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Radiomics in Spine Surgery.

Daniel Alsoof1, Christopher L McDonald1, Wesley M Durand2

  • 1Department of Orthopedic Surgery, Alpert Medical School of Brown University, Providence, RI, USA.

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|May 16, 2023
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This summary is machine-generated.

Radiomics, the analysis of medical images for hidden quantitative data, shows promise in spine surgery applications like deformity and osteoporosis. This review covers radiomic principles, spine literature, and current limitations.

Keywords:
artificial intelligencemachine learningradiomicsspine

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Area of Science:

  • Quantitative medical imaging analysis
  • Computational pathology
  • Biomedical data science

Background:

  • Radiomics extracts quantitative imaging features beyond human visual perception.
  • These features can be integrated with clinical and genomic data.
  • Machine learning and statistical methods are used for prediction models.

Purpose of the Study:

  • To review the fundamental principles of radiomic analysis.
  • To summarize current literature on radiomics in spine surgery.
  • To discuss the limitations of radiomic approaches in this field.

Main Methods:

  • Review of existing literature on radiomics and spine surgery.
  • Analysis of radiomic principles and applications.
  • Identification of research gaps and limitations.

Main Results:

  • Radiomics is applicable to spinal deformity, oncology, and osteoporosis detection.
  • Integration of radiomic features with clinical and genomic data enhances predictive models.
  • Significant research is emerging in spine surgery applications.

Conclusions:

  • Radiomics offers a novel quantitative approach to spine imaging analysis.
  • Further research is needed to overcome limitations and fully realize its potential in spine surgery.
  • This technique holds promise for improving diagnosis and treatment planning.