Robotics and the spine: a review of current and ongoing applications

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Object

Robotics in the operating room has shown great use and versatility in multiple surgical fields. Robot-assisted spine surgery has gained significant favor over its relatively short existence, due to its intuitive promise of higher surgical accuracy and better outcomes with fewer complications. Here, the authors analyze the existing literature on this growing technology in the era of minimally invasive spine surgery.

Methods

In an attempt to provide the most recent, up-to-date review of the current literature on robotic spine surgery, a search of the existing literature was conducted to obtain all relevant studies on robotics as it relates to its application in spine surgery and other interventions.

Results

In all, 45 articles were included in the analysis. The authors discuss the current status of this technology and its potential in multiple arenas of spinal interventions, mainly spine surgery and spine biomechanics testing.

Conclusions

There are numerous potential advantages and limitations to robotic spine surgery, as suggested in published case reports and in retrospective and prospective studies. Randomized controlled trials are few in number and show conflicting results regarding accuracy. The present limitations may be surmountable with future technological improvements, greater surgeon experience, reduced cost, improved operating room dynamics, and more training of surgical team members. Given the promise of robotics for improvements in spine surgery and spine biomechanics testing, more studies are needed to further explore the applicability of this technology in the spinal operating room. Due to the significant cost of the robotic equipment, studies are needed to substantiate that the increased equipment costs will result in significant benefits that will justify the expense.

Abbreviations used in this paper:RCT = randomized controlled trial; ROM = range of motion.

Abstract

Object

Robotics in the operating room has shown great use and versatility in multiple surgical fields. Robot-assisted spine surgery has gained significant favor over its relatively short existence, due to its intuitive promise of higher surgical accuracy and better outcomes with fewer complications. Here, the authors analyze the existing literature on this growing technology in the era of minimally invasive spine surgery.

Methods

In an attempt to provide the most recent, up-to-date review of the current literature on robotic spine surgery, a search of the existing literature was conducted to obtain all relevant studies on robotics as it relates to its application in spine surgery and other interventions.

Results

In all, 45 articles were included in the analysis. The authors discuss the current status of this technology and its potential in multiple arenas of spinal interventions, mainly spine surgery and spine biomechanics testing.

Conclusions

There are numerous potential advantages and limitations to robotic spine surgery, as suggested in published case reports and in retrospective and prospective studies. Randomized controlled trials are few in number and show conflicting results regarding accuracy. The present limitations may be surmountable with future technological improvements, greater surgeon experience, reduced cost, improved operating room dynamics, and more training of surgical team members. Given the promise of robotics for improvements in spine surgery and spine biomechanics testing, more studies are needed to further explore the applicability of this technology in the spinal operating room. Due to the significant cost of the robotic equipment, studies are needed to substantiate that the increased equipment costs will result in significant benefits that will justify the expense.

Technological advances have revolutionized spine surgery over the past 20 years. Many of these developments have been centered on the innovations of new technology implants and minimally invasive spine surgery. The goals of these improvements have been to balance the maintenance of a high degree of precision, to minimize risks of damage to neurovascular structures, to facilitate surgeon access and operating room dynamics, and to diminish harmful exposure to ionizing radiation in patients and the operative team. Because the risks associated with spine surgery are plentiful and limiting complications is imperative, implementing a robot-assisted technique has the potential to address many concerns associated with conventional surgery.

Robotic systems have been used in multiple surgical disciplines including gynecology, urology, and general surgery. In the last decade we have seen the application of this technology to spine surgery. Robots can potentially help with all matters of spine surgery including the following: precision in spinal instrumentation, eliminating dural and neurovascular injuries, minimizing exposure to radiation, and improving operating room workflow.5 At the same time, the technology affords the surgeon a significant improvement in coordination, 3D visualization, and a reduction in fatigue, and it offers the patient a smaller incision, lower risk of infections, minimal muscle retraction and thus postoperative pain, and shortened length of hospital stay.16 Apart from screw and rod insertion, the technology has been applied to other forms of spine operations and pathological conditions including tumor resections and ablations, vertebroplasties, and anesthetic blocks.5

This article provides an overview and update on the utility of robotics in spine surgery and spine biomechanics testing.

Methods

Using the National Library of Medicine search engine, PubMed, we searched the literature to identify articles that had been published between 1950 and 2013 that were pertinent to robotics in spine surgery. The key words used in the search were “spine” and/or “spinal” and/or “surgery” and/or “robotics” and/or “robots.” Relevant primary articles describing case reports or clinical studies were selected, and the reference lists from these articles were also inspected for other relevant articles. Each of the resultant articles was reviewed by all authors, discussed in a committee, and reported in this review. Reviews and editorials were excluded. Only publications in English-language, peer-reviewed journals were included. Articles were then categorized into cadaveric, human clinical, and biomechanics studies.

Results

In all, 45 articles were included. The following is a review and analysis of the 45 published reports and studies regarding robotics in spine surgery and spine biomechanics testing.

Robotics and the Operating Theater: A Match Made in Heaven

Since the advent of modern surgical robots in the early 1990s, robotic technology has become well established in urology, gynecology, and general surgery for its advantages in laparoscopic procedures.6,28,44 The da Vinci surgical system (Intuitive Surgical, Inc.) was approved by the FDA in 2000 for use in general surgery operations, in 2001 for urological operations, and in 2005 for gynecological surgery.1,22,44 In 2010 alone, more than 300,000 robotic procedures were completed, and exploration continues to find further avenues for use.44 Over the past decade, several advances have been made in robotic technology following years of experience with these robots in the operating room.1,44 One of the most widespread uses of robotic technology has developed in urology. Although both robot-assisted and laparoscopic prostatectomy have been shown to reduce blood loss and hospital stay significantly when compared with open prostatectomy, robotic technology has demonstrated a reduced learning curve and improved intraoperative visualization when compared with laparoscopy.4 Additional examples include high-definition visualization for small operative areas, robot accessibility in the operating room, and haptic feedback (the ability to inform surgeons regarding pressure and touch when using instruments).44

Over the past decade, robotic technology has been increasingly used in spine surgery, with a rapidly expanding breadth of applications.2,9,39 Several models are under research and development; for instance, the da Vinci surgical system has been used for paraspinal tumor removal and transoral odontoidectomy under a research protocol, with great success.5,23,24,30,34,45 SpineAssist (Mazor Surgical Technologies) is a miniature robot approved by the FDA for pedicle screw placement, which has been evaluated in multiple retrospective and a few prospective studies.7,9,15 Such robots have been incorporated in the spinal operating theater for the theoretical benefits of improved visualization, reduced radiation exposure for both patients and surgeons, and improved accuracy in placement of screws and implants.9,15 However, because this technology is increasingly used in the field, it will be important to provide evidence that the use of robot-assisted surgery is superior to freehand or image-guided methods in patient outcomes and cost-effectiveness.35–37

