scholarly journals Acoustic Radiation Force Impulse Imaging of Human Prostates: Initial In Vivo Demonstration

2012 ◽  
Vol 38 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Liang Zhai ◽  
Thomas J. Polascik ◽  
Wen-Chi Foo ◽  
Stephen Rosenzweig ◽  
Mark L. Palmeri ◽  
...  
2007 ◽  
Vol 33 (11) ◽  
pp. 1706-1719 ◽  
Author(s):  
Stephen J. Hsu ◽  
Richard R. Bouchard ◽  
Douglas M. Dumont ◽  
Patrick D. Wolf ◽  
Gregg E. Trahey

2002 ◽  
Vol 28 (2) ◽  
pp. 227-235 ◽  
Author(s):  
Kathryn Nightingale ◽  
Mary Scott Soo ◽  
Roger Nightingale ◽  
Gregg Trahey

2002 ◽  
Vol 24 (2) ◽  
pp. 100-108 ◽  
Author(s):  
Kathryn Nightingale ◽  
Roger Nightingale ◽  
Deborah Stutz ◽  
Gregg Trahey

Acoustic Radiation Force Impulse (ARFI) imaging is a method for characterizing local variations in tissue mechanical properties. In this method, a single ultrasonic transducer array is used to both apply temporally short localized radiation forces within tissue and to track the resulting displacements through time. Images of tissue displacement immediately after force cessation, maximum tissue displacement, the time it takes for the tissue to reach its maximum displacement, and the recovery time constant of the tissue are generated from the ARFI data sets. The information in each of these images demonstrates good agreement with matched B-mode images. The study presented here was designed to evaluate the relationship between changes in these ARFI parameters with known tissue mechanical properties in vivo. Utilizing a modified Siemens Elegra scanner with a 75L40 transducer array, ARFI images of vastus medialis muscle were generated in three of the authors under four levels of activation (0, 5.7, 14.5, and 23.3 N-m). Four ARFI datasets were acquired for each loading condition. The observed trends were that displacement magnitude, the time it took for the tissue to reach its maximum displacement, and recovery time constant decreased with increasing load (i.e., increasing muscle stiffness). Significant differences were observed between load levels and subjects for all parameters (p<0.01). The results indicate that ARFI imaging may be capable of quantifying tissue stiffness in real-time measurements, although further investigation is required.


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