Artificiële intelligentie en biomechanische modellering voor patiëntspecifieke orale chirurgische ingrepen

Artificial intelligence (AI) has made stunning progress in the last decade, mainly by advances in training deep neural networks with large data sets. Many of these solutions, initially developed for natural images, speech, or text, are now becoming successful in medical imaging. Yet, to date and to our best knowledge, literature related to the application of AI in oral and maxillofacial surgery remains very limited. Colossal investments are being made for research and development of AI and its integration within the medical field. At this moment, the prime focus for medical AI applications is related to more efficient diagnosis, in some cases attention is also given to enhanced treatment planning. Simultaneously, digital dentistry has been slowly developing during the last two decades to enter the daily practice. In this regard, softwares related to virtual planning of oral and maxillofacial surgery have emerged, enabling dentists and surgeons to create a virtual patient as such to improve planning for further surgery and oral rehabilitation. However, this digitalization process is moving slower than initially expected and surely not reaching out to all dentists and treatment procedures. At this moment less that 10% of all 3D images taken for implant placement procedures are further processed for surgical guides (internal numbers UZ Leuven). The reason for the slow introduction of such digital planning procedures is the complexity of the workflow needed to prepare the surgery and/or and the related time and inherent costs. Though, should it be possible to save time by AI driven surgical planning and treatment proposals, such digital technologies might hold an immense potential that could reshape the treatment planning phase, and potentially its execution, within the next few years. Therefore, the purpose of this doctoral project is to develop and clinically validate AI-driven planning tools for oral surgical procedures, such as tooth replacement (dental implants or tooth autotransplantation (TAT)), guided endodontics and orthodontics. The project plan will combine the knowledge already obtained in TAT surgical planning, tooth and jaw bone biomechanics and artificial intelligence with fundamental knowledge about the properties of different bone types and other oral components towards the clinical practice of oral surgical procedures, allowing for a patient- specific AI driven planning with a predictable outcome.

Publication Details

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Lirias (KU Leuven)
Published
2024-12-12
Primary Topic
Regional Economics and Spatial Analysis
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article

Artificiële intelligentie en biomechanische modellering voor patiëntspecifieke orale chirurgische ingrepen

Lirias (KU Leuven)
Regional Economics and Spatial Analysis
article

Artificiële intelligentie en biomechanische modellering voor patiëntspecifieke orale chirurgische ingrepen

article en

Abstract

Artificial intelligence (AI) has made stunning progress in the last decade, mainly by advances in training deep neural networks with large data sets. Many of these solutions, initially developed for natural images, speech, or text, are now becoming successful in medical imaging. Yet, to date and to our best knowledge, literature related to the application of AI in oral and maxillofacial surgery remains very limited. Colossal investments are being made for research and development of AI and its integration within the medical field. At this moment, the prime focus for medical AI applications is related to more efficient diagnosis, in some cases attention is also given to enhanced treatment planning. Simultaneously, digital dentistry has been slowly developing during the last two decades to enter the daily practice. In this regard, softwares related to virtual planning of oral and maxillofacial surgery have emerged, enabling dentists and surgeons to create a virtual patient as such to improve planning for further surgery and oral rehabilitation. However, this digitalization process is moving slower than initially expected and surely not reaching out to all dentists and treatment procedures. At this moment less that 10% of all 3D images taken for implant placement procedures are further processed for surgical guides (internal numbers UZ Leuven). The reason for the slow introduction of such digital planning procedures is the complexity of the workflow needed to prepare the surgery and/or and the related time and inherent costs. Though, should it be possible to save time by AI driven surgical planning and treatment proposals, such digital technologies might hold an immense potential that could reshape the treatment planning phase, and potentially its execution, within the next few years. Therefore, the purpose of this doctoral project is to develop and clinically validate AI-driven planning tools for oral surgical procedures, such as tooth replacement (dental implants or tooth autotransplantation (TAT)), guided endodontics and orthodontics. The project plan will combine the knowledge already obtained in TAT surgical planning, tooth and jaw bone biomechanics and artificial intelligence with fundamental knowledge about the properties of different bone types and other oral components towards the clinical practice of oral surgical procedures, allowing for a patient- specific AI driven planning with a predictable outcome.

Lirias (KU Leuven)
Quality Education
Openalex Percentile: Top 32%
Regional Economics and Spatial Analysis
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