Cerebral Gray and White Matter Involvement in Anorexia Nervosa Evaluated by T1, T2, and T2*Mapping

BACKGROUND AND PURPOSE Changes in the brain composition of anorexics could potentially be expected, opening the door to new imaging approaches where quantitative and qualitative MRI have a role. Our purpose was to investigate anorexia-related brain dehydration and myelin depletion by analyzing T1, T2, and T2* relaxation times of different brain structures in anorexics and controls. METHODS Thirty-eight anorexic female patients (mean age, 26.2 years; age range, 16.2-48.7 years; mean BMI, 14.5 kg/m(2); BMI range, 10.0-18.4 kg/m(2)) underwent brain MRI between August 2014 and August 2018. Controls were 16 healthy females (mean age, 28.0 years; age range, 22.3-34.7 years; mean BMI, 20.9 kg/m(2); BMI range, 18.4-26.6 kg/m(2)). T1, T2, and T2* relaxation times were obtained for different brain structures in anorexics and controls as part of this retrospective case-control study. RESULTS The T1 relaxation times of gray and white matter were significantly lower in anorexics (P = .009), whereas the T2 relaxation times of gray matter were higher (P < .001). There were no statistically significant differences in gray matter T2* relaxation times or in white matter T2 and T2* relaxation times between anorexics and controls. Occipital lobe gray matter showed the shortest T1, T2, and T2* relaxation times of all brain regions (P < .05). CONCLUSIONS T1 shortening in anorexics suggests both dehydration and myelin loss, whereas T2 prolongation points toward myelin loss (myelin water has lower T2), which seems to be less discernible in white matter. Shorter overall relaxation times in the most posterior regions of the brain suggest higher iron content.

Quantitative Susceptibility Mapping in the Human Brain

Diana Khabipova

Magnetic resonance imaging (MRI) offers a good tissue contrast and the ability to visualize many disease related morphologies. The work presented in this thesis investigates the study of underlying structure of the brain using quantitative methods with a special emphasis on quantitative susceptibility mapping (QSM). Magnetic susceptibility reflects the interaction of a material to the magnetic field and measures in biological tissues the magnetic susceptibility of inclusions. The reconstruction of QSM requires further processing steps as the magnetic field produced by the sources needs to be disentangled from the orders of magnitude bigger background field. The produced field also depends not only on the shape and the orientation, but also on the anisotropy of susceptibility and the microstructural compartmentalization of the biological source. For this reason, reconstruction methods need to be capable to calculate accurate values for different brain regions as well as applicable in the everyday clinical diagnosis. Within the framework of the thesis a data acquisition protocol based on a multiple-echo gradient echo sequence as well as a post-processing protocol was implemented. One of the processing steps, the background removal method, was applied to preserve the brain regions close to the cerebrospinal fluid (CSF). This method outperforms state of the art methods in this regions but is computationally intensive. Different brain regions were studied using quantitative methods with special emphasis on the QSM. A new method, modulated closed form solution, with extremely fast computational time is proposed. The comparison with other single orientation methods revealed similar results and the highest correlation to the state-of-the-art method (COSMOS) in the deep gray matter. The R2* maps calculated from the same dataset are also able to distinguish the deep gray matter structures with a similar quality. However, QSM shows a higher sensitivity in early stage multiple sclerosis lesions as well as white matter-gray matter structures. In the human cortex the obtained cortical maps show enhancement of primary sensory cortex, which is known to be highly myelinated, on three evaluated quantitative contrasts R1,R2* and susceptibility. The contrasts based on the relaxation rates, R1 and R2*, show a monotonically decrease from the white matter to the CSF imitating the decrease in iron and myelin. The susceptibility behaviour is more complex as iron and myelin content introduce an opposing sensitivity, allowing to study iron and myelin content when combining the three contrasts. The microstructural organization of white matter influences the R2*, R2 as well as field map from which QSM is calculated. This structure leads to an orientation dependence of the studied contrasts and for QSM the spherical assumption is not valid anymore. Therefore a new QSM method is introduced, which includes the Lorentzian correction in white matter. Main fibres such as forceps major and minor were analysed for the three different quantitative contrasts. The anisotropic component associated with susceptibility is similar for the relaxation rates whereas the isotropic component of R2* shows a higher variability. The resulting deep gray matter structure of the new QSM method remained similar to the state-of-the-art method when comparing the isotropic component but calculates physically meaningful susceptibility maps with improved contrast between known fibre bundles.

