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Proceedings Paper

Ultrasonic mechanical relaxation imaging of pH in biopolymers
Author(s): Mallika Sridhar; Huini Du; Claire Pellot-Barakat; Scott I. Simon; Michael F. Insana
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Paper Abstract

Ultrasonic Mechanical Relaxation (UMR) imaging is a new research technique for visualizing viscoelastic properties of tumors. Tissues behave mechanically as water-based polymers, similar to gelatin, with time-varying viscoelastic properties that depend on the chemical environment. We hypothesized that changes in pH, alter the polymer-fiber surface charge density that determines extent of polymer cross-linking. Gelatin samples with similar material properties and variable pH were prepared. A cone-plate viscometer measured the elastic as well as the viscous response of the polymer to a shear stress stimulus in the pH range of 6 to 8. To image local pH changes, two homogeneous gelatin samples were constructed, one made from buffered saline and the other was unbuffered. 0.05ml NaOH (pH 12) was injected into both samples and subsequent dynamic changes were imaged using UMR methods at 5, 20 and 50 minutes. UMR images include elastic strain and viscous creep relaxation maps produced by applying a compressive step-stress stimulus while recording RF echo frames at a high rate. Estimated local displacements occurring between frames in the echo sequence yield strain images. Relaxation parameters are estimated and mapped for each pixel using the strain time series to produce parametric UMR images. Viscometer experiments indicate that the viscoelastic properties of gelatin vary with pH. Also, elastic strain and viscous creep UMR images show contrast in the region of pH change. These results suggest that UMR methods can be used to explore the microenvironments of living tumors, where their viscoelastic properties are influenced by changes in pO2, pH and collagen density that predict metastatic potential and resistance to treatments.

Paper Details

Date Published: 28 April 2004
PDF: 10 pages
Proc. SPIE 5373, Medical Imaging 2004: Ultrasonic Imaging and Signal Processing, (28 April 2004); doi: 10.1117/12.536975
Show Author Affiliations
Mallika Sridhar, Univ. of California/Davis (United States)
Huini Du, Univ. of California/Davis (United States)
Claire Pellot-Barakat, Univ. of California/Davis (United States)
Scott I. Simon, Univ. of California/Davis (United States)
Michael F. Insana, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 5373:
Medical Imaging 2004: Ultrasonic Imaging and Signal Processing
William F. Walker; Stanislav Y. Emelianov, Editor(s)

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