Emerging technologies in the treatment of adult spinal deformity

Akshar V. Patel, Christopher A. White, John T. Schwartz, Nicholas L. Pitaro, Kush C. Shah, Sirjanhar Singh, Varun Arvind, Jun S. Kim, Samuel K. Cho

Research output: Contribution to journalReview articlepeer-review

13 Scopus citations

Abstract

Outcomes for adult spinal deformity continue to improve as new technologies become inte-grated 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 sat-isfaction. Machine learning can be used to predict complications, readmissions, and gener-ate 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.

Original languageEnglish
Pages (from-to)417-427
Number of pages11
JournalNeurospine
Volume18
Issue number3
DOIs
StatePublished - Sep 2021

Keywords

  • Artificial intelligence
  • Machine learning
  • Robot
  • Rods
  • Spine surgery

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