Spine surgery has significantly progressed due to innovations in surgical techniques, technology, and a deeper understanding of spinal pathology. However, numerous challenges persist, complicating successful outcomes. Anatomical intricacies at transitional junctions demand precise surgical expertise to avoid complications. Technical challenges, such as underestimation of the density of fixed vertebrae, individual vertebral characteristics, and the angle of pedicle inclination, pose additional risks during surgery. Patient anatomical variability and prior surgeries add layers of difficulty, often necessitating thorough pre- and intraoperative planning. Technological challenges involve the integration of artificial intelligence (AI) and advanced visualization systems. AI offers predictive capabilities but is limited by the need for large, high-quality datasets and the “black box” nature of machine learning models, which complicates clinical decision making. Visualization technologies like augmented reality and robotic surgery enhance precision but come with operational and cost-related hurdles. Patient-specific challenges include managing postoperative complications such as adjacent segment disease, hardware failure, and neurological deficits. Effective patient outcome measurement is critical, yet existing metrics often fail to capture the full scope of patient experiences. Proper patient selection for procedures is essential to minimize risks and improve outcomes, but criteria can be inconsistent and complex. There is the need for continued technological innovation, improved patient-specific outcome measures, and enhanced surgical education through simulation-based training. Integrating AI in preoperative planning and developing comprehensive databases for spinal pathologies can aid in creating more accurate, generalizable models. A holistic approach that combines technological advancements with personalized patient care and ongoing education is essential for addressing these challenges and improving spine surgery outcomes.

Anterior Cervical Discectomy and Fusion (ACDF) for cervical radiculopathy is commonly performed with a cage and plate in the United States, whereas in Europe, standalone cages are frequently used instead. Knowledge about difference in clinical outcome is scarce. Are there differences in clinical outcomes in patients undergoing ACDF using a cage with an anterior plate, a cage with integrated screws, or a standalone cage? 570 patients with cervical radiculopathy were included: 414 received a cage with plate (US), 54 received cages with integrated screws (US) and 102 received a standalone cage (86% Netherlands). The clinical outcomes Visual Analogue Scale arm and neck pain, and pain interference were assessed at baseline, 3, 6, 12 and 24 months after inclusion, and analysed using linear mixed-effects models. Furthermore, the Minimal Clinical Important Difference was assessed and to explore individual patient-level outcome, cut-off values for clinical success were utilized. Baseline clinical parameters were comparable in the three groups. Linear mixed-effects models revealed no statistically significant differences in clinical outcome over time. However, dichotomized clinical success rates for neck pain were significantly higher in the standalone group (62.9% at 6 months, 79.3% at 12 months, 85.7% at 24 months), compared to the cage with plate group (59.5%, 61.2%, 58.9%) and the integrated screws group, which showed more variability (58.3%, 26.7%, 44.4%). No substantial differences were observed at the group mean-level, however, the standalone cage group demonstrated higher individual-level success-rates, particularly regarding neck pain.