Notice and Invitation
Oral Defense of Master’s Thesis
Bioengineering Department
College of Engineering and Computing, George Mason University
Cristian Rios
Bachelor of Science, Bioengineering and Economics, George Mason University, 2017
Characterization of Myofascial Trigger Points Utilizing an Automated Shear Wave Elastography Approach
Monday, November 27, 2023 at 3:00 pm
Peterson 2000
In-person preferred.
Teams meeting ID: 243 038 714 046
Passcode: 9PPrds
All are invited to attend.
Committee
Dr. Siddhartha Sikdar, Thesis Director
Dr. Parag Chitnis, Chair
Dr. Jay Shah
Abstract
MPS is a leading and challenging musculoskeletal chronic pain problem, typically localized, that is well recognized but lacks a clear definition across the board. The lack of
clear definition is a result of limited epidemiology, pathophysiology, and diagnosis information for MPS. A key characteristic of MPS is having myofascial trigger points (MTrPs), defined as a palpable nodule within a taut band of a skeletal muscle and linked
to pain symptoms that are patient specific. Advances in ultrasound and shear wave elastography technologies to characterize MTrPs have shown merit to localize, determine hypoechogenicity properties, anisotropy properties of tissue, variance in blood flow distribution,
map tissue stiffness properties, understand impact on surrounding tissue, provide targeted and local treatment, and the role of fascia within MTrPs. Based on previous research advances, our group focused on using US-SWE to characterize the tissue anisotropy
of MTrPs from different population groups with the aim of extracting potential biomarkers for detecting and characterizing MTrPs. However, to address current limitations of SWE and data acquisition, our group investigated the merit of using an automated SWE
method for improving reproducibility and minimizing variance on extracted data. In this research, we conducted a total of three pilot studies in the following areas: 1) reproducibility of US-SWE on a single device, 2) reproducibility of US-SWE across multiple
devices, and 3) evaluating different population groups with MTrPs. The results of this study showed that the reproducibility within a single US-SWE device still has an evident amount of variance on the images extracted. Additionally, the reproducibility across
multiple US-SWE devices when evaluating the same muscle group still shows a significant amount of variance across devices. Given this, the results demonstrated that using the shear anisotropy ratio (SAR) as an extracted feature for distinguishing between different
populations groups has significant merit. However, SAR is affected by the variance observed from a given US-SWE device and data acquisition methodology. This data highlights the value of using an automated US-SWE method and potential extracted features, like
SAR, as having merit of being biomarkers for characterizing and detecting MTrPs.