Abstract
Study Design
Comparative cadaveric validation.
Objectives
To evaluate the influence of prior surgical experience on the accuracy and efficiency of robotic-assisted muscle-preserving (RAMP) decompression using human specimens.
Methods
RAMP decompressions were performed from T8 - L5 in 8 cadavers by a non-fellowship-trained surgeon (NFTS) and a fellowship-trained surgeon (FTS). Computed tomography (CT) images were used for preoperative robotic planning and registration. Operative durations were documented, postoperative CT imaging was used to evaluate decompression accuracy and quantified anterior cortical bone removal (ACBR).
Results
A total of 80 levels underwent RAMP decompression (40 thoracic, 40 lumbar). Median single-level operative times were 2.6 min (IQR 1.9-3.7) for NFTS and 2.1 min (IQR 1.6-3.0) for FTS, with no significant difference (P = 0.109). Decompression accuracy demonstrated submillimeter deviation from planned margins, with posterior deviation measuring 0.6 mm (IQR 0.5-1.5) for NFTS and 0.7 mm (IQR 0.4-1.0) for FTS (P = 0.573), and anterior deviation measuring 0.3 mm (IQR 0.1-0.5) in both (P = 0.938). ACBR did not differ significantly between NFTS and FTS. Operative times declined with experience in both surgeons. Initial single-level RAMP decompressions showed greater variability (NFTS: 3.13-8.10 min; FTS: 1.39-10.56 min), while later cases converged to narrower ranges (NFTS: 1.18-2.46 min; FTS: 1.16-2.11 min).
Conclusions
This first comparative cadaveric study evaluating surgeon experience in the novel RAMP decompression demonstrates high accuracy and incrementally improving efficiency regardless of prior robotic experience. These findings support the integration of decompression into robotic workflows and pave the way for a broader applicability of high-precision, muscle-preserving techniques in spine surgery.
Introduction
The integration of robotic-assisted (RA) platforms into spine surgery has improved the precision and reproducibility of spinal instrumentation, particularly in pedicle screw placement.1-5 By enhancing trajectory control and minimizing variability, these systems have contributed to safer, less invasive procedures.6,7 Despite these advances, the application of RA technologies in decompression procedures has remained limited, with only a few early studies exploring their feasibility in controlled bony removal.8-10 In one cadaveric investigation, thoracic and lumbar laminectomies were performed with a planar saw, demonstrating accurate cutting paths while maintaining cortical preservation. 8 A related porcine ex vivo study using ultrasonic planar osteotomes further showed reduced thermal generation compared with constant speed cutting. 9 While these reports confirmed technical feasibility, planar instruments are constrained to linear trajectories and therefore lack the adaptability required for focal decompression of stenotic segments. More recently, Altorfer et al 10 reported the use of a robotic bone removal instrument originally designed for facet decortication, showing feasibility in both an ex vivo and a single in vivo laminectomy.
Robotic-assisted muscle-preserving (RAMP) decompression introduces a novel approach that leverages robotic accuracy to achieve targeted laminar bone removal, with the objective of preserving paraspinal musculature and stabilizing elements. 10 This technique builds on the principles of unilateral access with an “over-the-top” contralateral decompression, while incorporating robotic trajectory guidance to improve consistency and minimize surgical morbidity.11-13 However, as this technique remains in the early stages of evaluation, its technical accuracy and reproducibility, and feasibility across different levels of surgical experience have yet to be established.
Implementation of robotic assistance in decompression procedures demands not only technical feasibility but also effective skill acquisition. 14 The learning curve plays a pivotal role in clinical adoption and informs the design of structured training protocols.15,16 Although prior studies on RA instrumentation, particularly pedicle screw placement, have estimated that procedural proficiency can be achieved after approximately 20 to 30 cases, decompression procedures pose a fundamentally different set of intraoperative demands.17,18 These include continuous spatial assessment of osseous anatomy, dynamic control of skiving forces, and careful trajectory management during bone resection. 5 Consequently, it remains unclear whether the learning trajectory observed for instrumentation procedures is applicable to RA decompression techniques.
