3D Myocardial Mechanical Wave Measurements

In vivo whole brain microvascular imaging in mice using transcranial 3D Ultrasound Localization Microscopy

“… 19 Translation to 3D ULM of the human brain will require the use of matrix transducers at a lower frequency between 1 and 3 MHz. 3D Ultrafast imaging with a large field of view has been recently demonstrated for cardiac applications using matrix transducers with diverging wave emissions at 2.5MHz 36 , 37 , 38 and this approach could be translated to 3D ultrafast imaging of the human brain through the temporal window. Imaging of the human whole-brain will however require the development of dedicated large aperture matrix transducers.…”

Coronary Flow Assessment Using 3-Dimensional Ultrafast Ultrasound Localization Microscopy

“…In the long term, translation to the human heart could be achieved with lower frequency matrix transducers. 3D Ultrafast imaging of the human heart with a large field of view has been recently demonstrated using matrix transducers with diverging wave emissions 13,22,23 and could be applied to 3D CorULM.…”

“…The median radius, flow velocity and flow rate increase significantly with adenosine. We then analyze the vasodilation as a function of the vessel size and figure 3.dshows that the relative dilation in response to adenosine is much larger in small vessels: small vessels[20][21][22][23][24][25][26][27][28][29][30] µm are dilated by 1.57±0.26 whereas larger vessels (>60µm) changed only by 1.07±0.2 (p<0.01). The global flow rate is analyzed for the entire vasculature and a two-fold increase of the microvascular coronary flow rate is found in response to adenosine which is in good agreement with the overall perfusion flow rate (control measurement) that increased from 8.80 ± 1.03 mL/min to 16.54 ± 2.35 mL/min (p<0.001).…”

Deep learning in ultrasound elastography imaging: A review

“…The source of vibration in SW elastography (SWE) can be external (actuator), 10 internal (radiation pressure), 11,12 or natural (e.g., SWs produced by closing heart valves). [13][14][15] In recent years, deep learning has been widely developed by the computer vision community. [16][17][18][19] However, the application of deep learning to analyze medical images is not straightforward.…”

“…As the shear modulus of various tissues spans over orders of magnitude, dynamic methods provide high contrast among different tissues/organs regarding their mechanical properties. The source of vibration in SW elastography (SWE) can be external (actuator), 10 internal (radiation pressure), 11,12 or natural (e.g., SWs produced by closing heart valves) 13–15 …”