Abstract

ObjectiveElectrical impedance myography (EIM) is a promising biomarker for amyotrophic lateral sclerosis (ALS). A key issue is how best to utilise the complex high dimensional, multi-frequency data output by EIM to fully characterise the progression of disease. MethodsMuscle volume conduction properties were obtained from EIM recordings of the tongue across three electrode configurations and 14 input frequencies (76 Hz–625 kHz). Analyses of individual frequencies, averaged EIM spectra and non-negative tensor factorisation were undertaken. Longitudinal data were collected from 28 patients and 17 healthy volunteers at 3-monthly intervals for a maximum of 9 months. EIM was evaluated against the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) bulbar sub-score, tongue strength and an overall bulbar disease burden score. ResultsLongitudinal changes to individual patient EIM spectra demonstrated complex shifts in the spectral shape. At a group level, a clear pattern emerged over time, characterised by an increase in centre frequency and general shift to the right of the spectral shape. Tensor factorisation reduced the spectral data from a total of 168 data points per participant per recording to a single value which captured the complexity of the longitudinal data and which we call tensor EIM (T-EIM). The absolute change in tensor EIM significantly increased within 3 months and continued to do so over the 9-month study duration. In a hypothetical clinical trial scenario tensor EIM required fewer participants (n = 64 at 50% treatment effect), than single frequency measures (n range 87–802) or ALSFRS-R bulbar subscore (n = 298). ConclusionsChanges to tongue EIM spectra over time in ALS are complex. Tensor EIM captured and quantified disease progression and was more sensitive to changes than single frequency EIM measures and other biomarkers of bulbar disease. SignificanceObjective biomarkers for the assessment of bulbar disease in ALS are lacking. Tensor EIM enhances the biomarker potential of EIM data and can improve bulbar symptom monitoring in clinical trials.

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