To explore the application effect of X-ray based on convolutional neural network in the rehabilitation of vertebral compression fractures.

From January 2022 to June 2023, 130 patients with vertebral compression fracture were selected from our hospital and randomly divided into routine X-ray-assisted PVP treatment (A) group and convolutional neural network X-ray-assisted PVP treatment (B) group, with 65 cases in each group, to observe the rehabilitation effects of the two groups.

All 130 patients were followed up completely, with a follow-up rate of 100.00%. The follow-up period ranged from 1 to 12 months, with an average of (7.33±1.95) months. Among them, the follow-up time of group A ranged from 1 to 12 months, with an average of (7.48±1.58) months. The follow-up period of Group B ranged from 1 to 12 months, with an average of (7.35±1.68) months. Compared with group A, the number of X-ray exposure, bone cement injection amount, intraoperative blood loss, operative time and hospitalization days in group B were significantly decreased (P<0.05). Compared with group A before treatment, there were no significant differences in anterior vertebra height and kyphotic Cobb angle between group A and group B (P>0.05). After treatment, the anterior vertebra height and kyphotic Cobb Angle of the two groups were significantly increased, and the Cobb Angle of the injured vertebra was significantly decreased, but there was no significant difference between group B and group A (P>0.05). Before surgery, there was no significant difference in the VAS score of group B compared with group A (P>0.05); 24 h after surgery, the VAS score of the two groups was significantly increased (P<0.05), and the VAS score of group A was significantly increased (P<0.05); 12 months after surgery, the VAS score of the two groups was significantly decreased (P<0.05), and the VAS score of group B was significantly lower than that of group A (P<0.05); Before surgery, there was no significant difference in ODI score between group B and group A (P>0.05). 24 h and 12 months after surgery, ODI score of both groups was significantly decreased (P<0.05), and that of group B was significantly decreased compared with group A (P<0.05). Compared with group A, the number of complications such as bone cement leakage, refracture of injured vertebra and fracture of adjacent vertebra in group B was significantly reduced, and the total adverse reaction rate in group B (6.15%) was significantly lower than that in group A (20.00%), with significant differences among groups (P<0.05).

X-ray based on convolutional neural network has a significant effect on vertebral compression fractures, and can significantly improve the rehabilitation effect of patients after vertebraplasty, which is worthy of clinical application.