M.A. Lubinski

Speckle tracking methods for ultrasonic elasticity imaging using short-time correlation

In ultrasound elasticity imaging, strain decorrelation is a major source of error in displacements estimated using correlation techniques. This error can be significantly decreased by reducing the correlation kernel. Additional gains in signal-to-noise ratio (SNR) are possible by filtering the correlation functions prior to displacement estimation. Tradeoffs between spatial resolution and estimate variance are discussed, and estimation in elasticity imaging is compared to traditional time-delay estimation. Simulations and experiments on gel-based phantoms are presented. The results demonstrate that high resolution, high SNR strain estimates can be computed using small correlation kernels (on the order of the autocorrelation width of the ultrasound signal) and correlation filtering.

Theoretical analysis and verification of ultrasound displacement and strain imaging

Evaluation of internal displacement and strain distributions in tissue under externally applied forces is a necessary step in elasticity imaging. To obtain a quantitative image of the elastic modulus, strain and displacement fields must be measured with reasonable accuracy and inverted based on an accurate theoretical model of soft tissue mechanics. In this paper, results of measured internal strain and displacement fields from gel-based phantoms are compared with theoretical predictions of a linear elastic model. In addition, some aspects of elasticity reconstruction based on measured displacement and strain fields are discussed.<<ETX>>

Lateral displacement estimation using tissue incompressibility

Using the incompressibility property of soft tissue, lateral displacements can be reconstructed from axial strain measurements. Results of simulations and experiments on gelatin-based tissue equivalent phantoms are compared with theoretical displacements, as well as estimates derived from traditional speckle tracking. Incompressibility processing greatly improves the accuracy and signal-to-noise ratio (SNR) of lateral displacement measurements compared with more traditional speckle tracking.

An elasticity microscope. Part I: Methods

An elasticity microscope images tissue stiffness at fine resolution. Possible applications include dermatology, ophthalmology, pathology, and tissue engineering. In addition, if the resolution approaches cellular dimensions, then this system may be very useful in understanding tissue micromorphology. Elasticity images can be reconstructed from displacement and strain fields measured throughout the specimen during controlled external loading. High frequency ultrasound is used to obtain these images by tracking coherent speckle motion during deformation. In this paper, methods are presented to track speckle in two dimensions with near unity correlation coefficients using a high frequency, single element focused transducer. These techniques include improved means for speckle tracking. Procedures to control boundary conditions for consistent specimen deformation and scanning techniques required to obtain a plane-strain state in the imaging plane are also discussed. To test these methods, a 50 MHz elasticity microscope was constructed.

Adaptive strain estimation using retrospective processing [medical US elasticity imaging]

Because errors in displacement and strain estimates depend on the magnitude of the induced strain, the strain signal-to-noise ratio (SNR) will be a function of the applied deformation. If deformation is applied at the body surface, it is difficult during data acquisition to select a single surface displacement providing the highest strain SNR throughout the image. By applying continuous deformation and capturing data in real-time, the surface displacement providing the highest strain SNR can be selected retrospectively. A method to adaptively optimize strain SNR over the image plane using retrospective processing is presented and demonstrated with experimental results.

ELASTICITY IMAGING FOR EARLY DETECTION OF RENAL PATHOLOGY

Early detection of renal pathology may be possible with elasticity imaging. This hypothesis was experimentally tested by quantitatively imaging internal mechanical strain due to surface deformations in an in vitro animal model of nephritis. Preliminary data support the hypothesis that kidney elasticity changes with renal damage and concomitant scarring before problems are detectable by traditional diagnostic techniques such as laboratory measurements of renal function.

Ultrasound elasticity imaging using Fourier based speckle tracking algorithm

Quantitative strain images of tissue equivalent phantoms have been obtained for a number of conditions using Fourier-based speckle tracking methods. Experimental results demonstrate that a non-palpable inclusion with Youngs modulus only 3 times greater than surrounding material can be easily detected. Comparison of experimental results with theoretical simulations quantifies the overall accuracy of the method.<<ETX>>

Reconstructive Elasticity Imaging

Changes in soft tissue elasticity are usually related to some abnormal, pathological process. Because the Young’s modulus can differ by orders of magnitude between soft tissues,l there has been consistent interest in tissue elasticity. Unfortunately, no imaging modality, including ultrasound, nuclear magnetic resonance (MRI) and computed tomography (CT), can directly provide information about elasticity. Recently, several investigators2-6 have used internal motion induced by external forces to monitor tissue mechanical properties. Although mechanical properties are ultimately linked to patterns of internal deformation, deformational geometry can greatly affect the pattern as well. Consequently, to uniquely image tissue elasticity, the Young’s modulus must be reconstructed from estimates of internal displacement and strain.

Reconstructive ultrasound elasticity imaging for renal transplant diagnosis: kidney ex vivo results.

It may be possible to diagnose and monitor scarring, inflammation and edema in transplant kidney using reconstructive ultrasound elasticity imaging. Kidney elasticity is expected to change dramatically with scar, and to a lesser degree, with acute inflammation and edema. The hypothesis that changes in kidney elasticity can be imaged using a clinical ultrasound scanner was experimentally tested with an ex vivo canine kidney model, and results on a single pair of kidneys are reported in this paper. A cross-linking agent affected kidney elasticity both globally and locally. Elasticity changes were monitored with accurate estimates of internal displacement and strain followed by Youngs modulus reconstruction. The results of this study strongly suggest that ultrasound elasticity imaging can detect elasticity changes in complex structures such as the kidney. Moreover, it has the potential to become an important clinical tool for renal transplant diagnosis.

Non-linear tissue elasticity: adaptive elasticity imaging for large deformations

Ultrasounds dynamic and interactive (i.e., real-time) nature is its major advantage compared to other imaging modalities. For elasticity imaging, real-time data capture provides an excellent foundation for retrospective data processing, including adaptive speckle tracking, incompressibility processing, and adaptive elasticity imaging. In this paper, we explore adaptive imaging of elasticity to estimate nonlinear tissue elasticity. Remote assessment of nonlinear tissue elasticity (i.e., strain hardening) can both increase contrast in elasticity images and present an independent means of tissue differentiation.