Abstract
Enabling technologies (ETs) have increasingly been developed and used in pediatric spine surgery over the past two decades, sparking ongoing discussion about their benefits and drawbacks. Relevant literature indicates that ETs can enhance pedicle screw safety and accuracy while decreasing radiation exposure to patients and surgical staff. However, steep learning curves initially lead to longer operative times, and the costs of implementing these technologies are significant. This review explores current ETs for pediatric pedicle screw placement, assessing their utility, advantages, limitations, and practical considerations for adoption. Technologies discussed include stereotactic navigation, machine-vision navigation, robotic systems, and 3D-printed modeling systems used for pedicle screw placement. The article evaluates pedicle screw accuracy, surgical procedure time and complications, radiation exposure, surgeon safety, learning curves, costs, and technological limitations.
Key Concepts
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(1)
ET methods for pedicle screw placement in pediatric spine surgery include stereotactic navigation, machine-vision navigation, robotic assistance, and 3D-printed drill guides.
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(2)
Implementing ETs in pediatric spine surgery can extend operative times and bring new challenges, including high initial costs, a steep learning curve, and technical difficulties.
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(3)
Gaining proficiency in ETs may eventually decrease operative time, improve pedicle screw placement accuracy, facilitate education, and support surgeon well-being.
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(4)
ETs may provide significant value in complex pediatric cases with severe deformities, small pedicles, and/or challenging anatomy.
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(5)
Ideally, best practices can be achieved through collaboration with colleagues.
Keywords: Enabling technology, Scoliosis, Robotics, Pedicle screw, Navigation
Introduction
The use of pedicle screws has laid the foundation for modern treatment of pediatric spinal deformities. Accuracy and safety of screw placement are paramount, as misplaced screws can have significant structural and neurological impacts, including poor fixation, nerve root injury, vascular perforation, or spinal cord damage [[1], [2], [3]]. Specifically in pediatric populations, patients may have small pedicles or aberrant anatomical structures, which can increase the difficulty of screw placement [4]. Freehand and fluoroscopy-guided techniques have been considered the mainstays for pedicle screw placement. However, with the advent of modern technology, surgical enabling technologies have developed.
An enabling technology (ET) is any innovation that enables one to complete a task or process more easily or effectively. In pediatric spine surgery, ETs are intended to improve the safety and accuracy of pedicle screw placement while reducing surgical time, complications, and patient and surgical team radiation exposure [5]. There are many available ETs, each with its own unique strengths and challenges. Surgeons who are classically trained in the freehand technique must decide whether to adopt ETs into their practice and which ones to pursue. This article reviews the benefits, challenges, and practical considerations for implementation and use of ETs for pediatric pedicle screw placement, including stereotactic and machine-vision navigation, robotic systems, and three-dimensional (3D) printed modeling systems. This review is accompanied by a podcast produced by the Pediatric Orthopaedic Society of North America (POSNA) and the Pediatric Spine Study Group (PSSG) (see Fig. 1).
Figure 1.
POSNA/PSSG/SRS enabling technologies podcast panelists.
Our panelists include:
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Jaysson Brooks, MD, The Scottish Rite for Children, Dallas, Texas
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Chris Hardesty, MD, University Hospitals Rainbow Babies & Children's Hospital, Cleveland, Ohio.
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Mark Erickson, MD, Children's Hospital Colorado.
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David Skaggs, MD, Cedars-Sinai Guerin Children's Hospital, Los Angeles, California.
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Jason Anari, MD, Children's Hospital of Philadelphia.
Types of enabling technologies in pediatric spine surgery
Stereotactic navigation systems
Stereotactic navigation systems use computer software and axial imaging to track instruments in space relative to the patient's anatomy in real time. These systems rely on computed tomography (CT) or 3D fluoroscopy for axial imaging, which is the main difference between available systems. CT-based navigation uses either preoperative or intraoperative 360° imaging to achieve high-resolution images of the patient's anatomy, aiding in pedicle screw placement and accuracy verification. In contrast, 3D fluoroscopy-based navigation employs intraoperative imaging that offers quicker, lower-resolution images with reduced radiation exposure. Axial imaging can also be used in the operating room without navigation to verify screw positioning after placement. Listen to Dr. Jason Anari describe his workflow for a Lenke Type 1B curve using stereotactic navigation (Audio Clip 1).
Machine-vision navigation systems
Machine-vision navigation or visible-light-based navigation systems utilize axial imaging combined with intraoperative cameras and optical sensors to enable the computer to visualize and navigate its environment. This technology has played a key role in the development of other non-surgical autonomous systems, such as self-driving cars, robotic vacuums, and drones. These systems employ a light projector and stereoscopic video cameras to quickly generate a 3D image of the patient's surface anatomy during surgery, which can be compared to preoperative or intraoperative axial imaging, typically a CT scan. The machine setup includes an overhead light projector with integrated video cameras attached to a computer workstation that displays the registered images [6].
