לוח שנה משולב

Magnetic resonance imaging (MRI) has undergone a significant expansion during the last two decades and to-date stands as one of the most prominent diagnostic modalities in use. This technique offers non-invasive and non-ionizing tool, capable of probing a wide range of materials, and providing a broad spectrum of contrasts via intricate manipulations of atomic nuclear magnetization. These properties, together with the introduction of new and improved hardware, have led to a gradual increase in the prevalence of MR imaging, and to the development of numerous new methods, which extend the capabilities of MRI beyond basic anatomical diagnosis. Examples include the study of various physiological functions, analyzing chemical / metabolic properties of materials and tissues, tracking dynamic processes, and more.
One of the major driving forces in contemporary MRI-research rests in the pursuit of new schemes for retrieving improved images, and using shorter acquisition times. A single distinct approach, however, underlies the majority of MR imaging, and is based on encoding and reading the image information in the frequency (k-space) domain. Recent reports by Prof. Lucio Frydman et al, have introduced a conceptually different approach for collecting MR spectra, which is based on a progressive SPatiotemporal-ENcoding (SPEN) of the magnetic spins in the sample. This novel approach enabled the ultrafast acquisition of multidimensional NMR spectra in a single-scan, thereby offering up to several orders of magnitude reduction in the corresponding scan time.
The work which will be presented in this lecture further investigated the potential of SPEN, within the context of MR imaging. This entailed several research avenues ranging from the design of various multidimensional imaging protocols, through the development of an image reconstruction algorithm based on super-resolution principles, and the subsequent application of these methods for in-vivo imaging in animals and humans. As will be demonstrated SPEN-based protocols are able to more optimally utilize the parameter space supported by MRI. This allows them to surpass conventional imaging methods when dealing with spatial field inhomogeneities, and in some cases provide the means to collect reliable information under conditions which were so far unsuitable for MR-based investigations.