Previous investigations into RA instrumentation have examined how prior surgical experience shapes the learning curve.17-19 Feng et al 20 evaluated junior surgeons performing pedicle screw placement with RA and found that, under supervision, they achieved shorter learning phases and superior accuracy in anatomically complex regions compared to conventional techniques. Furthermore, Shahi et al 18 found that early-career surgeons demonstrated a clear learning curve for robotic lumbar fusion, while senior attendings did not, suggesting that procedural familiarity may reduce the need for technology specific learning. These findings suggest that while prior experience confers advantages, robotic systems may support early proficiency among less experienced users, potentially narrowing the performance gap between junior and senior surgeons.
To date, no study has systematically evaluated the learning curve of RA decompression techniques. Understanding whether surgical experience meaningfully influences procedural accuracy and efficiency in RAMP decompression is critical for informing training curricula and guiding broader clinical implementation. This study evaluates the learning curve of RAMP decompression using a cadaveric model by comparing procedural metrics and accuracy between a non-fellowship-trained surgeon (NFTS) and a fellowship-trained spine surgeon (FTS). The primary objective was to assess procedural performance in terms of accuracy and operative time for RAMP decompression in NFTS and FTS across thoracic and lumbar levels. It is hypothesized that with structured planning and execution protocols, RAMP decompression yields comparable accuracy and efficiency regardless of prior training.
Methods
Study Design and Surgeon Experience
Each cadaver underwent RAMP decompressions at 10 spinal levels from T8 - L5 and refers to a unilateral laminotomy with contralateral “over-the-top” decompression performed through a modified Wiltse approach. 11 A left-sided approach was used in 4 (50%) cadavers and a right-sided approach in the remaining 4. All procedures were conducted between October 2024 to January 2025. Cadaveric specimens were included based on the absence of prior surgical intervention at the targeted spinal levels and the lack of significant spinal deformities. Ethical approval was obtained from the Institutional Review Board (IRB No. 2024-1721). The study was conducted in accordance with the Declaration of Helsinki (2013 revision). Informed consent was not required for this study as it was conducted on cadaveric specimens.
This cadaveric study evaluated the performance of RAMP decompression in relation to prior surgical experience, comparing two surgeons with distinct training backgrounds. The NFTS was a third-year orthopedic resident with prior observational exposure to RA procedures but no direct operative robotic experience. The RAMP decompression conducted in this study marked his first hands-on application of RA spine surgery techniques. In contrast, the FTS had completed both residency and spine fellowship at academic institutions and had extensive prior experience performing RA procedures independently.
Preoperative Imaging and Planning
One day prior to the procedures, fine-cut computed tomography (CT) scans were acquired using a GE Discovery/LightSpeed scanner (GE Healthcare, USA) with all specimens fully thawed. The imaging data were uploaded into the Mazor X robotic planning software (Version 5.0; Medtronic, USA) to define 4 burr trajectories per level. Each trajectory was configured to traverse the dorsal laminar cortex and cancellous bone while maintaining a trajectory depth that preserved the majority of the ventral lamina. Planning parameters accounted for the dimensions of the acorn-shaped burr (7.5 mm diameter, 8-20 mm depth). Preoperative planning was conducted jointly by the junior surgeon and the fellowship-trained surgeon, with technical support provided by experienced manufacturer representatives.
Robotic-Assisted Muscle-Preserving Decompression
Each cadaver was placed in a prone position on a radiolucent table, with the robotic platform installed laterally. Clamp fixation at the L1–L2 spinous processes was performed through a midline incision as part of the thoracic registration process. Oblique and anteroposterior fluoroscopic images (OEC 9900 Elite, GE Healthcare, USA) were acquired to complete system registration, after which burr trajectories were reviewed and adjusted as needed. A muscle-sparing modified Wiltse approach was used throughout. Prior to burring, each planned trajectory was confirmed using a navigated pointer to ensure alignment with the preoperative plan. Bone removal was initiated with a high-speed robotic burr, positioned 1-2 mm above the laminar surface to reduce the risk of skiving.
5
Trajectory execution was continuously tracked in real time on a separate display. A red circular indicator on the system interface confirmed completion upon reaching the predefined depth. Burr rotation remained under manual control and did not stop automatically. Conventional bone removal was not performed, ensuring that the procedural outcome reflected the robotic technique alone. RAMP decompressions proceeded in a cranial-to-caudal sequence, starting at T8 and continuing through T12. After completing thoracic decompressions, the clamp was removed, and a percutaneous Schanz-pin was placed at the posterior superior iliac spine. Fluoroscopic confirmation for registration was obtained, and decompressions resumed from L1 to L5 (Figures 1 and 2). Intraoperative Setup for Lumbar Robotic-Assisted Muscle-Preserving (RAMP) Decompression. (1) Tracked Handheld High-Speed Burr Used for Bone Removal. (2) Screen Displaying the Registered Computed Tomography with Real-Time Instrument Position (Dark Blue). (3) Optical Tracking System. (4) Robotic Arm Attached Directly to the Operating Table and (5) To the Posterior Superior Iliac Spine via a Percutaneous Schanz-pin Robotic Planning, Postoperative Imaging, and Intraoperative View of Robotic-Assisted Muscle-Preserving (RAMP) Decompression. (a) Axial Computed Tomography (CT) At the T8 Level Showing Robotic Planning of Four Trajectories (Yellow) for RAMP Decompression. (b) Postintervention CT confirming Accurate Bony Resection Along the Planned Paths. (c) Intraoperative Photograph Following Surgical Exposure, Demonstrating Completed RAMP decompression
Intraoperative Monitoring
Intraoperative variables included the time for a single RAMP decompression, as well as the total operative time required to perform five consecutive thoracic or lumbar decompressions, beginning with skin marking and surgical access. Any workflow disruptions, such as registration failures or deviations from the planned sequence, were documented. Surgical tasks alternated between the surgeons, with each decompression performed exclusively by the assigned operator.
Postoperative Evaluation
Postoperative evaluation began with CT imaging to quantify the extent of bone removal. Focus was placed on the posterior lamina and anterior cortical margins. Anterior cortical bone removal (ACBR) was classified as substantial when exceeding 3 mm ipsilaterally or 7.5 mm contralaterally. These thresholds reflect the geometry of the acorn-shaped burr and the anatomy of the lamina. On the ipsilateral side, the burr tip may approximate the ligamentum flavum before its full diameter traverses the anterior cortex; the threshold was therefore conservatively reduced to 3 mm. In contrast, contralateral decompression involves a tangential trajectory, where the burr circumference is relevant, justifying the 7.5 mm threshold. The presence of ACBR does not necessarily indicate dural violation, given the protective thickness of the ligamentum flavum (2-4 mm in asymptomatic individuals and frequently greater in stenotic patients).
21
Acomparative analysis of operative times, decompression accuracy between the NFTS and FTS, and unplanned facet joint violations were conducted using the difference between preplanned and actual decompression margins. All measurements were independently evaluated by 2 spine surgeons. In cases of discrepancy, final values were established through joint review and agreement (Figure 3). Contralateral and Ipsilateral Anterior Cortical Bone Removal (ACBR) after Robotic-Assisted Muscle-Preserving (RAMP) Decompression. (a) Axial Postintervention Computed Tomography (CT) Scan at L3 Demonstrating Contralateral ACBR, not Classified as Substantial (<7.5 mm; White Arrow). (b) Overlaid Burr Trajectory for Spatial Reference. (c) Axial CT Scan at T9 Depicting Ipsilateral ACBR, not Classified as Substantial (<3 mm; white arrow). (d) Corresponding Trajectory Overlay
Statistical Analysis
Continuous variables were summarized using medians and interquartile ranges (IQR), and their distributions were visualized with histograms. Categorical variables were reported as frequencies and percentages. Group comparisons for continuous data were conducted using the Kruskal-Wallis test, while associations between categorical variables were evaluated with the chi-square test. A P-value <0.05 was considered statistically significant. Trends in operative times were evaluated descriptively, and no formal modeling was applied. No separate interobserver reliability analysis was undertaken. All analyses were carried out using R software (version 4.3.2).