The movable arm functions both as a light source for the surgeon and as a light projector to produce images. Using surface markers, such as known landmarks or a reference array, the visible light navigation system can consistently generate images of the exposed anatomy to quickly recalibrate the preoperative axial imaging to the patient's position in the OR. This ability to rapidly realign the axial imaging with the patient's position in space is arguably the greatest advantage of machine-vision navigation, as it helps the surgeon minimize the effects of any accidental movement of the spine or navigation equipment. Another significant benefit compared to stereotactic navigation is the lack of intraoperative radiation exposure to the surgical team. Dr. Jaysson Brooks describes his workflow for a Lenke Type 1B curve using machine-vision navigation in Audio Clip 2.
Robotic systems
In pediatric spine deformity, robotic systems are used in conjunction with stereotactic navigation systems, typically based on CT [7]. Many robotic systems exist, offering varying degrees of robot and surgeon involvement. Shared-control robotic systems are most commonly used in spinal surgery, where hybrid robot and surgeon control are used [[7], [8], [9]]. In this approach, the surgeon can formulate a surgical plan from a preoperative CT, and the robot guides the trajectory of the surgeon's instruments intraoperatively [1,7]. These systems are designed to increase screw placement accuracy by leveraging preoperative or intraoperative imaging, real-time trajectory alignment, instrument visualization, and automated surgical performance [7]. Some authors have also cited decreased surgeon fatigue and tremor as an additional benefit [5]. Listen to Dr. David Skaggs outline his workflow for a simple spondylolysis using robotic assistance (Audio Clip 3).
3D-printed modeling systems
3D-printed templates are most commonly used as drill guides for pedicle screw placement, made precisely according to the patient's anatomy using preoperative CT scans. The surgeon typically consults with the company's engineering team to determine the optimal pedicle screw positions, sizes, and trajectories [10]. These guides dock firmly onto the spine during surgery, which serves as a safety mechanism to ensure they are used in the correct location [10,11]. 3D-printed modeling systems may prove most effective for complex spinal deformities, specifically in cases with smaller, more rotated pedicles [2,10]. Because the guides dock directly to the spine, these guides can achieve high screw placement accuracy regardless of movement [10,11]. In addition to the drill guide, some companies provide a 3D-printed replica of the patient's spine from the preoperative CT, intended to help the surgeon prepare for the case and, potentially, for use in the OR to better understand and visualize the patient's anatomy [10,11]. Listen to Dr. Chris Hardesty outline her workflow for a neuromuscular T2 to pelvis using 3D-printed drill guides (Audio Clip 5).
Clinical outcomes and comparisons
Accuracy of pedicle screw placement
One of the primary goals in pediatric spinal deformity is to further improve the safety and accuracy of pedicle screw placement [4]. Pedicle screw accuracy can be categorized using the Gertzbein-Robbins classification system (Table 1) [12]. Grade A and B screw placements are generally considered clinically acceptable and are therefore not considered misplaced or malpositioned.
Table 1.
Gertzbein-Robbins classification system [12].
| Grade | Breach Value | Classification |
|---|---|---|
| A | 0 mm | No breach, clinically acceptable |
| B | <2 mm | Minor cortical breach, clinically acceptable |
| C | >2 mm, <4 mm | Moderate cortical breach |
| D | >4 mm, <6 mm | Severe cortical breach |
| E | >6 mm | Very severe breach |
The current literature indicates that ETs consistently improve pedicle screw accuracy, particularly the rate of clinically acceptable screw placement. In a meta-analysis of pedicle screws placed using stereotactic (CT-based) navigation compared to freehand in pediatric spinal deformity surgery, Baldwin et al. [3] determined the odds of misplacing a screw to be three times lower when using navigation (P < .001), and the odds of placing a clinically acceptable screw to be three times higher with navigation (P < .01). Robotic systems have also shown a statistically significant increase in the rate of clinically acceptable pedicle screw placement. In a prospective study of 10 pediatric high-grade spondylolistheses analyzing the use of robotics with computer-assisted navigation, 100% of the screws were placed without pedicle breaches, neurological deficits, or complications [13]. The authors also noted adequate correction, as evidenced by statistically significant decreases in the lumbosacral angle and L5 slippage [13]. Interestingly, Widmann et al. [14] conducted a retrospective study of patients undergoing robot-assisted posterior spinal fusion at two institutions and found that over a nine-month period, there was a significant decrease in the breach rate from the first quartile (1.8%) to the third (0.59%) and fourth quartiles (0.56%), demonstrating that pedicle screw placement accuracy may increase with a surgeon's comfortability with the technology. Another study by Luo et al. [4] evaluated 137 pedicle and lateral mass screws placed in 16 patients younger than 10 years using freehand and stereotactic navigation, demonstrating a stereotactic navigation accuracy of 97.8%, which was significantly higher than that of the freehand group (P = .01).
