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Artificial Intelligence in Spine Imaging Interpretation.

Salvatore Gitto^1,2, Patrick Omoumi³, Domenico Albano^4,5

¹Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milan, Italy.

Seminars in Musculoskeletal Radiology

|April 14, 2026

Summary

This summary is machine-generated.

Artificial intelligence (AI) in spine imaging enhances diagnostic accuracy for spinal disorders. This review covers AI applications for fractures, deformities, and degenerative diseases, aiding radiologists in adopting new technologies.

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Area of Science:

Radiology and Medical Imaging
Artificial Intelligence in Medicine
Spinal Diagnostics

Background:

Spinal disorders are a major global cause of disability.
Imaging studies are crucial for assessing spinal conditions.
Current diagnostic workflows can be improved.

Purpose of the Study:

To review innovative artificial intelligence (AI) applications in spine imaging interpretation.
To focus on a pathology-based approach for AI in spinal diagnostics.
To provide an updated overview for musculoskeletal radiologists.

Main Methods:

Narrative review of artificial intelligence in spine imaging.
Focus on deep learning and conventional machine learning methods.
Pathology-based organization: vertebral fractures, spinal deformities, degenerative disease, skeletal tumors, inflammatory disorders, opportunistic screening.

Main Results:

AI demonstrates significant potential to improve diagnostic accuracy in spine imaging.
AI can enhance workflow efficiency for interpreting spinal pathologies.
Various AI applications exist across different spinal conditions.

Conclusions:

Artificial intelligence offers promising advancements for spine imaging interpretation.
Musculoskeletal radiologists can benefit from understanding AI applications for improved clinical adoption.
AI tools can assist in the efficient diagnosis of diverse spinal disorders.