Methodologies for Quantifying and Characterizing Strain Fields Resulting from Focused Ultrasound Therapies in Mouse Achilles Tendon using Ultrasound Imaging and Digital Image Correlation

Tendinopathy is a common pathology of tendons characterized by pain and a decrease in function resulting from changes in the tissue's structure and/or composition due to injury. Diagnosis of tendinopathy is determined by the qualitative analysis of a trained physician usually with assistance from an imaging modality. Although physicians can often identify tendinopathy, there are no quantitative metrics to evaluate tendon fatigue, damage, or healing. Physical therapy (PT) is a common treatment for patients with tendinopathy, and recent studies have investigated Focused Ultrasound (FUS) for its treatment of tendons. Developments in the use of FUS as a therapeutic have led to studies of the underlying mechanisms by which it operates. Digital Image Correlation (DIC) is a non-contact method of quantifying tissue displacements and strains of a deforming material using high resolution imaging DIC programs can evaluate and interpolate strain data by applying statistical image processing algorithms and solid continuum mechanics principles using a set of sequential image frames capturing the mechanical deformation of the specimen during testing. The studies presented in this thesis investigate methodologies for using DIC with ultrasound imaging of mouse Achilles tendons to characterize strains resulting from FUS therapies. The first method is based upon an orthogonal configuration of therapy and imaging transducers while the second investigates a coaxial experimental configuration. This work explores DIC as a viable means of quantifying the mechanical stimulation caused by FUS therapies on tendon tissue through ultrasound imaging to better understand the underlying mechanisms of FUS therapy.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Engineering Mechanics

Department dc:contributor.department

Engineering Science and Mechanics

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2022

Author dc:creator

• Salazar, Steven Anthony

Chair dc:contributor.committeechair

• Wang, Vincent M.

Committee members dc:contributor.committeemember

• Vlaisavljevich, Eli
• Arena, Christopher Brian

• Digital Image Correlation
• Focused Ultrasound
• Tendinopathy

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:35348

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/111468