MRI Biomarkers Gain Ground as Endpoints in Neurodegenerative Disease Trials and Diagnosis

Quantitative neuroimaging measures are emerging as critical biomarkers for both guiding clinical trials and improving diagnosis in a range of neurodegenerative diseases, according to recent consensus statements and research reviews. Two separate bodies of work highlight how magnetic resonance imaging (MRI) techniques can provide objective, sensitive measures of disease pathology and progression, supplementing or enhancing traditional clinical assessments.

In hereditary cerebellar ataxias, which include spinocerebellar ataxias SCA1, SCA2, and SCA3, as well as Friedreich ataxia, the Ataxia Global Initiative MRI Biomarkers Working Group has published a consensus statement reviewing candidate MRI end-points for clinical trials. These diseases are characterized by progressive gait ataxia, reduced fine motor coordination, and speech impairments secondary to neurodegeneration primarily affecting the cerebellum, brainstem, and/or spinal cord. The first disease-modifying therapy for any inherited ataxia was approved by the US Food and Drug Administration and the European Medicines Agency for treatment of Friedreich ataxia in 2022, and a rapidly increasing number of other candidate treatments are in the clinical trial pipeline. These candidates include small-molecule therapies and gene silencing or gene editing interventions.

Clinical outcome assessments, such as the Scale for the Assessment and Rating of Ataxia and the Friedreich Ataxia Rating Scale, are the current gold-standard trial end-points. However, natural history studies indicate that use of these scales necessitates sample sizes of 71–274 people per arm to detect a 50% slowing of disease with 80% statistical power in two-group interventional trials lasting one year. This requirement poses a barrier to trial feasibility in these rare diseases. The consensus statement provides evidence-based, disease-specific recommendations for MRI end-points to overcome these limitations. Candidate imaging measures include regional cerebellar and brainstem volume, spinal cord structure, white matter microstructure via diffusion MRI, and tissue composition via magnetic resonance spectroscopy and susceptibility MRI.

A parallel advance is occurring in the use of functional MRI (fMRI) for diagnosing and understanding multiple system atrophy (MSA). MSA is a neurodegenerative disorder characterized by α-synuclein pathology, autonomic dysfunction, parkinsonism, and cerebellar ataxia. The peak age of onset is in the sixth decade of life, with a current estimated prevalence of 1.9–4.9 per 100,000 people and a median survival of 6–10 years from symptom onset. The disease is classified into two subtypes: the parkinsonian subtype (MSA-P) and the cerebellar subtype (MSA-C), based on core symptoms.

Early diagnosis of MSA remains difficult due to the substantial overlap of initial motor symptoms with other parkinsonian syndromes, including Parkinson's disease and progressive supranuclear palsy. Recent research demonstrates that resting-state fMRI can capture subtype-specific network connectivity patterns, reflecting the respective underlying pathologies. The parkinsonian subtype shows predominant basal ganglia–cortical disruption, while the cerebellar subtype shows cerebellar–cortical disconnection. Furthermore, fMRI can distinguish MSA from Parkinson's disease and progressive supranuclear palsy based on characteristic disruptions in cerebellar-cortical network connectivity.

Beyond diagnosis, fMRI has shown potential in evaluating treatment effects. Neuromodulatory interventions such as transcranial magnetic stimulation have been associated with measurable network changes. Existing studies on fMRI in MSA, however, remain constrained by small sample sizes, single-center designs, and methodological variability. Future research directions include large, multicenter trials and standardized imaging protocols.

For the ataxias, the consensus statement also recommends further research to address remaining knowledge gaps. The objective characteristics of imaging biomarkers—objectivity, reproducibility, sensitivity to change, and applicability across a broad range of disease stages—are cited as favorable for their use as surrogate or early-phase primary outcome measures for treatment monitoring and participant selection. The ability to identify gene-positive individuals before symptom manifestation in hereditary ataxias raises the possibility of enrolling participants into preventive trials, but biomarker data are key for participant selection and outcome monitoring in such trials.