Many factors specific to surgery in the spine make the use of robotic technology ideal for improvement of techniques and outcomes. Placement of screws and implants can be assisted by robotic localization for accuracy and precision.36,39 The proximity of blood vessels and nerve roots to the bony structure creates the possibility of severe postoperative complications should errors occur.39 Procedures in the spine thus require fine motor coordination, which may be assisted by robotic minimization of hand tremor.36 Access to the spine and visualization through a long corridor are often difficult.33 Minimally invasive surgery has been shown to improve outcomes and recovery rates in addition to reducing complications, infection, blood loss, and tissue trauma.36 However, these procedures often require much longer periods of exposure to radiation for both surgeons and patients, causing many surgeons to rely on a standard open approach rather than a minimally invasive approach to the spine. From 2004 to 2007, a retrospective review of more than 100,000 spine cases showed that only 13.2% were minimally invasive in approach.11 Should robotic spine surgery provide an avenue for minimally invasive surgery while reducing intraoperative exposure to radiation and improving accuracy of screw placement, it may be considered a future standard for improving outcomes for both patients and surgeons.33,36,39

Cadaveric Studies of Robot-Assisted Spine Surgery

Paramount to assessing assumptions about robotic applications in spine surgery, as with any new surgical innovation, is how to test feasibility and efficacy. Although the hypothesized advantages and disadvantages robot-assisted spine surgery are plausible, they have not been delineated in a systematic approach. Efficacy is classically determined by quality designed clinical trials. However, there are many hurdles to designing clinical trials that involve surgical intervention—including randomization, blinding, and ethical concerns. Prior to testing new surgical techniques or equipment, feasibility studies must be completed to evaluate whether the aim of the new intervention is possible. The most convincing studies on the feasibility of robot-assisted spine surgery have been performed on human cadavers. The use of cadavers for this purpose has advantages and disadvantages. Although cadaveric anatomy is the same, there is no way to identify complications except by radiographic imaging after placement of instrumentation. Other outcomes and complications including pain, relief of symptoms, quality of life, bleeding, nerve root injuries, and more cannot be assessed. Table 1 illustrates the variety of cadaveric studies that have been performed and their characteristics.18,19,21,25–27,38,40

TABLE 1:

Literature review of models for robot-assisted spine surgery*

Authors & YearModel (no.)RobotStudy TypeSurgical ProcedurePurposeResults/Outcomes
Togawa et al., 2007cadaver (10)SpineAssist (Mazor)case seriesPS & translaminar facet screw & K-wire placement in lumbosacral spine using either open or MIS techniqueaccuracy of screw placement29 of 32 K-wires & all 4 screws placed w/ <1.5 mm of deviation; 16 of 19 K-wires placed w/ <1.5 mm of deviation
Lu et al., 2009cadaver (6), patient (6)computer-assisted drill templatecase serieslumbar PS placementfeasibility & efficacy of drill template for thoracolumbar PS placementreduced op time, reduced radiation exposure
Kostrzewski et al., 2012cadaver (6)custom robot w/ 4 dfcase seriesC1–2 transarticular screws (1 or 2)feasibility study of custom robot for cervical spine opmean translational error 1.94 mm & mean rotational error 4.35°
Kim et al., 201019cadaver (2)BFRScase reportT11–L5 bilat percutaneous PSsfeasibility of BFRS for percutaneous PS placementdifference in axial & sagittal screw angle in planned compared to postop: 2.45 ± 2.56° & 0.71 ± 1.21°, respectively
Thomale et al., 2005cadaver (2)custom spine frame, Bronze Millennium Armcase reportlumbar PSs at L-2, L-3, & L-5feasibility & accuracy of a custom frame & robot for lumbar PSsmeasuring w/ Bronze Arm, deviations were 0.71 mm (L-2), 0.79 mm (L-3), & 0.74 mm (L-5)
Lee et al., 201025cadaver (2)da Vinci surgical systemcase reporttransoral decompression of CCJfeasibility of da Vinci robot in transoral approach to CCJ30° scope allows for better op field angle
Lieberman et al., 2006cadaver (1)SpineAssist (Mazor)case reportlumbar PS & translaminar facet screw placementfeasibility of small robot mounted to spinous processshorter op time, accuracy w/in 1 mm of preplanned

BFRS = biplane fluoroscopy-guided robot system; CCJ = craniocervical junction; MIS = minimally invasive surgery; PS = pedicle screw.

Whereas many published studies consisted of 1–2 cadavers, Togawa et al.42 reported on the placement of lumbosacral pedicle screws, translaminar facet screws, and K-wires for which the SpineAssist Mazor robot was used in 10 cadavers. In that study a preoperative CT scan was obtained in each cadaveric torso, from which the 3D reconstructions were used for synchronization with the robot and surgical entry site planning. Multiple types of surgeries were performed, including K-wire placement with either an open or minimally invasive technique, pedicle screws with the PathFinder minimally invasive system, and translaminar placement of screws or K-wires completed using a Hover-T minimally invasive frame. Postoperatively, CT scans were performed to analyze accuracy of K-wire and screw placement. The results were divided based on their level of accuracy in regard to lateral, anteroposterior, and axial deviations on postoperative imaging compared with preoperative planning. High accuracy was defined as deviation within 1.5 mm of any axis, and low accuracy was a deviation > 1.5 mm. The K-wires had an overall average deviation of 0.87 ± 0.63 mm from preoperative planning, with no difference in open versus minimally invasive techniques. Pedicle screw placement was assessed separately; they had all been placed successfully, with an overall average deviation of 1.03 ± 0.59 mm. In the translaminar facet instrumentation surgery, the overall average K-wire deviation was 1.05 ± 0.56 mm. This study showed good feasibility and accuracy for the use of the SpineAssist robot for placement of pedicle and translaminar instrumentation in the lumbosacral spine.

The 2 next largest studies used 6 cadavers and tested the feasibility of a novel spinal stereotaxy system with reverse-engineered drill templates based on CT scan 3D reconstruction of thoracolumbar vertebrae and C1–2 transarticular screw placement.21,27 In the thoracolumbar model, the drill templates had the advantage of being inexpensive (US $20), requiring no extra equipment, and allowing for pedicle screw placement in 1–2 minutes. These findings were subsequently applied in 6 patients, with similar results.27 In the paper by Kostrzewski et al.,21 the authors reported how they designed a robot that uses thin-slice CT scans with navigation software to automatically position the robot properly for the surgeon to place the C1–2 transarticular screws. Their study showed a total time from registration to screw placement of 17 minutes, with translational screw errors averaging 1.94 mm (range 0.41–6.19 mm). These variables were equivalent to the surgeon's conventional nonrobot-assisted methods.21

Among the rest of the cadaveric studies in Table 1, none consisted of more than 2 cadavers. The procedures mostly investigated the feasibility of different spinal procedures by using a variety of robots. The different systems included the da Vinci surgical system as well as custom robot systems combined with navigation or fluoroscopy. Other procedures performed were mostly posterior lumbar pedicle screw instrumentation and 1 case report of a transoral decompression of the craniocervical junction.19,25,26,40

Modern-Day Robotics and Studies With Spine Surgery

Studies and Series Analyzing the SpineAssist System

Early case series of patients undergoing robotic spine surgery demonstrated the technical and surgical obstacles that needed to be addressed and overcome for successful wide-scale implementation in the operating room.2,39 In 2006, Barzilay et al.2 conducted a prospective trial of SpineAssist for lumbar fusion in 15 patients at 2 centers, in which 9 cases demonstrated either technical or clinical errors. Technical errors were attributed to improper registration of intraoperative fluoroscopic images with the preoperative CT scan. Clinical errors included excessive pressure on the guiding arm, which altered the trajectory of screw placement; inability of the robot to reach desired location; or improper attachment of the clamp to the spinous process. Sukovich et al.39 showed either full or partial success in 13 of 14 cases, with errors similarly attributed to increased soft-tissue pressure on the guiding arm and failure of registration. Additionally, software crashes and lengthy calculation time (9 seconds per screw) were noted as setbacks to be addressed in future development of the robotic technology, and the early version used in these studies has since been improved.2,39

Since the implementation of robotic technology to the world of spine surgery, several case series and retrospective cohort studies on robot-assisted pedicle screw placement have demonstrated superior accuracy of screw placement when compared with prior estimates of accuracy in freehand and image-guided techniques.9,15 In a retrospective multicenter analysis of 842 patients by Devito et al.,9 3204 (98%) of 3271 screws and guidewires were correctly placed with breaches < 2 mm according to fluoroscopy or the surgeon's clinical judgment. The Gertzbein and Robbins10 criterion for accuracy was used, which classifies a screw as 1) perfectly within the pedicle; 2) breaching < 2 mm; 3) breaching between 2 and 4 mm; or 4) breaching between 4 and 6 mm. A postoperative CT scan was available for assessment of screw placement in 139 patients, and 98.3% of these screws were placed within 2 mm (89.3% completely within the pedicle and 9% breaching < 2 mm).9 Almost half (49%) of the operations were performed percutaneously, and permanent nerve damage occurred in none of the patients.

The study by Devito et al.9 compared these error rates to a prior meta-analysis of conventional pedicle screw placement done by Kosmopoulos and Schizas20 in 2007, citing a 81.9% accuracy rate, although the analysis lacked a standard of accuracy for screw placement.9,20 The lack of postoperative CT scans for evaluation in the majority of patients studied is cause for criticism of the study.9,37 However, the increased rate of percutaneous procedures may reduce soft-tissue pressure and trajectory deviation, which may have led to superior results.9,12 Of note, many additional studies (Table 2) compared robotic screw malposition rates to the results of a study analyzing conventional screw placement by Hicks et al. in 2010.12 The systematic review of pedicle screw placement in pediatric patients found that 4.2% of screws were malpositioned, but when postoperative CT scans were measured for accuracy, 15.7% of screws were malpositioned. Although measurement techniques are not standardized, the estimated malposition rates of conventional screw placement in studies such as those conducted by Kosmopoulos and Schizas and Hicks et al. are much higher than those of current retrospective robotics studies.9,12,20

TABLE 2:

Literature review of reports analyzing robotics in spine surgery*

Authors & YearStudyRobotNo.OpOutcome MeasureResult
Barzilay et al., 2006prospective cohortSpineAssist15PS placementscrew placement on postop CT6/15 cases successful
Sukovich et al., 2006case seriesSpineAssist14PS placementsuccess of opfull/partial success in 13/14 cases
Hu et al., 2013case seriesSpineAssist102PS placementscrew placement on fluoroaccuracy: 98.9% robotic, 110 screws aborted
Hu & Lieberman, 2013case seriesSpineAssist174PS placementscrew placement onaccuracy increased over time
Devito et al., 2010retro multicenterSpineAssist842PS/guidewire insertionscrew placement on fluoroaccuracy: 98%
Kantelhardt et al., 2011retro; conventional open vs robotic open vs robotic percutaneousSpineAssist112PS placementscrew placement on postop CTaccuracy: 94.5% robotic, 91.4% hand-placed
Pechlivanis et al., 2009prospective cohortSpineAssist31PS placementscrew placement on postop CTaccuracy: 98.5% axial, 91% longitudinal plane
Schizas et al., 2012prospective cohort; conventional fluoro-assisted freehand vs robot-assistedSpineAssist34PS placementscrew placement on postop CTaccuracy: 79% robotic, 83% freehand
Ringel et al., 2012prospective RCT; fluoro-assisted freehand vs robot-assistedSpineAssist60PS placementscrew placement on postop CTaccuracy: 85% robotic, 93% freehand
Roser et al., 2013prospective RCT; freehand vs neuro-navigation vs robot-assistedSpineAssist64PS placementscrew placement on postop CTpreliminary accuracy: 99% robotic, 97.5% freehand, 92% navigation
Moskowitz et al., 2009case reportda Vinci1resection of neurofibromasuccess of opimproved visualization, no comp
Lee et al., 201024case reportda Vinci1transoral odontoidectomysuccess of opimproved visualization, no comp
Yang et al., 2011case reportda Vinci1paraspinal schwannomasuccess of opimproved visualization, reduced comp
Perez-Cruet et al., 2012case reportda Vinci2paraspinal schwannomasuccess of opgood patient outcome, no comp
Lee et al., 2013case reportda Vinci2ALIFsuccess of opgood patient outcome, reduced comp
Beutler et al., 2013case reportda Vinci1ALIFsuccess of opreduced blood loss & comp
Cho et al., 2012case seriesUnitrac5Metrx thoracic discectomysuccess of opgood patient outcome, reduced comp

ALIF = anterior lumbar interbody fusion; comp = complication; fluoro = fluoroscopy; retro = retrospective.

Hu et al.14 conducted another important case series of 102 consecutive patients in whom the SpineAssist was used, which yielded similarly high accuracy rates. In their investigation 949 (98.9%) of 960 robotically placed screws were successfully positioned and 11 were malpositioned, presumably due to incorrect onset of trajectory. Robotic guidance was aborted for 110 screws, which were generally attributed to failure of the robot to register preoperative plans with intraoperative imaging, and/or technical problems with the planned trajectory. The majority of these aborted screws were in the thoracic (61.8%) and lumbar spine (30%), and each was converted to manual placement. The study was limited, however; the evaluation was done with fluoroscopy, and accuracy was characterized as either successfully placed or malpositioned. In 2011, Kantelhardt et al.15 compared the conventional open procedure to robotic open and robotic percutaneous techniques in a retrospective cohort analysis, and found that 94.5% of robot-assisted and 91.4% of conventionally placed screws were placed completely within the bone on postoperative CT scans (p = 0.00001), whereas there was no significant difference between the open robotic versus percutaneous robotic procedure. Retrospective analyses of robot-assisted cohorts have overall demonstrated very high accuracy rates in large numbers of screw placements.9,14,15 Furthermore, in 2013 Hu and Lieberman13 contended that the successful placement of pedicle screws with robotic assistance follows a learning curve that increases with surgeons' experience. In a consecutive cohort study of 174 patients who underwent pedicle screw placement by the same surgeon, accuracy rates increased from 82% in the first 30 patients to 93%, 91%, and 95%, respectively, in the following groups of 30 patients. Although the learning curve may be different for an inexperienced surgeon, the study demonstrated that accuracy ratings may further improve with time.

