Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study

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.

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Key information

Conditions

Multiple Sclerosis Autoimmune Diseases Autoimmune Diseases of the Nervous System Demyelinating Autoimmune Diseases, CNS Demyelinating Diseases Immune System Diseases Multiple Sclerosis Brain Lesion Multiple Sclerosis Lesion Nervous System Diseases

Age range

18 year–65 year

Sex eligibility

All sexes

Study type

Observational

Primary location

University medical center Ljubljana, Ljubljana, Osrednjeslovenska, Slovenia

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

Atrophied lesion volume derived from MRI predicts confirmed EDSS disability progression

Time frame: 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 outcomes

Atrophied lesion volume derived from MRI predicts conversion to secondary progressive multiple sclerosis

Time frame: 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.

Sponsors and collaborators

Lead sponsor

University of Ljubljana

Other

Collaborators

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

Registry information

Acronym: AI ProMiS

Important dates

Study start: 2021
Primary completion: 2023
Study completion: 2023
First posted: Jun 22, 2022
Registry last updated: Dec 5, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

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