A New Class of Phantom Materials for Poroelastography Imaging Techniques

Non-invasive imaging of interstitial fluid transport parameters in solid tumors in vivo

In this paper, new and non-invasive imaging methods to assess interstitial fluid transport parameters in tumors in vivo are developed, analyzed and experimentally validated. These parameters include extracellular volume fraction (EVF), interstitial fluid volume fraction (IFVF) and interstitial hydraulic conductivity (IHC), and they are known to have a critical role in cancer progression and drug delivery effectiveness. EVF is defined as the volume of extracellular matrix per unit volume of the tumor, while IFVF refers to the volume of interstitial fluid per unit bulk volume of the tumor. There are currently no established imaging methods to assess interstitial fluid transport parameters in cancers in vivo. We develop and test new theoretical models and imaging techniques to assess fluid transport parameters in cancers using non-invasive ultrasound methods. EVF is estimated via the composite/mixture theory with the tumor being modeled as a biphasic (cellular phase and extracellular phase) composite material. IFVF is estimated by modeling the tumor as a biphasic poroelastic material with fully saturated solid phase. Finally, IHC is estimated from IFVF using the well-known Kozeny-Carman method inspired by soil mechanics theory. The proposed methods are tested using both controlled experiments and in vivo experiments on cancers. The controlled experiments were performed on tissue mimic polyacrylamide samples and validated using scanning electron microscopy (SEM). In vivo applicability of the proposed methods was demonstrated using a breast cancer model implanted in mice. Based on the controlled experimental validation, the proposed methods can estimate interstitial fluid transport parameters with an error below 10% with respect to benchmark SEM data. In vivo results demonstrate that EVF, IFVF and IHC increase in untreated tumors whereas these parameters are observed to decrease over time in treated tumors. The proposed non-invasive imaging methods may provide new and cost-effective diagnostic and prognostic tools to assess clinically relevant fluid transport parameters in cancers in vivo.

Assessment of the long bone inter-fragmentary gap size in ultrasound strain elastograms

The inter-fragmentary gap size (IFGS) is a critical factor affecting the propensity of bone healing. In this paper, we present a study to analyze ultrasound strain elastographic numerical features in samples with distinct IFGS using both simulations and experiments. Six fractured rabbit hind leg samples in total were used in this study with controlled IFGS of 1 mm, 5 mm and 1 cm. For the simulation, computed tomography (CT) scans of all six samples were used to create solid models. Finite element analysis (FEA) and subsequent elastography simulations were performed on the 3D models to produce tensorial strain field data. Features of bony fragment separation were defined on different strain components and computed for strains segmented at varying thresholds to evaluate their performance in estimating the IFGS. A threshold for each strain component was then determined, based on which extra 3D features of interest were defined and extracted from the segmented strain data. Then, all 3D features were compared statistically among the three nominal groups. Additional simulations and experiments of axial shear strain elastography (ASSE) on the median coronal plane of the same samples were also performed. Our results indicate that coronal plane axial shear (CPAS) strain elastography produces a separation feature which is statistically correlated with the IFGS, and that our elastography simulation module is effective in predicting the CPAS elastographic strain behavior for different IFGS.

Optimization of a Pixel-to-Pixel Curve-Fitting Method for Poroelastography Imaging

Ultrasound poroelastography is an imaging modality used to characterize the temporal behavior of soft tissue that can be modeled as a solid permeated by interconnected pores filled with liquid (poroelastic medium). It could be useful in the stage classification of lymphedema. Generally, time-constant models are applied to strain images, and precision of the fitting process, computational cost and versatility in response to changes in tissues properties are crucial aspects of clinical applications. In the work described here, we performed creep experiments on poroelastic phantoms and used rheologic models to visualize the changes in viscoelastic response associated with fluid mobility. We used the Levenberg-Marquardt algorithm as a fitting tool and performed parametric studies to improve its performance. On the basis of these studies, we proposed an optimization schema for the pixel-to-pixel curve-fitting process. We determined that the bimodal Kelvin-Voigt model describes efficiently the temporal evolution of the strain images in heterogeneous phantoms.