[1]
Liu Y. Potential risk of intelligent technologies in clinical orthopedics. Adv Exp Med Biol 2018; 1093: 281-8.
[2]
Kyrölä KK, Salme J, Tuija J, Tero I, Eero K, Arja H. Intra- and interrater reliability of sagittal spinopelvic parameters on full-spine radiographs in adults with symptomatic spinal disorders. Neurospine 2018; 15(2): 175-81.
[3]
Khalsa AS, Mundis GM, Yagi M, et al. Variability in assessing spinopelvic parameters with lumbosacral transitional vertebrae: Inter- and intraobserver reliability among spine surgeons. Spine 2018; 43(12): 813-6.
[4]
Ferrero E, Mazda K, Simon A-L, Ilharreborde B. Preliminary experience with SpineEOS, a new software for 3D planning in AIS surgery. Eur Spine J 2018; 27(9): 2165-74.
[5]
Chen D, Chen C-H, Tang L, et al. Three-dimensional reconstructions in spine and screw trajectory simulation on 3D digital images: A step by step approach by using Mimics software. J Spine Surg Hong Kong 2017; 3(4): 650-6.
[6]
Ailon T, Scheer JK, Lafage V, et al. Adult spinal deformity surgeons are unable to accurately predict postoperative spinal alignment using clinical judgment alone. Spine Deform 2016; 4(4): 323-9.
[7]
Moal B, Schwab F, Ames CP, et al. Radiographic outcomes of adult spinal deformity correction: A critical analysis of variability and failures across deformity patterns. Spine Deform 2014; 2(3): 219-25.
[8]
Ricciardi L, Stifano V, Proietti L, et al. Intraoperative and postoperative
segmental lordosis mismatch: Analysis of 3 fusion techniques.
World Neurosurg 2018; e659-e663. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29709745
[9]
Langella F, Villafañe JH, Damilano M, et al. Predictive accuracy of surgimap surgical planning for sagittal imbalance: A cohort study. Spine 2017; 42(22): E1297-304.
[10]
Pijpker PAJ, Kuijlen JMA, Kraeima J, Faber C. Three-dimensional planning and use of individualized osteotomy-guiding templates for surgical correction of kyphoscoliosis: A technical case report. World Neurosurg 2018; 119: 113-7.
[11]
Thayaparan GK, Owbridge MG, Thompson RG, D’Urso PS. Designing patient-specific 3D printed devices for posterior atlantoaxial transarticular fixation surgery. J Clin Neurosci 2018; 56: 192-8.
[12]
Khan A, Meyers JE, Siasios I, Pollina J. Next-generation robotic spine surgery: First report on feasibility, safety, and learning curve. Oper Neurosurg (Hagerstown) 2018. Available from: https://www.ncbi.nlm.nih.gov/pubmed/30247684
[13]
Le X, Tian W, Shi Z, et al. Robot-assisted versus fluoroscopy-assisted cortical bone trajectory screw instrumentation in lumbar spinal surgery: A matched-cohort comparison. World Neurosurg 2018; 120: e745-51.
[14]
Staartjes VE, Klukowska AM, Schröder ML. Pedicle screw revision in robot-guided, navigated, and freehand thoracolumbar instrumentation: A systematic review and meta-analysis. World Neurosurg 2018; 116: 433-43.
[15]
Filograna L, Lenkowicz J, Cellini F, et al. Identification of the most significant magnetic resonance imaging (MRI) radiomic features in oncological patients with vertebral bone marrow metastatic disease: a feasibility study. Radiol Med 2019; 124(1): 50-7.
[16]
Chiewvit P, Danchaivijitr N, Sirivitmaitrie K, Chiewvit S, Thephamongkhol K. Does magnetic resonance imaging give value-added than bone scintigraphy in the detection of vertebral metastasis? J Med Assoc Thail Chotmaihet Thangphaet 2009; 92(6): 818-29.
[17]
Barchetti F, Stagnitti A, Megna V, et al. Unenhanced whole-body MRI versus PET-CT for the detection of prostate cancer metastases after primary treatment. Eur Rev Med Pharmacol Sci 2016; 20(18): 3770-6.
Article Metrics
35
7
1
1