Bone defects can occur in various forms and present challenges to performing a standard micro-CT evaluation of bone quality because most measures are suited to homogeneous structures rather than ones with spatially focal abnormalities. Such defects are commonly associated with pain and fragility. Research involving bone defects requires quantitative approaches to be developed if micro-CT is to be employed. In this study, we demonstrate that measures of inter-microarchitectural bone spacing are sensitive to the presence of focal defects in the proximal tibia of two distinctly different mouse models:​ a burr-hole model for fracture healing research, and a model of osteolytic bone metastases. In these models, the cortical and trabecular bone compartments were both affected by the defect and were, therefore, evaluated as a single unit to avoid splitting the defects into multiple analysis regions. The burr-hole defect increased mean spacing (Sp) by 27.6%, spacing standard deviation (SpSD) by 113%, and maximum spacing (Sp_max) by 72.8%. Regression modeling revealed SpSD (β = 0.974, p < 0.0001) to be a significant predictor of the defect volume (R² = 0.949) and Sp_max (β = 0.712, p < 0.0001) and SpSD (β = 0.271, p = 0.022) to be significant predictors of the defect diameter (R² = 0.954). In the mice with osteolytic bone metastases, spacing parameters followed similar patterns of change as reflected by other imaging technologies, specifically bioluminescence data which is indicative of tumor burden. These data highlight the sensitivity of spacing measurements to bone architectural abnormalities from 3D micro-CT data and provide a tool for quantitative evaluation of defects within a bone.