Microvascular flow estimation by contrast-assisted ultrasound B-scan and statistical parametric images.
The microbubbles destruction/replenishment technique has been previously applied to estimating blood flow in the microcirculation. The rate of increase of the time-intensity curve (TIC) due to microbubbles flowing into the region of interest (ROI), as measured from B-mode images, closely reflects the flow velocity. In previous studies, we proposed a new approach called the time-Nakagami-parameter curve (TNC) obtained from Nakagami images to monitor microbubble replenishment for quantifying the microvascular flow velocity. This study aimed to further explore some effects that may affect the TNC to estimate the microflow, including microbubble concentration, ultrasound transmitting energy, attenuation, intrinsic noise, and tissue clutter. In order to well control each effect production, we applied a typical simulation method to investigate the TIC and TNC. The rates of increase of the TIC and TNC were expressed by the rate constants beta(I) and beta(N), respectively, of a monoexponential model. The results show that beta(N) quantifies the microvascular flow velocity similarly to the conventional beta(I) . Moreover, the measures of beta(I) and beta(N) are not influenced by microbubble concentration, transducer excitation energy, and attenuation effect. Although the effect of intrinsic signals contributed by noise and blood would influence the TNC behavior, the TNC method has a better tolerance of tissue clutter than the TIC does, allowing the presence of some clutter components in the ROI. The results suggest that the TNC method can be used as a complementary tool for the conventional TIC to reduce the wall filter requirements for blood flow measurement in the microcirculation.
Tsui
Po-Hsiang
PH
Division of Mechanics, Research Center for Applied Sciences, Academia Sinica, Taipei 11529, Taiwan. tsuiph@gate.sinica.edu.tw
Yeh
Chih-Kuang
CK
Chang
Chien-Cheng
CC
D000465:Algorithms; D000818:Animals; D001783:Blood Flow Velocity; D003198:Computer Simulation; D003287:Contrast Media; D005123:Eye / Q000000981:diagnostic imaging; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D045423:Microbubbles; D008833:Microcirculation; D055806:Microvessels / Q000000981:diagnostic imaging* / Q000502:physiology; D008955:Models, Cardiovascular; D015233:Models, Statistical; D011817:Rabbits; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography
D003287:Contrast Media