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Amyotrophic lateral sclerosis (ALS) has distinctive and well-established radiological signatures which are increasingly utilised in advanced machine-learning algorithms heralding exciting novel diagnostic applications.1 2
Quantitative spinal cord (SC) imaging provides a unique opportunity to evaluate both upper (UMN) and lower motor neuron (LMN) involvement, and recent studies have showcased its biomarker potential in ALS through reliable cross-sectional area (CSA) measurements, evaluation of diffusion tensor imaging (DTI) parameters, correlations with clinical measures and survival.3 4 Nevertheless, no studies have evaluated the diagnostic accuracy of SC metrics in ALS to date. Accordingly, the objective of this study was to evaluate the effectiveness of multimodal cervical imaging in distinguishing ALS from healthy controls (HC) using a random forest (RF) classification algorithm.5
Sixty patients with ALS and 45 age-matched controls gave informed consent to participate in a prospective neuroimaging study in the Pitié-Salpêtrière Hospital in Paris. Participating patients had probable or definite ALS according to the revised El-Escorial criteria. Patients with cognitive impairment, relevant comorbidities and taking medications other than riluzole were excluded from the study.
Cervical cord data were acquired from C2 to C7 on a 3T MRI system (Siemens TIM Trio). A T2-weighted three-dimensional turbo spin echo protocol was used for structural imaging with an isotropic voxel size 0.9×0.9×0.9 mm3, field of view (FOV)=280×280 mm2, 52 sagittal slices, repetition time (TR)=1500 ms, echo time (TE)=120 ms and acceleration factor=3.
DTI data were acquired using a single-shot echo-planar imaging sequence. The acquisition was cardiac gated with a voxel size=1×1×5 mm3, FOV=128×128 mm2, TR=700 ms, TE=96 ms, acceleration factor=2, b value=1000 s/mm2, 64 diffusion encoding directions and four averages.
3D gradient echo images were used …
Contributors GQ had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. M-MEM, GQ and SD actively participated in the design of the study, in the preparation of MRI protocol and in the establishment of MRI acquisition settings. TL and P-FP selected patients with ALS to include in the study and performed clinical and diagnostic evaluation. MRI acquisition, imaging data treatment and analysis were performed by GQ, M-MEM and SD. Statistical analysis was performed by GQ. Critical revision of the manuscript for important intellectual content was done by GQ, P-FP and PB. P-FP and VM-P obtained funding for the study. P-FP, VM-P, SD and M-MEM were responsible for the administrative, technical or material support. P-FP did the supervision.
Funding This study was supported by the Association Française contre les Myopathies-Téléthon (AFM-Téléthon) and the Institut pour la Recherche sur la Moelle épinière et l’Encéphale (IRME). The research leading to these results has also received funding from the program ‘ Investissements d’Avenir’ ANR-10-IAIHU-06. PB is supported by the Health Research Board Ireland (HRB EIA-2017-019), the Irish Institute of Clinical Neuroscience IICN— Novartis Ireland Research Grant (IICN 2016), and the Iris O’Brien Foundation. GQ is supported by a PhD grant by the University of Padova (Italy).
Competing interests None declared.
Patient consent Obtained.
Ethics approval Ethics Committee of Pitié-Salpetrière Hospital, Paris, France.
Provenance and peer review Not commissioned; externally peer reviewed.
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