New developments in imaging in ALS

Abstract

Neuroimaging in ALS has contributed considerable academic insights in recent years demonstrating genotype-specific topological changes decades before phenoconversion and characterising longitudinal propagation patterns in specific phenotypes. It has elucidated the radiological underpinnings of specific clinical phenomena such as pseudobulbar affect, apathy, behavioural change, spasticity, and language deficits. Academic concepts such as sexual dimorphism, motor reserve, cognitive reserve, adaptive changes, connectivity-based propagation, pathological stages, and compensatory mechanisms have also been evaluated by imaging. The underpinnings of extra-motor manifestations such as cerebellar, sensory, extrapyramidal and cognitive symptoms have been studied by purpose-designed imaging protocols. Clustering approaches have been implemented to uncover radiologically distinct disease subtypes and machine-learning models have been piloted to accurately classify individual patients into relevant diagnostic, phenotypic, and prognostic categories. Prediction models have been developed for survival in symptomatic patients and phenoconversion in asymptomatic mutation carriers. A range of novel imaging modalities have been implemented and 7 Tesla MRI platforms are increasingly being used in ALS studies. Non-ALS MND conditions, such as PLS, SBMA, and SMA, are now also being increasingly studied by quantitative neuroimaging approaches. A unifying theme of recent imaging papers is the departure from describing focal brain changes to focusing on dynamic structural and functional connectivity alterations. Progressive cortico-cortical, cortico-basal, cortico-cerebellar, cortico-bulbar, and cortico-spinal disconnection has been consistently demonstrated by recent studies and recognised as the primary driver of clinical decline. These studies have led the reconceptualisation of ALS as a "network" or "circuitry disease".

Keywords: Amyotrophic lateral sclerosis; Biomarkers; Cerebellum; Frontotemporal dementia; Magnetic resonance imaging; Motor neuron disease; Neuroimaging; Primary lateral sclerosis.

Fig. 1

Expanding the clinical and anatomical spectrum of ALS from motor symptoms to extra-motor manifestations, BMI body mass index

Fig. 2

The reconceptualisation of ALS as a “network disease”: from the description of focal cerebral changes to the evaluation of circuitry dysfunction

Fig. 3

Longitudinal imaging in ALS captures progressive neurodegenerative processes spanning the entire biological course of the disease. Machine-learning frameworks may be developed into viable diagnostic and prognostic applications

Fig. 4

The role of neuroimaging in ALS: testing academic hypotheses and the development of clinical applications