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Zeng, Qi

University of British Columbia

The progression of chronic liver disease, including hepatitis B, C, and non-alcoholic steatotic hepatitis, is closely associated with advancing fibrosis which stiffens the liver tissue over time. Magnetic resonance elastography is a quantitative imaging method that measures the liver tissue shear modulus over a volume and provides the most accurate imaging-based fibrosis staging results when compared to biopsy. While ultrasound-based elastography methods have been developed for liver fibrosis staging, they are mostly confined to providing measurements for a 1D or a 2D region of interest and with a limited imaging depth. In this thesis, a novel 3D ultrasound liver shear wave absolute vibro-elastography (S-WAVE) imaging technique is developed. With the aid of state-of-the-art 3D ultrasound hardware, 3D S-WAVE aims to provide quantitative and volumetric hepatic stiffness measurements comparable to magnetic resonance elastography. The new 3D S-WAVE utilizes a high element count matrix array transducer. With a modified 3D color power angiography imaging sequence, large field-ofview multi-frequency shear wave imaging could be achieved with a significantly shorter scan time. Learning-based automatic image segmentation and cross-modality registration techniques have also been developed to streamline the image processing pipeline and assist the comparison study between the S-WAVE and magnetic resonance elastography methods. Real-time shear wave imaging capability has also been enabled to improve the efficiency and repeatability of the S-WAVE exam. Validation studies with liver tissue phantoms and in vivo subjects have been designed and implemented using magnetic resonance elastography as the ground truth. The results showed that 3D S-WAVE had a high consistency with magnetic resonance elastography and outperformed conventional ultrasound transient elastography. The collected 3D S-WAVE data were also utilized to assess the performance difference between 2D and 3D elasticity reconstruction techniques. The results indicated that the 3D method effectively overcame the overestimation and the spatial bias issues which were commonly introduced by the 2D imaging method.

Text

2023-01-18

Attribution-NonCommercial-ShareAlike 4.0 International

http://hdl.handle.net/2429/83664

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-sa/4.0/