Where mapping procedures were embedded into standard software packages for image analysis, again only specific image data were processed, and there was rarely any information available about the actual processing algorithms used.
From a post-processing point of view, most of these techniques have used proprietary software programs for map reconstruction. A recent offspring of these techniques is called modified Look-Locker inversion recovery (MOLLI) and opens the door for high-resolution T1 mapping in cardiac applications such as the assessment of heart muscle scarring in patients with heart attacks. In the past, a number of image acquisition schemes have been developed to enable measurement and mapping of MR relaxation times. These maps provide a visualization of the T1 or T2 properties in a quantitative fashion, since the signal intensity of each pixel in such a map directly reflects the relaxation time calculated (typically in milliseconds). If this is done on a pixel-by-pixel basis, so called parametric "maps" can be created. In fact, to obtain pure T1 or T2 information, it is necessary to acquire a set of raw images that use varying acquisition parameters, and to perform multi-parameter curve fitting analysis on this raw data based on the mathematical functions that describe the underlying physical processes. ĭue to the composite nature of the MR signal, it is not possible to acquire raw images with "pure", quantifiable T1 or T2 properties in a direct fashion. Examples for recent research efforts include investigations into the relaxation behavior of human brain in patients with multiple sclerosis, studies of T1 and T2* changes under pharmacological stress in coronary artery disease, quantification of iron overload of the heart and liver in thalassaemia major, and analysis of myocardial fibrosis in aortic regurgitation. In clinical MR imaging, all three time constants represent characteristic magnetic properties of a given tissue, and changes from their normal values can be used to identify pathological states of that tissue. The degree to which these time constants determine signal intensity in an MR image depend on the technical parameters that are used for image acquisition. In particular, there are three time constants describing the behavior of the net magnetization vector M in an MR experiment: 1) the longitudinal or spin-lattice relaxation time T1, describing the recovery of the M z component of M 2) the transversal or spin-spin relaxation time T2, describing the decay of the M xy component of M and 3) T2*, which in contrast to T2 also includes the loss of phase coherence due to field inhomogeneities and susceptibility effects. Signal intensity in conventional MR images is influenced by a multitude of physical phenomena. Magnetic resonance (MR) imaging is a complex imaging modality, which has gained widespread use in modern medicine.
The program and its source code were made available as open-source software on the internet. The software allows researchers to optimize quantitative MR strategies in a manufacturer-independent fashion. MRmap is a flexible cross-platform research tool that enables accurate mapping of relaxation times from various pulse sequences. Completed maps were exported in DICOM format and could be read in standard software packages used for analysis of clinical and research MR data. Estimates of relaxation times compared favorably to those obtained from non-automated curve fitting. Computing times varied between 2 and 113 seconds. MRmap was successfully tested on three different computer platforms with image data from three different MR system manufacturers and five different sorts of pulse sequences: multi-image inversion recovery T1 Look-Locker/TOMROP T1 modified Look-Locker (MOLLI) T1 single-echo T2/T2* and multi-echo T2/T2*.
Additional features include a manual registration tool for source images with motion artifacts and a tabular DICOM viewer to examine pulse sequence parameters. ResultsĪfter defining requirements for a universal MR mapping tool, a software program named MRmap was created using a high-level graphics language. Such a software program would allow researchers to test and compare new imaging strategies and thus would significantly facilitate research in the area of quantitative tissue characterization. While there are basic software tools for specific pulse sequences, until now there is no universal software program available to automate pixel-wise mapping of relaxation times from various types of images or MR systems. In magnetic resonance (MR) imaging, T1, T2 and T2* relaxation times represent characteristic tissue properties that can be quantified with the help of specific imaging strategies.