Results
The study involved 8 human cadaveric specimens, including 6 male and 2 female bodies. Specimens had a mean age of 74.4 ± 7.1 years and a BMI of 24.6 ± 2.0 kg/m2. A total of 80 RAMP decompressions were completed, evenly distributed between thoracic and lumbar spinal levels. No workflow interruptions or registration failures were observed throughout the procedures.
Comparison of Surgeon Training Level
Comparison of Robotic-Assisted Muscle-Preserving (RAMP) Decompression by Surgeon Training Level. Comparison of Robotic-Assisted Muscle-Preserving (RAMP) Decompression by Surgeon Training Level. Single-Level RAMP Decompression Times Reflect Robotic Execution Only (Four Trajectories per Level), Excluding Skin Marking and Approach. Total Thoracic (T8–T12) and Lumbar (L1–L5) Times Include Skin Marking, Surgical Exposure, and Five-Level Decompression. Accuracy Reflects Deviation Between Planned and Postoperative Trajectories at Posterior Laminar and Anterior Cortical Margins. Values for Distance (mm) and Times (min) are Medians and Interquartile Ranges (IQR)
Anterior Cortical Bone Removal (ACBR) in Robotic-Assisted Muscle-Preserving (RAMP) Decompression by Surgeon Training Level. Anterior Cortical Bone Removal (ACBR) in Robotic-Assisted Muscle-Preserving (RAMP) Decompression by Surgeon Training Level. ACBR are Shown as Median Distances (IQR) and Absolute Counts. Substantial ACBR was Defined as >3 mm Ipsilaterally or >7.5 mm Contralaterally. A Distinction is Made Between Planned ACBR, Representing Intentional Anterior Cortex Removal According to Preoperative Trajectory Planning, and Unplanned ACBR, Representing Additional Cortical Breach Beyond the Planned Target Zone
Learning Curve
Single-level RAMP decompression times across thoracic and lumbar levels demonstrated a gradual decline in operative time for both NFTS and FTS. As illustrated in Figure 4, both groups showed similar efficiency, with trendlines indicating a shallow downward slope and minimal divergence between the 2 trajectories. Early decompressions showed a broad variability (NFTS: 3.13-8.10 min; FTS: 1.39-10.56 min), while later procedures converged toward shorter durations (NFTS: 1.18-2.46 min; FTS: 1.16-2.11 min). Exponential trendlines were fitted for both groups, with corresponding R2 values (0.2929 for FTS and 0.2764 for NFTS) and 95% confidence intervals. Comparison of Single-Level Robotic-Assisted Muscle-Preserving (RAMP) Decompression Times by Surgeon Training Level: Single-Level RAMP Decompression Times are Shown Across Thoracic and Lumbar Spine Levels, Stratified by Surgeon Training (Fellowship-Trained Surgeon (FTS) in Red, Non-Fellowship-Trained Surgeon (NFTS) in Blue). Exponential Trendlines are Displayed for Each Group (R² = 0.2929 for FTS, R² = 0.2764 for NFTS), with Shaded 95% Confidence Intervals
Discussion
This cadaveric study evaluated the influence of surgical experience on performance metrics during RAMP decompression, a recently introduced approach to posterior decompression. The hypothesis that RAMP decompression can be performed with comparable accuracy and efficiency regardless of prior training was supported by the findings. Across 80 thoracic and lumbar levels, the junior and fellowship-trained surgeons demonstrated similar operative times and decompression accuracy. It is important to note, RAMP decompression was executed with high precision overall, achieving submillimeter deviation from the planned resection margins, underscoring the reproducibility and control offered by robotic guidance in this workflow.
