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Enrolling by Invitation

NCT Number: NCT07032246

Clinical Impact Through AI-assisted MS Care - A Prospective Multi-center Study

The goal of the PROCLAIM study is to assess the effectiveness of quantitative brain MRI, as measured by icobrain mr, on the detection of disease activity in multiple sclerosis, including the identification of smouldering disease, and the downstream effects on clinical decision making and patient outcomes in a real-world setting.

The study will compare an intervention arm implementing quantitative brain MRI (using the CE-marked medical device software icobrain mr) as part of Standard of Care, and a control arm implementing Standard of Care without quantitative brain MRI.

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Key information

Conditions

Multiple Sclerosis Autoimmune Diseases Autoimmune Diseases of the Nervous System Clinically Isolated Syndrome Demyelinating Autoimmune Diseases, CNS Demyelinating Diseases Immune System Diseases Nerve Degeneration Nervous System Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Radiologically Isolated Syndrome

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

General University Hospital Prague, Prague, Czechia

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About this study

PROCLAIM (Clinical Impact through AI-assisted MS care: a prospective multi-centre study) is a prospective multi-country multi-site comparative effectiveness study conducted within the scope of the EU-funded research project "Clinical impact through AI-assisted MS Care" (CLAIMS). Quantitative brain MRI will be implemented in this study based on the icobrain mr medical device. icobrain mr is an AI software solution for brain MRI analysis in multiple sclerosis that provides quantitative measurements on disease activity and progression. icobrain mr is CE-marked as a medical device software Class IIa and will be used in PROCLAIM according to its intended use. The study does not involve procedures additional to those performed under the normal conditions of use of the device, nor any other invasive or burdensome procedures.

The study will assess the impact of using quantitative brain MRI, as measured by icobrain mr, on the quality of care. In particular, the study will evaluate the impact on detecting disease activity in MS, as well as on clinical decision-making and clinical outcomes in routine clinical practice for people with MS (pwMS). The study will target both the inflammatory and smouldering components of the disease using assessments already used in daily clinical routine. Exploratory analyses will focus on the relation to other biomarkers used in clinical routine of the participating sites (optic coherence tomography (OCT), evoked potentials (EPs)), as well as patient reported outcomes and passive monitoring measurements (sleep duration, step count and environmental temperature) collected via the icompanion patient app, in conjunction with clinical and radiological parameters.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Able to independently understand, evaluate and sign the informed consent form.
  • Able to comply with the study protocol, including having a mobile device capable of running the icompanion app.
  • Have a definite diagnosis of MS, confirmed as per revised McDonald 2017 criteria (treated or untreated) and/or a diagnosis of RIS/CIS (following the revised McDonald criteria presented during ECTRIMS 2024)
  • Patients early in the disease course of RRMS (CIS/RIS, RRMS with disease duration < 7 years), patients with initial diagnosis of relapsing MS and disease duration 12-18 years (prone to convert to SPMS).
  • Clinical and brain MRI data available at least one year prior to the study
  • Age >= 18 years

Exclusion criteria

  • Unable or unwilling to understand, evaluate and sign the informed consent form.
  • Any contraindications for undergoing an MRI.
  • Currently involved in another interventional study.
  • Currently pregnant or planning a pregnancy in the coming 2 years.
  • Any concomitant disease that may require chronic treatment with systemic corticosteroids or immunosuppressants during the study.
  • Retrospective MRI not meeting requirements: at least, 3D T1-weighted images and fluid-attenuated inversion recovery (FLAIR) images (3D, or 2D with maximal slice thickness of 3mm).
  • Patients with confirmed diagnosis of PPMS.

Treatment and study plan

quantitative brain MRI (icobrain mr)

Device

Quantitative brain MRI refers to using a specialised software to compute volumes of brain structures and of MS lesions from brain MRI scans, and to measures differences between a previous brain MRI scan and the current brain MRI scan.

The quantitative brain MRI solution being investigated in the PROCLAIM study is icobrain mr, a software solution that uses artificial intelligence (AI) to help with tracking of MS disease progression by measuring brain structures and lesions on magnetic resonance imaging (MRI).

Standard of Care (SOC)

Other

Standard of Care practices at each participating site for management of multiple sclerosis.

