Establishment of artificial intelligence-driven fluorescence morphometry reveals involvement of osteocyte perilacunar remodeling specifically in mandibular bone of ovariectomized rats

Bone dynamically changes its shape and structure in response to extra-tissue environments, so that bone morphometry has been a substantial method to evaluate pathophysiology of bone. Osteocytes embedded in mineralized bone matrix play key roles in systemic bone metabolism and characterize distinct bone sites. The jawbone has been described as a unique bone in the context of vertebrate evolution and function. Bone loss in the mandibular bone is less obvious in osteoporotic conditions than in other bones, such as vertebral and limb long bones, both in animal models and in clinical studies. Since osteocyte lacunae are complex and small (-10µm in length) in shape and size, respectively, comprehensive and unbiased morphometrical analysis of changes in the size of osteocyte lacunae was still an obstacle. This study established an artificial intelligence-driven morphometry with wide-field microscopy-based imaging of osteocyte lacunae. Successive comparative analyses demonstrated active perilacunar bone remodeling in the mandibular bone than in the parietal bone. This approach enabled us to statistically compare morphometric parameters in a more comprehensive and unbiased manner. We further discuss the possible unique contribution of the mandibular bone to the pathophysiology of osteoporosis. This study established an artificial intelligence-driven morphometry with wide-field microscopy-based imaging of osteocyte lacunae. Successive comparative analyses demonstrated active perilacunar bone remodeling in the mandibular bone than in the parietal bone. This approach enabled us to statistically compare morphometric parameters in a more comprehensive and unbiased manner.