4D microvascular imaging based on ultrafast Doppler tomography
4D ultrasound microvascular imaging was demonstrated by applying ultrafast Doppler tomography (UFD-T) to the imaging of brain hemodynamics in rodents. In vivo real-time imaging of the rat brain was performed using ultrasonic plane wave transmissions at very high frame rates (18,000 frames per second...
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Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2016-02, Vol.127, p.472-483 |
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Sprache: | eng |
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Zusammenfassung: | 4D ultrasound microvascular imaging was demonstrated by applying ultrafast Doppler tomography (UFD-T) to the imaging of brain hemodynamics in rodents. In vivo real-time imaging of the rat brain was performed using ultrasonic plane wave transmissions at very high frame rates (18,000 frames per second). Such ultrafast frame rates allow for highly sensitive and wide-field-of-view 2D Doppler imaging of blood vessels far beyond conventional ultrasonography. Voxel anisotropy (100μm×100μm×500μm) was corrected for by using a tomographic approach, which consisted of ultrafast acquisitions repeated for different imaging plane orientations over multiple cardiac cycles. UFT-D allows for 4D dynamic microvascular imaging of deep-seated vasculature (up to 20mm) with a very high 4D resolution (respectively 100μm×100μm×100μm and 10ms) and high sensitivity to flow in small vessels (>1mm/s) for a whole-brain imaging technique without requiring any contrast agent. 4D ultrasound microvascular imaging in vivo could become a valuable tool for the study of brain hemodynamics, such as cerebral flow autoregulation or vascular remodeling after ischemic stroke recovery, and, more generally, tumor vasculature response to therapeutic treatment.
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•We describe a new 4D microvascular imaging technique.•Combination of ultrasound ultrafast Doppler and tomographic reconstruction for 3D imaging•The technique reaches 100μm resolution and is sensitive to very slow blood flow (1mm/s).•4D capabilities during one cardiac cycle•It opens the way to 4D imaging on awake and moving animals. |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2015.11.014 |