordon Steven J. Lindauer Orthodontics & Craniofacial Research ABSTRACT Integrating artificial intelligence (AI) and advanced three‐dimensional (3D) imaging has revolutionised dentistry by enhancing diagnostics and treatment planning. Advanced algorithms and machine‐learning techniques may enable orthodontists to analyse complex cases and predict treatment outcomes accurately. This technology facilitates the creation of customised treatment plans that consider individual tooth morphology and periodontal health, optimising force application and minimising treatment time. Since their introduction, clear aligners have gained popularity, with over 17 million people treated by 2023. Compared with fixed appliances, clear aligners offer advantages, such as better aesthetics, comfort and oral hygiene. Treating patients with a compromised periodontium requires accurate diagnosis and treatment planning. This paper reviews how AI‐driven treatment planning software predicting root movement and visualising bone structures may impact treatment decisions and, ultimately, treatment outcomes. The technology behind machine learning and AI in designing clear aligners is discussed. Research shows that when viewing the cases in 3D, clinicians are more comfortable when treating crowding cases with a non‐extraction approach using interproximal reduction (IPR) only. However, it was interesting to note that clinicians with extensive experience treating clear aligner patients were more comfortable using IPR to address severe crowding cases when viewed in 2D, compared with those less experienced with clear aligners. However, when the cases were visualised in 3D, both groups showed equal comfort in using IPR, as the roots were within the bone. AI‐driven treatment planning software, utilising machine learning in conjunction with 3D modelling, may enhance the predictability of orthodontic movements while reducing treatment time and increasing patient satisfaction. 10.1111/ocr.12921 http://creativecommons.org/licenses/by-nc-nd/4.0/
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spellingShingle How AI ‐Driven Root and Bone Predictions Can Assist Clear Aligner Treatment Planning
Eser Tüfekçi
Caroline K. Carrico
Christina B. Gordon
Steven J. Lindauer
Orthodontics & Craniofacial Research
How AI ‐Driven Root and Bone Predictions Can Assist Clear Aligner Treatment Planning Eser Tüfekçi Caroline K. Carrico Christina B. Gordon Steven J. Lindauer Orthodontics & Craniofacial Research ABSTRACT Integrating artificial intelligence (AI) and advanced three‐dimensional (3D) imaging has revolutionised dentistry by enhancing diagnostics and treatment planning. Advanced algorithms and machine‐learning techniques may enable orthodontists to analyse complex cases and predict treatment outcomes accurately. This technology facilitates the creation of customised treatment plans that consider individual tooth morphology and periodontal health, optimising force application and minimising treatment time. Since their introduction, clear aligners have gained popularity, with over 17 million people treated by 2023. Compared with fixed appliances, clear aligners offer advantages, such as better aesthetics, comfort and oral hygiene. Treating patients with a compromised periodontium requires accurate diagnosis and treatment planning. This paper reviews how AI‐driven treatment planning software predicting root movement and visualising bone structures may impact treatment decisions and, ultimately, treatment outcomes. The technology behind machine learning and AI in designing clear aligners is discussed. Research shows that when viewing the cases in 3D, clinicians are more comfortable when treating crowding cases with a non‐extraction approach using interproximal reduction (IPR) only. However, it was interesting to note that clinicians with extensive experience treating clear aligner patients were more comfortable using IPR to address severe crowding cases when viewed in 2D, compared with those less experienced with clear aligners. However, when the cases were visualised in 3D, both groups showed equal comfort in using IPR, as the roots were within the bone. AI‐driven treatment planning software, utilising machine learning in conjunction with 3D modelling, may enhance the predictability of orthodontic movements while reducing treatment time and increasing patient satisfaction. 10.1111/ocr.12921 http://creativecommons.org/licenses/by-nc-nd/4.0/
title How AI ‐Driven Root and Bone Predictions Can Assist Clear Aligner Treatment Planning
topic Orthodontics & Craniofacial Research
url https://onlinelibrary.wiley.com/doi/10.1111/ocr.12921