Beyond the Surface: OrthoSelect's Journey to Revolutionary Orthodontic Care with the Relu® Engine
Transforming Orthodontics: The Relu Revolution
In the rapidly evolving world of orthodontic innovation, Steven Gardner, President of OrthoSelect, emerges as a pioneering force. Since steering the company's transition to digital technologies in 2009, Gardner has propelled OrthoSelect to new heights, making significant advances with its DIBS AI digital indirect bonding service offering. The collaboration with Relu, introducing the Relu® Engine, a unique technology that combines AI, deep learning and advanced imaging techniques, marks a significant leap forward. This technology brings previously hidden anatomical details including roots and bone into sharp focus, enabling orthodontists to make more accurate diagnoses and treatment plans, and shorten treatment times for patients.
The Challenge of the Unseen
Driven by the goal to unveil the hidden aspects of dental anatomy and automate orthodontic processes, Gardner sought technologies that could break through the limitations set by conventional tools. This quest for more profound insights led to the transformative partnership with Relu, setting the stage for groundbreaking improvements in orthodontic care.
DIBS AI: A Revolution in Bracket Placement
The evolution of DIBS AI, an integrated software and hardware platform providing automated case setups through advanced bracket positioning software, and the corresponding indirect bonding trays for any type of bracket, marked a significant leap forward in orthodontic technology.
Using the DIBS AI application, the process of case planning and preparation of brackets is streamlined into three steps: (1) orthodontists submit an Rx along with the patient’s intraoral scans; (2) they receive a case setup within a few hours, which they can review and approve; and (3) they receive the patient’s trays within 5-6 days, with brackets already inserted in the trays and ready to apply via an indirect bonding process.
The data generated by intraoral scanners shows only the outside of the teeth and gums. Images from cone beam computed tomography, or CBCT, also show the roots of teeth, bone, tissue, and nerve pathways. That additional information gives orthodontists a much deeper knowledge of the patient’s physiology, meaning they can plan more targeted and effective orthodontic treatments.
Gardner wanted to incorporate this expanded visibility, and the resulting benefits, into the DIBS AI application. He envisioned a tool that enhanced diagnostic precision while simplifying clinical workflows. This tool was DIBS AI combined with Relu's advanced imaging techniques – unlocking the full potential of both technologies.
"Marrying the Relu technology with our DIBS AI makes it possible now to see what happens when the full teeth are moved according to the braces. That visibility and control you have within a digital format is huge – because the doctors can do a lot of diagnosis and treatment planning before they ever put a single bracket on a single tooth,” says Gardner, emphasizing the synergies between the two technologies.
The Magic of Integration
The integration of the Relu® Engine into DIBS AI was a game-changer, says Gardner. This collaboration, powered by cutting-edge AI, deep learning and advanced imaging techniques, has not only enhanced diagnostic accuracy and treatment planning but also empowered orthodontists with comprehensive anatomical insights. It's about enhancing the view beyond the surface, as Gardner states.
The Relu® Engine AI-driven tool uses AI, deep learning and convolutional networks to combine and analyze the image data. The combined OrthoSelect/Relu® Engine solution is based on an API integration. For users, the expanded functionality is automated, and managed within the DIBS AI interface. When doctors submit a case, they can drag and drop the CBCT images, and the system asks if they would like to integrate roots and bone.
“We've got an automated process to take those scans from a cone beam scanner and basically embed them into our software. It automatically goes to Relu, Relu automatically works their magic, produces those roots and bones and then it automatically comes back to our system so that when our technicians are doing a case setup, the roots are already there,” says Gardner.
Typically, within 24 hours or so of submitting the case, the doctor gets an e-mail from OrthoSelect saying the case is ready for approval. “They open it up, and there it is with the roots, with the bone, everything is with the braces and the wires,” says Gardner.
A Patient-Centric Future
Gardner's vision encompasses technical innovation and a deep commitment to improving patient outcomes. Reflecting on his own experiences with braces as a teenager and the prolonged discomfort that extended wear can bring, Gardner shares, "The biggest impact of this technology is on the patients. By shortening treatment times, we're not just enhancing efficiency but fundamentally improving the patient's experience." The benefit to patients is clear, with data showing an average reduction of 6.6 months in treatment duration. "It's about getting better treatment results in less time," Gardner affirms, emphasizing the dual benefits of speed and quality that the technology facilitates, and the improved comfort and convenience it brings to patients.
The Impact
Since its inception in 2004, OrthoSelect's march towards revolutionizing dental care has reached across 14 countries, influencing over a thousand orthodontists. The synergy between OrthoSelect and Relu will not only broaden the capabilities of orthodontic professionals but will significantly elevate the standard of care delivered to patients globally.
“We're seeing so much more that we can do for the orthodontist,” says Gardner. “As we continue to develop the software, we want to give more visibility to the doctor, such as the animation of pre-treatment and post-treatment bio-mechanics, to show how teeth would move in real life. I would say we're on the cutting edge of orthodontic technology – and we're definitely disrupting,” he concludes.