Primary outcomes

  1. Impact of using icobrain mr on detecting (inflammatory or smouldering) disease activity

    Time frame: baseline

    The difference between control arm and interventional arm in the proportion of patients for whom disease activity or progression is reported by the neurologist at baseline.

  2. Impact of using icobrain mr on the clinical outcome

    Time frame: month 24

    The difference between control arm and interventional arm in the number of patients with no disease activity or progression at month 24.

Secondary outcomes

  1. Proportion of patients who switch treatment

    Time frame: baseline

    Difference between control arm and interventional arm in the proportion of patients who switch their treatment due to detection of disease activity at baseline.

  2. Objective of each treatment switch

    Time frame: baseline

    Descriptive analysis of the type and reason of treatment switches.

  3. Role of disease activity on MRI in the decision to make a treatment switch

    Time frame: baseline

    Difference between control arm and interventional arm in the proportion of patients who switch their treatment due to disease activity on MRI.

  4. Role of quantitative brain MRI in the decision to make a treatment switch

    Time frame: baseline

    Number of treatment switches in the interventional arm in which quantitative brain MRI played a role in the clinical decision-making process to switch DMT.

  5. Neurologist confidence in the clinical decision-making process (Likert scale: 1 - not confident, 2 - slightly confident, 3 - somewhat confident, 4 - fairly confident, 5 - very confident)

    Time frame: baseline

    Difference between control and interventional arm in the average confidence of the neurologist in the clinical decision-making process at baseline.

  6. Neurologist confidence in confirming the diagnosis of MS (Likert scale: 1 - not confident, 2 - slightly confident, 3 - somewhat confident, 4 - fairly confident, 5 - very confident)

    Time frame: baseline

    Difference between control and interventional arm in the average confidence of the neurologist in confirming diagnosis of MS at baseline.

  7. Neurologist confidence in confirming the conversion to SPMS (Likert scale: 1 - not confident, 2 - slightly confident, 3 - somewhat confident, 4 - fairly confident, 5 - very confident)

    Time frame: baseline

    Difference between control and interventional arm in the average confidence of the neurologist in confirming conversion to SPMS at baseline.

  8. Proportion of patients with detected smouldering or inflammatory disease components

    Time frame: baseline

    The difference between control arm and interventional arm in the proportion of patients for whom smouldering or inflammatory disease components are reported by the neurologist at baseline.

  9. Reported MRI findings at baseline

    Time frame: baseline

    Difference between control arm and interventional arm in the number of reported MRI findings at baseline, among:

    • new FLAIR lesions
    • enlarging FLAIR lesions
    • total FLAIR lesion volume
    • T1 hypointense lesions
    • T1 hyperintense lesions (if T1-post available)
    • whole brain volume loss
    • gray matter volume loss
    • central vein sign lesions (if SWI available)
    • paramagnetic rim lesions (if SWI available)
    • (cervical) spinal cord atrophy (if assessable)

  10. Proportion of patients with relapse associated worsening (RAW)

    Time frame: month 12 - month 24

    The difference between control arm and interventional arm in the proportion of patients for whom RAW disease activity or progression is reported by the neurologist at month 12 to month 24.

  11. Proportion of patients with smouldering associated worsening (SAW)

    Time frame: month 12 - month 24

    The difference between control arm and interventional arm in the proportion of patients for whom SAW disease activity or progression is reported by the neurologist at month 12 to month 24.

  12. Proportion of relapse-free participants between month 12 and month 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in the proportion of relapse-free participants between month 12 and month 24.

  13. Relapse rate between month 12 and month 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in the (baseline-adjusted) relapse rate between month 12 and month 24.

  14. Proportion of participants with EDSS progression between month 12 and 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in the proportion of participants with EDSS progression

  15. Change in clinical score Nine Hole Peg Test (9HPT) between month 12 and 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in clinical score 9HPT change between month 12 and 24

  16. Change in clinical score Timed 25-Foot Walk (T25WT) between month 12 and 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in T25WT change between month 12 and 24

  17. Change in clinical score Symbol Digit Modalities Test (SDMT) between month 12 and 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in SDMT change between month 12 and 24

  18. MRI findings as assessed by icobrain mr in combination with the radiologist at month 24

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in the MRI findings as assessed by icobrain mr in combination with the radiologist from month 12 and month 24.

