Quantitative evaluation of rat sciatic nerve degeneration using high-frequency ultrasound

Yuanshan Wu, Victor Barrere, Aiguo Han, Michael P. Andre, Elisabeth Orozco, Xin Cheng, Eric Y. Chang, Sameer B. Shah

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we evaluated the utility of using high-frequency ultrasound to non-invasively track the degenerative process in a rat model of peripheral nerve injury. Primary analyses explored spatial and temporal changes in quantitative backscatter coefficient (BSC) spectrum-based outcomes and B-mode textural outcomes, using gray level co-occurrence matrices (GLCMs), during the progressive transition from acute to chronic injury. As secondary analyses, correlations among GLCM and BSC spectrum-based parameters were evaluated, and immunohistochemistry were used to suggest a structural basis for ultrasound outcomes. Both mean BSC spectrum-based and mean GLCM-based measures exhibited significant spatial differences across presurgical and 1-month/2-month time points, distal stumps enclosed proximity to the injury site being particularly affected. The two sets of parameters sensitively detected peripheral nerve degeneration at 1-month and 2-month post-injury, with area under the receiver operating charactersitic curve > 0.8 for most parameters. The results also indicated that the many BSC spectrum-based and GLCM-based parameters significantly correlate with each other, and suggested a common structural basis for a diverse set of quantitative ultrasound parameters. The findings of this study suggest that BSC spectrum-based and GLCM-based analysis are promising non-invasive techniques for diagnosing peripheral nerve degeneration.

Original languageEnglish (US)
Article number20228
JournalScientific reports
Volume13
Issue number1
DOIs
StatePublished - Dec 2023
Externally publishedYes

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Quantitative evaluation of rat sciatic nerve degeneration using high-frequency ultrasound'. Together they form a unique fingerprint.

Cite this