Funding outcome

This research project aims to use artificial intelligence interpretation of 3D dental imaging in order to improve early detection of osteoporosis in postmenopausal women. Osteoporosis is a bone remodeling disorder that weakens bones, reducing bone mineral density and culminating in an increased likelihood of fractures. As a result of hormonal changes that accelerate bone loss, postmenopausal women are disproportionately impacted by osteoporosis. Early diagnosis of osteoporosis can result in timely clinical intervention that would drastically improve patients' quality of life. Currently, the clinical method used to assess bone mineral density is dual-energy x-ray absorptiometry (DXA). However, DXA scanning is problematic in that it is inaccurate across women with different body types and that it is typically ordered only for older women who have already experienced significant risk factors. As a result, there is a distinct need to develop opportunistic screening strategies targeted to women's health. As part of regular dental care, many patients routinely undergo 3D dental imaging. This X-Ray modality captures images of the jawbone, displaying alterations in jawbone quality that can be correlated to overall bone mineral density changes. This study aims to train an artificial intelligence (AI) model to recognize these jawbone changes in postmenopausal women. To do so, the AI model will analyze jawbone imaging differences between 50 postmenopausal women with osteoporosis and 50 control patients. The model's accuracy will be validated by testing its ability to identify postmenopausal osteoporotic patients from a new set of images. This research focuses specifically on postmenopausal women, addressing a critically under addressed aspect of women's health. With 70% of women attending the dentist on an annual basis, dental imaging serves as an opportunistic screening tool that can improve osteoporosis early detection, bone health, and quality of life.