Multiple Sclerosis Clinical Trial
— INFLANETOfficial title:
Study of Neuroinflammation in Multiple Sclerosis by PET-MRI Imaging Using the Radiotracer ([18F]-DPA-714) : a Multicentre Cohort Study
The Service Hospitalier Frédéric-Joliot (SHFJ) and Paris Brain Institute (ICM) groups have identified [18F]-DPA-714 as a promising second-generation TSPO tracer, a macromolecule overexpressed in neuroinflammatory conditions, for PET imaging. They have also developed a non-invasive quantification methodology, enabling the generation of individual neuroinflammation maps in MS patients. Recent findings from [18F]-DPA-714 PET imaging in MS patients revealed that most of the white matter lesions contained a smoldering component, even when considered inactive on MRI, and that their neuroinflammatory profiles were associated with longitudinal disability worsening. The Inflanet project aims to leverage a unique consortium comprising French radiochemists, radiopharmacists, nuclear medicine/neuroimaging experts, and MS neurologists to establish the first national network dedicated to [18F]-DPA-714 PET imaging in MS, so far limited to monocentric studies. The objectives of the INFLANET project are (1) to conduct the first multicenter study assessing neuroinflammation in patients with active MS using [18F]DPA-714 PET tracer, and (2) to establish a methodology suitable for the quantification of multicenter PET data obtained with [18F]DPA-714. The INFLANET initiative aims to disseminate TSPO PET within the French MS research community, thereby opening the unique perspective of future large-scale, multicenter studies. These endeavors are expected to enhance our capacity to predict diseases, stratify patients, and assess new therapeutic interventions.
| Status | Not yet recruiting |
| Enrollment | 41 |
| Est. completion date | March 1, 2026 |
| Est. primary completion date | March 1, 2026 |
| Accepts healthy volunteers | Accepts Healthy Volunteers |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility | Inclusion Criteria: RRMS patients: - Age between 18 and 55 years old - RRMS according to the 2017 Mc Donald criteria - At least 9 supra-tentorial white matter lesions on T2/FLAIR MRI - Last treatment with methylprednisolone should have been performed at least 1 month before PET examinations - No current disease modifying therapy - Indication for a highly active disease modifying treatment: Natalizumab, anti CD20 antibody, Alemtuzumab, sphingosine-1 phosphate modulator, or cladribine. This will consist either as patients with an active form of relapsing MS or patients who have experienced two relapses during the previous year - Affiliation to a social security scheme or beneficiary of such a scheme (except "Aide Médicale d'Etat") Healthy Volunteers: - Age between 18 and 55 years old - Without any evolutive pathology - Able to understand the study objectives and procedures - Affiliation to a social security scheme or beneficiary of such a scheme (except "Aide Me´dicale d'Etat") Exclusion Criteria: For all participants: - Any reasons, which does not allow to perform MRI, including claustrophobia, the implant of a pace-maker or the presence of an intra-ocular foreign body, (a contra-indication questionnaire will be filled in beforehand) - Realization of any test using radioactivity within the last 12 months - Low Affinity Binding profile (analyse of TSPO polymorphism done at screening visit) - Pregnancy, breast-feeding, lack of efficient contraception for women of childbearing potential - Current symptoms of severe or uncontrolled renal, hepatic, hematological, gastrointestinal, pulmonary or cardiac disease, or any other chronic neurological diseases - Unwillingness to be informed in case of unexpected MRI abnormality (with a significant medical anomaly) - Patient under legal protection - Participation in another interventional study or being in the exclusion period at the end of a previous study RRMS patients: - Hypersensitivity to gadoteric acid - Meglumine or any drug containing gadolinium - Severe renal insufficiency (creatinine clearance < 60mL/min and GFR <30ml / min / 1.73m2). |
| Country | Name | City | State |
|---|---|---|---|
| France | CERMEP | Lyon | |
| France | Département de Neurologie,Pierre Wertheimer Neurological Hospital | Lyon | |
| France | CIC Neurosciences, GH Pitié-Salpêtrière | Paris | |
| France | Centre Eugène Marquis | Rennes | |
| France | Service de Neurologie, CHU Pontchaillou | Rennes |
| Lead Sponsor | Collaborator |
|---|---|
| Assistance Publique - Hôpitaux de Paris |
France,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | To quantify the smoldering component of white matter lesions in people with MS, as compared with [18F]-DPA-714 binding in the white matter of HC who underwent a PET a acquisition with the same camera camera than patients in each center. | The respective proportion of lesions classified as homogeneously active, rim active and inactive for every single patient with MS. Classification of lesions will be based on predefined data-driven threshold of activity in lesions subareas (Hamzaoui et al, 2023). | 26 month | |
| Secondary | To quantify for each patient the regional neuroinflammatory load, measured as [18F]-DPA-714 DVR, in specific regions of interest: total brain, normal appearing white matter, cortex, thalami, deep grey matter. | Regional mean and voxel wise individual maps of innate immune cells activation derived from baseline [18F]-DPA-714 PET : they will be expressed as mean DVR values and as percentage of voxel classified as "DPA+", for each region of interest: whole brain, NAWM, grey matter, cortex, thalami, deep grey matter, white matter T2 lesions, white matter T1 lesions. | 26 month | |
| Secondary | The MRI signatures of each lesional subtypes, and correlation between MRI metrics and [18F]-DPA-714 DVR in each region of interest. | MRI data: T1, T2, FLAIR, SWI, QSM, MTR, ihMT, diffusion collected at baseline. This will include the assessment of novel algorithms that have been generated through deep learning and attempt to reproduce PET using multimodal MRI datasets. | 26 month |
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