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      KCI등재 SCIE SCOPUS

      Emerging Technologies in the Treatment of Adult Spinal Deformity

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      https://www.riss.kr/link?id=A107863045

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      다국어 초록 (Multilingual Abstract)

      Outcomes for adult spinal deformity continue to improve as new technologies become integrated into clinical practice. Machine learning, robot-guided spinal surgery, and patient-specific rods are tools that are being used to improve preoperative planning and patient satisfaction. Machine learning can be used to predict complications, readmissions, and generate postoperative radiographs which can be shown to patients to guide discussions about surgery. Robot-guided spinal surgery is a rapidly growing field showing signs of greater accuracy in screw placement during surgery. Patient-specific rods offer improved outcomes through higher correction rates and decreased rates of rod breakage while decreasing operative time. The objective of this review is to evaluate trends in the literature about machine learning, robot-guided spinal surgery, and patient-specific rods in the treatment of adult spinal deformity.
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      Outcomes for adult spinal deformity continue to improve as new technologies become integrated into clinical practice. Machine learning, robot-guided spinal surgery, and patient-specific rods are tools that are being used to improve preoperative planni...

      Outcomes for adult spinal deformity continue to improve as new technologies become integrated into clinical practice. Machine learning, robot-guided spinal surgery, and patient-specific rods are tools that are being used to improve preoperative planning and patient satisfaction. Machine learning can be used to predict complications, readmissions, and generate postoperative radiographs which can be shown to patients to guide discussions about surgery. Robot-guided spinal surgery is a rapidly growing field showing signs of greater accuracy in screw placement during surgery. Patient-specific rods offer improved outcomes through higher correction rates and decreased rates of rod breakage while decreasing operative time. The objective of this review is to evaluate trends in the literature about machine learning, robot-guided spinal surgery, and patient-specific rods in the treatment of adult spinal deformity.

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      참고문헌 (Reference)

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      3 Sadrameli SS, "Utility of patientspecific rod instrumentation in deformity correction: singleinstitution experience" 4 : 256-260, 2020

      4 Ehlers AP, "Use of patient-reported outcomes and satisfaction for quality assessments" 23 : 618-622, 2017

      5 Fiere V, "UNID Patient-Specific Rods show a reduction in rod breakage incidence" MEDICREA USA Corp 2017

      6 Smith JS, "Treatment of adult thoracolumbar spinal deformity: past, present, and future" 30 : 551-567, 2019

      7 Chang M, "The role of machine learning in spine surgery: the future is now" 7 : 54-, 2020

      8 Li J, "The impact of robot-assisted spine surgeries on clinical outcomes: a systemic review and metaanalysis" 16 : 1-14, 2020

      9 Shillingford JN, "The free-hand technique for S2-Alar-Iliac screw placement: a safe and effective method for sacropelvic fixation in adult spinal deformity" 100 : 334-342, 2018

      10 Terran J, "The SRS-Schwab adult spinal deformity classification: assessment and clinical correlations based on a prospective operative and nonoperative cohort." 73 : 559-568, 2013

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      2 Hu X, "What is the learning curve for robotic-assisted pedicle screw placement in spine surgery" 472 : 839-844, 2014

      3 Sadrameli SS, "Utility of patientspecific rod instrumentation in deformity correction: singleinstitution experience" 4 : 256-260, 2020

      4 Ehlers AP, "Use of patient-reported outcomes and satisfaction for quality assessments" 23 : 618-622, 2017

      5 Fiere V, "UNID Patient-Specific Rods show a reduction in rod breakage incidence" MEDICREA USA Corp 2017

      6 Smith JS, "Treatment of adult thoracolumbar spinal deformity: past, present, and future" 30 : 551-567, 2019

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      21 Bederman SS, "Robotic guidance for S2-Alar-Iliac screws in spinal deformity correction" 30 : E49-E53, 2017

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      23 Chen X, "Robot-assisted orthopedic surgery in the treatment of adult degenerative scoliosis: a preliminary clinical report" 15 : 282-, 2020

      24 Gao S, "Robot-assisted and conventional freehand pedicle screw placement: a systematic review and meta-analysis of randomized controlled trials" 27 : 921-930, 2018

      25 Barton C, "Risk factors for rod fracture after posterior correction of adult spinal deformity with osteotomy: a retrospective case-series" 10 : 30-, 2015

      26 Archavlis E, "Rates of upper facet joint violation in minimally invasive percutaneous and open instrumentation: a comparative cohort study of different insertion techniques" 79 : 1-8, 2018

