Clinical trial NCT06248827: Creation of a Clinical Database of Lumbar Spine MRI
Official title: Creation of a Clinical Database of Lumbar Spine MRI
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Low Back Pain
Keywords: Low back pain
MRI
Lead sponsor: Caerus Medical
Sponsor class: INDUSTRY
Collaborators: name: Centre hospitalier de l'Université de Montréal (CHUM)
First posted: 2024-02-08
Enrollment: 500
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Adult patients (over 18 years of age), men and women, suffering of low back pain who underwent a lumbar spine MRI exam

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.

Eligibility criteria: Inclusion Criteria:

* Adult patient aged ≥ 18, no age limit;
* Suffering of low back pain ;
* Patient exam performed at the Centre Hospiralier Universitaire de Montreal (CHUM), Canada

Exclusion Criteria:

* Patients with orthopedic material
* Patients with traumatic cases (ex : accidents)

Primary outcomes:
measure: Establish a database of patients who underwent a MRI exam of the lumbar spine at the Centre Hospitalier Universitaire de Montreal (CHUM) in Canada.
timeFrame: 1 year
Secondary outcomes:
measure: Data annotation and developpment of artificial intelligence algorithms
timeFrame: 2 years
Other outcomes:
Locations:
Study officials:
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