The pathophysiological process common to neuropathies is fatty replacement of muscle tissue, more commonly known as intramuscular fat fraction (F.F). MRI is an imaging technique that enables us to distinguish between muscle and fat tissue, and thus to objectify in vivo structural changes within nerves and muscles in neuropathic patients. In addition to visualizing these changes, quantitative neuromuscular MRI (qMRI) can be used to quantify a number of biomarkers associated with these pathophysiological processes. Over the past few years, this procedure has become a relevant tool in a number of neuromuscular pathologies, such as acquired and hereditary neuropathies. Thanks to its non-ionizing nature and its ability to explore tissues in three dimensions, MRI is the technique of choice for evaluating these diseases, complementing the clinical and electrophysiological scores available.

In a context where numerous therapic strategies are being evaluated for the treatment of peripheral nervous system diseases, the clinical and electrophysiological scores currently available are proving inadequate for the detection of early change or a positive therapeutic effect. On the basis of a limited number of studies, quantitative MRI could provide much more sensitive therapeutic monitoring data over short periods of time which is crucial for future therapeutic trials.

The most interesting MRI biomarker to date would therefore be the FF, which represents the percentage of fatty infiltration of muscles following pathological nerve damage. Other MRI biomarkers, such as quantified magnetization transfer ratio (MTR), proton density (PD), water transverse relaxation time (wT2) and three-dimensional volume, enable us to study the degenerative and inflammatory phenomena at work in these neuropathies from different angles, detailing the nerve and muscle damage in patients compared with healthy controls or presymptomatic patients. In patients with Charcot-Marie-Tooth (CMT) neuropathy in particular, qMRI is the only tool to detect significant longitudinal variation over a one-year period, revealing an average increase in FF in the lower limbs of +1.5% over 12 months. Confirmation of these results and their extension to other neuropathies such as hereditary amyloid neuropathies (ATTR-PN) or acquired demyelinating neuropathies (ADN) is therefore justified, but requires the implementation of standardized longitudinal studies including these different pathologies.

As strong correlations between these MRI biomarkers and the main clinical scores have been demonstrated in several cross-sectional studies, the clinical value of this non-invasive tool is beyond doubt.

The main limitation to the clinical deployment of this technology remains the time required for the manual segmentation step to delineate the areas of interest. The ongoing development of new image analysis techniques, as well as the contribution of artificial intelligence and deep learning to the imaging data extraction process, are well on the way to solving this problem, but require continuous updating of practices to identify the most interesting MRI biomarkers, facilitate their extraction and thus measure their clinical application with a view to future therapeutic trials.

Inclusion Criteria:

• Male or female between 18 and 80 years of age,
• Patients who have freely given their consent to participate in this study,
• Patient with genetically confirmed hereditary CMT neuropathy
• or patient with an acquired demyelinating neuropathy such as typical PIDC or anti-MAG of typical form
• or a patient with a genetically confirmed pathogenic mutation in the transthyretin (TTRn) gene,
• Patients who are beneficiaries or entitled beneficiaries of a social security scheme.

Exclusion Criteria:

• Patients with co-morbidity or a history of other peripheral neuropathy,
• Patients with alcohol or psychoactive substance abuse,
• Patients with contraindications to MRI exploration: claustrophobia, pacemakers, Holter systems, IUDs, metal surgical clips, metal prostheses or implants (or other metal foreign bodies),
• Patient unable to perform the MRI due to severe handicap,
• Patient in a period of exclusion from another research protocol at the time of signing the consent/non-opposition form,
• Subjects covered by articles L1121-5 to 1121-8 of the French Public Health Code (minors, adults under guardianship or trusteeship, patients deprived of their liberty, pregnant or breast-feeding women),
• Persons who cannot read and understand the French language well enough to be able to give their consent to participate in research.