Vibroelastography (VE) is a technique in which tissue is continuously stimulated by a multi-frequency excitation. The applied vibration is in the range of a few to a few hundred microns which does not produce discomfort to the patient. The deformation of the tissue is then tracked while the excitation is applied. Since the excitation is dynamic, dynamic parameters such as viscosity are also measured in addition to elasticity. Due to the multi-frequency nature of the excitation, other tissue parameters such as frequency-dependent features and non-linear properties can also be measured. Furthermore, VE enables tissue characterization both in the low frequency regime and in the high frequency regime, simultaneously. As a result, the low frequency response can yield relative elasticity and viscosity parameters, while the high frequency response and wave patterns can be processed to obtain absolute mechanical parameters such as shear modulus, Young’s modulus and shear viscosity. Relative and absolute viscoelastic parameters are generated by VE in real-time during a single imaging sequence, which provides several physical features for further tissue typing and characterization. The outcome of VE can be one or more images of relative or absolute parameters or a single value representing a likelihood map of malignancy within a region of interest.
Vibroelastography can be performed in real-time in either two dimensions (2D) or three dimensions (3D), depending on the type of the ultrasound transducer and the clinical application. The 3D version of VE is capable of producing elasticity images with similar quality as that of the magnetic resonance elastography (MRE) at a fraction of the cost and the time it takes to perform MRE.
In 2D vibroelastography, a plane is continuously images while being excited externally. The excitation can be applied either through vibrating the probe or through an independent shaker. The type
of excitation highly depends on the clinical application. The pipeline of image processing consists of collecting a few ultrasound RF frames while tissue is being excited, measuring tissue motion and applying a viscoelastic model to the tissue motion that accounts for the multi-frequency nature of the displacements. The processing pipeline for 2D vibroelastography has been optimized insofar as in displays real-time images at the native ultrasound acquisition frame-rate.
For more information, see Eskandari, et al., “Identifying malignant and benign breast lesions using vibroelastography,” 2013 IEEE Ultrasonics Symposium, In Press, July 2013.
Thin Volume Vibroelastography
In this method of vibroelastography, a steady-state vibration is applied to the tissue to generate displacements while a thin volume of the tissue is scanned by ultrasound over a short period. The thin volume consists of a middle plane and at least two planes adjacent to that. The number of planes is selected such that the ultrasound volumetric data acquisition and VE image computation is performed in real-time. The VE algorithm yields measured viscoelastic parameters within the middle plane. Thanks to the volumetric data that is captured in this types of elastography, it has been demonstrated that the accuracy is comparable to the gold standard MRE.
For more information, see Baghani, et al., “Real-Time Quantitative Elasticity Imaging of Deep Tissue Using Free-Hand Conventional Ultrasound,” Med Image Comput Comput Assist Interv. 2012; 15(Pt 2):617-24.
Vibroelastography can be performed over a full volume to reconstruct a 3D image of the viscoelastic properties of tissue. This can be done with a 3D transducer or by automatic sweeping of a linear transducer. The 3D elasticity data can then be rendered on the screen for offline analysis of the volume. One of the main applications for this method of vibroelastography is prostate where physicians can examine the entire volume for suspicio
us lesions or radiation oncologists can make a better planning for radiation therapy.
For more information, see Mahdavi, et al., “Fusion of Ultrasound B-Mode and Vibro-Elastography Images for Automatic 3-D Segmentation of the Prostate,” IEEE Trans. on Medical Imaging, vol. 31, no. 11, pp. 2073-2082, Nov. 2012.