Prospective cohort studies (Table 2) of patients who have undergone robot-assisted pedicle screw placement have shown conflicting results, demonstrating the need for further prospective and randomized studies for clarification.33,37 Pechlivanis et al.33 evaluated the SpineAssist in 31 patients, showing that 98.5% of pedicle screws were placed within 2 mm in the axial plane on postoperative CT scans, and 91% of screws were placed in the longitudinal plane. Schizas et al.37 studied 34 consecutive patients, comparing 64 screws placed with SpineAssist and 64 placed with conventional fluoroscopic guidance using the freehand technique. On postoperative CT scans, 79% of robot-assisted screws (compared with 83% of fluoroscopy-guided freehand screws) were placed perfectly within pedicle margins. Because accuracy rates vary greatly between studies, it is important to consider variation in surgeon experience with the robot, accessibility in the operating room, and patient factors such as bone density, which may alter effectiveness data of early trials.33,36

Currently, there are few prospective trials or randomized controlled trials (RCTs) comparing accuracy rates (Table 2).35–37 Ringel et al.35 conducted a single-center prospective RCT for placement of lumbar and sacral pedicle screws comparing SpineAssist robot-assisted technique to freehand with fluoroscopic guidance in 60 patients. Accuracy assessed using the Gertzbein and Robbins10 criterion on postoperative CT scans showed that 93% of freehand screws were correctly placed within 2 mm of the pedicle, compared with 85% in the robot-assisted group. This result is surprising, given that observational cohort studies have noted greatly increased accuracy.9,14,33 Although randomization and postoperative evaluation were accounted for, a criticism of the study points out that a bed mount was used for each patient, which may have led to increased relative motion between the patient and the bed, and therefore decreased accuracy.13,35 An additional randomized controlled prospective study done by Roser et al.36 compared conventional freehand versus standard open neuronavigation versus robot-assisted pedicle screw placement. Preliminary results in 37 patients have demonstrated 97.5% accuracy (completely within the pedicle) for freehand, 92% accuracy for surface-matching neuronavigation, and 99% accuracy for robot-assisted screws. The current data from randomized prospective trials are inconclusive and scarce, requiring further study and multicenter analysis from various experienced surgeons for further elucidation of the accuracy of pedicle screw placement.35–37 Nevertheless, Schizas et al.37 argued the importance of the fact that robots can place these screws as well or almost as well as an experienced surgeon, which may be important when combined with the potential advantages of decreased fatigue and radiation exposure. Improvements in implementation of these devices in spine surgery and more experience with the technique, when considered in light of the benefits of visualization and potential reduced radiation exposure afforded by this technology, will most likely provide better outcomes in spine surgery.6,9

The da Vinci Surgical System: Spinal Applications

Although accuracy estimates are still debated, several case reports cite many advantages observed when expanding use of robotic assistance into spine operations. Established for general surgery in 2000, the da Vinci surgical system has been used with great success within the past few years in various spine procedures such as anterior lumbar interbody fusion,6,24 transoral odontoidectomy,30 resection of thoracolumbar neurofibroma,30 and resection of paraspinal schwannoma.34,35 Although case reports differ greatly in procedure and technique, there were several observations made in every case that proved beneficial for patient outcomes (Table 2).6,19,23,24,34,45 Visualization was unanimously considered superior when using the robotic system.6,30,45 The increased magnification offered by robotic assistance provided improved visualization for careful dissection of associated nerves and blood vessels.3,12 The 3D, high-definition capability was useful for visualization at the level of the anatomy.6,30 Beutler et al.6 specifically described the reduced morbidity created by a transperitoneal approach and maintenance of nearby structures allowed with the protection of the robotic system. Improved visualization and dissection of intraabdominal structures was directly related to benefits in patient outcomes.45 Lee et al.23 noted that this technique may lead to reduction in postsurgical complications such as urological or sexual dysfunction. Smaller incisions and reduced blood loss, lower morbidity and complications, reduced postoperative opioid use, shorter hospital stay, and rapid recovery were observed in multiple case studies.6,15,28,34

Spine Biomechanics Testing

In recent years, a number of robotic systems innovations have enabled in vitro biomechanical studies to approach conditions more closely approximating real-world, in vivo scenarios. Several of these innovations are summarized in Table 3. The literature describes 3 protocols for robotic control system design in biomechanical testing of the spine: stiffness, or position-controlled; flexibility, or load-controlled; and hybrid-controlled testing.31,32 Early robotic controllers consisted of positioncontrolled devices that simply made motor-controlled displacement along 3 or 6 df. The disadvantage of such simple control systems is that the actual loads can be prescribed only indirectly to a specimen by calculating from the positional displacements. A key goal of recent robotic systems development, therefore, has been to improve on the present state of the art to achieve continuous, real-time, load-controlled or hybrid-controlled (as opposed to position-controlled) testing and to apply it in various scenarios approximating physiological ranges of motion (ROMs). Another important advantage of robot-based spinal testing systems is multiaxial motion, which allows for reorienting force vectors in real time to better simulate in vivo conditions.

TABLE 3:

Literature review of robotic system innovations for in vivo spine biomechanical testing*

System DescriptionReferenceKey InnovationPurpose of InnovationMSU Model Used
fuzzy logic controllerTian, 2005application of fuzzy logic control to robotics for spine biomechanical testingto demonstrate fuzzy logic control as an alternative to hybrid control for human spine biomechanical testingrigid body-spring model system
6-df parallel robot systemWalker & Dickey, 2007introduction of a parallel robotic system for spine biomechanical testingto develop a 6-df parallel robot & control system for in vitro lumbar spine biomechanics testsporcine lumbar multiunit lumbar MSU (L2–7)
multisegment spine testing systemSchulze et al., 2012robotic system for multisegment spinal specimens combined w/ optical motion analysis of rigid body markersto evaluate a new testing system for multisegment specimens that uses robot combined w/ optical motion analysis systemcalf lumbar single MSU (L3–4) & multiunit MSU (L2–6)
CLTSKelly & Bennett, 2013describes a CLTSto develop core capabilities that can be applied to improved simulation of in vivo spinal loadshuman cadaveric single lumbar MSU (L4–5)
CLTSBennett & Kelly, 2013robotic methodology based on CLTS to control application of real-time dynamic force vectors throughout physiological ROMapplication of CLTS technology from Kelly & coworkers to apply a force dynamically following moving midline of disc in real timehuman cadaveric single lumbar MSU (L4–5)
hybrid control algorithmBell et al., 2013novel hybrid control algorithmto develop a realistic, adaptive control algorithm that combines traditional paradigms of “load control” & “displacement control” into a hybrid system; the hybrid system was found to minimize off-axis forces & resulted in large neutral zone & ROMhuman cadaveric single cervical MSU (C4–5 or C6–7)
direct force controlMartínez et al., 2013direct force control method for spine biomechanical testingto apply the direct force control method to robotic systems for multisegment spine biomechanical testing, improving on position- or load-based control methodsporcine multiunit cervical MSU (C2–4)

CLTS = cartesian-based real-time load-controlled testing system; MSU = motion segment unit.

