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Real-time imaging of elastic properties of soft tissue with ultrasound

University of British Columbia

Current imaging devices such as computed tomography (CT) , ultrasound (US) and magnetic resonance imaging (MRI) are not directly capable of measuring the mechanical properties of soft tissue even though such measurement would have a high clinical demand. Elastography with the aid of ultrasound has been well established in the literature as a strain imaging technique. Under certain conditions, these strain images can give a clear illustration of the underlying tissue stiffness distributions which has been shown to provide useful clinical information. Vibro Elastography is another new imaging system that performs a transfer function analysis of the tissue motion. The shape of the transfer function can be analyzed further and the stiffness of tissue can be estimated from the magnitude of the transfer functions at low-frequencies. This thesis introduces a fast and accurate motion tracking algorithm which is at the heart of both strain imaging and stiffness imaging. The algorithm achieves real-time performance (> 20 fps) without any need for additional hardware and its overhead. The performance of the proposed method is evaluated quantitatively according to its signal-to-noise ratio, contrast-to-noise ratio, dynamic range, resolution and sensitivity with both simulation data and phantom data. Also, the computational efficiency of the algorithm is compared with current real-time motion tracking algorithms. The results show that it is the most time efficient algorithm to date. Furthermore the performance of the proposed method is evaluated qualitatively from the real-time images that are generated in both tissue mimicking phantoms and real tissues in vivo. By using this method two real-time elastography packages have been implemented which can easily be clinically applied. These implementations run at 35fps for strain images and 2fps for transfer function images of 16,000 pixels on an Ultrasonix RP500 ultrasound machine.

Text

2009-12-22

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http://hdl.handle.net/2429/16987

Electrical and Computer Engineering

University of British Columbia

UBCV

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