Volumetric MRI is a promising outcome measure of muscle reinnervation.

The development of outcome measures that can track the recovery of reinnervated muscle would benefit the clinical investigation of new therapies which hope to enhance peripheral nerve repair. The primary objective of this study was to assess the validity of volumetric Magnetic Resonance Imaging (MRI) as an outcome measure of muscle reinnervation by testing its reproducibility, responsiveness and relationship with clinical indices of muscular function. Over a 3-year period 25 patients who underwent nerve transfer to reinnervate elbow flexor muscles were assessed using intramuscular electromyography (EMG) and MRI (median post-operative assessment time of 258 days, ranging from 86 days pre-operatively to 1698 days post- operatively).

Use of statistical parametric mapping (SPM) to enhance electrical impedance tomography (EIT) image sets.

Use of statistical parametric mapping (SPM), which is widely used in analysis of neuroimaging studies with fMRI and PET, has the potential to improve quality of EIT images for clinical use. Minimal modification to SPM is needed, but statistical analysis based on height, not extent thresholds, should be employed, due to the 20-80% variation of the point spread function, across EIT images. SPM was assessed in EIT images reconstructed with a linear time difference algorithm utilizing an anatomically realistic finite element model of the human head.

A new analytical method to diagnose congenital myasthenia with stimulated single-fiber electromyography.

Stimulated single-fiber electromyography (SSF-EMG) is useful to assess neuromuscular junction (NMJ) abnormalities in children. Conventionally mean consecutive difference (MCD) analysis measures the jitter for each muscle-fiber potential. We present a new algorithm that analyzes the entire SSF-EMG waveform.