Other outcomes

  1. Correlation of spinal cord C2/C3-level atrophy with measurements of clinical disease worsening

    Time frame: baseline, month 12, month 24

    Correlations between whole brain MRI-derived C2/C3 atrophy measurements and EDSS, 9HPT, SDMT, T25WT.

  2. Correlation of paramagnetic rim lesion load with measurements of clinical disease worsening

    Time frame: baseline, month 12, month 24

    Correlations between whole brain MRI-derived paramagnetic rim lesion measurement and EDSS, 9HPT, SDMT, T25WT.

  3. Correlation of OCT-derived parameters with measurements of clinical disease worsening

    Time frame: month 24

    Correlations between OCT-derived parameters (Peripapillary nerve fiber layer thickness (pRNFL); Combined ganglion cell layer and inner plexiform layer (GCIPL); Total macular volume (TMV); Macula shape parameters (Pit flat disk area, Average pit flat disk diameter, Inner rim volume, Major slope disk length); Optic nerve head shape parameters (total volume, Annular volume, BMO-MRW (Bruch's membrane opening - minimum rim width) Distance, BMO-MRW (Bruch's membrane opening - minimum rim width) Area) with EDSS, 9HPT, SDMT, T25WT, CDW and clinical disease worsening.

  4. Correlation of Evoked Potentials-derived parameters with measurements of clinical disease worsening

    Time frame: month 24

    Correlations between Evoked Potentials-derived parameters (latencies/amplitudes/scores) with EDSS, 9HPT, SDMT, T25WT, CDW and PIRA-induced clinical disease worsening.

    Cross-sectional and longitudinal correlations between visual Evoked Potentials and Optical Computed Tomography measures (when available).

    Cross-sectional and longitudinal correlations between somatosensory and motor Evoked Potentials measures and spinal cord MRI measures (when available).

  5. icompanion patient reported EDSS (prEDSS)

    Time frame: baseline - month 24

    Difference between control arm and interventional arm in the icompanion prEDSS, assessed as a change from baseline to month 12 and month 24.

  6. icompanion patient reported SymptoMScreen

    Time frame: baseline - month 24

    Difference between control arm and interventional arm in the icompanion patient reported SymptoMScreen, assessed as a change from baseline to month 12 and month 24.

  7. icompanion patient reported Neuro-QoL Cognition

    Time frame: baseline - month 24

    Difference between control arm and interventional arm in the icompanion patient reported Neuro-QoL Cognition, assessed as a change from baseline to month 12 and month 24.

  8. icompanion patient reported Neuro-QoL Fatigue

    Time frame: baseline - month 24

    Difference between control arm and interventional arm in the icompanion patient reported Neuro-QoL Fatigue, assessed as a change from baseline to month 12 and month 24.

  9. icompanion Symbol Test score

    Time frame: baseline - month 24

    Difference between control arm and interventional arm in the icompanion Symbol Test score, assessed as a change from baseline to month 12 and month 24.

  10. icompanion Finger Dexterity Test score

    Time frame: month 12 - month 24

    Difference between control arm and interventional arm in the icompanion Finger Dexterity Test score, assessed as a change from baseline to month 12 and month 24.

  11. Correlation of patient reported outcomes, digital tests and/or passive monitoring measurements with measurements of clinical disease worsening.

    Time frame: month 24

    Correlations between patient reported outcome (prEDSS, SymptoMScreen, Neuro-Qol, icognition) and/or passive monitoring measurements with EDSS, 9HPT, SDMT, T25WT, and clinical disease worsening.

  12. Accuracy of RECLAIM prognostic models for disease progression

    Time frame: baseline - month 24

    Accuracy of predicted disease progression of AI prognostic models developed in the RECLAIM study (https://clinicaltrials.gov/study/NCT06280755) using baseline data, and actual clinical disease progression at month 24

Sponsors and collaborators

Lead sponsor

icometrix

Industry

Collaborators

  • Casa di Cura IGEA
  • Charite University, Berlin, Germany
  • General University Hospital, Prague
  • Ruhr University of Bochum
  • Technische Universität Dresden

Registry information

Acronym: PROCLAIM

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Jun 22, 2025
Registry last updated
Dec 9, 2025

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.

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