Hydrogel Design Optimization for Measuring Ultrasound Using Laser Doppler Vibrometry

Over the past decade, work in the medical field has been geared towards the development of ultrasonic systems for medical diagnostic imaging applications. Compared to other imaging modalities, patient contact is a significant source of variability unique to ultrasound. Contact sensitive applications such as remote patient/neonatal monitoring, tracking wound healing, and imaging of sensitive skin areas can significantly benefit from a non-contact ultrasound system. Laser ultrasound (LUS) imaging offers potential advancements over conventional ultrasound, especially in achieving highresolution imaging of tissue structures and the elimination of liquid coupling mediums and probe-to-body contact. The thesis presents an innovative approach to enhance the performance of LUS signals in human tissue by utilizing hydrogels, hydrophilic polymeric materials known for high-water content and biocompatibility, as a surface treatment layer for ultrasound detection and generation. The system integrates and synchronizes linear stage automation, transducer acoustic wave generation, laser doppler vibrometry (LDV), and LabView integration. High speed data acquisition (DAQ) through a dedicated Pico Technology setup streams digitized data directly to the host PC. LDV measurements highlighted the crucial role of bead concentration within hydrogels. Velocity amplitude measurements reflected an inverse relationship with increasing bead concentrations, peaking at approximately 700 mm/s. However, higher bead concentrations yielded better data accuracy and reduced noise, suggesting an optimal range for bead concentration.A comparison of noise ranges across different hydrogel bead concentrations highlighted improved data quality and precision for concentrations exceeding 0.015 g/mL. Furthermore, laser-based measurements indicated that hydrogel with a bead concentration of 0.02 g/mL provided consistent and enhanced signal amplitude. The findings present a pivotal step towards optimizing LUS for clinical applications, opening new doors in medical imaging and diagnostics.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Caraballo-Justiniano, Eugenio

Advisor dc:contributor.advisor

• Anthony, Brian W.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/152810

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/152810