AI ProMiS: Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study

Sponsor
University of Ljubljana (Other)
Overall Status
Recruiting
CT.gov ID
NCT05426980
Collaborator
Novartis (Industry), General and Teaching Hospital Celje (Other), University Medical Centre Ljubljana (Other), University Medical Centre Maribor (Other), General Hospital Izola (Other)
1,200
4
18.5
300
16.2

Study Details

Study Description

Brief Summary

The study proposal focuses on multiple sclerosis (MS), a chronic incurable disease of the central nervous system (CNS). The MS disease is characterised by recurrent transient disability progression, quantified by increase in the extended disability status score (EDSS), and subsequent remission (disappearance of symptoms and reduced EDSS score) or, alternatively, a gradual EDSS disability progression and exacerbation of associated symptoms. At the same time, the MS is characterised by multifocal inflammatory lesions disseminated throughout the white and grey matter of the CNS, which can be observed and quantified in the magnetic resonance (MR) scans. The proposed study will address the critical unmet need of computer-assisted extraction and assessment of prognostic factors based from an individual patient's brain MR scan, such as lesion count, volume, whole-brain and regional brain atrophy, and atrophied lesion volume, in order to evaluate the capability for personalized future disability progression prediction.

Condition or Disease Intervention/Treatment Phase

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    1200 participants
    Observational Model:
    Cohort
    Time Perspective:
    Retrospective
    Official Title:
    Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study
    Actual Study Start Date :
    Dec 13, 2021
    Anticipated Primary Completion Date :
    Jun 30, 2023
    Anticipated Study Completion Date :
    Jun 30, 2023

    Outcome Measures

    Primary Outcome Measures

    1. Atrophied lesion volume derived from MRI predicts confirmed EDSS disability progression [Atrophied lesion volume quantified from two or more MR scans across the span of at least one and up to five years]

      Patients will be divided into two groups based on the presence or absence of EDSS disability progression (DP) during the observation period. The DP converters will be classified as patients with an EDSS change of at least 1.5 if the baseline EDSS is less than 1.0, those with an EDSS change of at least 1.0 if the baseline EDSS is 1.0-5.5, and those with an EDSS change of at least 0.5 if the baseline EDSS is 5.5 or higher [15]. DP converters should have confirmed progression of EDSS impairment over a period of at least 6 months. DP non-converters include individuals who do not meet the criteria for conversion. Atrophied lesion volume will be quantified from MR scans taken >6 months prior to the observed EDSS increase. Advanced artificial intelligence based image analysis tools will be applied to assess the atrophied lesion volume.

    Secondary Outcome Measures

    1. Atrophied lesion volume derived from MRI predicts conversion to secondary progressive multiple sclerosis [Atrophied lesion volume quantified from two or more MR scans across the span of least one and up to five years]

      Patients will be divided into two groups, i.e. those who transitioned from clinically isolate syndrome (CIS) or relapsing-remitting (RR) to secondary progressive (SP) form of MS and those who were diagnosed with CIS/RRMS during the observation period. A consilium for patients with MS will confirm the SPMS diagnosis by consensus. Atrophied lesion volume will be quantified from MR scans taken >6 months prior to the observed conversion to the SPMS. Advanced artificial intelligence based image analysis tools will be applied to assess the atrophied lesion volume.

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years to 65 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    Yes
    Inclusion Criteria:
    • persons diagnosed with MS (any phenotype; according to the 2010 McDonald criteria) and CIS patients

    • availability of at least two MRI exams with both FLAIR and T1-weighted scans of the same participant over a period of at least 6 months at the most recent examination

    • availability of demographic, clinical data and treatment information for the same participant over a period of at least 6 months at the most recent examination

    • availability of EDSS score and at least one previous EDSS scores for the same participant over a period of at least 6 months at the most recent examination

    Exclusion Criteria:
    • other clinically relevant systemic diseases if the researcher considers them to be significant

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 University medical center Ljubljana Ljubljana Osrednjeslovenska Slovenia 1000
    2 General and teaching hospital Celje Celje Slovenia 3000
    3 General hospital Izola Izola Slovenia
    4 University medical center Maribor Maribor Slovenia 2000

    Sponsors and Collaborators

    • University of Ljubljana
    • Novartis
    • General and Teaching Hospital Celje
    • University Medical Centre Ljubljana
    • University Medical Centre Maribor
    • General Hospital Izola

    Investigators

    • Principal Investigator: Ziga Spiclin, PhD, University of Ljubljana

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Ziga Spiclin, Associate professor, PhD, University of Ljubljana
    ClinicalTrials.gov Identifier:
    NCT05426980
    Other Study ID Numbers:
    • 0120-570/2021/5
    First Posted:
    Jun 22, 2022
    Last Update Posted:
    Jun 22, 2022
    Last Verified:
    Jun 1, 2022
    Individual Participant Data (IPD) Sharing Statement:
    No
    Plan to Share IPD:
    No
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Ziga Spiclin, Associate professor, PhD, University of Ljubljana
    Additional relevant MeSH terms:

    Study Results

    No Results Posted as of Jun 22, 2022