Commonly diagnosed in advanced breast cancer patients, especially in vertebrae, bone metastases can appear lytic, sclerotic, or anywhere in between these extremes. Given its ability to alter the therapeutic strategy, bone metastases is a critical issue in staging and follow-up of breast cancer. This work presents a novel computer-aided diagnosis (CAD) system to detect metastasis in vertebrae by using whole body computed tomography (CT). An automated method is developed to extract ROIs of trabecular centrum from vertebrae. Eleven texture features and their inter-slice differences are then calculated for each ROI. Next, total 33 features are fed into an artificial neural network (ANN) to determine whether any abnormality occurs in the trabecular centrum. The datasets include 35 breast cancer patients who underwent a whole-body PET/CT scan between 2007 and 2011. The average sensitivity, specificity, and accuracy are 85.4%, 91.8%, and 89.7%, respectively. Capable of identifying possible bone lesions by using CT images, the proposed CAD system can incorporate with features of nuclear medicine images to increase diagnostic accuracy in an automated CAD system for estimating bone metastases quantitatively.