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Updated: Dec 8, 2025
Multi-timescale Microscopy Methods for the Characterization of Fluorescently-labeled Microbubbles for Ultrasound-Triggered Drug Release
Published on: June 12, 2021
In vivo Nakagami-m parametric imaging of microbubble-enhanced ultrasound regulated by RF and VF processing techniques
Diya Wang1,2, Dong Liu1, Yuchao Sang2
1Department of Radiation Oncology, University of California, San Francisco, CA, 94115, USA.
Purpose:
Application of the Nakagami statistical model and associated m parameter has the potential to suppress artifacts from adjustable system parameters and operator selections typical in echo amplitude-coded microbubble-enhanced ultrasound (MEUS). However, the feasibility of applying m estimation and determination of the associated Nakagami distribution features for in vivo MEUS remain to be investigated. Sensitivity and discriminability of m-coded MEUS are often limited since raw envelopes are regulated by complex radiofrequency (RF) and video-frequency (VF) processing. This study aims to develop an improved imaging approach for the m parameter estimation which can overcome the above limitations in in vivo condition.
Method:
The regulation effects of RF processing of pulse-inversion (PI) harmonic detection techniques and VF processing of logarithmic compression in Nakagami distributions were investigated in MEUS. A window-modulated compounding moment estimator was developed to estimate the MEUS m values. The sensitivity and discriminability of m-coded MEUS were quantified with contrast-to-tissue ratio (CTR), contrast-to-noise ratio (CNR), and axial and lateral resolutions, which were validated through in vivo perfusion experiments on rabbit kidneys.
Results:
Regulated by RF and VF processing, the distributions of MEUS obeyed the Nakagami statistical model. The Nakagami-fitted correlation coefficient was 0.996 ± 0.003 (P < 0.05 in the t test and P < 0.001 in the Kolmogorov-Smirnov test). Among each of the m-coded MEUS methods, the logarithmic m-coded PI-MEUS scheme effectively characterized the peripheral rim perfusion features and details within the renal cortex. The CTR and CNR in this region reached 7.9 ± 1.5 dB and 34.4 ± 1.7 dB, respectively, which were higher than those of standard amplitude-coded MEUS; and the axial and lateral resolutions were 1.02 ± 0.02 and 0.91 ± 0.02 mm, respectively, which were slightly longer than those of amplitude-coded MEUS.
Conclusions:
The Nakagami statistical model could characterize MEUS even when the envelope distributions were regulated by RF and VF processing. The logarithmic m-coded PI-MEUS scheme significantly improved the sensitivity, discriminability, and robustness of m estimation in MEUS. The scheme provides an option to remove artifacts in echo amplitude-coded MEUS and to distinctly characterize the inherent microvasculature enhanced by microbubbles, with potential to improve and expand the role of MEUS in diagnostic ultrasound.