      27 Le XF, "Rate and risk factors of superior facet joint violation during cortical bone trajectory screw placement: a comparison of robot-assisted approach with a conventional technique" 12 : 133-140, 2020

      28 Branche K, "Radius of curvature in patient-specific short rod constructs versus standard pre-bent rods" 14 : 944-948, 2020

      29 Fan Y, "Radiological and clinical differences among three assisted technologies in pedicle screw fixation of adult degenerative scoliosis" 8 : 890-, 2018

      30 Moal B, "Radiographic outcomes of adult spinal deformity correction: a critical analysis of variability and failures across deformity patterns" 2 : 219-225, 2014

      31 박상민, "Radiographic and Clinical Outcomes of Robot-Assisted Posterior Pedicle Screw Fixation: Two-Year Results from a Randomized Controlled Trial" 연세대학교의과대학 59 (59): 438-444, 2018

      32 Safaee MM, "Predictive modeling of length of hospital stay following adult spinal deformity correction: analysis of 653 patients with an accuracy of 75% within 2 days" 115 : e422-e427, 2018

      33 Lafage R, "Predictive model for selection of upper treated vertebra using a machine learning approach" 146 : e225-e232, 2021

      34 Langella F, "Predictive accuracy of surgimap surgical planning for sagittal imbalance: a cohort study" 42 : E1297-E1304, 2017

      35 Kim JS, "Predicting surgical complications in patients undergoing elective adult spinal deformity procedures using machine learning" 6 : 762-770, 2018

      36 White HJ, "Predicting patient-centered outcomes from spine surgery using risk assessment tools: a systematic review" 13 : 247-263, 2020

      37 Sharma A, "Predicting clinical outcomes following surgical correction of adult spinal deformity" 84 : 733-740, 2019

      38 Passias PG, "Pre-operative planning and rod customization may optimize post-operative alignment and mitigate development of malalignment in multisegment posterior cervical decompression and fusion patients" 59 : 248-253, 2019

      39 Blondel B, "Posterior global malalignment after osteotomy for sagittal plane deformity: it happens and here is why" 38 : E394-, 2013

      40 Schizas C, "Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy" 78 : 240-245, 2012

      41 Tian W, "Pedicle screw insertion in spine: a randomized comparison study of robot-assisted surgery and fluoroscopy-guided techniques" 1 : 4-10, 2016

      42 Prost S, "Patient-specific’ rods in the management of adult spinal deformity. One-year radiographic results of a prospective study about 86 patients" 66 : 162-167, 2020

      43 Solla F, "Patient-specific rods for thoracic kyphosis correction in adolescent idiopathic scoliosis surgery: preliminary results" 106 : 159-165, 2020

      44 Solla F, "Patient-specific rods for surgical correction of sagittal imbalance in adults: technical aspects and preliminary results" 32 : 80-86, 2019

      45 Overley SC, "Navigation and robotics in spinal surgery: where are we now?" 80 : S86-S99, 2017

      46 Lehner K, "Narrative review of predictive analytics of patient-reported outcomes in adult spinal deformity surgery" 11 : 89S-95S, 2021

      47 Kim HJ, "Monitoring the quality of robot-assisted pedicle screw fixation in the lumbar spine by using a cumulative summation test" 40 : 87-94, 2015

      48 Zhu F, "Misplacement pattern of pedicle screws in pediatric patients with spinal deformity: a computed tomography study" 27 : 431-435, 2014

      49 Sukovich W, "Miniature robotic guidance for pedicle screw placement in posterior spinal fusion: early clinical experience with the SpineAssist" 2 : 114-122, 2006

      50 Martini ML, "Machine learning with feature domains elucidates candidate drivers of hospital readmission following spine surgery in a large singlecenter patient cohort" 87 : E500-E510, 2020

      51 Sidey-Gibbons JAM, "Machine learning in medicine: a practical introduction" 19 : 64-, 2019

      52 Kleck CJ, "Long-term treatment effect and predictability of spinopelvic alignment after surgical correction of adult spine deformity with patient-specific spine rods" 45 : E387-, 2020

      53 Gonzalez D, "Initial intraoperative experience with robotic-assisted pedicle screw placement with stealth navigation in pediatric spine deformity: an evaluation of the first 40 cases" 2020

      54 Fiani B, "Impact of robot-assisted spine surgery on health care quality and neurosurgical economics: a systemic review" 43 : 17-25, 2020

      55 Kochanski RB, "Image-guided navigation and robotics in spine surgery" 84 : 1179-1189, 2019

      56 Galbusera F, "Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach" 28 : 951-960, 2019

      57 Mancuso CA, "Fulfillment of patients’ expectations of lumbar and cervical spine surgery" 1167-1174, 2016

      58 Keric N, "Evaluation of surgical strategy of conventional vs. percutaneous robot-assisted spinal trans-pedicular instrumentation in spondylodiscitis" 11 : 17-25, 2017