The selected innovations highlighted in Table 3 show considerable progress in the design of robotic systems for biomechanical spine testing over the past decade. Tian41 introduced fuzzy logic control in robotic software as an improved alternative to hybrid control. Walker and Dickey43 provided an early demonstration of a parallel robotic system in which 6 df was used for biomechanical joint testing, which improves on serial robot designs by enabling complex 3D loading patterns and facilitating studies on specimens with poorly understood load-deformation properties. Schulze et al.38 demonstrated the ingenious combination of a multisegment robotic spine testing system with optical markers that can be affixed to rigid points on the specimen. With the aid of a camera, the relative motion of these optical markers can be used to ascertain the load-deformation characteristics of a complex specimen, such as a spinal segment with multiple joints. Two papers from the Memphis group4,17 highlight the development and application of a novel cartesian-based real-time load-controlled robotic testing system. Their validating experimental application exemplifies the advantages of robotic testing over nonrobotic platforms; namely to apply a dynamically oriented force. Their system is capable of applying a real-time dynamically reorienting force that follows the midline of the intervertebral disc as the joint of the specimen moves with rotation and deformation, which allows rigorous testing throughout the physiological ROM. Bell et al.3 developed a realistic, adaptive control algorithm based on a hybrid-controlled model that was found to minimize off-axis forces and increase the size of the neutral zone and ROM. Last, Martínez et al.29 demonstrated a direct force control method that improves on position-controlled and load-controlled methods and is ideally suited for multisegment testing.

Robotic spinal biomechanical testing systems, like their surgical counterparts, remain in the early phases of innovation. At this time, it is unclear which integrated testing system will become the gold standard and which innovations will prove essential to future work. Moreover, the field of spine surgery still awaits the first dramatic clinical innovation to derive directly from the use of improved robotic biomechanical testing platforms. In the next decade, as robots enable biomechanical testing systems to model in vivo reality more closely, there is the promise of more rapid and effective testing of devices and procedures that will improve patient care. Moreover, innovations in robotic biomechanical testing systems may provide much-needed synergy for the tandem evolution of intraoperative robots for spine surgery.

Discussion

From the standpoint of future studies in robot-assisted spine surgery, the focus should be to explore those issues that limit the technology from widespread adoption. Certainly the major categories that encompass the limitations in robotic adoption revolve around cost, lack of advanced tools, and time efficiency. These factors in many ways are interrelated and can conceivably be studied in a single encompassing prospective or retrospective study. Advancements in each category on a “micro” level can lead to improvements on a “macro” analysis. For instance, the technology that needs to be explored on a “micro” level would be development of discectomy tools, drill attachments, and modularity of the robotic arm that can interchange various specialized tools in a quick and efficient manner. Once these tools are developed, the robotic process could far exceed the precision and accuracy of the human hand. Clinical studies on tumor resection and difficult spinal access areas (transforaminal or posterior lumbar interbody fusion, costotransvertebral corpectomy, pedicle subtraction osteotomies, and so on) could potentially highlight the superiority of robotic assistance.

In addition to the advantage of visualization, the freedom of motion provided by the robotic arms was comparable to that of human hands, and steadiness was considered superior to human hand performance.8,30,45 Cho et al.8 used a robotic arm (Unitrac; Aesculap) during an oblique paraspinal approach for thoracic disc herniation with a tubular retractor.27 Their case series of 5 patients demonstrated the advantages of using the robotic arm as a pneumatic holding device; the surgery was more feasible with the robot's stronger holding power and stiffer angle. Yang et al.45 considered the robot-assisted retroperitoneal approach to resection of paraspinal schwannoma to be superior to the conventional technique in minimally invasive access as well as safer for the patient. Superior control in a narrow working space at great depth was noted for transoral odontoidectomy.24 As these case studies demonstrate, there is potential for application of this technology to such high-risk, minimally invasive operations.

At the same time, many of the listed studies have noted obstacles with robotic assistance that the investigators thought should be overcome before its implementation into mainstream spine surgery.6,23,24 The cost of robotic technology was cited as one of the major obstacles to its feasibility and consistent use across multiple institutions.5,23 Other noted difficulties have been logistical in nature; it is technically challenging and time-consuming to set up an operating room while coordinating a robot, imaging, and working without a team trained and capable of handling its use.6,23 Also significant, the robot lacks the tools for bony dissection or discectomy, and therefore these portions of the case had to be performed around the robot.23,24 Training a surgical team to use and work around the robot requires a considerable amount of time and expense, which would require significant patient benefits to outweigh these setbacks.6,24

A ubiquitous observation throughout robot-assisted surgery studies is the increased time required for both preoperative planning and intraoperative use.35,36,45 Ringel et al.35 noted a significant increase both in planning time for screw trajectories (24 minutes) and in surgical time (11 minutes). Additional studies cited increased pre- and intraoperative time relative to freehand techniques in screw placement and tumor resection.36,45 The general consensus, however, was that this increased time may be reduced by a learning curve for each surgeon using a new device.13,45

Reduction in radiation exposure is one of the major theoretical advantages that robotics may provide to minimally invasive spine surgery.2,5 According to the prospective RCT conducted by Ringel et al.,35 there was no significant difference in radiation exposure between robot-assisted and freehand techniques. When including preoperative planning CT scanning for the robotic procedure (which may differ by level and protocol), this study claimed that a higher dose of radiation was incurred by the patient. Similarly, Schizas et al.37 demonstrated no significant difference in radiation between the 2 groups in a prospective cohort study. In contrast, Kantelhardt et al.15 retrospectively observed that the average x-ray exposure per screw was 77 seconds for conventional procedures, and 34 seconds in robot-guided procedures. Roser et al.36 noted a similar decrease in radiation by almost half in the robot-assisted group compared with the freehand group in a prospective RCT. Because both retrospective and prospective studies show contradictory results, this is another aspect of robot-assisted spine surgery that needs further investigation to resolve the discrepancies.

