Common and Specific Information From Neuroimaging and Smartphone (MS-CSI)

Individual Gait Pattern and MRI Lesion Load to Quantify Gait Impairment in MS: A Cross Sectional Study.

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).

Study Overview

• Status: Recruiting
• Conditions: Multiple Sclerosis
• Intervention / Treatment: Other: eGait

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.

• Study Type: Observational
• Enrollment (Anticipated): 100

Contacts and Locations

• Study Contact: Name: David LAPLAUD, PHD; Phone Number: 33 2 40 16 52 00; Email: david.laplaud@chu-nantes.fr

Study Locations

• France
  • Loire-Atlantique
    • Nantes, Loire-Atlantique, France, 44093
      • Recruiting
      • Nantes University Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: N/A
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

MS patients cohort followed at Nantes university hospital or Rennes university hospital (OFSEP HD cohort)

Description

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
• 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

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Clustering analyze based on IGP	IGP consists of a curve, based on quaternion and representing the rotation recorded by the IMU during an average gait cycle (0-1).	At the inclusion
Clustering analyze based on EDSS score	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.	At the inclusion
Clustering analyze based on MRI lesion load	MRI characteristics are spinal and extraspinal lesion volumes.	At the inclusion

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correlation with disability	Correlation of IGP obtained during a walk of 25 feet with Expanded Disability Status Scale (EDSS). 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. Here EDSS of 0 to 2 inclusive defined as mild, 2,5 to 4 inclusive as moderate and EFDSS of 4,5 to 6 inclusive defined as severe	At the inclusion
Correlation with MRI lesion load	Add lesion load (Spinal and extraspinal lesion volume) from MRI to previous correlation.	At the inclusion
Building a predictive model for lesion load involving in walk ability from IGP	Root mean square error between observed and lesion load predicted by the model, calculated by cross-validation.	At the inclusion
Building a predictive model for group belonging from group established in main outcome based on IGP	Multiclass accuracy between real and predict group, calculated by cross-validation	At the inclusion

Collaborators and Investigators

• Sponsor: Nantes University Hospital
• Collaborators: Rennes University Hospital

Study record dates

Study Major Dates

• Study Start (Actual): April 3, 2023
• Primary Completion (Anticipated): April 1, 2025
• Study Completion (Anticipated): April 1, 2025

Study Registration Dates

• First Submitted: July 20, 2022
• First Submitted That Met QC Criteria: July 28, 2022
• First Posted (Actual): August 1, 2022

Study Record Updates

• Last Update Posted (Actual): April 7, 2023
• Last Update Submitted That Met QC Criteria: April 6, 2023
• Last Verified: March 1, 2023

More Information

Terms related to this study

• Keywords: MRI; Gait; Wearable sensor
• Additional Relevant MeSH Terms: Nervous System Diseases; Immune System Diseases; Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Demyelinating Diseases; Autoimmune Diseases; Multiple Sclerosis
• Other Study ID Numbers: RC20_0203

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No