Machine-vision navigation and 3D-printed modeling systems have exhibited similar results; however, the data are limited. In a retrospective single-institution analysis of 687 screw placements in 25 patients with pediatric neuromuscular scoliosis using machine-vision navigation, 98% of screws placed were excellent (grade A), and all breaches were classified as grade B [15]. Garg and colleagues [2] found a significant increase in Grade A screw placement when using 3D-printed guides as compared to freehand (P = .03). While excellent screw placement does not necessarily translate to better clinical outcomes, Grade A placement becomes more important in cases where screw placement is particularly challenging or where there is a high risk of breach, such as in patients with neuromuscular curves [3]. These patients tend to have complex anatomy and severe curves with a high degree of rotation. For complex cases such as these, ETs that improve clinically acceptable screw accuracy may be valuable, even for surgeons who prefer freehand techniques for more standard pediatric spinal deformities.
Radiation exposure
All of the aforementioned ETs require axial imaging, often in the form of a preoperative CT scan. Using standard-dose CT protocols for preoperative imaging can expose the patient to high levels of radiation [16,17]. Radiation exposure, particularly in pediatric populations, may predispose patients to developing germline mutations or other oncologic disorders; therefore, optimization of radiation dose exposure is crucial to maximize the benefits of ETs and minimize the harmful effects to the patient [[16], [17], [18]].
Newer low-dose axial imaging protocols can minimize radiation exposure while maintaining sufficient image detail [4,16]. Sakhrekar et al. have reported the successful use of “ultra-low dose” CT scans with machine-vision navigation to provide suitable imaging of bony anatomy while restricting other imaging modalities to reduce radiation exposure to levels comparable to a standard spinal radiograph. Sullivan et al. conducted a single-center cohort study to compare effective radiation dose in patients who underwent low-dose intraoperative CT for stereotactic navigation with that in patients who underwent low- or standard-dose preoperative CT for machine-vision navigation. They determined that the patients who underwent a low-dose preoperative CT were exposed to significantly less radiation than patients who underwent low-dose intraoperative CT imaging (P < .0001) [16]. Despite using the same low-dose protocol, intraoperative CT required an average of 2.2 scans to visualize all vertebral levels, whereas preoperative CT required only one scan [16]. This same study also determined that standard-dose preoperative CT scans exposed the patient to 23 times more radiation than either navigation system with the low-dose protocol [16]. New systems are being designed to generate CT-like images for navigation based on magnetic resonance imaging (MRI) rather than CT, potentially making scoliosis surgery radiation-free.
It is important to consider that while a patient is exposed to radiation during and potentially before a single surgery, surgical team members are exposed in every case, which can be hundreds of exposures per year. Although there are safe ways for surgical team members to be in the OR during radiation spins, the need to move staff behind screens may increase surgical times or compromise the sterile field, and the need to wear lead may lead to occupational injuries [18].
Surgeon preservation
Nationally, over 60% of orthopaedic surgeons experience neck pain, and 23% have a cervical radiculopathy [19]. In a survey of Scoliosis Research Society (SRS) members, nearly 25% reported rotator cuff disease and 28% reported neck pain with radiculopathy, both well above the reported rates in the general population [20]. These occupation-related injuries can be attributed to many factors, including the significant amount of upper extremity work to manually cannulate pedicles with a probe, the torque needed to manually screw implants, or the need to wear heavy lead for long surgeries [[19], [20], [21]]. These injuries pose an opportunity for changes, such as ETs, to prevent these issues and increase the number of years a surgeon may be able to operate [19].
