AI in Spine Imaging: Review of Novel Diagnostic Technologies for Intervertebral Disc Disease

AI-integrated imaging (X-ray, CT, MRI) improves diagnosis of intervertebral disc disorders, but current models face limitations from small sample sizes and variable performance; multi-modal fusion and end-to-end workflows offer future promise, according to a narrative review.

• Narrative review summarizing machine learning and deep learning applications across X-ray, CT, and MRI for spine imaging.
• Key challenges highlighted: limited sample size and quality, as well as model performance issues; no external validation data pooled.
• Future directions include multi-modal data fusion and end-to-end diagnostic workflows to facilitate clinical translation.

RadPigeon summaries are original and for information only. They are not clinical advice.