Mina Mahdian, an associate professor at the Stony Brook School of Dental Medicine, and Prateek Prasanna, an assistant professor in the Department of Biomedical Informatics, have been awarded a $300,000 grant by the National Institute of Dental and Craniofacial Research (NIDCR) under the National Institutes of Health (NIH). The funding will support their research into whether routine dental imaging can help detect early signs of heart disease.
The two-year project is titled “Automated Characterization of Arterial Calcification in Dental Cone Beam Computed Tomography as Predictors of Cardiovascular Disease.” It aims to create an AI-driven tool capable of identifying and characterizing arterial calcifications seen in cone beam CT (CBCT) scans commonly used in dental practices. These mineral deposits could indicate cardiovascular risk.
Mahdian expressed enthusiasm for the project: “I am excited about this project, as this is the first study to apply quantitative imaging biomarkers, such as radiomics, to characterize vascular calcifications in CBCT to predict cardiovascular disease.” She noted that while most current AI research focuses on common dental pathologies, this project highlights AI's potential role in predicting cardiovascular risks based on dental CBCTs.
Prasanna added insights from his perspective at the IMAGINE Lab: “At the IMAGINE Lab, we’re committed to pushing the boundaries of what AI can do for healthcare... This project is a prime example of how advanced machine learning and imaging analysis can reveal hidden signals in routine scans...”
If successful, this technology could function as an early warning system during routine dental visits. It would alert providers to potential risk factors and encourage timely follow-up with medical professionals.
Patrick M. Lloyd, dean of Stony Brook School of Dental Medicine, commented on the significance: “Dr. Mahdian’s NIH award demonstrates the collaborative potential that exists when a dental school resides on a university campus... It is from collegial environments like ours that discoveries are made.”
The research receives support under Award Number R03DE033489 from NIDCR.