An emphasis on workflow and design must also be at the forefront of future robot-assisted spine surgery. As great as the focus is on engineering and technology development in robots, there must be an equal emphasis on design and logistics. The success of the technology is dependent on the ease of use and increased efficiency that it can offer the surgeon. Studies looking at low-profile, flexible robotic arms, or even robotic arms that are attached to the ceiling as opposed to the operating table or a cumbersome base frame are examples of designs that can be further explored. The incorporation of image-guided navigation and electrophysiological neuromonitoring into robotic arms to “de-clutter” the operative field is another example of how design studies can improve the surgeon's experience. From a workflow standpoint, so-called simultaneous robotic spine surgery, in which a preprogrammed robotic arm instruments the bony pedicle spine while the surgeon is simultaneously executing a laminar decompression, presents a novel concept that appears very achievable with current robotic arm technology. Ultimately, these types of future studies could translate into decreased operating times, less blood loss, faster recoveries, and ultimately better clinical outcomes to justify the overall costs.

Conclusions

There are numerous potential advantages and limitations to robotic spine surgery, as has been suggested in retrospective and prospective studies, and in case reports in the literature. In terms of accuracy, retrospective analyses have indicated accuracy rates comparable to those with conventional techniques, which may even be significantly lower. Randomized trials are few in number and show conflicting results regarding accuracy; these results require further investigation to resolve the discrepancies. The various advantages of robotics are improved intraoperative visualization and dissection, smaller incisions, reduced blood loss, reduced recovery time, and shorter hospital stay. The disadvantages that have been noted, although perhaps surmountable with future technological improvements, include the need for greater surgeon experience, cost, training time, and operating room dynamics. Given the potential advantages of robotic technology for improvements in spine surgery, spine biomechanics testing, and patient outcomes, more research is needed to study the applicability of this technology in the spinal operating room. Future research should include large multicenter RCTs with multiple surgeons and a standardized accuracy rating system, such as postoperative CT imaging. Due to the substantial costs of the robotic equipment and the additional associated training necessary, research is needed to substantiate that the increased costs will result in significant benefits that will justify the considerable expense.

Disclosure

Dr. Kim is a consultant for DePuy Synthes. The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author contributions to the study and manuscript preparation include the following. Conception and design: Drazin. Analysis and interpretation of data: Drazin, Shweikeh, Arnell, Barnard. Drafting the article: Drazin, Shweikeh, Amadio, Arnell, Barnard. Critically revising the article: Drazin, Shweikeh, Kim, Johnson. Reviewed submitted version of manuscript: Drazin, Arnell, Kim, Johnson. Approved the final version of the manuscript on behalf of all authors: Drazin. Study supervision: Johnson.

References

  • 1

    Ahmed KIbrahim AWang TTKhan NChallacombe BKhan MS: Assessing the cost effectiveness of robotics in urological surgery—a systematic review. BJU Int 110:154415562012

  • 2

    Barzilay YLiebergall MFridlander AKnoller N: Miniature robotic guidance for spine surgery—introduction of a novel system and analysis of challenges encountered during the clinical development phase at two spine centres. Int J Med Robot 2:1461532006

  • 3

    Bell KMHartman RAGilbertson LGKang JD: In vitro spine testing using a robot-based testing system: comparison of displacement control and “hybrid control.”. J Biomech 46:166316692013

  • 4

    Bennett CRKelly BP: Robotic application of a dynamic resultant force vector using real-time load-control: simulation of an ideal follower load on cadaveric L4-L5 segments. J Biomech 46:208720922013

  • 5

    Bertelsen AMelo JSánchez EBorro D: A review of surgical robots for spinal interventions. Int J Med Robot 9:4074222013

  • 6

    Beutler WJPeppelman WCDimarco LA: The da Vinci robotic surgical assisted anterior lumbar interbody fusion: technical development and case report. Spine (Phila Pa 1976) 38:3563632013

  • 7

    Cahill KSWang MY: Evaluating the accuracy of robotic assistance in spine surgery. Neurosurgery 71:N20N212012

  • 8

    Cho JYLee SHJang SHLee HY: Oblique paraspinal approach for thoracic disc herniations using tubular retractor with robotic holder: a technical note. Eur Spine J 21:262026252012

  • 9

    Devito DPKaplan LDietl RPfeiffer MHorne DSilberstein B: Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study. Spine (Phila Pa 1976) 35:210921152010

  • 10

    Gertzbein SDRobbins SE: Accuracy of pedicular screw placement in vivo. Spine (Phila Pa 1976) 15:11141990

  • 11

    Hamilton DKSmith JSSansur CAGlassman SDAmes CPBerven SH: Rates of new neurological deficit associated with spine surgery based on 108,419 procedures: a report of the scoliosis research society morbidity and mortality committee. Spine (Phila Pa 1976) 36:121812282011

  • 12

    Hicks JMSingla AShen FHArlet V: Complications of pedicle screw fixation in scoliosis surgery: a systematic review. Spine (Phila Pa 1976) 35:E465E4702010

  • 13

    Hu XLieberman IH: What is the learning curve for robotic-assisted pedicle screw placement in spine surgery?. Clin Orthop Relat Res 2013

  • 14

    Hu XOhnmeiss DDLieberman IH: Robotic-assisted pedicle screw placement: lessons learned from the first 102 patients. Eur Spine J 22:6616662013

  • 15

    Kantelhardt SRMartinez RBaerwinkel SBurger RGiese ARohde V: Perioperative course and accuracy of screw positioning in conventional, open robotic-guided and percutaneous robotic-guided, pedicle screw placement. Eur Spine J 20:8608682011

  • 16

    Kazemi NCrew LKTredway TL: The future of spine surgery: new horizons in the treatment of spinal disorders. Surg Neurol Int 4:Suppl 1S15S212013

  • 17

    Kelly BPBennett CR: Design and validation of a novel Cartesian biomechanical testing system with coordinated 6DOF real-time load control: application to the lumbar spine (L1-S, L4-L5). J Biomech 46:194819542013

  • 18

    Kim MJHa YYang MSDo HYKim KNKim H: Robot-assisted anterior lumbar interbody fusion (ALIF) using retroperitoneal approach. Acta Neurochir (Wien) 152:6756792010

  • 19

    Kim SChung JYi BJKim YS: An assistive image-guided surgical robot system using O-arm fluoroscopy for pedicle screw insertion: preliminary and cadaveric study. Neurosurgery 67:175717672010

  • 20

    Kosmopoulos VSchizas C: Pedicle screw placement accuracy: a meta-analysis. Spine (Phila Pa 1976) 32:E111E11202007

  • 21

    Kostrzewski SDuff JMBaur COlszewski M: Robotic system for cervical spine surgery. Int J Med Robot 8:1841902012

