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Research ArticleLumbar Spine

Top 25 Most-Cited Articles on Robotic-Assisted Lumbar Spine Surgery

Andy Ton, Nicole Hang, William Liu, Ryan Liu, Patrick C. Hsieh, Jeffrey C. Wang, Raymond J. Hah and Ram K. Alluri
International Journal of Spine Surgery February 2024, 18 (1) 37-46; DOI: https://doi.org/10.14444/8565
Andy Ton
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
BS
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  • For correspondence: andyton@usc.edu
Nicole Hang
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
BA
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William Liu
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
BS
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Ryan Liu
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
BS
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Patrick C. Hsieh
2 Department of Neurological Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
MD
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Jeffrey C. Wang
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
MD
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Raymond J. Hah
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
MD
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Ram K. Alluri
1 Department of Orthopedic Surgery, Keck School of Medicine at The University of Southern California, Los Angeles, CA, USA
MD
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    Figure 1

    Flowchart diagram outlining the systematic review process used to identify the top 25 most-cited articles.

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    Figure 2

    Annual publication trends in articles on robotic lumbar spine surgery from 2000 to 2022.

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    Figure 3

    Number of published articles by journal on robotic lumbar spine surgery from 2000 to 2022.

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    Table 1

    Top 25 most-cited articles on robotic-assisted lumbar spine surgery ranked hierarchically by cumulative number of citations.

