Quantitative tissue perfusion imaging using nonlinear ultrasound localization microscopy

Abstract

Abstract Ultrasound localization microscopy (ULM) is a recent advancement in ultrasound imaging that uses microbubble contrast agents to yield vascular images that break the classical diffraction limit on spatial resolution. Current approaches cannot image blood flow at the tissue perfusion level since they rely solely on differences in velocity to separate tissue and microbubble signals; lower velocity microbubble echoes are removed during high pass wall filtering. To visualize blood flow in the entire vascular tree, we have developed nonlinear ULM, which combines nonlinear pulsing sequences with plane-wave imaging to segment microbubble signals independent of their velocity. Bubble localization and inter-frame tracking produces super-resolved images and, with parameters derived from the bubble tracks, a rich quantitative feature set that can describe the relative quality of microcirculatory flow. Using the rat spinal cord as a model system, we showed that nonlinear ULM better resolves some smaller branching vasculature compared to conventional ULM. Following contusion injury, both gold-standard histological techniques and nonlinear ULM depicted reduced in-plane vessel length between the penumbra and contralateral gray matter (−16.7% vs. −20.5%, respectively). Here, we demonstrate that nonlinear ULM uniquely enables investigation and potential quantification of tissue perfusion, arguably the most important component of blood flow.