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Related Experiment Video

Updated: Feb 17, 2026

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An Evaluation of Lumbar Foraminal Stenosis Radiologic Grading Systems: A Systematic Review.

Laura C M Ndjonko1, Nikol N Kralimarkova2, Yashoswini Chakraborty1

  • 1Northwestern University, Evanston, Illinois, USA.

Spine Surgery and Related Research
|February 16, 2026
PubMed
Summary

The Lee et al. grading system is the most frequently used for lumbar foraminal stenosis (LFS). While reliable, its correlation with clinical symptoms requires further investigation, with AI showing future promise.

Keywords:
Lee et al.cross-sectional imaginggrading systemslumbar foraminal stenosissystematic review

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Area of Science:

  • Neurosurgery
  • Radiology
  • Orthopedic Surgery

Background:

  • Symptomatic lumbar foraminal stenosis (LFS) involves neuroforamen narrowing, compressing spinal nerves and causing radicular pain.
  • Current diagnostic imaging lacks a consensus grading system for LFS, leading to inconsistent patient care.
  • This review evaluates LFS grading systems to identify the most utilized and effective methods for assessing anatomical severity and clinical correlation.

Purpose of the Study:

  • To systematically review and compare existing grading systems for lumbar foraminal stenosis (LFS).
  • To identify the most frequently used LFS grading systems in published literature.
  • To determine the most effective and reliable LFS grading system for correlating anatomical severity with clinical symptoms.

Main Methods:

  • Systematic review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
  • Comprehensive literature search of PubMed, Embase, and Cochrane Trials up to July 2024.
  • Narrative and descriptive synthesis of data from 35 eligible studies, including bias assessment.

Main Results:

  • Magnetic resonance imaging (MRI) was the primary modality (88.6%) across 35 reviewed studies.
  • Seven LFS grading systems were identified; the Lee et al. system was most common (69%), followed by Wildermuth et al. (14.3%).
  • Artificial intelligence (AI) grading systems were noted in two studies (5.7%), with mixed findings on symptom correlation.

Conclusions:

  • The Lee et al. grading system is the most established and reliable for LFS evaluation in current literature.
  • While some studies suggest a link between the Lee et al. system and clinical outcomes, this association needs further validation.
  • Emerging AI technologies hold potential for enhancing the diagnostic accuracy and clinical applicability of LFS grading systems.