Individual Gait Pattern and MRI Lesion Load to Quantify Gait Impairment in MS: A Cross Sectional Study.
Overview
- Phase
- N/A
- Intervention
- Not specified
- Conditions
- Multiple Sclerosis
- Sponsor
- Nantes University Hospital
- Enrollment
- 100
- Locations
- 1
- Primary Endpoint
- Clustering analyze based on IGP
- Status
- Recruiting
- Last Updated
- last month
Overview
Brief Summary
Gait alteration is frequent in MS and limitation in walking ability is a major concern in MS patients. Umanit and LMJL (Nantes university) has developed a device call egait to assess walking ability in individuals (eg MS patients).
Detailed Description
This device consists in a commercialized IMU sensor (MetaMotionR Sensor, Mbientilab) worn at the right hip, a smartphone app and dedicated algorithm/mathematical model to extract raw sensor data and calculate individual gait pattern (IGP). This IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle. Pursue previous works conducted on (IGP to assess) gait alteration in MS by adding (to IGP) new information from MRI.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Diagnosis of MS based on McDonald criteria (including Relapsing-remitting and progressive MS)
- •Over 18 years old /age greater than 18 years
- •Patients followed at Nantes university hospital or Rennes university hospital
- •Last known EDSS before inclusion ranging from 0 to 6 inclusive/EDSS of 0 to 6 inclusive, prior inclusion
- •No relapse within 3 months
- •With a Medullar MRI planed as part as usual care
- •MRI scan can be performed within a maximum of 4 months after or before the walking test.
- •Affiliated person or beneficiary of a social security scheme
Exclusion Criteria
- •Bilateral aid needed to walk
- •Women who are pregnant
- •Patient having expressed their opposition
- •Patient under guardianship or security measure
Outcomes
Primary Outcomes
Clustering analyze based on IGP
Time Frame: At the inclusion
IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle (0-1).
Clustering analyze based on EDSS score
Time Frame: At the inclusion
EDSS is an ordinal scale measuring disability and ranging from 0 (normal examination) to 10 (death due to MS) in a 0,5-point increments from score 1.
Clustering analyze based on MRI lesion load
Time Frame: At the inclusion
MRI characteristics are spinal and extraspinal lesion volumes.
Secondary Outcomes
- Correlation with disability(At the inclusion)
- Correlation with MRI lesion load(At the inclusion)
- Building a predictive model for lesion load involving in walk ability from IGP(At the inclusion)
- Building a predictive model for group belonging from group established in main outcome based on IGP(At the inclusion)