Registration, frameshifts, and skiving
Robotic and navigation systems must be calibrated to the patient's anatomy in the OR via registration. Registering each vertebra may reduce surgical efficiency and increase operative times; however, these concerns may be mitigated once ET proficiency is attained (see Learning Curves) [15]. Registration occurs in a precise position, and any movement to the body or machinery occurring between registration and screw placement can diminish the accuracy of pedicle screw placement (see Video 3) [10]. Frameshifts, or inadvertent movements that cause the reference array to shift, are an essential consideration in ETs, particularly robotics. If a surgeon is unaware that a frameshift has occurred, the proposed trajectory or bony anatomy shown by the ET may differ from the patient's anatomy during surgery, thereby increasing the risk of neurovascular complications. To calibrate most navigation systems, a reference array is fixed to a known anatomic landmark, such as the spinous process of the lowest instrumented vertebral level, and the surgeon ensures that the anatomic landmark corresponds to what is displayed by the system (see Video 3) [4]. It is important to note that the spinous process may fracture when docking an array, which can result in a frameshift [15]. Spinous process fracture is more likely in neuromuscular or osteopenic curves, and docking the probe to a placed pedicle screw may reduce this risk [15].
An important difference between navigation systems lies in their ability to re-register during a case. That is, if motion occurs and the navigation no longer appears accurate, some systems allow the surgeon to recalibrate the axial imaging to the patient's anatomy. In contrast, others require repeat imaging, such as another O-arm spin. The ability to quickly re-register is a notable benefit of machine vision navigation. Some stereotactic navigation systems also allow re-registration, for instance by using known landmarks such as “fiducial screws.”
Another concern, particularly with robotic systems, is the potential loss of haptic feedback. Most orthopaedic surgeons rely on “feel” when operating, especially when cannulating or probing a pedicle. Drilling with a robotic system often compromises or alters haptic feedback, which can be challenging for freehand-trained surgeons who are becoming acquainted with these newer methods [14]. Newer systems have mechanisms to preserve haptic feedback, such as oscillating instruments that allow surgeons to maintain “feel” when drilling and inserting pedicle screws [9,14]. Some systems also have mechanisms to prevent drill bit skiving, which can occur even when inserting screws freehand, by alerting the surgeon when the drill bit is misaligned or by smoothing the bone before drilling [9]. Some surgeons may also adopt a hybrid system when using ETs, particularly during teaching. For example, the advanced technology may be used to confirm the pedicle pathway via stereotactic navigation, but the haptic “feel” of the gearshift probe may still be used to cannulate the pedicle [9].
Learning curves
Some surgeons, particularly those most comfortable with freehand technique and who have low breach rates, may be wary of adopting an ET due to the associated learning curve and workflow disruption [5]. New workflows can theoretically increase surgical time; however, the current literature suggests that surgical time may decrease after proficiency with an ET is achieved. Garg et al. [2] reported a significant reduction in surgical time when using 3D-printed drill guides, particularly for complex spinal deformities. They noted that the required preoperative planning time and the complete stripping of soft tissue to dock the drill guide were primarily offset by the reduction in surgical time achieved with the drill guide [2]. McLaughlin et al. [11] conducted another study assessing the use of 3D-printed drill guides for adolescents with idiopathic spinal deformities and found screw placement times to be significantly faster than with freehand. Additionally, they reported reduced blood loss with 3D-printed drill guides, which may be particularly important for neuromuscular cases, as these cases tend to take longer and patients often have limited blood reserves [11]. Lim et al. [22] reported similar findings with machine-vision navigation, noting that after ET proficiency was achieved, blood loss was reduced compared with freehand.
Support for trainees
ETs may also enhance training for residents and fellows. Having an ET available while teaching freehand skills may provide a form of “fail-safe,” as the trainee may attempt to align their screw using freehand techniques, then check their precision and trajectory using the ET. This may allow early trainees to gain more technical experience with reduced risk to patients [10]. Sakrekhar et al. [15] found no significant difference in screw placement accuracy between senior surgeons and trainees using machine-vision navigation, demonstrating that trainees can achieve high levels of screw placement accuracy when using ETs to assist in their learning.
However, it is crucial that ETs serve only as an adjunct to a surgeon's anatomical knowledge and judgment, and surgeons must ensure that ET guidance aligns with their own knowledge and tactile feedback [1,5,15]. Increased reliance on technology at the expense of applied anatomy skills and technique could lead to severe adverse outcomes, particularly if the technology malfunctions or frameshifts occur [1]. Additionally, trainees may leave to work at institutions where ETs are not readily available, necessitating reliance on their freehand skills. While using ETs as a teaching tool may be beneficial, it is prudent that trainees be prepared to perform surgeries in their absence [1,5].
Financial considerations
Upfront costs for purchasing surgical navigation systems include not only the equipment, which can range from $500,000 to over $2 million, but also maintenance and training. Without clear evidence of the clinical benefits of these technologies, it is difficult to justify such significant expenditures [1]. The early learning curve associated with the implementation of ETs may lead to longer operating times, which translate into higher costs for a hospital or surgical center [1]. However, after surgeons become proficient with ETs, the upfront costs may eventually be offset by improved surgical outcomes, including reduced complication rates, shorter hospital stays, and fewer revision surgeries [1].
