A review of cardiovascular clinical and research applications of MRI phase-contrast velocity imaging, also known as velocity mapping or flow imaging. Phase-contrast basic principles, advantages, limitations, common pitfalls and artefacts are described. It can measure many different aspects of the complicated blood flow in the heart and vessels: volume flow (cardiac output, shunt, valve regurgitation), peak blood velocity (for stenosis), patterns and timings of velocity waveforms and flow distributions within heart chambers (abnormal ventricular function) and vessels (pulse-wave velocity, vessel wall disease). The review includes phase-contrast applications in cardiac function, heart valves, congenital heart diseases, major blood vessels, coronary arteries and myocardial wall velocity.

A need exists to noninvasively assess renal interstitial fibrosis, a common process to all kidney diseases and predictive of renal prognosis. In this translational study, Magnetic Resonance Imaging (MRI) T1 mapping and a new segmented Diffusion-Weighted Imaging (DWI) technique, for Apparent Diffusion Coefficient (ADC), were first compared to renal fibrosis in two well-controlled animal models to assess detection limits. Validation against biopsy was then performed in 33 kidney allograft recipients (KARs). Predictive MRI indices, ΔT1 and ΔADC (defined as the cortico-medullary differences), were compared to histology. In rats, both T1 and ADC correlated well with fibrosis and inflammation showing a difference between normal and diseased kidneys. In KARs, MRI indices were not sensitive to interstitial inflammation. By contrast, ΔADC outperformed ΔT1 with a stronger negative correlation to fibrosis (R2 = 0.64 against R2 = 0.29 p < 0.001). ΔADC tends to negative values in KARs harboring cortical fibrosis of more than 40%. Using a discriminant analysis method, the ΔADC, as a marker to detect such level of fibrosis or higher, led to a specificity and sensitivity of 100% and 71%, respectively. This new index has potential for noninvasive assessment of fibrosis in the clinical setting.

Purpose: To use a volume-selective 3D turbo spin echo (TSE) technique to image the carotid artery wall and measure distensibility. Materials and Methods:A high-resolution volume-selective 3D TSE sequence has been developed. Volume selection is accomplished by orthogonal gradients for the 90°a nd 180°excitations and allows a 3D volume of vessel wall to be imaged in a relatively short time. The technique has been developed to allow imaging at any defined phase of the cardiac cycle so that the vascular function and distensibility can be studied.Results: Scan efficiency is increased by the reduced phase encode field of view (FOV) (k y steps) by the use of selective volume excitation. Significantly more slices (k z phase encode steps) for vessel coverage can be acquired with the same scan time as that of the conventional sequence while maintaining signal-to-noise ratio (SNR) levels. The practical value of the technique was demonstrated on 10 normal subjects with high-resolution vessel distensibility measurements of the carotid arteries. Conclusion:A volume-selective TSE method has been used for carotid artery wall imaging and measurement of distensibility in normal subjects. Larger coverage of the vessel, and therefore more information for clinical diagnostics, was achieved with the same overall scan time with an SNR comparable to that of 2D full FOV images.

Spiral acquisition schemes offer unique advantages such as flow compensation, efficient k-space sampling and robustness against motion that make this option a viable choice among other non-Cartesian sampling schemes. For this reason, the main applications of spiral imaging lie in dynamic magnetic resonance imaging such as cardiac imaging and functional brain imaging. However, these advantages are counterbalanced by practical difficulties that render spiral imaging quite challenging. Firstly, the design of gradient waveforms and its hardware requires specific attention. Secondly, the reconstruction of such data is no longer straightforward because k-space samples are no longer aligned on a Cartesian grid. Thirdly, to take advantage of parallel imaging techniques, the common generalized autocalibrating partially parallel acquisitions (GRAPPA) or sensitivity encoding (SENSE) algorithms need to be extended. Finally, and most notably, spiral images are prone to particular artifacts such as blurring due to gradient deviations and off-resonance effects caused by B(0) inhomogeneity and concomitant gradient fields. In this article, various difficulties that spiral imaging brings along, and the solutions, which have been developed and proposed in literature, will be reviewed in detail.