Learning Curve
The adoption of robotic technologies in spine surgery reflects a broader shift toward precision-driven operative strategies, offering structured execution, spatial fidelity, and reproducibility that may complement and refine traditional surgical workflows.14,22,23 Among the practical considerations in clinical implementation, the learning curve has received particular attention. Multiple studies have quantified the number of cases required to achieve procedural proficiency, with most suggesting that baseline competency in RA pedicle screw placement is reached after approximately 20 to 30 cases.15,17,18,24 For example, Shi et al 24 reported a significant reduction in operative time after the first 14 cases, driven primarily by decreased screw placement time, while setup and registration times remained unchanged.
This study shows that for 40 RAMP decompressions per surgeon, procedural proficiency can be achieved within a limited number of cases, indicating that the associated learning curve is not prohibitively steep. This aligns with the findings of Pennington et al, 17 who found that most robotic spine surgery learning curves plateaued particularly in operative time, screw placement efficiency, and accuracy. Studies that failed to detect a learning curve were often limited by small sample sizes or low thresholds, such as 30 screws, which may underestimate the case exposure needed to capture meaningful improvement. Although estimates vary by procedure, technology, and outcome measures, the data indicate that proficiency can be reached relatively quickly when supported by structured training and supervision.
Surgeon Proficiency
Beyond case volume, the influence of prior surgical experience has also been examined in the context of RAMP decompression. Shahi et al, 18 reported that experienced surgeons demonstrated negligible changes in operative efficiency over time, whereas early-career attendings displayed a more pronounced learning curve, with operative times and fluoroscopy use. Similarly, Siddiqui et al 19 found that both experienced surgeons and supervised fellows showed improved accuracy after approximately 30 screws, but that a second fellow entering the workflow at a later stage reached this proficiency even more quickly, likely due to improved guidance and established institutional protocols. In the present study, the junior and fellowship-trained surgeons achieved comparable performance across multiple metrics. Although early decompressions showed greater variability in timing, this stabilized rapidly in both groups, with later cases showing tight convergence. These findings align with Feng et al, 20 who demonstrated that under supervision, junior surgeons can match or even exceed the early performance of more experienced operators when using robotic platforms. Collectively, these results underscore the potential of robotic assistance to flatten traditional experience-based hierarchies, allowing procedural accuracy and efficiency to be standardized across experience levels.
The observed parity in performance between NFTS and FTS, along with learning curve analyses in RA spine surgery for pedicle screw placement, demonstrates a relatively fast acquisition of proficiency. This suggests that RAMP decompression may be implemented within existing surgical frameworks without requiring extensive prior experience in robotic systems.15,24,25 Optimal execution depends on strict adherence to core principles of RA spine surgery: accurate planning, reliable registration, motion control, and skiving prevention.5,26 These aspects should be considered and implemented in a structured curriculum as proposed by Pennington et al. 17 This study advocates for a minimum of 30 performed robotic cases for senior-level residents specializing in spine surgery. Integrating these principles into training programs may further enhance procedural consistency and safety, facilitating the effective adoption of RA spine techniques.
Robotic-Assisted Muscle-Preserving Decompression
As robotic assistance continues to reshape spinal instrumentation, its extension to decompression procedures represents an evolving frontier. This study presents a structured framework for RA “over-the-top” decompression, establishing a reproducible first stage in a hybrid approach that can be complemented by tubular or endoscopic techniques.11,27,28 Robotic execution enables highly controlled bone removal with submillimeter accuracy, providing a level of precision that enhances safety near critical neural structures and sets a reliable foundation for further soft tissue decompression. Importantly, the muscle-sparing nature of RAMP decompression preserves paraspinal integrity by avoiding detachment of stabilizing musculature.29-32 Maintaining the connective tissue is essential not only for facilitating early postoperative recovery but also for reducing long-term biomechanical stress on adjacent segments, potentially lowering the risk of degeneration.33-35
Beyond the procedural learning curve associated with surgeon proficiency, this study also revealed a parallel trajectory of technical learning that informed the optimization of the RAMP decompression workflow. While robotic assistance ensures high spatial accuracy, its successful implementation depends equally on thoughtful integration of instrumentation, interface feedback, and real-time operative awareness.36,37 In one instance, an unplanned anterior breach occurred due to over-advancement of the high-speed burr despite visual confirmation on the system interface. This deviation, although isolated, underscores the inherent risk of relying solely on software-based cues without accounting for tactile resistance and dynamic tissue interaction. Importantly, even a single unplanned anterior breach must be regarded as a critical safety signal, as cortical violation carries the potential for dural or neural compromise if protective buffers are exceeded. Its occurrence highlights that robotic precision does not fully mitigate the need for vigilance and robust safeguard mechanisms. Such findings reinforce the importance of integrating protective instrumentation strategies. The use of flat-tipped burrs or self-stopping mechanisms may prevent inadvertent cortical breaches during the final phase of resection. As robotic decompression evolves, standardization must extend beyond planning and registration to include instrument selection and feedback integration.
