Amyotrophic lateral sclerosis (ALS) or Lou Gehrig disease is a rare, clinically heterogeneous, progressive, neurodegenerative disease that affects upper motor neurons (UMNs) in the frontal lobe and lower motor neurons (LMNs) in the brainstem and spinal cord . In the United States, the reported incidence is approximately two new cases each year per 100,000, and prevalence is between 5 and 7 cases per 100,000 . The cause of the disease is unknown and is sporadic in more than 95% of cases. Only 2% of cases are caused by mutations in the superoxide dismutase gene . The disease is incurable, and there are currently two drugs approved by the Food and Drug Administration, riluzole and edaravone, that have been somewhat effective in prolonging the lives and reducing decline in daily function of affected individuals . Even though ALS predominantly affects motor function, 50% of patients experience associated cognitive impairment, and 2%–3% have accompanying frontotemporal dementia .
The motor function phenotypes in ALS are heterogeneous and are typically determined by three independent attributes: body region of onset, relative mix of UMN and LMN involvement, and rate of progression . LMN dysfunction is diagnosed with electromyography and muscle biopsy; however, demonstrating UMN involvement, which is critical for monitoring disease progression and treatment efficacy, is much more challenging and has been the focus of neural imaging .
Several research groups have tried to develop magnetic resonance imaging (MRI)-based biomarkers that can reliably detect and quantify the degree of UMN involvement, correlate with severity and regional distribution of motor dysfunction, and predict disease progression. Findings on conventional MRI in patients with ALS, fluid attenuated inversion recovery (FLAIR) high signal intensity in the white matter corresponding to the corticospinal tracts, and T2 low-signal intensity in the motor cortex are neither sensitive nor specific for this disease . More advanced MRI methods including high-resolution volumetric imaging, susceptibility-weighted imaging, diffusion tensor imaging (DTI), proton MR spectroscopy (MRS), perfusion imaging, magnetization transfer imaging, and functional imaging, supported by sophisticated image processing tools such as surface- and voxel-based morphometry, as well as quantitative susceptibility mapping, have the potential for providing effective imaging biomarkers for ALS . Primary motor cortical thinning, based on surface-based morphometry, has been shown to be a sensitive diagnostic marker for ALS; however, the correlation with clinical sign and symptoms remains unclear . T2* hypointensity scores, presumably secondary to excessive iron deposition in the motor cortex strongly correlated with Revised ALS Functional Rating Scale (ALSFRS-R) . DTI-derived parameters such as mean diffusivity and fractional anisotropy provide reproducible and quantitative alterations along the corticospinal tracts . However, correlations between these parameters and clinical measures including UMN score and ALSFRS-R have been inconsistent. Compared to healthy controls, MRS-derived parameters, N-Acetyl Aspartate (NAA), NAA/Cho, and NAA/Cr have demonstrated significant reduction in the motor cortex in patients with ALS with reported recovery after a short course of treatment with riluzole, underscoring the potential for MRS in monitoring the treatment efficacy . Correlations between resting state as well as task-related functional imaging and rapidity of disease progression and duration remain weak and inconsistent . Recently, multimodal MRI of the spinal cord, including volumetric imaging, DTI, and magnetization transfer imaging in patients with ALS, has been shown to be a better predictor of survival than clinical variables .
In this issue of Academic Radiology , Fabes et al. presented an effective imaging biomarker for ALS, based on FLAIR imaging. They compared normalized quantitative FLAIR signal intensity from the corpus callosum and corticospinal tracts between patients and controls and across patient subgroups (classic ALS, primary lateral sclerosis, versus flail arm). In the longitudinal portion of their study, the authors correlated rate of change in normalized quantitative FLAIR with rate of decline in ALSFRS-R and executive function. Their interesting results showed significantly higher signal intensity in patients compared to controls, increased accuracy of patient subgroup classification when quantitative FLAIR signal intensity was added to rate of change in ALSFRS-R and UMN scores, and a correlation between rate of change in signal intensity in the corticospinal tracts and decline in ALSFRS-R and executive function. The advantages of their imaging biomarker include reliance on conventional sequences that do not require extra scan time for typically disabled patients, and hence makes easier follow-up imaging as the disease progresses; quantitative nature of their method, which produces more objective and reproducible results; and ability to provide strong phenotype subgroup classification and to correlate with decline in executive function and ALSFRS-R. Further validation of their imaging biomarker with larger cohorts of patients with various phenotypes of ALS is needed, and its incorporation into a multimodal MRI approach may prove to be quite a robust surrogate marker for disease stratification and prognostication, as well as monitoring response to new therapies.
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