The financial implications of misplaced or breached screws have been analyzed in adult spine surgery. Sankey et al. [23] conducted a medicolegal analysis demonstrating that litigation arising from misplaced screws resulted in an adjusted average payout of over $1.2 million from 1995 to 2019. Their assessment of the annual financial benefit of robotics in spine cases identified savings from reduced OR time and improved accuracy of pedicle screw placement, totaling $5,713 and $314,661, respectively. Additionally, reduced hospital stays attributable to robotics saved hospitals $251,860 annually. In another analysis, Watkins and colleagues [24] demonstrated that the decrease in revision rates with stereotactic navigation compared with the fluoroscopy-assisted freehand technique resulted in a $71,286 reduction in surgical revision costs. While this data cannot necessarily be extrapolated to pediatric populations, these findings suggest that the consideration of ETs for more complex cases with a higher likelihood of revision may be cost-effective for hospitals [7].
Summary
There are many available options for enabling technologies in pediatric spine surgery, specifically to assist with pedicle screw placement. Preliminary data on these technologies indicate that their use may improve pedicle screw placement accuracy while reducing radiation exposure for patients and staff. Implementation of ETs, particularly for seasoned surgeons, is associated with a steep learning curve; however, many surgeons report that, after gaining proficiency with their respective ET, their surgical times have decreased, their confidence in screw placement has increased, and their comfort level with new trainees has improved. Discussions about the implementation of ETs and workflows will enable the best outcomes for surgeons considering the use of ETs in their practice.
Additional links
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AAOS Webinar: Enabling Technology in Pediatric Spine Surgery
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POSNA's Peds Ortho: "Enabling Tech" in Pediatric Spine Surgery
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POSNAcademy: Power Pedicle Preparation and Screw Insertion In Treatment of Pediatric Spinal Deformity
Funding
No funding was received to assist with preparation of this manuscript.
Ethics approval and consent
Complete written informed consent was obtained from the patient, their guardian or legal representative for the publication of this study and accompanying images.
Declaration of competing interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The members of the Pediatric Spine Study Group are listed below:
David Bauer, Blake Montgomery, Anthony Catanzano, Carter Clement, Jean Ouellet, Stuart Weinstein, Craig Louer, Anand Segar, Suken Shah, Kevin Morash, Aaron Shaw, Judson Karlen, Michael Hughes, Otis Shirley, Andrew Jea, Nichola Wilson, Margaret Baldwin, Moyo Kruyt, Kenzo Cotton, Keith Orland, Lauren Torrey, Jennifer Holmes, Rolando Figueroa Roberto, Bruno Braga, Paul Rushton, Eric Huang, Sarah Southon Hryniuk, David Lebel, Stephen Plachta, Keith Baldwin, Louis Bezuidenhout, Edwin Kulubya, Andrea Simmonds, Taemin Oh, Carl St. Remy, Laura Meyer, Jeffrey Henstenburg, Smitha Mathew, Lukas Keil, Kenneth Noonan, Kyle Stampe, Kevin Lim, Luke Drake, Andy Stadler, Omar Iqbal, Arun Hariharan, John Dahl, Graham Shea, Karim Kantar, Stacy Ng, Karl Balsara, Tuo Peter Li, Dmitri Falkner, David Lazarus, Susana Nunez Pereira, Robert Lark, Tenner Guillaume, Steven Hwang, Joshua Klatt, Yehia