Osteoporotic and Neoplastic Compression Fracture Classification on Longitudinal CT
This work addresses a domain-specific medical imaging problem for treatment planning, but it is incremental as it applies existing methods to new data.
The researchers tackled the problem of classifying vertebral compression fractures as osteoporotic or neoplastic using automated measurements from longitudinal CT studies, achieving classification accuracies of up to 0.820 with a combined feature set.
Classification of vertebral compression fractures (VCF) having osteoporotic or neoplastic origin is fundamental to the planning of treatment. We developed a fracture classification system by acquiring quantitative morphologic and bone density determinants of fracture progression through the use of automated measurements from longitudinal studies. A total of 250 CT studies were acquired for the task, each having previously identified VCFs with osteoporosis or neoplasm. Thirty-six features or each identified VCF were computed and classified using a committee of support vector machines. Ten-fold cross validation on 695 identified fractured vertebrae showed classification accuracies of 0.812, 0.665, and 0.820 for the measured, longitudinal, and combined feature sets respectively.