High-Resolution Cone-Beam Tomography for Assessing Angiogenesis in Jawbone Regeneration Models.

Abstract

Orofacial bone tissue engineering addresses bone loss caused by trauma, malformations, or tumors, enabling restoration and implant rehabilitation. Angiogenesis plays a crucial role in osteogenesis by ensuring nutrient and oxygen transport essential for bone regeneration. Preclinical large animal models are vital for translational research and require noninvasive, nondestructive methods aligned with 3Rs principles (Replacement, Reduction, and Refinement) to assess angiogenesis. This study proposes high-resolution cone-beam computed tomography subtraction angiography (HR-CBCT-SA) adapted for the orofacial region as an innovative method for monitoring angiogenesis during jawbone regeneration. Three Yucatan minipigs with a surgically created buccal wall jawbone defect per hemimandible were followed for 90 days by CBCT-SA to assess vascular remodeling. Morphometric parameters, including vessel number, node count, radius, and length, were analyzed and validated against histological morphometry. CBCT-SA revealed vascular dynamics during healing. By day 10, increased vessel and node counts along with reduced vessel radius and length indicated neoangiogenesis. At day 30, vessel maturation was aligned with transition of fibrous tissue to osteoid matrix deposition. By day 90, vascular metrics stabilized, reflecting bone remodeling phases characterized by replacement of lamellar and medullary bone replacement. Extrabony vascular networks underwent more pronounced changes than intrabony vessels, underscoring the leading role of periosteum in regeneration. Histology validated CBCT-SA findings, although resolution limitations prevented detection of vessels smaller than 500 µm. Nevertheless, CBCT-SA captured angiogenic changes over time and supported nondestructive monitoring without compromising tissue integrity. This study establishes HR-CBCT-SA as a reliable, nondestructive imaging technique for assessing vascular changes during jawbone regeneration in preclinical models. It demonstrates significant translational potential because of the clinically validated use of CBCT-angiography. Advances in artificial intelligence (AI)-driven image analysis are expected to enhance sensitivity and accuracy, improving vascular assessment. Moreover, this approach can be extended for investigating vascular-related oral pathologies (e.g., radiochemical osteonecrosis of the jaws), offering valuable tool to advance research in jawbone regeneration.