      59 Safaee MM, "Epidemiology and socioeconomic trends in adult spinal deformity care" 87 : 25-32, 2020

      60 Barton C, "Early experience and initial outcomes with patient-specific spine rods for adult spinal deformity" 39 : 79-86, 2016

      61 Edström E, "Does augmented reality navigation increase pedicle screw density compared to free-hand technique in deformity surgery? Single surgeon case series of 44 patients" 45 : E1085-E1090, 2020

      62 Ames CP, "Development of deployable predictive models for minimal clinically important difference achievement across the commonly used health-related quality of life instruments in adult spinal deformity surgery" 44 : 1144-1153,

      63 Schwartz JT, "Deep learning automates measurement of spinopelvic parameters on lateral lumbar radiographs" 45 : E671-E678, 2021

      64 Raman T, "Decision tree-based modelling for identification of predictors of blood loss and transfusion requirement after adult spinal deformity surgery" 14 : 87-95, 2020

      65 Chae DS, "Decentralized convolutional neural network for evaluating spinal deformity with spinopelvic parameters" 197 : 105699-, 2020

      66 Alvarado AM, "Cost-effectiveness of adult spinal deformity surgery" 11 : 73S-78S, 2021

      67 Zhou LP, "Comparison of cranial facet joint violation rate and four other clinical indexes between robot-assisted and freehand pedicle screw placement in spine surgery: a meta-analysis" 45 : E1532-E1540, 2020

      68 Devito DP, "Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study" 35 : 2109-2115, 2010

      69 Lee NJ, "Can machine learning accurately predict postoperative compensation for the uninstrumented thoracic spine and pelvis after fusion from the lower thoracic spine to the sacrum?" 8 : 2020

      70 Sardjono TA, "Automatic Cobb angle determination from radiographic images" 38 : E1256-E1262, 2013

      71 Cho BH, "Automated measurement of lumbar lordosis on radiographs using machine learning and computer vision" 10 : 611-618, 2020

      72 Rasouli JJ, "Artificial intelligence and robotics in spine surgery" 11 : 556-564, 2021

      73 John T. Schwartz, "Applications of Machine Learning Using Electronic Medical Records in Spine Surgery" 대한척추신경외과학회 16 (16): 643-653, 2019

      74 Ames CP, "Adult spinal deformity:epidemiology, health impact, evaluation, and management" 4 : 310-322, 2016

      75 Diebo BG, "Adult spinal deformity" 394 : 160-172, 2019

      76 Prost S, "Adult spinal deformities:can patient-specific rods change the preoperative planning into clinical reality? Feasibility study and preliminary results about 77 cases" 2020 : 6120580-, 2020

      77 Ringel F, "Accuracy of robot-assisted placement of lumbar and sacral pedicle screws: a prospective randomized comparison to conventional freehand screw implantation" 37 : E496-E501, 2012

      78 Macke JJ, "Accuracy of robot-assisted pedicle screw placement for adolescent idiopathic scoliosis in the pediatric population" 10 : 145-150, 2016

      79 . Shaw KA, "Accuracy of robot-assisted pedicle screw insertion in adolescent idiopathic scoliosis: is triggered electromyographic pedicle screw stimulation necessary" 4 : 187-194, 2018

      80 Fan Y, "Accuracy of pedicle screw placement comparing robot-assisted technology and the free-hand with fluoroscopy-guided method in spine surgery: an updated meta-analysis" 97 : e10970-, 2018

      81 Li HM, "Accuracy of pedicle screw placement and clinical outcomes of robot-assisted technique versus conventional freehand technique in spine surgery from nine randomized controlled trials: a meta-analysis" 45 : E111-E119, 2020

      82 Parker SL, "Accuracy of free-hand pedicle screws in the thoracic and lumbar spine: analysis of 6816 consecutive screws" 68 : 170-178, 2011

      83 Perdomo-Pantoja A, "Accuracy of current techniques for placement of pedicle screws in the spine: a comprehensive systematic review and meta-analysis of 51,161 screws" 126 : 664-678.e3, 2019

      84 Kim HJ, "A prospective, randomized, controlled trial of robot-assisted vs freehand pedicle screw fixation in spine surgery" 13 (13): 2017

      85 Korez R, "A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation" 29 : 2295-2305, 2020

      86 Wallace N, "3D-printed patientspecific spine implants: a systematic review" 33 : 400-407, 2020

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