MRI-Based Artificial Intelligence Prediction of Fluoroscopic C-Arm Angles for Lumbar Transforaminal Epidural Steroid Injections

NCT07875855 — Not yet recruiting, 80 participants, Marmara University

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MRI-Based Artificial Intelligence Prediction of Fluoroscopic C-Arm Angles for Lumbar Transforaminal Epidural Steroid Injections: A Prospective Accuracy Study

RegistryNCT07875855
StatusNot yet recruiting
Study typeObservational
Enrollment80 (Estimated)
SponsorMarmara University (Other)
ConditionsLumbar Radicular Pain, Artifical Intelligence
InterventionsAI based evaluation (Other)
Datesstart 2026-12-01 (estimated), primary completion 2027-05-01 (estimated), completion 2027-12-01 (estimated), first posted 2026-10-15, last updated 2026-10-15

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-Summary

This study aims to prospectively evaluate the accuracy of artificial intelligence (AI) in predicting fluoroscopic C-arm oblique and craniocaudal angles from pre-procedural lumbar magnetic resonance (MR) images for lumbar transforaminal epidural steroid injections (TFESI). The AI predictions will be compared to the final reference C-arm angles determined by an experienced operator during the procedure.

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+Detailed description

Lumbar transforaminal epidural steroid injection (TFESI) is an interventional pain treatment commonly used for lumbar radicular pain. It requires appropriate fluoroscopic visualization of the targeted nerve root and neural foramen to safely advance the needle. During the procedure, the fluoroscopic C-arm must be positioned at appropriate oblique and craniocaudal angles to optimally visualize the target anatomical structures. The required C-arm angles vary among patients due to individual anatomical features such as vertebra and pedicle morphology, facet joint structure, vertebral rotation, and lumbar lordosis. Currently, these angles are determined based on operator experience and sequential fluoroscopic images, often requiring multiple repositioning attempts and additional radiation exposure. Since many patients undergo lumbar MR imaging prior to TFESI, utilizing anatomical information from these existing images could help predict patient-specific initial C-arm angles. This study will use an AI-based system (ChatGPT) to evaluate standard T2-weighted lumbar MR images and predict the optimal oblique and craniocaudal C-arm angles. The operating physician will be blinded to the AI predictions and will determine the C-arm positioning based solely on their clinical evaluation. The study aims to evaluate whether AI can accurately predict these angles and to determine if prediction accuracy varies based on the target lumbar level and patient characteristics.

+Arms and interventions

  • AI based evaluation (Other): AI-based evaluation of pre-procedural T2-weighted lumbar MR images to predict optimal fluoroscopic C-arm angles (oblique and craniocaudal)

+Outcome measures

Primary outcomes

  • The absolute error (in degrees) between the AI-predicted oblique and craniocaudal C-arm angles and the reference angles determined by the operator during the procedure [Baseline]: The absolute error (in degrees) between the AI-predicted oblique and craniocaudal C-arm angles and the reference angles determined by the operator during the procedure

+Eligibility

Sex: All, ages: 18 Years to 75 Years

Inclusion Criteria:

* Being between 18-75 years of age.
* Scheduled for TFESI due to lumbar radicular pain as part of routine clinical practice based on clinical and imaging findings.
* Planned for unilateral or bilateral, single or multi-level TFESI.
* Having appropriate quality lumbar MR images obtained within the last 6 months prior to the procedure.
* Providing written informed consent.

Exclusion Criteria:

* History of spinal surgery at the target lumbar level that could significantly alter anatomy and fluoroscopic imaging (e.g., instrumentation, fusion, or significant bone resection).
* Presence of severe scoliosis or structural spinal deformity affecting the standard TFESI technique or standard fluoroscopic projections.
* Significant motion, metal, or other imaging artifacts on lumbar MR images.
* Inadequate quality of any of the pre-defined standardized sagittal, parasagittal, or axial T2-weighted images in the current MRI examination.
* Inability to perform or cancellation of the planned TFESI procedure for any reason.

+Study documents