Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study

NCT05426980 | Completed

• 1 other identifier: 0120-570/2021/5
• Study Type: observational
• Target: 654
• Locations: 1 country
• Sites: 4

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.

Conditions

Multiple Sclerosis; Multiple Sclerosis Lesion; Multiple Sclerosis Brain Lesion

Keywords

Artificial intelligence; Prediction model; Magnetic resonance imaging; Computer-assisted image analysis

Outcome Measures

Primary Outcomes (1)

• Atrophied lesion volume derived from MRI predicts confirmed EDSS disability progression

  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.

  Atrophied lesion volume quantified from two or more MR scans across the span of at least one and up to five years

Secondary Outcomes (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

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study will be based on a retrospective secondary analysis of demographic and clinical data and MRI scans of approximately 1200 Slovenian patients with MS that are regularly monitored between 2015 and present.

You may qualify if:

• 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

You may not qualify if:

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

Sponsors & Collaborators

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

Study Sites (4)

University medical center Ljubljana

Ljubljana, Osrednjeslovenska, 1000, Slovenia

Location

General and teaching hospital Celje

Celje, 3000, Slovenia

Location

General hospital Izola

Izola, Slovenia

Location

University medical center Maribor

Maribor, 2000, Slovenia

Location

MeSH Terms

Conditions

Multiple Sclerosis

Condition Hierarchy (Ancestors)

Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Demyelinating Diseases; Autoimmune Diseases; Immune System Diseases

Study Officials

• Ziga Spiclin, PhD

  University of Ljubljana

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate professor, PhD

Study Record Dates

• First Submitted: May 26, 2022
• First Posted: June 22, 2022
• Study Start: December 13, 2021
• Primary Completion: September 30, 2023
• Study Completion: September 30, 2023
• Last Updated: December 5, 2023

Record last verified: 2023-11

Data Sharing

• IPD Sharing: Will not share

Locations

SL (4)