    Author and Publication YearJournalSummary DescriptionTimes Cited (Total)Citations Per YearRobot System
    1. Kantelhardt et al (2011)10 European Spine JournalRetrospective cohort analysis of 112 consecutive patients demonstrating shorter intraoperative fluoroscopy time and increased screw accuracy within open robotic-assisted vs conventional open pedicle screw placement.22120SpineAssist
    2. Devito et al (2010)11 SpineRetrospective observational case series of 3271 pedicle screw and guide-wire insertions with SpineAssist guidance across 14 hospitals from June 2005 to June 2009, wherein clinical acceptance and accuracy were assessed and compared with freehand techniques as reported by the literature.21518SpineAssist
    3. Hyun et al (2017)12 SpineRandomized clinical trial of 60 patients showing significantly reduced fluoroscopy exposure and length of stay in patients undergoing single- and two-level robotic-guided lumbar fusion relative to conventional fluoroscopic guidance.14830Renaissance
    4. Schatlo et al (2014)13 Journal of Neurosurgery: SpineRetrospective cohort analysis of 95 consecutive patients with degenerative lumbar pathologies showing comparable surgical time, length of stay, and screw placement accuracy in robotic-assisted vs fluoroscopy.13016SpineAssist
    5. Kim et al (2017)14 International Journal of Medical Robotics and Computer-Assisted SurgeryRandomized controlled trial of 78 patients with lumbar spinal stenosis showing superior outcomes with respect to facet joint violation and convergence orientation with robotic-assisted PLIF vs conventional freehand techniques.12224Renaissance
    6. Lieberman et al (2006)15 NeurosurgeryObservational cadaveric case study substantiating screw placement accuracy with SpineAssist when comparing actual screw and planned screw trajectories on postprocedure computed tomography.1208SpineAssist
    7. Pechlivanis et al (2009)16 SpineProspective observational case series of 31 patients validating accuracy of pedicle screw placement in patients undergoing PLIF with percutaneous posterior pedicle screw insertion using passive guidance provided by a bone-mounted miniature robotic device (SpineAssist).1189SpineAssist
    8. Lonjon et al (2016)4 European Spine JournalProspective 1:1 matched-cohort analysis of 20 consecutive patients reporting higher screw placement precision using robotic-assistance (ROSA) over freehand techniques.11119ROSA
    9. van Dijk et al (2015)17 SpineRetrospective case series of 112 consecutive patients undergoing PLIFs with SpineAssist demonstrating accurate screw placement, wherein intraoperative screw placement was consistent with preoperative plan.9213SpineAssist
    10. Lieberman et al (2012)18 Journal of Spinal Disorders and TechniquesProspective cohort analysis of 12 cadavers across 17 surgeons showing decreased radiation exposure, fluoroscopy time per screw, procedure time, screw placement deviation, and pedicle wall breaches while maintaining increased accuracy of percutaneous pedicle screw placement with the use of the SpineAssist system compared with freehand techniques.919SpineAssist
    11. Keric et al (2017)19 Neurosurgical FocusRetrospective case series of 413 patients who underwent spinal screw implantation with Renaissance showing high reliability and accuracy in screw placement with lower peri- and early postoperative complications relative to other percutaneous screw placement techniques across the literature.8116Renaissance
    12. Barzilay et al (2006)20 International Journal of Medical Robotics and Computer-Assisted SurgeryProspective case series of 15 patients who underwent robot-assisted lumbar spine fusion with the SpineAssist system which identified technical and clinical variables contributing to difficult cases.775SpineAssist
    13. Lefranc et al (2016)21 Expert Review of Medical DevicesTechnical review outlining surgical technique, indications for use, future directions, and advantages associated with use of the new ROSA robot in performing accurate pedicle screw placement and minimally invasive percutaneous surgical procedures.7312ROSA
    14. Khan et al (2019)5 Operative NeurosurgeryRetrospective case series of 20 patients who underwent robotically assisted pedicle screw insertion performed by a single surgeon with preliminary results showing 98.7% accuracy in 75 pedicle screw placements, reinforcing feasibility of robotic guidance in lumbar spine surgery.7124Mazor X
    15. Kim et al (2015)22 SpineProspective randomized controlled study that demonstrated similar quality of performance and accuracy as measured by a cumulative summation test in pedicle screw fixation in 20 patients who underwent robot-assisted MIS PLIF and 20 patients who underwent conventional open PLIF using freehand technique.6710Renaissance
    16. Schatlo et al (2015)23 Acta NeurochirurgicaRetrospective chart review of 258 patients requiring thoracic and/or lumbar spine surgery with posterior instrumentation showed that robot-assisted screw placement is safe with a 3.8% screw malposition rate.6710 TiRobot
    17. Gao et al (2018)24 European Spine JournalSystematic review and meta-analysis of 6 studies incorporating 158 patients (688 pedicle screws) in the robot-assisted group and 148 patients (672 pedicle screws) in the conventional freehand group demonstrated that both groups exhibited similar accuracy rate of pedicle screw implantation, but the robot-assisted technique was associated with longer operative time.6516 N/A (5 Mazor, 1 Tianji)
    18. Le et al (2018)6 World NeurosurgeryRetrospective matched-cohort study of 58 patients undergoing pedicle screw insertion through the cortical bone for lumbar fixation that demonstrated perfect trajectory for 87.2% of robotic-assisted screw insertion and 66.9% of conventional freehand screw instrumentation.5915Renaissance
    19. Urakov et al (2017)25 Neurosurgical FocusRetrospective review of prospectively collected data from 33 patients who underwent robot-assisted thoracolumbar pedicle instrumentation that showed no correlation regarding speed and accuracy of instrumentation between surgeon’s years of operative experience and commitment to spine surgery as their future speciality.4910Renaissance
    20. Li et al (2020)26 SpineMeta-analysis of 9 randomized controlled trials with 696 patients demonstrated that robot-assisted pedicle screw placement reduced radiation dose and decreased intraoperative radiation exposure time while showing greater accuracy compared with pedicle screw instrumentation by conventional freehand technique.4724TiRobot
    21. Schröder et al (2017)27 Neurosurgical FocusRetrospective cohort study of 72 patients who had undergone an MIS PLIF or MIS TLIF and completed a follow-up ≥12 months demonstrated that robot-guided screw trajectories are more accurate compared with trajectories established by freehand techniques which reduce rate of revision surgery for screw malposition and improve visual analog scale and Oswestry Disability Index scores.469Renaissance
    22. Fan et al (2017)28 Medical Science MonitorProspective cohort study of 890 pedicle screws placed in 190 patients for treatment of degenerative lumbar disease demonstrated that robot-assisted technique unsuccessfully showed significant differences for accuracy of pedicle screw insertion compared with freehand technique but greatly reduced blood loss, fluoroscopy time per screw, and postoperative stay.459SpineAssist
    23. Kuo et al (2016)29 PLoS ONERetrospective review of 64 patients who either underwent or did not undergo TLIF demonstrated that the Renaissance robotic system can accurately place pedicle screws, and secondary registration enhances accuracy by providing intraoperative evaluation of screw positioning.458Renaissance
    24. Tian et al (2020)30 NeurospineCase series of 62 thoracolumbar pedicle screws implanted in 12 patients using 5G telerobotic remote telecommunication showed the potential of utilizing telemedical service in the future.4020TiRobot
    25. Wolf et al (2001)31 SpineObservational case series of morphometric data using computed tomography of the lumbar spine of 55 patients who provided additional information on vertebrae geometry and its relation to entry points for screw insertion for spinal procedures.402N/A
    • Abbreviations: MIS, minimally invasive surgery; PLIF, posterior lumbar interbody fusion; TLIF, transforaminal lumbar interbody fusion.

