Micro-computed tomography-based highly automated 3D segmentation of the rat spine for quantitative analysis of metastatic disease.

Noninvasive evaluation of metastatic disease in the spine has generally been limited to 2D qualitative or semiquantitative analysis techniques. This study aims to develop and evaluate a highly automated micro-CT-based quantitative analysis tool that can measure the architectural impact of metastatic involvement in whole vertebrae. Micro-CT analysis of rat whole vertebrae was conducted using a combination of demons deformable registration, level set curvature evolution, and intensity based thresholding techniques along with upsampling and edge enhancement techniques. The algorithm was applied to 6 lumbar vertebrae (L1-3) from 6 rnu/rnu rats (3 healthy rats and 3 with metastatic involvement). Osteolytic metastatic involvement was modeled via MT1 human breast cancer cells. Excellent volumetric concurrency was achieved in comparing the automated micro-CT-based segmentations of the whole vertebrae, trabecular centrums, and individual trabecular networks to manual segmentations (98.9%, 96.1%, and 98.3%, respectively; 6 specimens), and the automated segmentations were achieved in a fraction of the time. The algorithm successfully accounted for discontinuities in the cortical shell caused by vasculature and osteolytic destruction. As such, this work demonstrates the potential of this highly automated segmentation tool to permit rapid precise quantitative structural analysis of the spine with minimum user interaction in the analysis of both healthy and pathological (metastatically involved) vertebrae. Future optimization and the incorporation of lower-resolution imaging parameters may allow automated analysis of clinical CT-based measures in addition to preclinical micro-CT-based analyses of the structural impact and progression of pathological processes in the spine.