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AI in Orthodontics: Improving Treatment Planning & More

by | October 25, 2024

Due to AI’s speed and accuracy, its capabilities are continuously explored in the medical field. Today, the use of AI in EHR management, tailored treatment plans, and virtual health assistants is increasingly becoming the norm. 

However, there’s a new area where AI is being explored: orthodontics. 

Specifically, AI in dental treatment planning is set to transform the orthodontics industry, with data analysis, automation, and 3D imaging and visualization all providing huge benefits. 

That said, only a few AI applications in orthodontics have reached full clinical maturity and regulatory approval, meaning we’ve just reached the tip of the iceberg in exploring its full potential. 

Keep reading to learn more about orthodontic technology, where we’ll discuss the key areas of AI in orthodontics, how AI can help in treatment planning, and future challenges that must be addressed.  

3 Key Areas of AI in Orthodontics and Implant Dentistry   

A study on the application of AI in orthodontics states that AI has shown numerous applications in orthodontics, contributing to diagnosis, treatment planning, and clinical practice. It also claims that while AI still cannot fully replace human experts, it can serve as a quality-assuring component in clinical routine. So, what does this mean? 

It means that AI not only enhances the quality of care that patients receive but also provides huge benefits to orthodontists in their everyday practices.  

To better understand how AI can be leveraged in orthodontics, let’s take a look at the 3 main areas where AI is making a difference: 

  • AI in Orthodontics Diagnosis: Diagnosing patients is not only time-consuming but also a critical component of effective treatment planning, as it requires a thorough analysis to ensure accuracy. By using advanced algorithms, AI in dental radiology can examine photographs, X-rays, and intraoral scans to identify issues quickly, therefore streamlining the entire diagnosis process. 
  • AI in Orthodontics Clinical Practice: There are various ways that AI can be integrated into everyday clinical practices. To save time and resources, AI technologies can automate administrative tasks such as scheduling, billing, and record keeping. They can also enable remote monitoring of patients and provide clinical decision support, helping create a more efficient workflow. 
  • AI in Orthodontics Treatment Planning: AI helps streamline decision-making, predict treatment outcomes, and create treatment plans depending on the unique needs of each patient. These capabilities have the potential to transform the entire treatment planning process, allowing orthodontists to increase accuracy and reduce the time required to develop treatment plans. 

As you can see, artificial intelligence has the potential to redefine many existing practices. While all the above applications are important, there’s one that stands out for its impact in this field: AI in dental treatment planning.  

As we’ll see below, there are various ways that custom AI solutions can help orthodontic clinics enhance their treatment planning, enabling them to provide better care for their patients. 

How AI Can Help in Orthodontics Treatment Planning 

The future of AI in orthodontics is bright, with the potential to streamline many critical processes, increase efficiency, and enhance outcomes, and the advantages of AI in dental care overall will likely continue to grow as its use becomes more widespread. 

Keep reading to explore the 4 main areas where AI in dental treatment planning can be applied. 

Tooth Extraction from Gingiva in 3D Scan

Tooth extraction is a common practice in orthodontics, commonly performed due to infection, gum disease, and overcrowding, among other reasons. With AI, orthodontists can better determine whether extraction is required in individual cases, therefore assisting in treatment planning. 

So how does this work? 

AI systems use machine learning techniques to analyze data from scans and create high-resolution, detailed 3D models of teeth and surrounding structures. They can then automate various processes, such as the analysis of 3D scans and tracking changes in dental structures over time. 

These capabilities play a critical role in decision-making. Since there are various factors to determine whether extraction is required, such as orthodontic defects and expected outcomes, AI tools can facilitate this entire process.  

In fact, initial studies on extraction decision aids have shown promising results, with AI algorithms achieving over 80% agreement with expert decisions. However, these findings have limitations, such as the AI systems being trained on limited data and certain considerations not being included.  

That said, there are many tools and features that are currently being overlooked, meaning this field requires more development and custom software solutions for optimal results. 

Animal Pilot Study

A recent study was done to evaluate gingival segmentation from 3D scans with AI. To perform this study, the lower jaws of Yorkshire pigs were scanned, and the 3D images created from the scans were processed using a deep-learning model. In a study of 108 locations, the measurements taken in a clinical setting and those taken virtually were very closely related. The study concludes by stating: 

“In summary, the artificial intelligence-based virtual measurement proposed in this work provides an innovative technique potentially for accurately measuring soft tissue thickness using clinical routine 3D imaging systems, which will aid clinicians in generating a more comprehensive diagnosis with less invasive procedures and, in turn, optimize the treatment plans with more predictable outcomes.” 

Read full study 

Lateral Cephalogram Analysis and Landmark Detection

Lateral cephalogram landmark detection analyzes facial structure to help plan treatments like braces and surgeries, making it a critical process in the orthodontic realm. So where does AI fit into this process? 

AI models help enhance the accuracy of measurements, therefore assisting orthodontists in treatment planning. These tools help increase automation and reduce the time required for analysis, making them a valuable tool for landmark detection. 

One of the benefits of using AI for lateral cephalogram landmark detection is that it can be leveraged by orthodontists with varying levels of professional experience. Its ability to streamline the analysis of lateral cephalograms and detect landmarks makes it a great tool for less experienced clinicians in orthodontic treatment planning. On the other hand, it reduces the treatment planning procedure for even the most experienced orthodontists. 

One study claims that AI is a promising tool that facilitates the tracing of cephalometric landmarks in daily clinical practice. However, the study explains that the success of AI in cephalometry depends on many factors, such as the operator’s clinical training and experience, the number and quality of radiographs, and the type of algorithm or application. 