Limitations
The cadaveric setting limits generalizability to live surgery, and as with most preclinical models, the study is limited in statistical power due to sample size constraints. With only 2 surgeons performing 80 decompressions, the study carries a risk of type II error. Nevertheless, the primary aim was to validate the technical feasibility, accuracy, and reproducibility of the RAMP decompression workflow in a controlled cadaveric environment. The study involved two surgeons, which may introduce bias related to individual learning patterns. A senior surgeon with more experience did not perform any RAMP decompressions, which limits the evaluation of adaptability across broader experience levels. Moreover, the inclusion of only two operators restricts the generalizability of the findings across different levels of surgical training, and future studies involving a larger and more diverse group of surgeons will be necessary to validate these results. Although each surgeon performed 40 decompressions, this volume appeared sufficient to achieve procedural competency; however, further improvement may occur with greater operative experience. Operative times reported in this study reflect the decompression phase alone and do not account for the full procedural workflow. While the findings confirm high accuracy and reproducibility, the study does not assess patient-level outcomes or long-term clinical effectiveness.
Outlook
This study represents an essential step toward the integration of decompression techniques into robotic spine workflows. By demonstrating that both junior and fellowship-trained surgeons achieved comparable performance, the findings support the notion that adoption of RA decompression may not require extensive prior robotic experience. The next phase will require validation in a real-world, prospective clinical setting, using adapted instrumentation that accommodates the subtleties of live surgery. In parallel, development efforts could explore the incorporation of magnetic resonance imaging-based planning and registration, offering a radiation-free alternative with enhanced soft-tissue resolution.38,39 Beyond osseous resection, future robotic workflows could be designed to accommodate controlled and anatomically precise soft tissue decompression. Advancing in this direction would enhance the clinical relevance of robotic systems by addressing the full spectrum of surgical demands.
Conclusion
This study demonstrates that the novel RAMP decompression can be performed with high accuracy and consistent efficiency, independent of prior surgical experience. Across 80 thoracic and lumbar levels, both junior and fellowship-trained surgeons achieved comparable outcomes in operative time and decompression precision. These findings support the feasibility of incorporating RAMP decompression into standard robotic workflows and pave the way for its potential in broader applicability as a high-precision, muscle-preserving technique in spinal surgery.
Footnotes
Ethical Approval
Ethical approval was obtained from the Institutional Review Board (IRB No. 2024-1721). Informed consent was not required for this study as it was conducted on cadaveric specimens.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a research grant from the Rama and Shashi Marda Foundation.
Declaration of Conflicting Interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JLC is the Senior Editor of the American Journal of Neuroradiology and Advisor for Remedy Logic. ETT received Institutional research grants from GE HealthCare, Siemens Healthineers, and AMAG Pharmaceuticals. DRL is a Consultant and on the Advisory Board for Choice Spine; consultant for Depuy Synthes; has Ownership Interest from Woven Orthopedic Technologies, Vestia Ventures MiRus Investment LLC HS2, LLC and ISPH II, LLC; has Research Support from Medtronic Sofamor Danek USA, Inc.; has Royalties from Nuvasive, Inc.; is on the Advisory Board and has Ownership Interest from Remedy Logic; is a Consultant and has Royalties from Stryker; is a Consultant and has Ownership Interest from Viseon, Inc. For the remaining authors, no conflicts of interest were declared.