Clinical trial NCT05426980: Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study
Official title: Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Multiple Sclerosis
Multiple Sclerosis Lesion
Multiple Sclerosis Brain Lesion
Keywords: Artificial intelligence
Prediction model
Magnetic resonance imaging
Computer-assisted image analysis
Lead sponsor: University of Ljubljana
Sponsor class: OTHER
Collaborators: name: Novartis
name: General and Teaching Hospital Celje
name: University Medical Centre Ljubljana
name: University Medical Centre Maribor
name: Izola General Hospital
First posted: 2022-06-22
Enrollment: 654
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: RETROSPECTIVE
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.

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.


Eligibility criteria: 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

Primary outcomes:
measure: Atrophied lesion volume derived from MRI predicts confirmed EDSS disability progression
timeFrame: Atrophied lesion volume quantified from two or more MR scans across the span of at least one and up to five years
Secondary outcomes:
measure: Atrophied lesion volume derived from MRI predicts conversion to secondary progressive multiple sclerosis
timeFrame: Atrophied lesion volume quantified from two or more MR scans across the span of least one and up to five years
Other outcomes:
Locations:
city: Ljubljana
country: Slovenia
facility: University medical center Ljubljana
state: Osrednjeslovenska
city: Celje
country: Slovenia
facility: General and teaching hospital Celje
city: Izola
country: Slovenia
facility: General hospital Izola
city: Maribor
country: Slovenia
facility: University medical center Maribor
Study officials:
affiliation: University of Ljubljana
name: Ziga Spiclin, PhD
role: PRINCIPAL_INVESTIGATOR
References: