Development of an Artificial Intelligence based Clinical Assessment System for the diagnosis of patients with Lumbar Prolapsed Intervertebral Disc

Development of an Efficient Artificial Intelligence based Clinical Assessment System for patients with Lumbar Prolapsed Intervertebral Disc and its Correlation with Magnetic Resonance Imaging findings - NIL

Status

Active, not recruiting

Phases

Phase 2

Study type

Interventional

Source

CTRI

Registry ID

CTRI/2023/09/058094

Enrollment

Registered

2023-09-27

Start date

Unknown

Completion date

Unknown

Last updated

2023-10-16

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

Conditions

Health Condition 1: M488- Other specified spondylopathies

Interventions

Intervention1: Artificial intelligence-based diagnosis of lumbar prolapsed intervertebral disc: Both males and females within the age group of 20 to 50 years and BMI 23 kg/m with low back pain and mee

Eligibility

Inclusion criteria

Inclusion criteria: Overweight and obese patients (BMI = 23 kg/m2)49 Patient with low back pain. Patient with or without radicular pain along a specific dermatome. Patient with or without neurological signs and symptoms. Patient with MRI of lumbar spine. Patients with or without lumbosacral list.

Exclusion criteria

Exclusion criteria: MRI showing degenerative disc disease. Patient with leg length discrepancy. Patients with any spine structural impairments. Patient with red flags (spondylosis, spondylolisthesis, spondylodiscitis, Spinal canal stenosis, metastasis, bladder–bowel involvement, osteoporosis, trauma, spinal fractures and dislocations, etc.)

Design outcomes

Primary

Measure	Time frame
Measure and compare the proportion of patients properly diagnosed with prolapsed intervertebral disc and its categorization into different stages.Timepoint: Immediately after recruitment, i.e., in the baseline.	—

Secondary

Measure	Time frame
NILTimepoint: NIL	—

Countries

India

Contacts

Public ContactSandeep Pattnaik

M.M Institute of Physiotherapy and Rehabilitation

manu.goyal@mmumullana.org8307715320

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026