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Improving MRI spine evaluation of Modic changes using artificial intelligence techniques

Redesigning Conventional Evaluation of Modic Changes on Spine MRI Using Machine Learning Assisted Assessment An Observational Study - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/04/108565
Enrollment
100
Registered
2026-04-16
Start date
Unknown
Completion date
Unknown
Last updated
2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: M538- Other specified dorsopathies

Interventions

Intervention1: Nil: Nil

Sponsors

SAVEETHA MEDICAL COLLEGE AND HOSPITAL
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Patients undergoing MRI of the spine with features suggestive of Modic changes Patients with adequate MRI image quality suitable for machine learning assisted analysis Patients who provide informed consent for use of imaging data for research purposes

Exclusion criteria

Exclusion criteria: Patients with a history of prior spinal surgery Patients with spinal infections, tumors or fractures Patients with severe motion artifacts or poor quality MRI images unsuitable for analysis Patients with congenital spinal deformities Patients unwilling or unable to provide informed consent

Design outcomes

Primary

MeasureTime frame
Assessment of Modic changes on MRI using machine learning assisted analysisTimepoint: At baseline at the time of initial MRI scan—

Secondary

MeasureTime frame
Inter-observer variability in detection and classification of Modic changes between radiologists and machine learning modelTimepoint: At the time of image analysis—

Countries

India

Contacts

Public ContactDR VADUPU UDAYA BHANU

saveetha medical college

proliton87@gmail.com9701587566

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: May 1, 2026