Research database

The MARVEL project draws its motivation from the problem of high levels of acoustic noise currently present in Magnetic Resonance Imaging (MRI) scans. Our proposed approach exploits an innovative approach based on metamaterials, which can provide a novel, more efficient solution compared to existing traditional noise-reduction solutions. Metamaterials have been successfully developed in recent years to achieve advanced wave manipulation and control in electromagnetics, elasticity and acoustics. The participants of this proposal have developed novel bioinspired metamaterial designs in the FET Open "BOHEME" (863179) project, and applied them to noise abatement. MARVEL now aims to take advantage of these new concepts to realize a thin noise insulating labyrinthine metamaterial layer to be applied to the internal surface of the cylindrical MRI cavity, taking up a negligible thickness and producing a large noise reduction in the most challenging low-frequency region (below 1 kHz). The graded design enables a wide operating frequency range, covering the most critical frequencies in MRI sequences. The objective of MARVEL is now to advance the current demonstrator from TRL 3/4 to TRL 7, realizing a working prototype in various commercial scanners, from 1.5T to 7T. The target device will entail significant advantages compared to existing solutions since it can be easily installed without modifying MRI operation, is immune to high magnetic fields, can be applied to all scanner types, and is extremely cost efficient, since it is a passive system. As a spin-off from this application, MARVEL will also develop the same metamaterial concept to reduce in RF noise in ultra-low field scanners. We aim to develop a viable and competitive business model, able to deliver our value proposition to the market and respond to client needs. In this way, we will realize an effective transition of our technological breakthrough to innovation in the sustainable economy landscape.

• Federico Bosia (Principal Investigator)
• Antonio Gliozzi (Component of the research team)