Investigation of Physical Phenomena Underlying Temporal-Enhanced Ultrasound as a New Diagnostic Imaging Technique: Theory and Simulations

Temporal-enhanced ultrasound (TeUS) is a novel noninvasive imaging paradigm that captures information from a temporal sequence of backscattered US radio frequency data obtained from a fixed tissue location. This technology has been shown to be effective for classification of various in vivo and ex v...

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Veröffentlicht in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control ferroelectrics, and frequency control, 2018-03, Vol.65 (3), p.400-410
Hauptverfasser: Bayat, Sharareh, Azizi, Shekoofeh, Daoud, Mohammad I., Nir, Guy, Imani, Farhad, Gerardo, Carlos D., Pingkun Yan, Tahmasebi, Amir, Vignon, Francois, Sojoudi, Samira, Wilson, Storey, Iczkowski, Kenneth A., Lucia, M. Scott, Goldenberg, Larry, Salcudean, Septimiu E., Abolmaesumi, Purang, Mousavi, Parvin
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Sprache:eng
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Zusammenfassung:Temporal-enhanced ultrasound (TeUS) is a novel noninvasive imaging paradigm that captures information from a temporal sequence of backscattered US radio frequency data obtained from a fixed tissue location. This technology has been shown to be effective for classification of various in vivo and ex vivo tissue types including prostate cancer from benign tissue. Our previous studies have indicated two primary phenomena that influence TeUS: 1) changes in tissue temperature due to acoustic absorption and 2) micro vibrations of tissue due to physiological vibration. In this paper, first, a theoretical formulation for TeUS is presented. Next, a series of simulations are carried out to investigate micro vibration as a source of tissue characterizing information in TeUS. The simulations include finite element modeling of micro vibration in synthetic phantoms, followed by US image generation during TeUS imaging. The simulations are performed on two media, a sparse array of scatterers and a medium with pathology mimicking scatterers that match nuclei distribution extracted from a prostate digital pathology data set. Statistical analysis of the simulated TeUS data shows its ability to accurately classify tissue types. Our experiments suggest that TeUS can capture the microstructural differences, including scatterer density, in tissues as they react to micro vibrations.
ISSN:0885-3010
1525-8955
DOI:10.1109/TUFFC.2017.2785230