Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of...

In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning V-Net network, the traditional V-Net was optimized first and a new and improved V-Net was proposed. The introduced U-Net, V-Net, and convolutional neural network (CNN) were compared in this study. Then, 106 patients with osteoporotic thoracolumbar compression fractures were enrolled, and 128 centrums were divided into the test group with 53 cases of PKP and the control group with 53 cases of percutaneous vertebroplasty (PVP) according to different surgical protocols. All patients underwent CT scan based on the improved V-Net, and data of centrum measurement indicators, pain score, and therapeutic evaluation results of the modified Macnab were collected. The Dice coefficient of the improved V-Net was observably higher than that of U-Net, V-Net, and CNN, while the Hausdorff distance was lower than that of U-Net, V-Net, and CNN (P < 0.05). The anterior height, central height, and posterior height of the centrum were significantly higher than those in the control group after operation (3, 5, and 7 days), while the Cobb angle of vertebral kyphosis was significantly lower than that in the control group (P < 0.05). The score of visual analog scale (VAS) and analgesic use score of patients in the test group were markedly lower than those in the control group (3, 5, and 7 days after operation), P < 0.05. Besides, the excellent and good rate of the test group was remarkably higher than that of the control group, P < 0.05. Hence, the improved V-Net had better quality of segmentation and reconstruction than the traditional deep learning network. Compared with PVP, PKP was helpful in restoring the height of the centrum in patients with osteoporotic thoracolumbar compression fractures and correct kyphosis, with better analgesic effect safety.