Tissues in the human body can be distinguished with magnetic resonance imaging (MRI) depending on their MR parameters, such as the longitudinal T1 relaxation, the transverse T2 relaxation, and the proton density (PD). In clinical routine, the MR scanner settings, such as echo time (TE), repetition time (TR), and flip angle, are most often chosen to highlight or suppress signal intensity of tissues, resulting in T1-weighting or T2-weighting in a contrast image. These procedures are well-established and relatively quick. For many years radiologic interpretation with magnetic resonance (MR) imaging has focused on qualitative visual assessment of anatomy and disease processes rather than quantitative analysis. A major disadvantage of using such contrast images is that the absolute intensity has no direct meaning and diagnosis relies on comparison with surrounding tissues in the image. In many cases it is therefore necessary to perform several different contrast scans. A more direct approach is the absolute quantification of the tissue parameters T1, T2, and PD. In this case, pathology can be examined on a pixel-by-pixel basis to establish the absolute deviation compared to the normal values and the progress of the disease could then be expressed in absolute numbers. Quantitative and qualitative MR imaging offer complementary medical information and use the same technology platform and equipment. While the patient information generated with conventional scanning is primarily visual, quantitative MRI provides information that is intrinsically more tissue-specific and is less dependent on subjective visual assessment. The quantitative data can also be postprocessed to take advantage of new ways of looking at the wealth of information available such as segmentation based on biophysical properties and anatomy, distribution histograms, and synthetic MR images of user-definable and variable weighting (variable at the time of image interpretation). In clinical applications T1 and T2 mapping offer insights into pathophysiology in vivo which is important in drug development, development of imaging biomarker for personalized medicine, early diagnosis with the possibility of disease-modifying drugs, a predictive marker for outcome, to identify patients at risk (e.g for OA) and monitoring of treatment response and quality control of tissue engineering (e.g. cartilage transplantation). T1 mapping has gained high interest in non-ischemic cardiomyopathies, myocarditis and other cardiac diseases and has become part of the routine cardiac MR imaging protocol. In liver imaging iron corrected T2 mapping allows evaluation of ballooing and inflammation and iron corrected T1 mapping information on fibrosis and inflammation. In neuroimaging quantitative T1, T2 and PD maps provide a robust input for computer algorithms to automatically detect grey matter, white matter and cerebrospinal fluid, providing an accurate means to monitor brain atrophy in neuro-degenerative diseases. Recently a model was proposed with which it is possibe to detect myelin partial volume. Owing to the magnetization exchange between the rapidly relaxing myelin water and surrounding intra-and extracellular water, the presence of myelin is inferred using the observed changes in relaxation times and PD. It could be shown that myelin values are reduced in MS plaques and even perilesional white matter has lower myelin values than normal appearing white matter which implies that myelin imaging is sensitive to pathological changes difficult to discern with conventional sequences. Although the advantages of absolute quantification are obvious, its clinical use is still limited. At least three major obstacles need to be addressed to stimulate widespread clinical usage. For many methods, the excessive scan time associated with the measurement of the three parameters has so far prohibited its clinical application. However, in recent years there has been substantial progress with absolute quantification of T1, T2, PD, and the B0 inhomogeneity of a whole volume with high resolution in a mere 5 min and the development of MR Fingerprinting. The second obstacle, which must not be underestimated, is the clinical evaluation of the images. So far, there is only limited experience in using absolute T1, T2, and PD maps in clinical routines and most radiologists want to confirm their findings using conventionally-weighted contrast images. The third obstacle and this is a very critical one is the definition what is a normal T1 and T2 value in different tissues? A large variability of T1 values (e.g. gray matter values range from 968 to 1815 ms, muscle values range from 898 to 1509 ms) and a large dispersion of T2 values (e.g. fat values range from 41 to 371 ms, bone marrow values range from 40 to 160 ms, muscle values range from 27 to 44 ms) was reported. Many factors can cause systematic errors that can compromise the accuracy of the T1 and T2 maps: systematic bias of the measurement method, systematic bias of the data processing method, noise and flip angle effects. These factors are discussed in detail and solutions how to overcome them are presented.

Acknowledgements

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