Pedicle screw fixation is a serious challenge in spinal surgery when confronted with osteoporosis. The in vitro osteoporosis experiment is the most direct and effective method to study the biomechanical properties of osteoporotic vertebrae. In this paper, the research was conducted by constructing in vitro models of osteoporotic pig vertebrae. In these models, the CT value and screw pull-out force of automatic trajectory planning based on the CT value and manual trajectory planning were evaluated and compared. The results showed that automatic trajectory planning was significantly better than manual trajectory planning in terms of screw pull-out force, which may suggest that automatic pedicle screw trajectory planning based on CT values is a valuable method for pedicle screw placement in osteoporosis.
The best models for studying osteoporosis in humans are from human cadavers, which are difficult to study because of their limited availability. One possible approach is to study vertebral specimens from large animals [23,24,25]. In this study, we used EDTA immersion and continuous pumping to demineralize pig vertebrae, which ensured that the vertebrae’s cortical bone and cancellous bone could be demineralized at the same time. This procedure significantly shortened the time needed to reach osteoporosis. Moreover, this method does not seriously damage the structure of bone trabeculae in the vertebral body and retains the biomechanical properties of the vertebral body. Lee, C. Y. et al.  used EDTA to decalcify the pig vertebrae and, by measuring its microstructure and mechanical properties, concluded that EDTA decalcification can help to produce a vertebral model with biomechanical properties consistent with human osteoporosis.
Pedicle screw placement in patients with osteoporosis has always been a difficult problem in spine surgery. Existing solutions include cement augmentation screw placement, cortical bone track screw placement (CBT), placement of varied materials in the screw path to increase local tissue density, increasing the screw diameter, and changing the screw thread structure. However, these methods all have their limitations. Bone cement leakage is a common complication of bone cement augmented screws, with a leakage rate of 11.6–82.4%, which can cause serious complications such as nerve injury, vascular injury, pulmonary cement embolism, cardiac embolism and anaphylactic shock . In CBT, screws are inserted through the isthmus, and the screws can only be inserted into the posterior 1/3 of the vertebral body. The pull-out force is limited to the midposterior column, and the potential for correction of spinal malformation is poor. Filling the screw path with different materials, such as autologous bone, can increase the density around the screw in a certain time, but with time, the implanted material may gradually absorb or decompose, and the tissue density around the screw will gradually decrease, eventually leading to fixation failure . Increasing the screw diameter and changing the screw thread structure can increase the pull-out force, but blindly increasing the screw diameter may cause pedicle fracture and decrease the pull-out force [8, 29]. It is, therefore, necessary to seek other solutions.
The development and validation of automatic pedicle screw planning systems based on preoperative or intraoperative CT are in line with the current development trend of digital and intelligent spinal surgery. Computer-assisted preoperative planning pedicle screw placement is a relatively fast process that can be performed without the automatic participation of a spine surgeon . The optimization of the pedicle screw placement trajectory combined with the CT value is expected to improve the fixation effect of pedicle screws. The automated planning system reduces the time required for preoperative or intraoperative planning, optimizes the procedure of spinal navigation surgery, avoids the problem of different optimal trajectories planned by different doctors, and optimizes the fixation strength of pedicle screws. In this paper, we reported software that can plan the trajectory of the maximum pull-out force screw according to the CT value of the vertebrae and verify the safety and effectiveness of software automatic trajectory planning. Since the widely used preoperative CT and intraoperative O-arm images can only display the CT value of the tissue, this study adopted the CT value as the evaluation index to simulate the actual application scenario. Since previous studies have proven a linear relationship between the CT value and BMD, this method is feasible. In contrast to the previously reported automated planning trajectory, the automated planning trajectory used in this study did not require pedicle screws to pass through the midpoint of the pedicle, as the midpoint of the pedicle tends not to be the area with the densest bone tissue . To achieve a higher extractable force of the screw, the screw needs to be as close to the cortical bone as possible without penetrating or causing the cortical bone fracture. Compared with Vijayan, R, et al. , this planning method does not adopt the method of establishing a model atlas for pedicle screw planning. Although building a database can greatly reduce the time required for planning, it also loses the individualized characteristics of patients. The planning method in this study was to conduct screw planning according to the actual CT reconstructed images of patients, which can avoid screw misplacement caused by failure to match the atlas due to vertebral variation.
