CALD is an inflammatory demyelinating disease that causes severe motor and cognitive deficit leading to rapid death. Hematopoietic stem cell transplantation (HSCT) can halt neuroinflammation in CALD through the replacement of microglia (i.e., brain immune system) but only if performed during its early phase.
Using standard brain MRI, it is estimated that only 30% of adult CALD patients are identified. Complex and lengthy clinical evaluations together with MRI reading from experts improve CALD detection but are not available in routine clinical practice.
Diffusion tensor imaging is a quantitative microstructural technique that can identify neuroinflammation at a very early stage. Still, its implementation in clinical practice has been very limited due to high inter-center measurements variability and bias due to data quality issues. The approach we will use solves these problems by introducing an automatic calibration and standardization with systematic quality control enabling the use of all MRI scanners in clinical settings.
The innovative aspect of this project lies on the validation of an expert-independent prognosis biomarker able to specifically identify patients at high-risk to convert to CALD so that treatment can be initiated at the early stage of neuroinflammation.
We aim to demonstrate that this tool has at least a 2-fold sensitivity compared to the current standard of care.
> 18 years old
Male gender
Genetically diagnosed with ALD by carrying an ABCD1 pathogenic variant
Signed written informed consent
Patient with non-arrested CALD
Other neurological conditions such as brain tumour, stroke or a traumatic head injury
Contraindication to MRI (claustrophobia, implanted metal components in the head, panic disorder, epilepsy)
People under legal protection measure (tutorship, curatorship or safeguard measures)
Assistance Publique - Hôpitaux de Paris
Lead sponsor
Braintale
Collaborator