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High-resolution harmonic motion imaging (HR-HMI) for tissue biomechanical property characterization

	author = {Teng Ma and Xuejun Qian and Chi Tat Chiu and Mingyue Yu and Hayong Jung and Yao-Sheng Tung and K. Kirk Shung and Qifa Zhou},
	title = {High-resolution harmonic motion imaging (HR-HMI) for tissue biomechanical property characterization},
	journal = {Quantitative Imaging in Medicine and Surgery},
	volume = {5},
	number = {1},
	year = {2014},
	keywords = {},
	abstract = {Background: Elastography, capable of mapping the biomechanical properties of biological tissues, serves as a useful technique for clinicians to perform disease diagnosis and determine stages of many diseases. Many acoustic radiation force (ARF) based elastography, including acoustic radiation force impulse (ARFI) imaging and harmonic motion imaging (HMI), have been developed to remotely assess the elastic properties of tissues. However, due to the lower operating frequencies of these approaches, their spatial resolutions are insufficient for revealing stiffness distribution on small scale applications, such as cancerous tumor margin detection, atherosclerotic plaque composition analysis and ophthalmologic tissue characterization. Though recently developed ARF-based optical coherence elastography (OCE) methods open a new window for the high resolution elastography, shallow imaging depths significantly limit their usefulness in clinics. 
Methods: The aim of this study is to develop a high-resolution HMI method to assess the tissue biomechanical properties with acceptable field of view (FOV) using a 4 MHz ring transducer for efficient excitation and a 40 MHz needle transducer for accurate detection. Under precise alignment of two confocal transducers, the high-resolution HMI system has a lateral resolution of 314 μm and an axial resolution of 147 μm with an effective FOV of 2 mm in depth. 
Results: The performance of this high resolution imaging system was validated on the agar-based tissue mimicking phantoms with different stiffness distributions. These data demonstrated the imaging system’s improved resolution and sensitivity on differentiating materials with varying stiffness. In addition, ex vivo imaging of a human atherosclerosis coronary artery demonstrated the capability of high resolution HMI in identifying layer-specific structures and characterizing atherosclerotic plaques based on their stiffness differences. 
Conclusions: All together high resolution HMI appears to be a promising ultrasound-only technology for characterizing tissue biomechanical properties at the microstructural level to improve the image-based diseases diagnosis in multiple clinical applications.},
	url = {}