Evaluation of ULM for sub-wavelength imaging of microvasculature in skeletal muscles : A simulation study

A vital part of the human anatomy is the circulatory system, which branches out in a vast network of vessels delivering oxygen and other nutrients to all parts of the body. In a human adult, there are about 40 billion capillaries with a diameter of about 10 µm. The behavior of the blood flow in the capillaries can be used to identify, for example, diabetes or cancer. The current method for analyzing capillaries involves removing a section of the tissue and looking at it through a microscope. To avoid having to remove tissue from the patient, a method for imaging the capillaries inside living tissue is desired. A possible candidate for the future of capillary imaging is ultrasound localization microscopy (ULM). ULM attempts to solve a well-known limitation in ultrasound imaging, the diffraction limit. The classical limit of diffraction sets a limit on the resolution achievable based on the wavelength of the transmitted soundwave. The best possible resolution would be roughly half of the transmitted wavelength, which means that objects smaller than that cannot be imaged accurately. A standard clinical ultrasound system uses wavelengths in the hundreds of micrometers when imaging deep organs. Capillaries, which are much smaller than that, can not accurately be imaged with standard ultrasound systems. ULM utilizes the detection of individual microbubbles injected into the bloodstream to pinpoint the microbubble location to a much higher precision than what the diffraction limit would allow. By combining the localization of hundreds of microbubbles, an image of the capillaries is achieved. In this study, we investigate the performance of ULM for imaging the sub-wavelength structures of capillaries in skeletal muscle. A simulation model of capillaries in skeletal muscle was built to achieve the necessary images. The model was built in Vantage 4.2.0 (Verasonics Inc.), which runs in MATLAB. The simulation model was designed to simulate microbubbles moving in capillaries in the image plane. From the results in this study, we can conclude that ULM is a viable option for imaging capillaries in skeletal muscle and can achieve a resolution that far surpasses the diffraction limit. We show that the capillaries' shape and their proximity to each other can affect the final image. The intensity of background noise relative to the microbubble signal also substantially impacts the performance of ULM but might be avoided due to the high contrast between background noise and microbubble signal. Furthermore, we show that, if the background is stationary, the background tissue signal can easily be removed with singular value decomposition (SVD). Notice: The full text of this report has been censored due to confidentiality and will not be available to the public