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    Table 2

    Newcastle-Ottawa assessment scale of cohort studies within the top 25 most-cited articles ordered by citation ranking.

    StudyRepresentative of CohortsSelection of Nonexposed CohortAscertainment of ExposureOutcome of Interest Absent at Start of StudyCohort ComparabilityOutcome AssessmentSufficient Follow-upAdequacy of Follow-upTotal Score
    1. Kantelhardt et al (2011)10 ********8
    3. Hyun et al (2017)12 *********9
    4. Schatlo et al (2014)13 *********9
    5. Kim et al (2017)14 *********9
    8. Lonjon et al (2016)4 ***** ****9
    10. Lieberman et al (2012)18 --*--***4
    15. Kim et al (2015)22 ****-***7
    18. Le et al (2018)6 --******6
    19. Urakov et al (2017)25 --------0
    21. Schröder et al (2017)27 --------0
    22. Fan et al (2017)28 ****-***7
    • View popup
    Table 3

    Joanna Briggs Institute (JBI) critical appraisal tool assessments of case series within the top 25 most-cited articles ordered by citation ranking.

    JBI Assessment Categories2. Devito et al (2010)6. Lieberman et al (2006)7. Pechlivanis et al (2009)9. van Dijk et al (2015)11. Keric et al (2017)12. Barzilay et al (2006)14. Khan et al (2019)16. Schatlo et al (2015)23. Kuo et al (2016)24. Tian et al (2020)25. Wolf et al (2001)
    Clear inclusion criteriaNoNoYesYesYesNoYesYesYesNoNo
    Reliable data collectionNoYesNoYesYesNoYesYesYesNoNo
    Valid methodology for assessing outcomesYesYesYesYesYesNoYesYesYesNoNo
    Consecutive seriesYesNoYesYesYesYesYesYesYesNoNo
    Inclusion of all possible participants/casesNoNoYesNoYesYesYesYesYesNoYes
    Relevant demographics reportedYesNoYesYesYesYesNoNoYesYesYes
    Baseline clinical characteristics reportedNoNoNoNoYesYesNoNoYesNoNo
    Clear description of outcomesYesYesYesYesYesYesYesYesYesYesYes
    Study site/setting describedYesNoNoNoYesYesNoNoYesYesNo
    Appropriate statistical analysisYesYesYesYesYesNoYesYesYesYesYes
    Total Score (/10)6477106871043
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1 Feb 2024
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Top 25 Most-Cited Articles on Robotic-Assisted Lumbar Spine Surgery
Andy Ton, Nicole Hang, William Liu, Ryan Liu, Patrick C. Hsieh, Jeffrey C. Wang, Raymond J. Hah, Ram K. Alluri
International Journal of Spine Surgery Feb 2024, 18 (1) 37-46; DOI: 10.14444/8565

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Top 25 Most-Cited Articles on Robotic-Assisted Lumbar Spine Surgery
Andy Ton, Nicole Hang, William Liu, Ryan Liu, Patrick C. Hsieh, Jeffrey C. Wang, Raymond J. Hah, Ram K. Alluri
International Journal of Spine Surgery Feb 2024, 18 (1) 37-46; DOI: 10.14444/8565
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