PeriAlert device spots early signs of trouble with dental implants

Dental implants are gaining popularity, with the percentage of Americans with implants expected to reach 32% by next year. While they are a reliable and long-lasting solution for replacing lost teeth, implants still come with risks, including peri-implantitis, which starts with gum inflammation but can progress to bone loss and implant failure.  

To improve the longevity of dental implants, a team of undergraduate biomedical engineers at Johns Hopkins University are working on a new way to catch warning signs of inflammation.

“A major challenge in combating peri-implantitis is the lack of testing technologies that can detect or predict early inflammations,” said team leader Stone Meng, a third-year biomedical engineering student. “Our solution will enable dentists to identify this problem early, which is critical for protecting the long-term success of expensive dental implants for patients.” 

The team will present its project on April 29 at the Whiting School of Engineering’s Design Day, an annual event showcasing students’ solutions to real-world problems.  

Meng said the team’s goal is to give dentists a tool to detect inflammation when it is reversible and well before it progresses to peri-implantitis, which often requires surgical intervention.  To do this, the student’s prototype device determines implant health by measuring the pH of peri-implant crevicular fluid (PICF), a fluid that accumulates between the implant and the surrounding gums. A sample is collected using an absorbent paper point and analyzed with the team’s computing software, producing a pH reading that indicates potential inflammation.  

During the design process, the team identified a key challenge: how to collect the PICF sample and create a method to analyze pH images in the same workflow. The team settled on using absorbent paper points to collect the sample —instead of traditional pH test paper as originally planned —because paper points are a commonly used dental tool that would be familiar and easy for clinical users.

For the analysis component, the students opted for a sensor system connected to a credit-card sized Raspberry Pi computer, a setup that allowed for quick prototyping and the design of custom algorithms.  

“This challenge has honed our ability to work dynamically, by forcing us to adopt a pragmatic approach, pivoting quickly, and taking calculated risks,” said Meng. “Now our current focus is pushing our minimum viable product toward clinical testing as quickly as possible.”  

If successful, the team’s work will fill a longstanding need in dentistry, said U.S Air Force Major Robert Koski, the project’s clinical mentor and a practicing dentist.  

“The impact that an effective and easy-to-use diagnostic device will have on dental implant success is potentially tremendous, because it allows us to more accurately predict and track when intervention is needed to improve patient care.” said Koski. “It’s been very exciting to see what these bright and curious students have accomplished so far.” 

For now, the students are designing the device for use in dental clinics but see an opportunity to develop an at-home version that would allow patients to monitor their own implant health, said Meng.  

The PeriAlert team includes Nicole Beaubien, Yuki Hodo, Aditya Jain, Ziyan (Lily) Lin, Gavi Melman, Anna Vargas, and Chelsea Wong.