Carbon-Fiber-Reinforced Polyetheretherketone (CFR-PEEK) instrumentation is increasingly preferred in spinal oncology for its physical properties, minimizing imaging artifacts and facilitating precise postoperative radiotherapy planning and tumor surveillance. However, a significant technical limitation exists: the current unavailability of dedicated CFR-PEEK pedicle screws for the cervical spine. The smallest available implants are designed for thoracic use (minimum diameter 4.5 mm, minimum length 25 mm), posing substantial risks of neurovascular injury when applied to smaller cervical pedicles. We present a technical note/feasibility report illustrated by a single case of robot-assisted placement of thoracic CFR-PEEK screws in the cervical spine for the treatment of a C7 Giant Cell Tumor. Following neoadjuvant therapy with Denosumab, a single-stage, two-step circumferential resection and reconstruction was performed. The anterior step was complicated by an iatrogenic injury to the highly adherent left vertebral artery (VA), which was successfully repaired. Consequently, the posterior step required maximal precision to preserve the sole remaining intact VA on the right side. Given the anatomical mismatch between the 4.5 mm thoracic screws and the narrow cervical pedicles (measuring as narrow as 3.2 mm on the critical right side), robotic navigation (ExcelsiusGPS^®) was utilized to plan and execute safe trajectories. Specifically, on the side of the intact VA, a small, controlled medial cortical violation was planned to avoid lateral vascular compromise. The procedure resulted in rigid, artifact-free stabilization with no immediate neurological sequelae. This single-case experience suggests that robotic guidance may facilitate adaptation of thoracic CFR-PEEK instrumentation to the cervical spine in selected oncologic scenarios; reproducibility, costs, and long-term outcomes remain uncertain.

Background: Accurate pedicle screw placement remains essential in spinal instrumentation, and robotic navigation has been introduced to improve safety, reproducibility, and workflow standardization. This study evaluated the accuracy of robot-assisted pedicle screw placement using the Excelsius GPS platform during the first year of implementation at two centers and analyzed the associated learning curve. Methods: Consecutive patients undergoing robot-assisted spinal instrumentation between April 2024 and April 2025 were retrospectively reviewed. Screw accuracy was assessed on intraoperative three-dimensional imaging using the Gertzbein–Robbins Scale (GRS). Grades A and B were considered clinically acceptable, whereas grades C–E were considered clinically non-acceptable. Sacral S1 screws and oncological cases requiring carbon fiber-reinforced PEEK instrumentation were excluded from the primary analysis and evaluated separately when appropriate. Robotic workflow time was defined as the interval between the first intraoperative three-dimensional acquisition used for planning and the second acquisition used for screw verification. Results: The primary standard non-oncological cohort included 102 patients and 455 non-S1 screws. Overall, 411 screws were classified as GRS A, yielding a perfect intrapedicular placement rate of 90.3%. Clinically acceptable accuracy was achieved in 449 of 455 screws, corresponding to a GRS A + B rate of 98.7% (95% CI, 97.2–99.4%). Only six screws were classified as GRS C–E, with no GRS D screws observed. Clinically acceptable accuracy was comparable between centers. In Center 1, all clinically non-acceptable screws occurred within the first nine cases, and GRS A + B accuracy increased from 92.9% in the first trimester to 100% thereafter. Median robotic workflow time was 64.4 min per case and 13.9 min per screw. Conclusions: This two-center early experience supports the accuracy and reproducibility of ExcelsiusGPS-assisted spinal instrumentation. Chronological analysis showed that clinically non-acceptable breaches were concentrated in the early implementation phase; however, this observation should be considered exploratory because of the low event count. The study supports high clinically acceptable accuracy and broadly comparable robotic workflow metrics across centers. Chronological patterns observed during early implementation should be interpreted as exploratory rather than as proof of a formal learning curve.