This study employed a patient-specific finite element model. To quantify the effect of anterior and posterior surgical approaches on adjacent segment biomechanics of the patient-specific spine and spinal cord. Adjacent segment degeneration (ASD) is a well-documented complication following cervical fusion, typically resulting from accelerated osteoligamentous deterioration and subsequent symptomatic neural compression. Despite the known impact of spinal fusion on adjacent segment biomechanics, comprehensive comparison between anterior and posterior surgical approaches remains elusive. Understanding these biomechanical changes is crucial for predicting and managing ASD, thereby aiding preoperative surgical planning. Patient-specific finite element modeling (FEM) of the cervical spine and spinal cord were created. Surgical simulation was performed for multi-segment anterior cervical discectomy fusion (ACDF) (C4-C7) and posterior cervical laminectomy with fusion (PCLF) (C5-6 laminectomy and C4-C7 fusion). Physiological motions were simulated by applying a 2 Nm moment and 75 N force. At the superior adjacent segment, the ACDF model exhibited a higher range of motion (ROM) during neck flexion compared to PCLF. Conversely, in neck extension, PCLF showed a higher ROM than ACDF. At the superior adjacent segment, the ACDF model showed greater spinal cord stress during flexion. During extension, PCLF was associated with greater spinal cord stress. At the inferior adjacent segment, ACDF was associated with greater spinal cord stress than PCLF during flexion. At the superior adjacent segment, ACDF also led to increased intradiskal pressure and capsular ligament strain during flexion, whereas PCLF showed these increases during extension. Our findings indicate the differential effect of ACDF and PCLF on biomechanics at the cervical spine's adjacent segments, with the patient-specific model with ACDF showing greater changes and potential for degeneration. This study highlights the utility of patient-specific FEMs in enhancing surgical decision-making through personalized medicine.
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