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Estimating Myofiber Size With Electrical Impedance Myography: a Study In Amyotrophic Lateral Sclerosis MICE.


ABSTRACT: INTRODUCTION:A method for quantifying myofiber size noninvasively would find wide use, including primary diagnosis and evaluating response to therapy. METHODS:Using prediction algorithms, including the least absolute shrinkage and selection operator, we applied multifrequency electrical impedance myography (EIM) to amyotrophic lateral sclerosis superoxide dismutase 1?G93A mice of different ages and assessed myofiber size histologically. RESULTS:Multifrequency EIM data provided highly accurate predictions of myofiber size, with a root mean squared error (RMSE) of only 14% in mean myofiber area (corresponding to?±?207?µm2 for a mean area of 1,488?µm2 ) and an RMSE of only 8.8% in predicting the coefficient of variation in fiber size distribution. DISCUSSION:This impedance-based approach provides predictive variables to assess myofiber size and distribution with good accuracy, particularly in diseases in which myofiber atrophy is the predominant histological feature, without the requirement for biopsy or burdensome quantification. Muscle Nerve 58: 713-717, 2018.

SUBMITTER: Kapur K 

PROVIDER: S-EPMC6246784 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Estimating Myofiber Size With Electrical Impedance Myography: a Study In Amyotrophic Lateral Sclerosis MICE.

Kapur Kush K   Nagy Janice A JA   Taylor Rebecca S RS   Sanchez Benjamin B   Rutkove Seward B SB  

Muscle & nerve 20180902 5


<h4>Introduction</h4>A method for quantifying myofiber size noninvasively would find wide use, including primary diagnosis and evaluating response to therapy.<h4>Methods</h4>Using prediction algorithms, including the least absolute shrinkage and selection operator, we applied multifrequency electrical impedance myography (EIM) to amyotrophic lateral sclerosis superoxide dismutase 1 G93A mice of different ages and assessed myofiber size histologically.<h4>Results</h4>Multifrequency EIM data provi  ...[more]

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