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Chapter 1
Introduction
1.1 Magnetic Resonance Imaging: a fundamental tool for
neuroimaging
The principles of Nuclear Magnetic Resonance (NMR) were laid in the late ‘40s by Purcell [1] and Bloch [2], and represented a completion of much of the work done in the preceding years that revolutionised the knowledge of physics. The discovery of this phenomenon represented an important confirmation of quantum mechanics, and led later to other significant findings on the ultimate structure of the matter. However, while NMR was immediately valued as a tool for fundamental physics research, its possible imaging applications were at that time completely unimagined. Much of the subsequent development of the field of NMR can be viewed as turning artefacts of the original techniques into powerful tools for measuring other properties of matter.
It is known, in fact, that since the resonant frequency of a nucleus is proportional to the magnetic field, any inhomogeneities of the magnet translate into an unwanted broadening of the spectral lines. In 1973 Lauterbur proposed that NMR techniques could also be used for imaging by deliberately altering the magnetic field homogeneity in a controlled way [3]. By applying a linear gradient field to a sample, the NMR signals from different locations were spread out in frequency, instead of overlapping in an uncontrolled way. The measure of the frequency distribution in presence of a field gradient provided a direct measure of the distribution of signals within the sample: an image. The first commercial magnetic resonance imagers were built in the early 1980s, and magnetic resonance imaging is now an essential part of clinical radiology.
With the improvement of the imaging hardware, it became evident that even with an ideally perfect magnet, field inhomogeneities would be present in any case since the sample to image, i.e. the human body itself, leads to local variations in the magnetic field. These field inhomogeneities first appeared in images as artifacts, either as image distortion or local signal reduction because of spin dephasing due to precession at different rates, which eventually reduces the net signal. In the early 1990s, though, one of these body-related inhomogeneity effects was measured, since it was demonstrated that the oxygenation state of
Introduction
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hemoglobin has a measurable effect on the signal measured with MR imaging [4]. This finding soon led to the capability of mapping brain activity based on blood oxygenation changes accompanying neural activation [5]. What was primarily considered as an inconvenience of the imaging technique became soon the basis for a new branch, functional
MRI (fMRI). This technique has become a standard tool for functional
neuroimaging and is now widely used for mapping the working human brain.
More than thirty years after their introduction, MR scanners represent nowadays a basic tool for clinical operators, which can exploit their great capabilities in imaging with high contrast soft tissues without any invasive procedure. Their usage is becoming even more frequent since MRI-based techniques are receiving an explosion of interest in the neuroscience and clinical investigations. The widespread availability of the technology, its relatively low cost per examination, and the lack of recognized risks to repeated applications have already ensured that fMRI will have a major role in both basic and clinical neuroscience for some time to come.
1.2 Aims of the study
Although MRI is now recognized as an irreplaceable tool for investigation of human brain, there are several important issues that still need being clarified so that this imaging technique can express its widest potentialities.
Since MRI has recently become also a device for brain functional analysis, the chances to obtain a correct diagnosis of the brain functioning are directly related to the capability of understanding exactly what to expect from the MR signal during functional activity. This is a basic and difficult issue for MRI, since the relation between MR signal and functional activation is extremely complex and still not completely known.
The goal of this thesis is therefore to clarify through theoretical models and experimental sessions the processes with which brain anatomy and functionality is “transformed” by the imaging device into signals and images. Starting from this assumption, this thesis covers many topics of current investigation by the researcher community.
The principle on which this work is structured is that a preliminary understanding of the MR signal produced by blood containing regions can lead to the design and optimization of the scanning procedure and provide indications on the quality of the results obtained.
In agreement with this principle, this work introduces a general framework of numerical simulations to forecast venous BOLD signal from analytical models based on theoretical behaviour of blood and
Introduction
3 cerebral tissues. The results obtained with these simulations represent a basic knowledge with which to evaluate the performance of MR scanning procedure. As an example, in this thesis it is shown how to assess the efficacy of a particular venographic imaging procedure, such as contrast enhanced high-resolution BOLD venography [6].
Together with the analysis of this particular technique, the numerical simulations provided indications in order to redesign the whole procedure of BOLD venography. This represents an important result achieved, since angiographic methodologies are becoming more and more important for the diagnosis of many cerebral diseases.
A further goal of this thesis was to develop a methodology with which to investigate the origin of the BOLD functional response in relation with brain vasculature. This problem is an important issue, as there are great expectations on the validity of BOLD functional maps, since they are the ultimate tools with which to perform diagnosis on the brain health state.
1.3 Thesis organization
In this thesis, chapter 2 and chapter 3 are namely dedicated to the principle of Nuclear Magnetic Resonance and Magnetic Resonance Imaging. In these two chapters the basic concepts of the imaging techniques are introduced, starting with the understanding of the physical phenomenon of NMR, moving to the principles of signal frequency encoding and concluding with the imaging hardware required to perform MRI.
Chapter 4 and chapter 5 describe two important applications of MRI, i.e. brain angiography and functional MRI. In chapter 4 several techniques are introduced to perform brain angiography, explaining advantages and limits of each technique and focusing in particular on high-resolution venography. In chapter 5, instead, the implications of functional activation on MR signal are discussed, thus introducing BOLD fMRI. Also in this case the main issues of this technique are discussed and analyzed.
Chapter 6 through chapter 9 include instead the original contribution of the doctorate activity. Chapter 6 illustrates a practical application of the use of numerical simulation to predict BOLD signal. In this chapter it is shown how to evaluate the MR signal starting from the vessel configuration, and how to assess with the aid of these results how the use of a T1-reducing contrast agent is effective in high-resolution BOLD venography.
In chapter 7 a theoretical-experimental study is depicted, in which high-resolution BOLD venography is analyzed and redesigned in order to overcome its pitfalls and to exploit its full potentialities. Tests on
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digital phantoms and real MR images are shown which confirm the validity of the method.
Chapter 8 introduces an anatomical-functional experimental procedure to study the cortical functional response in relation the brain micro- and macrovasculature. In this chapter a procedure is described to segment the brain vasculature from BOLD venography dataset, and to correlate the functional signal intensity to the underlying vasculature.
Finally, in chapter 12, the most important conclusions of this work are summarized and some speculations are given on the most promising future developments of this research topic.
1.4 References
1 Purcell, E. M., Torrey, H. C. and Pound, R. V. Resonance Absorption by Nuclear Magnetic Moments in a Solid. Phys. Rev. 1946;69,37-38 2 Bloch, F., Hansen, W. W. and Packard, M. Nuclear Induction. Phys.
Rev.1946; 69,127
3 Mansfield, P. and Grannell, P. K. NMR `diffraction' in solids? J. Phys. 1973 C 6, L422-L426.
4 Ogawa S, Lee TM, Nayak AS, et al. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med. 1990;14:68-78
5 Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, Kennedy DN, Hoppel BE, Cohen MS, Turner R, Cheng HM, Brady TJ, Rosen BR. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A 1992;89:5675-5679
6 Lin W, Mukherjee P, An H, Yu Y, Wang Y, Vo K, Lee B, Kido D, Improving High-Resolution MR Bold Venographic Imaging Using a T1 Reducing Contrast Agent, Journal of Magnetic Resonance Imaging 10:118–123 (1999)
