Arthritis is the most common chronic disease in Canada, placing a tremendous burden to the health system. From the 6 million Canadians living with arthritis, around 700,000 are in the province of Alberta. It affects 1 in every 1,000 Canadian children. In this disease, the temporomandibular joint (TMJ) is almost always the first joint involved. This joint connects the lower jaw to the skull, allowing the mouth to open and close. TMJ arthritis in children can cause devastating facial deformities compromising daily activities such as speaking and chewing. Since there is no cure for the damage caused, it is important to detect and treat this condition early to prevent lifelong jaw problems.
Accessible, cheaper and safer imaging is needed to diagnose and treat TMJ arthritis early to avoid the costs, delays and need for sedation related to MRI images, which is used to diagnose this condition. Ultrasound (US) is safer, more comfortable for children and cheaper for the health system. Not to mention, its portability that allows its use in diverse health care facilities, including rural communities and remote areas. However, the challenge is that US requires significant training and expertise to interpret the images.
We are developing an AI-assisted image analysis tool to be integrated to a portable handheld ultrasound to help screening TMJ arthritis in children. For this, we will scan the joint of children diagnosed with arthritis in the main children's hospital of Alberta. These images will then be used to develop the AI assisted image-analysis tool. This innovative tool will overcome existing barriers and improve health by advancing digital health.
Presented by:
Fabiana Almeida
Fabiana Almeida is a clinical researcher and Assistant Professor at the School of Dentistry, University of Alberta, Edmonton, Canada. She completed her dental degree and specialty training in Oral and Maxillofacial Radiology in Brazil, alongside an MSc and PhD in Health Sciences—Oral Diagnosis.
Her research focuses on imaging and new technologies—particularly Ultrasound and Artificial Intelligence—in the diagnosis process in Dentistry. She started working with Ultrasound in 2017 during her postdoctoral fellowship at the University of Alberta, where she investigated the potential of Ultrasound as a diagnostic tool in Dentistry—particularly for assessing jaw joint disorders and the tissues supporting teeth. Dr Almeida was part of a multidisciplinary team that developed an innovative intraoral ultrasound device for chairside diagnostic use in Dentistry. In addition, she has led the development of an AI model to assist in identifying jaw joint disorders in MRI scans. Her work aims to improve the diagnosis process through the integration of emerging technologies in imaging.
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