Assessment of Treatment Need and Tooth Position Analysis

The position of a person’s teeth affects both the function and appearance of their everyday movements, contributing to issues like jaw pain, tooth decay, and wear and tear. For these reasons, tooth positioning is critical in many orthodontic procedures, requiring a deep analysis to create a successful treatment plan. 

This is where AI comes into play. 

One of the ways orthodontists can leverage AI to enhance treatment planning is by using it to analyze clinical imagery, such as intraoral scans or photographic data. To do so, machine learning algorithms are trained on thousands of similar cases, enabling them to quickly assess tooth alignment.  

AI also helps create 3D reconstructions of the patient’s dental structures, providing orthodontists with a clearer, more detailed view of tooth positioning and bone structure.  

In addition to assisting with diagnosis, orthodontic software also provides orthodontists with decision support for treatment decisions, such as whether a patient needs surgery or a tooth extraction. At the same time, these systems help identify risks for treatments, such as periodontal bone loss, therefore assisting with treatment planning and increasing the patient’s overall satisfaction.  

future of ai in orthodontics

Areas Where AI Can Improve Orthodontics Treatment Planning 

While AI in dental care may sound like a futuristic concept, its capabilities are already being implemented in orthodontic clinics around the world. For that reason, it’s clear that orthodontists have much to gain from emerging technologies, with the opportunity to use AI orthodontics to streamline many everyday tasks. 

The main areas where AI has shown potential in this industry include: 

  • Data analysis: AI can analyze different types of data, such as X-rays and 3D images, to help orthodontists diagnose patients and create successful treatment plans. Since AI models are trained on large datasets, these systems also compare patient information with similar cases, therefore helping orthodontists identify risks and create a more personalized approach. 
  • 3D imaging and visualization: AI helps create 3D reconstructions of patients’ dental structures, providing a detailed view of a patient’s teeth, jaw, and soft tissue structures to assist with the treatment planning process. AI-based diagnostic tools can then analyze these images to facilitate early detection and diagnosis. 
  • Automation and personalization: AI can automate administrative tasks such as scheduling, billing, and record-keeping, enabling orthodontists to focus on patient care. AI’s ability to analyze various aspects of patient data also helps orthodontists create more personalized treatment plans, therefore enhancing the outcomes of treatments. 

The Future Challenges of AI in Orthodontics 

While the use of AI in orthodontics is promising, there are certain challenges that must be addressed to ensure secure and efficient AI systems.  

Here are some of the obstacles you should be aware of: 

  • Data quality: The quality of data impacts the AI models’ performance, accuracy, and reliability, making it a critical factor in AI applications. To ensure unbiased and ethical outcomes, AI systems must be trained on large datasets that are relevant and high quality. Data governance policies can be used to define data quality standards, processes, and roles, therefore reducing errors. 
  • Patient data privacy: Orthodontic clinics that want to adopt AI technologies must make patient data privacy a top priority. To protect against unauthorized access and data breaches, healthcare organizations must implement robust security measures such as end-to-end encryption and regular security audits. By partnering with an experienced development company, your business can implement comprehensive data privacy protocols that are tailored to your unique needs. 
  • Explainability of decisions: Explainable AI refers to a set of tools and frameworks that allow humans to understand the results and output of AI systems. There are certain techniques that developers can use to increase transparency in AI systems, such as providing detailed information about proprietary datasets used in training AI models, maintaining documentation of AI models (such as training methodologies and development processes), and conducting regular audits. 
  • Accountability: Anyone who uses AI systems must be held accountable for the actions of the systems they utilize. This means that orthodontic clinics that adopt AI technologies are responsible for ensuring AI tools are ethical, secure, and trained responsibly. One of the ways to do this is by partnering with a software development company that has experience creating custom AI solutions in the healthcare sector. 
  • Integration into existing systems: AI integration is a big concern, as it requires careful planning to ensure compatibility. When you create a custom AI solution, your development partner will carefully assess your current IT infrastructure to ensure that the AI solution integrates seamlessly and is fully compatible with existing systems. 

While there are multiple challenges that your business may face, experienced AI development companies know how to navigate them to achieve optimal results.  

It’s important to note that AI is not meant to take over the work of specialists but rather enhance their capabilities and enable them to streamline many critical processes. While the critical thinking skills and specialized knowledge of experts will stay at the forefront of orthodontics, they can now leverage generative AI capabilities to enhance processes.

Conclusion 

By using computer science in orthodontics, orthodontic clinics can streamline treatment planning, enhance the accuracy of treatment outcomes, and automate everyday tasks.  

That said, while the future of AI in orthodontics is bright, businesses must know how to navigate the obstacles that come with AI integration. By partnering with a software development company that specializes in AI development, businesses can ensure they stay compliant, protect sensitive patient data, and successfully integrate AI into existing systems. 

At Scopic, we believe in the potential of leveraging artificial intelligence in various industries, including orthodontics. As a leading AI development company, we offer various AI services, including strategic consultation, generative AI solutions, and custom machine learning solutions. 

Contact us today for a free quote on your next project. 

About Creating AI in Orthodontics Guide

This guide was authored by Baily Ramsey, and reviewed by Enedia Oshafi, Director of Business Development at Scopic.

Scopic provides quality and informative content, powered by our deep-rooted expertise in software development. Our team of content writers and experts have great knowledge in the latest software technologies, allowing them to break down even the most complex topics in the field. They also know how to tackle topics from a wide range of industries, capture their essence, and deliver valuable content across all digital platforms.

Note: This blog’s images are sourced from Freepik.

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