El-Bromboly, James Sanders, Chris Bonfield, Daniel Miller, Jason Cheung, Mark Erickson, Felix Brassard, Tomoko Tanaka, Kyle Miller, Craig Birch, John Ghazi, Jessica McQuerry, Tyler Tetreault, Ferran Pellise, Karl Rathjen, Mohammed Alshareef, Michal Szczodry, Haemish Crawford, Michael Schmitz, Stefan Parent, Purnendu Gupta, Jacob Schulz, Susan Nelson, Rajiv Iyer, Nigel Price, Joseph Perra, Michael Kelly, Daniel Hedequist, Brian Kelly, Dan Sucato, Jochen Son-Hing, David Bumpass, Sara Van Nortwick, Jorge Fabregas, Mark Camp, Alvin Crawford, Lawrence Karlin, Gokhan Demirkiran, René Castelein, John Emans, Richard McCarthy, David Roye, Douglas Brockmeyer, Peter Sturm, George Thompson, Noriaki Kawakami, Randy Betz, Muharrem Yazici, Francisco Perez-Grueso, John Smith, Charles Johnston, Cynthia Nguyen, Jeffrey Martus, Jean-Marc Mac Thiong, Peter Newton, Raymond Knapp, Lionel Metz, Mohamed Esawy, Richard Schwend, Bryan Menapace, Lawrence Lenke, Benny Dahl, Michelle Carid, Brett Shannon, Laura Bellaire, John Anderson, Lindsay Crawford, Francesco Mangano, David Gonda, Thomas Errico, Shannon Kelly, Nan Wu, Brian Snyder, Alejandro Jose Marquez-Lara, Jose Herrera, Kim Hammerberg, Derek Kelly, Aki Puryear, Mari Groves, Arvindera Ghag, Erin MacKintosh, Edward Ahn, Hubert Labelle, Danielle Katz, David Wrubel, Harry Akoto, Mohammad Diab, David Harter, Sean Lew, Rober Cho, Stuart Mackenzie, Nancy Miller, Luis Rodriguez, Steve Richards, Christopher Reilly, Dan Drake, Stephen George, Timothy Skalak, Mundluru Surya, Andrew Tice, Tim Hresko, Shengru Wang, Scott Yang, Joe Stone, Morgan Jones, Daniel Bouton, Jennifer Bauer, Benjamin Martin, William Accousti, Jwalant Mehta, Oheneba Boachie-Adjei, Eduardo Beauchamp, Andrew Bowey, Kwadwo Yankey, Antony Field, Younas Shiraz, Vijay Ravindra, Timothy Borden, Raphael Vialle, Hamdi Sukkarieh, Munish Gupta, Matthew Newton Ede, Greg Mundis, Kenny Kwan, Daniel Couture, Jose Miguel Sanchez Marquez, Jason Howard, Bill Warner, Viral Jain, Alexa Karkenny, Norman Ramirez, Firoz Miyanji, Terry Jianguo Zhang, Olivier Chemaly, William Phillips, Elizabeth Kabara, Peter Gabos, Alejandro Peiro Garcia, Dennis Devito, Frank Gerow, Paul Koljonen, John Thometz, Selina Poon, AbdelHafez Amr, Robert Bernstein, David Marks, Subaraman Ramchandran, Kenneth Cheung, Toba Niazi, Tyler Christman, Joshua Speirs, Stephen Albanese, Katie Fehnel, Josh Holt, Rebecca Burke, Aaron Buckland, Joel Turtle, Darryl Lau, Hai Le, Christina Sayama, Vidyadhar Upasani, William Lavelle, Gunnar Tysklind, Jeffrey Campbell, David Bennett, Patrick Carry, Hiroko Matsumoto, Gregory Redding, Oscar Mayer, Carl-Eric Aubin, Kevin Smit, Michelle Welborn, Michael Glotzbecker, Christina Hardesty, David Skaggs, Stephanie Ihnow, Kenneth Illingworth, Lorena Floccari, Richard Anderson, Klane White, Lindsay Andras, Amer Samdani, Michael Heffernan, Joshua Murphy, Laurel Blakemore, Juan Rodriguez-Olaverri, Amy McIntosh, Walter Truong, Brandon Ramo, Josh Pahys, Megan Johnson, Jack Flynn, Allen Kadado, Brett Lullo, Ron El-Hawary, A. Noelle Larson, Michael Vitale, Lawrence Haber, Benjamin Roye, Jason Anari, John Vorhies, Jonathan Martin, Ryan Fitzgerald, Matthew Oetgen, Jaysson Brooks, Sumeet Garg, Behrooz A. Akbarnia, Stuart Mitchell, Robert Murphy, Matthew Landrum, Ilkka Helenius, Paul Sponseller, Todd Ritzman, Ying Li, Burt Yaszay, Scott Luhmann, Jaime Gomez, Ishaan Swarup, Grant Hogue, Dominick Tuason, Pat Cahill, Jeffrey Sawyer.
Footnotes
Supplementary material related to this article can be found at https://doi.org/10.1016/j.jposna.2025.100313.
