A new formalism for the quantification of tissue perfusion by the destruction-replenishment method in contrast ultrasound imaging.
A new formalism is presented for the destruction-replenishment perfusion quantification approach at low mechanical index. On the basis of physical considerations, best-fit methods should be applied using perfusion functions with S-shape characteristics. These functions are first described for the case of a geometry with a single flow velocity, then extended to the case of vascular beds with blood vessels having multiple flow velocity values and directions. The principles guiding the analysis are, on one hand, a linearization of video echo signals to overcome the log-compression of the imaging instrument, and, on the other hand, the spatial distribution of the transmit-receive ultrasound beam in the elevation direction. An in vitro model also is described; it was used to confirm experimentally the validity of the approach using a commercial contrast agent. The approach was implemented in the form of a computer program, taking as input a sequence of contrast-specific images, as well as parameters related to the ultrasound imaging equipment used. The generated output is either flow-parameter values computed in regions-of-interest, or parametric flow-images (e.g., mean velocity, mean transit time, mean flow, flow variance, or skewness). This approach thus establishes a base for extracting information about the morphology of vascular beds in vivo, and could allow absolute quantification provided that appropriate instrument calibration is implemented.
Arditi
Marcel
M
Bracco Research SA, Ultrasound Physics, Plan-les-Ouates, Geneva, Switzerland. marcel.arditi@brg.bracco.com
Frinking
Peter J A
PJ
Zhou
Xiang
X
Rognin
Nicolas G
NG
D000465:Algorithms; D000818:Animals; D001158:Arteries / Q000000981:diagnostic imaging* / Q000502:physiology*; D001783:Blood Flow Velocity / Q000502:physiology*; D003198:Computer Simulation; D003287:Contrast Media; D004452:Echocardiography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008955:Models, Cardiovascular; D019047:Phantoms, Imaging; D012039:Regional Blood Flow / Q000502:physiology*
D003287:Contrast Media