Objective: Electrical impedance myography (EIM) performed on the centre of the tongue shows promise in detecting amyotrophic lateral sclerosis (ALS). Lateral recordings may improve diagnostic performance and provide pathophysiological insights through the assessment of asymmetry. However, it is not known if electrode proximity to the muscle edge, or electrode rotation, distort spectra. We evaluated this using finite element-based modelling. Approach: Nine thousand EIM from patients and healthy volunteers were used to develop a finite element model for phase and magnitude. Simulations varied electrode proximity to the muscle edge and electrode rotation. LT-Spice simulations assessed disease effects. Patient data were assessed for reliability, agreement and classification performance. Main results: No effect on phase spectra was seen if all electrodes remained in contact with the tissue. Small effects on magnitude were observed. Cole-Cole circuit simulations indicated capacitance reduced with disease severity. Lateral tongue muscle recordings in both patients and healthy volunteers were reproducible and symmetrical. Combined lateral/central tongue EIM improved disease classification compared to either placement alone. Significance: Lateral EIM tongue measurements using phase angle are feasible. Such measurements are reliable, find no evidence of tongue muscle asymmetry in ALS and improve disease classification. Lateral measurements enhance tongue EIM in ALS.

Objective. Electrical impedance myography (EIM) shows promise as an effective biomarker in amyotrophic lateral sclerosis (ALS). EIM applies multiple input frequencies to characterise muscle properties, often via multiple electrode configurations. Herein, we assess if non-negative tensor factorisation (NTF) can provide a framework for identifying clinically relevant features within a high dimensional EIM dataset. Approach. EIM data were recorded from the tongue of healthy and ALS diseased individuals. Resistivity and reactivity measurements were made for 14 frequencies, in three electrode configurations. This gives 84 (2 × 14 × 3) distinct data points per participant. NTF was applied to the dataset for dimensionality reduction, termed tensor EIM. Significance tests, symptom correlation and classification approaches were explored to compare NTF to using all raw data and feature selection. Main Results. Tensor EIM provides highly significant differentiation between healthy and ALS patients (p < 0.001, AUROC = 0.78). Similarly tensor EIM differentiates between mild and severe disease states (p < 0.001, AUROC = 0.75) and significantly correlates with symptoms (ρ = 0.7, p < 0.001). A trend of centre frequency shifting to the right was identified in diseased spectra, which is in line with the electrical changes expected following muscle atrophy. Significance. Tensor EIM provides clinically relevant metrics for identifying ALS-related muscle disease. This procedure has the advantage of using the whole spectral dataset, with reduced risk of overfitting. The process identifies spectral shapes specific to disease allowing for a deeper clinical interpretation.

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease in urgent need of disease biomarkers for the assessment of promising therapeutic candidates in clinical trials. Raman spectroscopy is an attractive...

Raman spectroscopy shows promise as a biomarker for complex nerve and muscle (neuromuscular) diseases. To maximise its potential, several challenges remain. These include the sensitivity to different instrument configurations, translation across preclinical/human tissues and the development of multivariate analytics that can derive interpretable spectral outputs for disease identification. Nonnegative matrix factorisation (NMF) can extract features from high-dimensional data sets and the nonnegative constraint results in physically realistic outputs. In this study, we have undertaken NMF on Raman spectra of muscle obtained from different clinical and preclinical settings. First, we obtained and combined Raman spectra from human patients with mitochondrial disease and healthy volunteers, using both a commercial microscope and in-house fibre optic probe. NMF was applied across all data, and spectral patterns common to both equipment configurations were identified. Linear

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