Contributor Information
R. Carter Clement, Email: carter.clement@gmail.com.
Pediatric Spine Study Group:
David Bauer, Blake Montgomery, Anthony Catanzano, Carter Clement, Jean Ouellet, Stuart Weinstein, Craig Louer, Anand Segar, Suken Shah, Kevin Morash, Aaron Shaw, Judson Karlen, Michael Hughes, Otis Shirley, Andrew Jea, Nichola Wilson, Margaret Baldwin, Moyo Kruyt, Kenzo Cotton, Keith Orland, Lauren Torrey, Jennifer Holmes, Rolando Figueroa Roberto, Bruno Braga, Paul Rushton, Eric Huang, Sarah Southon Hryniuk, David Lebel, Stephen Plachta, Keith Baldwin, Louis Bezuidenhout, Edwin Kulubya, Andrea Simmonds, Taemin Oh, Carl St. Remy, Laura Meyer, Jeffrey Henstenburg, Smitha Mathew, Lukas Keil, Kenneth Noonan, Kyle Stampe, Kevin Lim, Luke Drake, Andy Stadler, Omar Iqbal, Arun Hariharan, John Dahl, Graham Shea, Karim Kantar, Stacy Ng, Karl Balsara, Tuo Peter Li, Dmitri Falkner, David Lazarus, Susana Nunez Pereira, Robert Lark, Tenner Guillaume, Steven Hwang, Joshua Klatt, Yehia El-Bromboly, James Sanders, Chris Bonfield, Daniel Miller, Jason Cheung, Mark Erickson, Felix Brassard, Tomoko Tanaka, Kyle Miller, Craig Birch, John Ghazi, Jessica McQuerry, Tyler Tetreault, Ferran Pellise, Karl Rathjen, Mohammed Alshareef, Michal Szczodry, Haemish Crawford, Michael Schmitz, Stefan Parent, Purnendu Gupta, Jacob Schulz, Susan Nelson, Rajiv Iyer, Nigel Price, Joseph Perra, Michael Kelly, Daniel Hedequist, Brian Kelly, Dan Sucato, Jochen Son-Hing, David Bumpass, Sara Van Nortwick, Jorge Fabregas, Mark Camp, Alvin Crawford, Lawrence Karlin, Gokhan Demirkiran, René Castelein, John Emans, Richard McCarthy, David Roye, Douglas Brockmeyer, Peter Sturm, George Thompson, Noriaki Kawakami, Randy Betz, Muharrem Yazici, Francisco Perez-Grueso, John Smith, Charles Johnston, Cynthia Nguyen, Jeffrey Martus, Jean-Marc Mac Thiong, Peter Newton, Raymond Knapp, Lionel Metz, Mohamed Esawy, Richard Schwend, Bryan Menapace, Lawrence Lenke, Benny Dahl, Michelle Carid, Brett Shannon, Laura Bellaire, John Anderson, Lindsay Crawford, Francesco Mangano, David Gonda, Thomas Errico, Shannon Kelly, Nan Wu, Brian Snyder, Alejandro Jose Marquez-Lara, Jose Herrera, Kim Hammerberg, Derek Kelly, Aki Puryear, Mari Groves, Arvindera Ghag, Erin MacKintosh, Edward Ahn, Hubert Labelle, Danielle Katz, David Wrubel, Harry Akoto, Mohammad Diab, David Harter, Sean Lew, Rober Cho, Stuart Mackenzie, Nancy Miller, Luis Rodriguez, Steve Richards, Christopher Reilly, Dan Drake, Stephen George, Timothy Skalak, Mundluru Surya, Andrew Tice, Tim Hresko, Shengru Wang, Scott Yang, Joe Stone, Morgan Jones, Daniel Bouton, Jennifer Bauer, Benjamin Martin, William Accousti, Jwalant Mehta, Oheneba Boachie-Adjei, Eduardo Beauchamp, Andrew Bowey, Kwadwo Yankey, Antony Field, Younas Shiraz, Vijay Ravindra, Timothy Borden, Raphael Vialle, Hamdi Sukkarieh, Munish Gupta, Matthew Newton Ede, Greg Mundis, Kenny Kwan, Daniel Couture, Jose Miguel Sanchez Marquez, Jason Howard, Bill Warner, Viral Jain, Alexa Karkenny, Norman Ramirez, Firoz Miyanji, Terry Jianguo Zhang, Olivier Chemaly, William Phillips, Elizabeth Kabara, Peter Gabos, Alejandro Peiro Garcia, Dennis Devito, Frank Gerow, Paul Koljonen, John Thometz, Selina Poon, AbdelHafez Amr, Robert Bernstein, David Marks, Subaraman Ramchandran, Kenneth Cheung, Toba Niazi, Tyler Christman, Joshua Speirs, Stephen Albanese, Katie Fehnel, Josh Holt, Rebecca Burke, Aaron Buckland, Joel Turtle, Darryl Lau, Hai Le, Christina Sayama, Vidyadhar Upasani, William Lavelle, Gunnar Tysklind, Jeffrey Campbell, David Bennett, Patrick Carry, Hiroko Matsumoto, Gregory Redding, Oscar Mayer, Carl-Eric Aubin, Kevin Smit, Michelle Welborn, Michael Glotzbecker, Christina Hardesty, David Skaggs, Stephanie Ihnow, Kenneth Illingworth, Lorena Floccari, Richard Anderson, Klane White, Lindsay Andras, Amer Samdani, Michael Heffernan, Joshua Murphy, Laurel Blakemore, Juan Rodriguez-Olaverri, Amy McIntosh, Walter Truong, Brandon Ramo, Josh Pahys, Megan Johnson, Jack Flynn, Allen Kadado, Brett Lullo, Ron El-Hawary, A.Noelle Larson, Michael Vitale, Lawrence Haber, Benjamin Roye, Jason Anari, John Vorhies, Jonathan Martin, Ryan Fitzgerald, Matthew Oetgen, Jaysson Brooks, Sumeet Garg, Behrooz A. Akbarnia, Stuart Mitchell, Robert Murphy, Matthew Landrum, Ilkka Helenius, Paul Sponseller, Todd Ritzman, Ying Li, Burt Yaszay, Scott Luhmann, Jaime Gomez, Ishaan Swarup, Grant Hogue, Dominick Tuason, Pat Cahill, and Jeffrey Sawyer
Supplementary material
The following are the Supplementary data to this article:
Dr. Erickson demonstrates the use of a robotic system for pedicle screw insertion.