  • 22

    Lau SVaknin ZRamana-Kumar AVHalliday DFranco ELGotlieb WH: Outcomes and cost comparisons after introducing a robotics program for endometrial cancer surgery. Obstet Gynecol 119:7177242012

  • 23

    Lee JYBhowmick DAEun DDWelch WC: Minimally invasive, robot-assisted, anterior lumbar interbody fusion: a technical note. J Neurol Surg A Cent Eur Neurosurg 74:2582612013

  • 24

    Lee JYLega BBhowmick DNewman JGO'Malley BW JrWeinstein GS: Da Vinci robot-assisted transoral odontoidectomy for basilar invagination. ORL J Otorhinolaryngol Relat Spec 72:91952010

  • 25

    Lee JYO'Malley BWNewman JGWeinstein GSLega BDiaz J: Transoral robotic surgery of craniocervical junction and atlantoaxial spine: a cadaveric study. Laboratory investigation. J Neurosurg Spine 12:13182010

  • 26

    Lieberman IHTogawa DKayanja MMReinhardt MKFriedlander AKnoller N: Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement: Part I—Technical development and a test case result. Neurosurgery 59:6416502006

  • 27

    Lu SXu YQZhang YZLi YBXie LShi JH: A novel computer-assisted drill guide template for lumbar pedicle screw placement: a cadaveric and clinical study. Int J Med Robot 5:1841912009

  • 28

    Marano AChoi YYHyung WJKim YMKim JNoh SH: Robotic versus laparoscopic versus open gastrectomy: a meta-analysis. J Gastric Cancer 13:1361482013

  • 29

    Martínez HObst TUlbrich HBurgkart R: A novel application of direct force control to perform in-vitro biomechanical tests using robotic technology. J Biomech 46:137913822013

  • 30

    Moskowitz RMYoung JLBox GNParé LSClayman RV: Retroperitoneal transdiaphragmatic robotic-assisted laparoscopic resection of a left thoracolumbar neurofibroma. JSLS 13:64682009

  • 31

    Panjabi MM: Biomechanical evaluation of spinal fixation devices: I. A conceptual framework. Spine (Phila Pa 1976) 13:112911341988

  • 32

    Panjabi MM: Hybrid multidirectional test method to evaluate spinal adjacent-level effects. 22:2572652007

  • 33

    Pechlivanis IKiriyanthan GEngelhardt MScholz MLücke SHarders A: Percutaneous placement of pedicle screws in the lumbar spine using a bone mounted miniature robotic system: first experiences and accuracy of screw placement. Spine (Phila Pa 1976) 34:3923982009

  • 34

    Perez-Cruet MJWelsh RJHussain NSBegun EMLin JPark P: Use of the da Vinci minimally invasive robotic system for resection of a complicated paraspinal schwannoma with thoracic extension: case report. Neurosurgery 71:1 Suppl Operative2092142012

  • 35

    Ringel FStüer CReinke APreuss ABehr MAuer F: Accuracy of robot-assisted placement of lumbar and sacral pedicle screws: a prospective randomized comparison to conventional freehand screw implantation. Spine (Phila Pa 1976) 37:E496E5012012

  • 36

    Roser FTatagiba MMaier G: Spinal robotics: current applications and future perspectives. Neurosurgery 72:Suppl 112182013

  • 37

    Schizas CThein EKwiatkowski BKulik G: Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy. Acta Orthop Belg 78:2402452012

  • 38

    Schulze MHartensuer RGehweiler DHölscher URaschke MJVordemvenne T: Evaluation of a robot-assisted testing system for multisegmental spine specimens. J Biomech 45:145714622012

  • 39

    Sukovich WBrink-Danan SHardenbrook M: Miniature robotic guidance for pedicle screw placement in posterior spinal fusion: early clinical experience with the SpineAssist. Int J Med Robot 2:1141222006

  • 40

    Thomale UWKneissler MHein AMaetzig MKroppenstedt SNLueth T: A spine frame for intra-operative fixation to increase accuracy in spinal navigation and robotics. Comput Aided Surg 10:1511552005

  • 41

    Tian L: An intelligent control method based on fuzzy logic for a robotic testing system for the human spine. J Biomech Eng 127:8078122005

  • 42

    Togawa DKayanja MMReinhardt MKShoham MBalter AFriedlander A: Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement: part 2–evaluation of system accuracy. Neurosurgery 60:2 Suppl 1ONS129ONS1392007

  • 43

    Walker MRDickey JP: New methodology for multi-dimensional spinal joint testing with a parallel robot. Med Biol Eng Comput 45:2973042007

  • 44

    Wedmid ALlukani ELee DI: Future perspectives in robotic surgery. BJU Int 108:102810362011

  • 45

    Yang MSKim KNDo HYPennant WHa Y: Robot-assisted resection of paraspinal Schwannoma. J Korean Med Sci 26:1501532011

Article Information

Address correspondence to: Doniel Drazin, M.D., Department of Neurosurgery, Cedars-Sinai Medical Center, Maxine Dunitz Neurosurgical Institute, 8631 W. Third St., Ste. 800E, Los Angeles, CA 90048. email: doniel.drazin@cshs.org.

Please include this information when citing this paper: DOI: 10.3171/2014.1.FOCUS13526.

© AANS, except where prohibited by US copyright law.

Headings

References

1

Ahmed KIbrahim AWang TTKhan NChallacombe BKhan MS: Assessing the cost effectiveness of robotics in urological surgery—a systematic review. BJU Int 110:154415562012

2

Barzilay YLiebergall MFridlander AKnoller N: Miniature robotic guidance for spine surgery—introduction of a novel system and analysis of challenges encountered during the clinical development phase at two spine centres. Int J Med Robot 2:1461532006

3

Bell KMHartman RAGilbertson LGKang JD: In vitro spine testing using a robot-based testing system: comparison of displacement control and “hybrid control.”. J Biomech 46:166316692013

4

Bennett CRKelly BP: Robotic application of a dynamic resultant force vector using real-time load-control: simulation of an ideal follower load on cadaveric L4-L5 segments. J Biomech 46:208720922013

5

Bertelsen AMelo JSánchez EBorro D: A review of surgical robots for spinal interventions. Int J Med Robot 9:4074222013

6

Beutler WJPeppelman WCDimarco LA: The da Vinci robotic surgical assisted anterior lumbar interbody fusion: technical development and case report. Spine (Phila Pa 1976) 38:3563632013

7

Cahill KSWang MY: Evaluating the accuracy of robotic assistance in spine surgery. Neurosurgery 71:N20N212012

8

Cho JYLee SHJang SHLee HY: Oblique paraspinal approach for thoracic disc herniations using tubular retractor with robotic holder: a technical note. Eur Spine J 21:262026252012

9

Devito DPKaplan LDietl RPfeiffer MHorne DSilberstein B: Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study. Spine (Phila Pa 1976) 35:210921152010

