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Purpose To present a theoretical basis for noninvasively characterizing in vivo fluid-mechanical energy losses, and to apply it in a pilot study of patients known to express abnormal aortic flow patterns. Methods 4D flow MRI was used to characterize laminar viscous energy losses in the aorta of normal controls (n=12, age=37±10), patients with aortic dilation (n=16, age=52±8), and patients with aortic valve stenosis matched for age and aortic size (n=14, age=46±15), using a relationship between the 3D velocity field and viscous energy dissipation. Results Viscous energy loss was significantly elevated in the thoracic aorta for patients with dilated aorta (3.6±1.3 mW, p=0.024) and patients with aortic stenosis (14.3±8.2 mW, p<0.001) compared to healthy volunteers (2.3±0.9 mW). The same pattern of significant differences were seen in the ascending aorta, where viscous energy losses in patients with dilated aortas (2.2±1.1 mW, p=0.021) and patients with aortic stenosis (10.9±6.8 mW, p<0.001) were elevated compared to healthy volunteers (1.2±0.6 mW). Conclusion This technique provides a capability to quantify the contribution of abnormal laminar blood flow to increased ventricular afterload. In this pilot study, viscous energy loss in patient cohorts was significantly elevated and indicates that cardiac afterload is increased due to abnormal flow.

Purpose To improve velocity–to-noise ratio (VNR) and dynamic velocity range at 4D flow MRI by using dual-velocity encoding (dual-venc) with k-t GRAPPA acceleration. Materials and Methods A dual-venc 4D flow MRI sequence with k-t GRAPPA acceleration was developed using a shared reference scan followed by three-directional low- and high-venc scans (TR/TE/FA=6.1ms/3.4ms/15°, temporal/spatial resolution=43.0ms/1.2×1.2×1.2mm3). The high-venc data was used to correct for aliasing in the low-venc data, resulting in a single dataset with the favorable VNR of the low-venc but without velocity aliasing. The sequence was validated at a 3 Tesla MRI Scanner in phantom experiments and applied in 16 volunteers to investigate its feasibility for assessing intracranial hemodynamics (net flow and peak velocity) at the major intracranial vessels. In addition, image quality and image noise was assessed in the in-vivo acquisitions. Results All 4D flow MRI scans were acquired successfully with an acquisition time of 20±4min. The shared reference scan reduced the total acquisition time by 12.5% compared to two separate scans. Phantom experiments showed 51.4% reduced noise for dual-venc compared to high-venc and an excellent agreement of velocities (ρ=0.8, p<0.001). The volunteer data showed decreased noise in dual-venc data (54.6% lower) compared to high-venc, and improved image quality, as graded by two observers: less artifacts (P<0.0001), improved vessel conspicuity (P<0.0001), and reduced noise (P<0.0001). Conclusion Dual-venc 4D flow MRI exhibits the superior VNR of the low-venc acquisition and reliably incorporates low- and high-velocity fields simultaneously. In-vitro and in-vivo data demonstrate improved flow visualization, image quality and image noise.

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