Dr. Hardesty demonstrates the use of a 3D-printed drill guide to place markers for pedicle screws.
Dr. Carter Clement demonstrates the use of stereotactic navigation with fiducial screws for pedicle screw insertion during a T9-L2 posterior spinal fusion.
Dr. Skaggs demonstrates how to pulse the drill to prevent skiving.
Dr. Anari's workflow for a Lenke Type 1B curve using stereotactic navigation.
Dr. Brooks' workflow for a Lenke Type 1B curve using machine-vision navigation.
Dr. Skaggs' workflow for a simple spondylolysis with robotic assistance.
Dr. Hardesty's workflow for a neuromuscular T2 to pelvis using 3D-printed drill guides.
Dr. Jaysson Brooks explains how low-dose CT can reduce radiation exposure for the patient.
Dr. Jaysson Brooks discusses how surgeon preservation pushed him to try using machine-vision navigation.
Dr. Mark Erickson discusses the importance of minimizing motion during the use of robotic systems.
Dr. Skaggs and Dr. Hardesty discuss how to retain haptic feedback while using ETs.
Dr. Hardesty notes how the advent of ETs has increased her comfort level with complex cases.
Dr. Erickson explains how he became interested in ETs after practicing for over 20 years with freehand.
Dr. Erickson discusses his learning curve with robotic systems and how achieving proficiency improved his workflow.
Dr. Anari shares how the use of ETs has helped his comfort level with teaching early trainees.
Dr. Hardesty discusses the importance of teaching freehand technique to trainees and maintaining her own freehand skills.
Dr. Erickson discusses how he uses robotics as a teaching tool, but is always monitoring and adjusting his trainees.
References
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Associated Data
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Supplementary Materials
Dr. Erickson demonstrates the use of a robotic system for pedicle screw insertion.
Dr. Hardesty demonstrates the use of a 3D-printed drill guide to place markers for pedicle screws.
Dr. Carter Clement demonstrates the use of stereotactic navigation with fiducial screws for pedicle screw insertion during a T9-L2 posterior spinal fusion.
Dr. Skaggs demonstrates how to pulse the drill to prevent skiving.
Dr. Anari's workflow for a Lenke Type 1B curve using stereotactic navigation.
Dr. Brooks' workflow for a Lenke Type 1B curve using machine-vision navigation.
Dr. Skaggs' workflow for a simple spondylolysis with robotic assistance.
Dr. Hardesty's workflow for a neuromuscular T2 to pelvis using 3D-printed drill guides.
Dr. Jaysson Brooks explains how low-dose CT can reduce radiation exposure for the patient.
Dr. Jaysson Brooks discusses how surgeon preservation pushed him to try using machine-vision navigation.
Dr. Mark Erickson discusses the importance of minimizing motion during the use of robotic systems.
Dr. Skaggs and Dr. Hardesty discuss how to retain haptic feedback while using ETs.
Dr. Hardesty notes how the advent of ETs has increased her comfort level with complex cases.
Dr. Erickson explains how he became interested in ETs after practicing for over 20 years with freehand.
Dr. Erickson discusses his learning curve with robotic systems and how achieving proficiency improved his workflow.
Dr. Anari shares how the use of ETs has helped his comfort level with teaching early trainees.
Dr. Hardesty discusses the importance of teaching freehand technique to trainees and maintaining her own freehand skills.
Dr. Erickson discusses how he uses robotics as a teaching tool, but is always monitoring and adjusting his trainees.