Physikalisch-Technische Bundesanstalt

FB 8.1 Medizinische Messtechnik

Abbestr. 2-12

10587  Berlin

Telephone:   +49 30 3481 7471



Compressed sensing MRI for 4D-cardiac flow quantification

PIs: Jeanette Schulz-Menger, Sebastian Schmitter, Gitta Kutyniok

Application area: MRI

Modality: Cardiovascular

Background: 4D-flow MRI is of growing interest in different fields of cardiovascular medicine at all stages of life, as it provides new insights into hemodynamics, e.g. in the ascending aorta in subjects with bicuspid aortic valve disease or in patients with outflow tract stenosis. Furthermore, quantification of vessel wall injury by flow measurements may give insights into myocardial injury, for example in vascular disease. Nevertheless, 4D-flow MRI still suffers substantially from limited temporal and spatial resolution, and from long image acquisition times.

Aim: The objective of this PhD project is to increase the temporal and spatial resolution of 4D-flow MRI while limiting the acquisition time. This will be achieved by compressed sensing (CS) techniques, which exploit the inherent sparsity of MRI signals in different transformation domains. Different k-space sampling schemes as well as different CS reconstruction techniques such as shearlets based or dictionary learning techniques will be implemented and their performance will be quantitatively assessed. The accuracy and reproducibility of the quantitative values will be evaluated in experiments with pulsatile flow phantoms, in comparison to standard 4D flow imaging techniques. A CS based imaging protocol will then be applied in-vivo in a study with healthy volunteers, followed by a clinical pilot study including patients suffering from cardiovascular diseases.

Methods: Whereas the in-vivo studies are envisaged to be conducted primarily on a 3 Tesla MRI system, an additional focus will be set on investigating the advantages of higher magnetic field strengths (7 Tesla) for the developed CS methods. It is expected that the higher SNR and the stronger spatial variations of the receive sensitivity profiles will benefit the reconstruction methods and therefore will enhance the accuracy.