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Applications of Artificial Intelligence and Machine Learning in Spine MRI.

Aric Lee1, Wilson Ong1, Andrew Makmur1,2

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Artificial intelligence (AI) and machine learning (ML) are enhancing spine MRI diagnostics, improving image acquisition, analysis, and patient care. Future research should focus on foundation models and real-world clinical implementation.

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Area of Science:

  • Radiology and Medical Imaging
  • Artificial Intelligence in Medicine
  • Machine Learning Applications

Background:

  • Diagnostic imaging, especially Magnetic Resonance Imaging (MRI), is crucial for assessing spine pathologies.
  • Advancements in artificial intelligence (AI) and machine learning (ML) offer new applications in spine MRI.

Purpose of the Study:

  • To review and examine the current applications of AI and ML in spine MRI.
  • To identify key research themes, gaps, and future directions in this field.

Main Methods:

  • A systematic literature search was performed across major databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) following PRISMA guidelines.
  • 50 studies were selected from 1226 initial results for data extraction and thematic categorization.
  • Studies were categorized into Image Acquisition and Processing, Segmentation, Diagnosis and Treatment Planning, and Patient Selection and Prognostication.

Main Results:

  • AI demonstrates significant potential to improve various aspects of spine MRI, including image acquisition, processing, segmentation, and diagnostic capabilities.
  • Current research highlights AI's role in diagnosis, treatment planning, patient selection, and prognostication.
  • Thematic analysis revealed key areas of AI application and development within spine MRI.

Conclusions:

  • AI and ML are poised to revolutionize spine MRI by enhancing efficiency and accuracy across the clinical workflow.
  • Future research should prioritize foundation models, large-language models, and real-world clinical validation to address generalizability and implementation challenges.
  • Collaborative efforts are essential to maximize the benefits of AI in spine MRI for improved patient outcomes.