University of Illinois at Urbana-Champaign
Power doppler ultrasound for peripheral perfusion imaging
Abstract
dc:descriptionPower-Doppler ultrasound (PD-US) imaging has the potential to routinely monitor blood perfusion changes without contrast enhancement. PD-US imaging is sensitive to blood cell motion echoes in the microvasculature, but it is generally nonspecific due to difficulties in filtering out nonblood echoes. However, with the clutter and noise power minimized to achieve PD-US images that predictably map relative perfusion, PD-US methods can reliably indicate spatiotemporal variations in muscle perfusion. To achieve this, a spatial registration method is applied to echo signals prior to principal components analysis (PCA)-based clutter and noise filtering. This thesis explores the computational model of tissue perfusion that simulates typical in vivo conditions, which considers directed and diffuse blood perfusion states in a field of moving clutter and noise. Echo-signal simulations primarily demonstrate sub-sample spatial registration of echo frames prior to clutter filtering over a range of tissue motion seen clinically. Registration narrows the eigen-spectrum of the tissue clutter component to a point where PCA filters are highly efficient at eliminating clutter power, minimizing in-plane clutter motion effectively. However, the clutter filter's ability to pass blood-signal power depends on the spatial patterns of blood cell movement in tissues. Symmetric Doppler spectra are commonly observed for peripheral perfusion data, indicating nondirectional or diffuse perfusion patterns for which PD-US methods predictably pass 30-50% of the true blood-signal power. Therefore, spatial registration methods can significantly improve the reliability of PD-US imaging to represent tissue perfusion. In-vivo experiments on mice confirm that non-contrast PD-US imaging can reliably monitor relative spatiotemporal changes in muscle perfusion. PD-US imaging showed the occlusion and re-perfusion process clearly. This study supports the development of PD-US methods for monitoring perfusion changes in patients at risk for peripheral artery disease.
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Electrical & Computer Engr
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2023
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Dai, Bingze
- Contributors dc:contributor
-
- Insana, Michael F
Subjects
dc:subject × 6Rights
dc:rights- Statement dc:rights
-
- Copyright 2023 Bingze Dai
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/121423