Creation of a Clinical Database of Lumbar Spine MRI
- Conditions
- Low Back Pain
- Interventions
- Other: Data Collection
- Registration Number
- NCT06248827
- Lead Sponsor
- Caerus Medical
- Brief Summary
The creation of a clinical database including patients who suffer from low back pain and underwent a lumbar spine MRI Exam.
This database will allow us to :
* Collect patients symptoms, medical history, and MRI exams
* Launch the annotation of the MRI exams by expert radiologists
* Link and relate information between the exams and the diagnostic done by the experts
* Train and develop a diagnostic platform for th spinal pathologies based on artificial intelligence.
- Detailed Description
Low back pain is classically characterized by pain in the lower back, which may be accompanied by varying degrees of restricted mobility and pain radiating down to the feet. The management of low back pain is a global public health issue, since it represents one of the major causes of disability worldwide.
Degenerative disc disease (DDD) is the most common underlying pathology. These include herniated discs, pinched discs and degenerative spondylolisthesis (slippage of one vertebra in relation to its neighbor). Worldwide, 266 million patients suffer from DDD every year. The socio-economic impact of these pathologies is considerable.
DDD results from a variety of pathologies that may interact with each other. The diversity of these pathologies and the complexity of their interactions often lead to failure of a clear diagnosis, and consequently to inappropriate treatment.
In clinical practice, MRI is the reference test for the diagnosis of these pathologies, but inter-observer reliability remains moderate between 2 practitioners (sensitivity 56% and Cohen's κ ⊂ \[0.41-0.6\]) or even low (κ ⊂ \[0.21-0.4\]) between 2 practitioners of different specialties. So there is still a major gap to be bridged in order to make radiologists' diagnoses more reliable and standardized.
In this context, the creation of a clinical database including patient symtoms and exams is of hogh interest.Thsi database will allow us to :
1. Annotate the MRI exams by experts radiologists in order to train and develop AI algorithms
2. Create a tool to support radiologists in their diagnoses would therefore be a considerable step forward. Such a tool, combined with non-invasive data, would make it possible to establish a specific diagnosis early on,
The database will also allow us to develop or participate in multicentric clinical studies, at the national or international level, as well as to facilitate the identification of correlations between MRI findings, the patients symptoms and the origin of the low back pain.
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 500
- Adult patient aged ≥ 18, no age limit;
- Suffering of low back pain ;
- Patient exam performed at the Centre Hospiralier Universitaire de Montreal (CHUM), Canada
- Patients with orthopedic material
- Patients with traumatic cases (ex : accidents)
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Lumbar Spine MRI exams Data Collection An information letter will be delivered by the investigator physician to the patients to inform them on the study, its implementation and their complete freedom to participate or not. 1. MRI Data from exams (DICOM format) * Sagittal T1 * Sagittal T2 * Sagittal DIXON * Sagittal STIR * Sagittal FLAIR * Axial T2 2. Clinical Data from questionnaires * biometric data (height, weight), * age * gender, * smoking status, * comorbidities, * basic clinical examination, * medical history.
- Primary Outcome Measures
Name Time Method Establish a database of patients who underwent a MRI exam of the lumbar spine at the Centre Hospitalier Universitaire de Montreal (CHUM) in Canada. 1 year
- Secondary Outcome Measures
Name Time Method Data annotation and developpment of artificial intelligence algorithms 2 years * Annotation of the lumbar spine MRI exams by experts radiologists according to a standardized annotation protocol for lumbar spine pathologies.
* Training of artificial intelligence algorithms based on the database created and annotation collected.
* Development of a diagnostic platform for spinal pathologies.
* Realization of clinical studies specific the annotations on the MRI exams and the patient prevalence.