Classification of vertebral compression fractures in magnetic resonance images using shape analysis

Fractures with partial collapse of vertebral bodies are referred to as "vertebral compression fractures" (VCFs). VCFs can have different etiologies comprising trauma, bone failure related to osteoporosis (benign), or metastatic cancer (malignant). This paper presents a study aimed to help in the classification of VCFs in magnetic resonance imaging (MRI). We used T1-weighted MRI of the lumbar spine in the sagittal plane. Images from 63 patients diagnosed with at least one VCF were studied. Shape features as normalized compactness, convex deficiency, Hu's moments and Fourier-descriptor-based feature were extracted from 102 lumbar vertebral bodies with VCFs and 106 normal lumbar vertebral bodies. Classification was performed using different classifiers with different feature combinations. Results obtained show that shape analysis was able to correctly distinguish between normal and fractured vertebral bodies with a correct classification rate up to 90.58% and between benign and malignant with a correct classification rate up to 80.39%.