Abstract
A number of acoustic super-resolution techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit. A crucial aspect of all ultrasound (US) super-resolution (SR) methods using single microbubble localization is time-efficient detection of individual bubble signals. Due to the need for bubbles to circulate through the vasculature during acquisition, slow flows associated with the microcirculation limit the minimum acquisition time needed to obtain adequate spatial information. Here, a model is developed to investigate the combined effects of imaging parameters, bubble signal density, and vascular flow on SR image acquisition time. We find that the estimated minimum time needed for SR increases for slower blood velocities and greater resolution improvement. To improve SR from a resolution of λ /10 to λ /20 while imaging the microvasculature structure modeled here, the estimated minimum acquisition time increases by a factor of 14. The maximum useful imaging frame rate to provide new spatial information in each image is set by the bubble velocity at low blood flows (<150 mm/s for a depth of 5 cm) and by the acoustic wave velocity at higher bubble velocities. Furthermore, the image acquisition procedure, transmit frequency, localization precision, and desired super-resolved image contrast together determine the optimal acquisition time achievable for fixed flow velocity. Exploring the effects of both system parameters and details of the target vasculature can allow a better choice of acquisition settings and provide improved understanding of the completeness of SR information.
Highlights
Non-invasive imaging of the microvasculature is crucial for the early detection and intervention of diseases such as cancer [1], [2], ischemia [3] and peripheral arterial disease [4]–[6]
Obtaining these isolated signals may be achieved in a number of ways, including the use of suitable microbubble concentrations with contrast imaging modes and background subtraction techniques [7], [8], or linear imaging techniques with singular value decomposition [11], [12], differential imaging [13], differential imaging with spatiotemporal nonlocal means filtering [14] or background subtraction methods [9][15][20]
Ranges of tissue blood volumes are shown for regions of colangiocellular cancer and hepatocellular carcinoma
Summary
Non-invasive imaging of the microvasculature is crucial for the early detection and intervention of diseases such as cancer [1], [2], ischemia [3] and peripheral arterial disease [4]–[6].Acoustic super-resolution (SR) techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit using microbubble contrast agents [7]–[16]. A crucial aspect of all methods based on single-bubble localization is the detection of spatially isolated signals from microbubbles [17]–[19]. The recent use of nanodroplets for US-SR has the benefit of providing sparsely activated microbubbles without the requirement for sufficient blood flow [21], [22]. In all these cases, the number of individual microbubble signals detected and localized per frame is restricted by the diffraction limited nature of the acquired data. Since these methods rely upon the combined localization information gathered over a series of frames, minimizing potentially long acquisition
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