In this study, the manual planning group adopted parallel placement technology, which inserted screw parallel to the upper endplate of the vertebral body. The sagittal angle was 3.23 ± 1.64°, while the automatic planning was 19.19 ± 1.87°, which was significantly different (P < 0.05), but both were within the allowable range . The automatically planned trajectory is closer to the upper wall of the pedicle. Eventually, it points to the upper endplate of the vertebral body to maximize the CT value of the whole trajectory to obtain the maximum screw pull-out force. Through measurement comparison, we found that in the osteoporosis model, the trajectory CT value of the software automatic planning group was significantly higher than that of the manual planning group by 25.7% (P < 0.01). It should be noted that the CT values of screw tracks automatically planned in the decalcification group were 21.4% higher than those manually planned in the control group (P < 0.01). The use of 3D printed guide plates to place pedicle screws was exactly accurate. The displacement and angle errors of the actual screw and planned screw positions showed no significant difference (P > 0.05). The screws were completely located in the cortical bone, there was no perforation of the pedicle or anterior vertebral margin, and no local microfracture occurred. In vitro tests, 3D-printed guide plates are a viable alternative in scenarios where computer navigation is not available. However, in clinical application, it is impossible for surgeons to completely remove the soft tissue on the surface of the vertebrae, which makes it difficult to accurately fix the 3D-printed guide plates in the corresponding positions, resulting in the actual positions of the inserted pedicle screws significantly deviated from the planned trajectories. Therefore, the combination of automatic planning and surgical navigation systems may be the best way to use the automatic planning system in clinical practice.
Biomechanical research also proves that the automatic planning method is effective. The screw trajectory planned according to the CT value obtained a larger screw pull-out force than the traditional manually planned trajectory (P < 0.05). It should be noted that although the CT value of the automatically planned trajectory in the decalcification group was 21.4% higher than that of the manually planned trajectory in the control group, the screw pull-out force was only 97.4% of that in the control group. This result may suggest that the BMD of the bone tissue around the screw trajectory also influences the pull-out force of the screw, which requires further finite element analysis to explain the reason. Despite this, the automatic plan increased the pull force by 44.7% compared with the manual plan in the decalcification group, which was close to the proportion of improvement in bone cement-reinforced screws (47%) . These results suggest that automatic planning based on CT values is an effective method for pedicle screw placement in osteoporotic vertebrae. This method does not require the placement of additional filler materials and avoids the serious complications caused by leakage of filler materials.
The software can export trajectory coordinates and match them with reconstructed CT images, which provides a basis for future association and matching with surgical navigation systems. In the future, combined with navigation systems or surgical robot technology, optimal trajectory planning and screw placement of the osteoporotic vertebral body can be achieved increasingly quickly, providing a new option for pedicle screw placement of the osteoporotic vertebral body.
In this study, an in vitro demineralized osteoporosis model of a porcine lumbar spine was used, and the evaluation index was only the CT value, without considering microscopic parameters such as bone trabecular structure. The structure of the pig lumbar vertebra is different from that of the human vertebra and EDTA decalcification simulates not true osteoporosis but more osteomalacia. The applicability of the pedicle screw should be verified in the patient’s CT and cadaver osteoporosis models. Specimens treated with preservatives inescapability caused changes in the material properties of specimens. Therefore, using fresh specimens to further improve the accuracy of the experimental study is necessary. In the pedicle screw pull-out experiment, we simulated direct violent pull-out, which had limited agreement with the actual pull-out situation in the human body. The pull-out force could be measured again after the cyclic fatigue test. This study specifically to age groups, requiring follow-up studies on normal vertebrae. The sample size of the test was small, and subsequent studies with larger sample sizes are needed to confirm its accuracy and effectiveness. Different designs and populations demographics to further investigate the effect of this automatic planning software are also needed.