Quantitative Particle Characterization by Scattered Ultrasound

The topic of this thesis is an acoustic scattering technique for detennining the compressibility and density of individual particles. The particles, which have diameters on the order of 10 µm, are modeled as fluid spheres. Ultrasonic tone bursts of 2 µsec duration and 30 MHz center frequency scatter from individual particles as they traverse the focal region of two confocally positioned transducers. One transducer acts as a receiver while the other both transmits and receives acoustic signals. The resulting scattered bursts are detected at 90° and at 180° (backscattered). Using either the long wavelength (Rayleigh) or the weak scatterer (Born) approximations, it is possible to detennine the compressibility and density of the particle provided we possess a priori knowledge of the particle size and the host properties. The detected scattered signals are digitized and stored in computer memory. With this information we can compute the mean compressibility and density averaged over a population of particles ( typically 1000 particles) or display histograms of scattered amplitude statistics. An experiment was run first run to assess the feasibility of using polystyrene polymer microspheres to calibrate the instrument. A second study was performed on the buffy coat harvested from whole human blood. Finally, chinese hamster ovary cells which were subject to hyperthermia treatment were studied in order to see if the instrument could detect heat induced membrane blebbing.

QUANTITATIVE THREE DIMENSIONAL ELASTICITY IMAGING

Neoplastic tissue is typically highly vascularized, contains abnormal concentrations of extracellular proteins (e.g. collagen, proteoglycans) and has a high interstitial fluid pres- sure compared to most normal tissues. These changes result in an overall stiffening typical of most solid tumors. Elasticity Imaging (EI) is a technique which uses imaging systems to measure relative tissue deformation and thus noninvasively infer its mechanical stiffness. Stiffness is recovered from measured deformation by using an appropriate mathematical model and solving an inverse problem. The integration of EI with existing imaging modal- ities can improve their diagnostic and research capabilities. The aim of this work is to develop and evaluate techniques to image and quantify the mechanical properties of soft tissues in three dimensions (3D). To that end, this thesis presents and validates a method by which three dimensional ultrasound images can be used to image and quantify the shear modulus distribution of tissue mimicking phantoms. This work is presented to motivate and justify the use of this elasticity imaging technique in a clinical breast cancer screening study. The imaging methodologies discussed are intended to improve the specificity of mammography practices in general. During the development of these techniques, several issues concerning the accuracy and uniqueness of the result were elucidated. Two new algorithms for 3D EI are designed and characterized in this thesis. The first provides three dimensional motion estimates from ultrasound images of the deforming ma- terial. The novel features include finite element interpolation of the displacement field, inclusion of prior information and the ability to enforce physical constraints. The roles of regularization, mesh resolution and an incompressibility constraint on the accuracy of the measured deformation is quantified. The estimated signal to noise ratio of the measured displacement fields are approximately 1800, 21 and 41 for the axial, lateral and eleva- tional components, respectively. The second algorithm recovers the shear elastic modulus distribution of the deforming material by efficiently solving the three dimensional inverse problem as an optimization problem. This method utilizes finite element interpolations, the adjoint method to evaluate the gradient and a quasi-Newton BFGS method for optimiza- tion. Its novel features include the use of the adjoint method and TVD regularization with piece-wise constant interpolation. A source of non-uniqueness in this inverse problem is identified theoretically, demonstrated computationally, explained physically and overcome practically. Both algorithms were test on ultrasound data of independently characterized tissue mimicking phantoms. The recovered elastic modulus was in all cases within 35% of the reference elastic contrast. Finally, the preliminary application of these techniques to tomosynthesis images showed the feasiblity of imaging an elastic inclusion.