10

Gertzbein SDRobbins SE: Accuracy of pedicular screw placement in vivo. Spine (Phila Pa 1976) 15:11141990

11

Hamilton DKSmith JSSansur CAGlassman SDAmes CPBerven SH: Rates of new neurological deficit associated with spine surgery based on 108,419 procedures: a report of the scoliosis research society morbidity and mortality committee. Spine (Phila Pa 1976) 36:121812282011

12

Hicks JMSingla AShen FHArlet V: Complications of pedicle screw fixation in scoliosis surgery: a systematic review. Spine (Phila Pa 1976) 35:E465E4702010

13

Hu XLieberman IH: What is the learning curve for robotic-assisted pedicle screw placement in spine surgery?. Clin Orthop Relat Res 2013

14

Hu XOhnmeiss DDLieberman IH: Robotic-assisted pedicle screw placement: lessons learned from the first 102 patients. Eur Spine J 22:6616662013

15

Kantelhardt SRMartinez RBaerwinkel SBurger RGiese ARohde V: Perioperative course and accuracy of screw positioning in conventional, open robotic-guided and percutaneous robotic-guided, pedicle screw placement. Eur Spine J 20:8608682011

16

Kazemi NCrew LKTredway TL: The future of spine surgery: new horizons in the treatment of spinal disorders. Surg Neurol Int 4:Suppl 1S15S212013

17

Kelly BPBennett CR: Design and validation of a novel Cartesian biomechanical testing system with coordinated 6DOF real-time load control: application to the lumbar spine (L1-S, L4-L5). J Biomech 46:194819542013

18

Kim MJHa YYang MSDo HYKim KNKim H: Robot-assisted anterior lumbar interbody fusion (ALIF) using retroperitoneal approach. Acta Neurochir (Wien) 152:6756792010

19

Kim SChung JYi BJKim YS: An assistive image-guided surgical robot system using O-arm fluoroscopy for pedicle screw insertion: preliminary and cadaveric study. Neurosurgery 67:175717672010

20

Kosmopoulos VSchizas C: Pedicle screw placement accuracy: a meta-analysis. Spine (Phila Pa 1976) 32:E111E11202007

21

Kostrzewski SDuff JMBaur COlszewski M: Robotic system for cervical spine surgery. Int J Med Robot 8:1841902012

22

Lau SVaknin ZRamana-Kumar AVHalliday DFranco ELGotlieb WH: Outcomes and cost comparisons after introducing a robotics program for endometrial cancer surgery. Obstet Gynecol 119:7177242012

23

Lee JYBhowmick DAEun DDWelch WC: Minimally invasive, robot-assisted, anterior lumbar interbody fusion: a technical note. J Neurol Surg A Cent Eur Neurosurg 74:2582612013

24

Lee JYLega BBhowmick DNewman JGO'Malley BW JrWeinstein GS: Da Vinci robot-assisted transoral odontoidectomy for basilar invagination. ORL J Otorhinolaryngol Relat Spec 72:91952010

25

Lee JYO'Malley BWNewman JGWeinstein GSLega BDiaz J: Transoral robotic surgery of craniocervical junction and atlantoaxial spine: a cadaveric study. Laboratory investigation. J Neurosurg Spine 12:13182010

26

Lieberman IHTogawa DKayanja MMReinhardt MKFriedlander AKnoller N: Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement: Part I—Technical development and a test case result. Neurosurgery 59:6416502006

27

Lu SXu YQZhang YZLi YBXie LShi JH: A novel computer-assisted drill guide template for lumbar pedicle screw placement: a cadaveric and clinical study. Int J Med Robot 5:1841912009

28

Marano AChoi YYHyung WJKim YMKim JNoh SH: Robotic versus laparoscopic versus open gastrectomy: a meta-analysis. J Gastric Cancer 13:1361482013

29

Martínez HObst TUlbrich HBurgkart R: A novel application of direct force control to perform in-vitro biomechanical tests using robotic technology. J Biomech 46:137913822013

30

Moskowitz RMYoung JLBox GNParé LSClayman RV: Retroperitoneal transdiaphragmatic robotic-assisted laparoscopic resection of a left thoracolumbar neurofibroma. JSLS 13:64682009

31

Panjabi MM: Biomechanical evaluation of spinal fixation devices: I. A conceptual framework. Spine (Phila Pa 1976) 13:112911341988

32

Panjabi MM: Hybrid multidirectional test method to evaluate spinal adjacent-level effects. 22:2572652007

33

Pechlivanis IKiriyanthan GEngelhardt MScholz MLücke SHarders A: Percutaneous placement of pedicle screws in the lumbar spine using a bone mounted miniature robotic system: first experiences and accuracy of screw placement. Spine (Phila Pa 1976) 34:3923982009

34

Perez-Cruet MJWelsh RJHussain NSBegun EMLin JPark P: Use of the da Vinci minimally invasive robotic system for resection of a complicated paraspinal schwannoma with thoracic extension: case report. Neurosurgery 71:1 Suppl Operative2092142012

35

Ringel FStüer CReinke APreuss ABehr MAuer F: Accuracy of robot-assisted placement of lumbar and sacral pedicle screws: a prospective randomized comparison to conventional freehand screw implantation. Spine (Phila Pa 1976) 37:E496E5012012

36

Roser FTatagiba MMaier G: Spinal robotics: current applications and future perspectives. Neurosurgery 72:Suppl 112182013

37

Schizas CThein EKwiatkowski BKulik G: Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy. Acta Orthop Belg 78:2402452012

38

Schulze MHartensuer RGehweiler DHölscher URaschke MJVordemvenne T: Evaluation of a robot-assisted testing system for multisegmental spine specimens. J Biomech 45:145714622012

39

Sukovich WBrink-Danan SHardenbrook M: Miniature robotic guidance for pedicle screw placement in posterior spinal fusion: early clinical experience with the SpineAssist. Int J Med Robot 2:1141222006

40

Thomale UWKneissler MHein AMaetzig MKroppenstedt SNLueth T: A spine frame for intra-operative fixation to increase accuracy in spinal navigation and robotics. Comput Aided Surg 10:1511552005

41

Tian L: An intelligent control method based on fuzzy logic for a robotic testing system for the human spine. J Biomech Eng 127:8078122005

42

Togawa DKayanja MMReinhardt MKShoham MBalter AFriedlander A: Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement: part 2–evaluation of system accuracy. Neurosurgery 60:2 Suppl 1ONS129ONS1392007

43

Walker MRDickey JP: New methodology for multi-dimensional spinal joint testing with a parallel robot. Med Biol Eng Comput 45:2973042007

44

Wedmid ALlukani ELee DI: Future perspectives in robotic surgery. BJU Int 108:102810362011

45

Yang MSKim KNDo HYPennant WHa Y: Robot-assisted resection of paraspinal Schwannoma. J Korean Med Sci 26:1501532011

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