Lumbar Radicular PainNCT07875855
MRI-Based Artificial Intelligence Prediction of Fluoroscopic C-Arm Angles for Lumbar Transforaminal Epidural Steroid Injections
An observational study of Lumbar Radicular Pain and Artifical Intelligence, run by Marmara University.
Trial 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). Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Lumbar Radicular Pain, Artifical Intelligence
- What is being tested?
- AI based evaluation
- How many people
- 80 participants
- Where
- No sites listed yet
- Study dates
- 1 Dec 2026to 1 Dec 2027
- How long will I take part?
- 3 Weeks
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: dult patients scheduled for unilateral or bilateral, single or multi-level TFESI due to lumbar radicular pain as part of routine clinical practice.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: MRI-Based Artificial Intelligence Prediction of Fluoroscopic C-Arm Angles for Lumbar Transforaminal Epidural Steroid Injections: A Prospective Accuracy Study
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.
Read the 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.
- Conditions
- Lumbar Radicular Pain, Artifical Intelligence
- Being tested
- AI based evaluation
- Keywords
- Lumbar Transforaminal Epidural Steroid Injection (TFESI), Artificial Intelligence., Fluoroscopic C-arm Angles, Lumbar MRI
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI based evaluationOther
AI-based evaluation of pre-procedural T2-weighted lumbar MR images to predict optimal fluoroscopic C-arm angles (oblique and craniocaudal)
What is being measured
The primary outcome is the main question the study is designed to answer.
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
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
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Oct 2026
- Study start1 Dec 2026 (estimated)
- Primary completion1 May 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lumbar Radicular PainStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 80 participants (estimated)
- Target duration
- 3 Weeks
Sponsor and investigators
- Lead sponsor
- Marmara University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Halis Uğur, Marmara University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07875855
- Sponsor's protocol ID
- 09.2026.26-0729
- Status last verified
- Sep 2026
- First submitted
- 7 Sep 2026
- Last updated
- 15 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- MRI-Based Artificial Intelligence Prediction of Fluoroscopic C-Arm Angles for Lumbar Transforaminal Epidural Steroid Injections: A Prospective Accuracy Study
- ClinicalTrials.gov ID
- NCT07875855
- Acronym / sponsor ID
- 09.2026.26-0729
- Conditions
- Lumbar Radicular Pain, Artifical Intelligence
- Keywords
- Lumbar Transforaminal Epidural Steroid Injection (TFESI), Artificial Intelligence., Fluoroscopic C-arm Angles, Lumbar MRI
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 80 participants (estimated)
- Lead sponsor
- Marmara UniversityUniversity, hospital or other
- Study start
- 1 Dec 2026 (estimated)
- Primary completion
- 1 May 2027 (estimated)
- Study completion
- 1 Dec 2027 (estimated)
- First posted
- 15 Oct 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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.
Study design
- Observational model
- Other
- Time perspective
- Prospective
- Target follow-up
- 3 Weeks
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- dult patients scheduled for unilateral or bilateral, single or multi-level TFESI due to lumbar radicular pain as part of routine clinical practice.
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI based evaluationAI-based evaluation of pre-procedural T2-weighted lumbar MR images to predict optimal fluoroscopic C-arm angles (oblique and craniocaudal) | Other | – |
Primary outcome
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
Time frame: 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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
An observational study of Lumbar Radicular Pain and Artifical Intelligence, run by Marmara University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 15 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Savaş Şencan, Assoc. Prof. of Algology, M.D (+905370665713, savas-44@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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 (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Oct 2026.