Potential for Early Fracture Risk Assessment in Patients with Metastatic Bone Disease Using Parametric Response Mapping of CT Images

Pathologic vertebral compression fractures (PVCFs) cause significant morbidity in patients with metastatic bone disease. Limitations in existing clinical biomarkers leave clinicians without reliable metrics for predicting PVCF, thus impeding efforts to prevent this severe complication. To establish the feasibility of a new method for defining the risk of a PVCF, we retrospectively analyzed serial computed tomography (CT) scans from 5 breast cancer patients using parametric response mapping (PRM) to quantify dynamic bone miniral density (BMD) changes that preceded an event. Vertebrae segmented from each scan were registered to the same spatial frame and voxel classification was accomplished using a predetermined threshold of change in Hounsfield units (HU), resulting in relative volumes of increased (PRM_HU+), decreased (PRM_HU−), or unchanged (PRM_HU0) attenuation. A total of 7 PVCFs were compared to undiseased vertebrae in each patient serving as controls. A receiver operator curve (ROC) analysis identified optimal imaging times for group stratification. BMD changes were apparent by an elevated PRM_HU+ as early as 1 year before fracture. ROC analysis showed poor performance of PRM_HU− in stratifying PVCFs versus controls. As early as 6 months before PVCF, PRM_HU+ was significantly larger (12.9 ± 11.6%) than control vertebrae (2.3 ± 2.5%), with an area under the curve of 0.918 from an ROC analysis. Mean HU changes were also significant between PVCF (26.8 ± 26.9%) and control (−2.2 ± 22.0%) over the same period. A PRM analysis of BMD changes using standard CT imaging was sensitive for spatially resolving changes that preceded structural failure in these patients.