Developing an in-vivo physiological porcine model of inducing acute atraumatic compartment syndrome towards a non-invasive diagnosis using shear wave elastography

Jong Woo Kang, Jong Woong Park, Tae Hyun Lim, Keun Tae Kim, Song Joo Lee

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Compartment syndrome (CS) is a pathological event caused by elevated intracompartmental pressure (ICP); however, changes from the onset of inducing atraumatic CS remained unclear. The study aimed to investigate the physiological changes in a newly developed in vivo porcine acute atraumatic CS model. CS was induced by ischemia–reperfusion injury in the left hind leg of fourteen pigs divided into an echogenicity group (EG) and a shear wave elastography group (SEG). Echogenicity was measured in EG, and shear elastic modulus (SEM) was measured in SEG seven times before, at the onset of inducing CS, and every 30 min after the onset over eight hours. Simultaneously, ICP, blood pressure, and muscle perfusion pressure (MPP) were also measured in both groups. Our results indicate that SEM of the experimental leg in SEG significantly increased as CS developed compared to the control leg (p = 0.027), but no statistical difference in the echogenicity in EG was found between the experimental leg and control leg. There were also significant correlations between SEM and ICP (p < 0.001) and ICP and MPP (p < 0.001). Our method and findings can be a basis to develop a non-invasive diagnostic tool using a shear wave elastography for atraumatic CS.

Original languageEnglish
Article number21891
JournalScientific reports
Volume11
Issue number1
DOIs
Publication statusPublished - 2021 Dec

Bibliographical note

Publisher Copyright:
© 2021, The Author(s).

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Developing an in-vivo physiological porcine model of inducing acute atraumatic compartment syndrome towards a non-invasive diagnosis using shear wave elastography'. Together they form a unique fingerprint.

Cite this