Literature DB >> 32828046

Quantitative ultrasound of the tongue: Echo intensity is a potential biomarker of bulbar dysfunction in amyotrophic lateral sclerosis.

C E McIlduff1, M G Martucci2, C Shin2, K Qi2, A K Pacheck2, H Gutierrez2, M Mortreux2, S B Rutkove2.   

Abstract

OBJECTIVES: To learn if quantitative ultrasound (QUS) distinguishes the tongues of healthy participants and amyotrophic lateral sclerosis (ALS) patients by echo intensity (EI) and to evaluate if EI correlates with measures of bulbar function.
METHODS: Ultrasound was performed along the midline of the anterior tongue surface in 16 ALS patients and 16 age-matched controls using a linear hockey stick 16-7 MHz transducer. A region of interest was manually drawn and then EI was determined for the upper 1/3 of the muscle. For patients, the ALS functional rating scale - revised (ALSFRS-R) was used to calculate bulbar sub-scores and the Iowa Oral Performance Instrument (IOPI) was used to measure tongue strength.
RESULTS: EI was significantly higher in ALS patients than in healthy participants (49.8 versus 37.8 arbitrary units, p < 0.01). In the patient group, EI was negatively correlated with ALSFRS-R bulbar sub-score (RS = -0.65, p < 0.01). An inverse correlation between EI and tongue strength did not reach significance (RS = -0.34, p = 0.28).
CONCLUSIONS: This study suggests that EI can differentiate healthy from diseased tongue muscle, and correlates with a standard functional measure in ALS patients. SIGNIFICANCE: Tongue EI may represent a novel biomarker for bulbar dysfunction in ALS.
Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Amyotrophic lateral sclerosis; Biomarker; Bulbar, Echo intensity; Tongue; Ultrasound

Mesh:

Substances:

Year:  2020        PMID: 32828046      PMCID: PMC8898046          DOI: 10.1016/j.clinph.2020.06.027

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  47 in total

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2.  Comparison of Tongue Characteristics Classified According to Ultrasonographic Features Using a K-Means Clustering Algorithm.

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  2 in total

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