EPFL2016

Distribution of the monocarboxylate transporter MCT2 in human cerebral cortex: an immunohistochemical study

Pierre Magistretti, Luc Pellerin

The monocarboxylate transporter MCT2 belongs to a large family of membrane proteins involved in the transport of lactate, pyruvate and ketone bodies. Although its expression in rodent brain has been well documented, the presence of MCT2 in the human brain has been questioned on the basis of low mRNA abundance. In this study, the distribution of the monocarboxylate transporter MCT2 has been investigated in the cortex of normal adult human brain using an immunohistochemical approach. Widespread neuropil staining in all cortical layers was observed by light microscopy. Such a distribution was very similar in three different cortical areas investigated. At the cellular level, the expression of MCT2 could be observed in a large number of neurons, in fibers both in grey and white matter, as well as in some astrocytes, mostly localized in layer I and in the white matter. Double staining experiments combined with confocal microscopy confirmed the neuronal expression but also suggested a preferential postsynaptic localization of synaptic MCT2 expression. A few astrocytes in the grey matter appeared to exhibit MCT2 labelling but at low levels. Electron microscopy revealed strong MCT2 expression at asymmetric synapses in the postsynaptic density and also within the spine head but not in the presynaptic terminal. These data not only demonstrate neuronal MCT2 expression in human, but since a portion of it exhibits a distinct synaptic localization, it further supports a putative role for MCT2 in adjustment of energy supply to levels of activity.

2008

Quantitative morphometry analysis of the fetal brain using clinical MR imaging

Meritxell Bach Cuadra, Gabriele Vincenzo Bonanno, Marie Schaer, Jean-Philippe Thiran

In vivo fetal magnetic resonance imaging provides a unique approach for the study of early human brain development [1]. In utero cerebral morphometry could potentially be used as a marker of the cerebral maturation and help to distinguish between normal and abnormal development in ambiguous situations. However, this quantitative approach is a major challenge because of the movement of the fetus inside the amniotic cavity, the poor spatial resolution provided by very fast MRI sequences and the partial volume effect. Extensive efforts are made to deal with the reconstruction of high-resolution 3D fetal volumes based on several acquisitions with lower resolution [2,3,4]. Frameworks were developed for the segmentation of specific regions of the fetal brain such as posterior fossa, brainstem or germinal matrix [5,6], or for the entire brain tissue [7,8], applying the Expectation-Maximization Markov Random Field (EM-MRF) framework. However, many of these previous works focused on the young fetus (i.e. before 24 weeks) and use anatomical atlas priors to segment the different tissue or regions. As most of the gyral development takes place after the 24th week, a comprehensive and clinically meaningful study of the fetal brain should not dismiss the third trimester of gestation. To cope with the rapidly changing appearance of the developing brain, some authors proposed a dynamic atlas [8]. To our opinion, this approach however faces a risk of circularity: each brain will be analyzed / deformed using the template of its biological age, potentially biasing the effective developmental delay. Here, we expand our previous work [9] to propose post-processing pipeline without prior that allow a comprehensive set of morphometric measurement devoted to clinical application. Data set & Methods: Prenatal MR imaging was performed with a 1-T system (GE Medical Systems, Milwaukee) using single shot fast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms, FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatial resolution 1.09mm). For each fetus, 6 axial volumes shifted by 1 mm were acquired under mother’s sedation (about 1min per volume). First, each volume is segmented semi-automatically using region-growing algorithms to extract fetal brain from surrounding maternal tissues. Inhomogeneity intensity correction [10] and linear intensity normalization are then performed. Brain tissues (CSF, GM and WM) are then segmented based on the low-resolution volumes as presented in [9]. A high-resolution image with isotropic voxel size of 1.09 mm is created as proposed in [2] and using B-splines for the scattered data interpolation [11]. Basal ganglia segmentation is performed using a levet set implementation on the high-resolution volume [12]. The resulting white matter image is then binarized and given as an input in FreeSurfer software (http://surfer.nmr.mgh.harvard.edu) to provide topologically accurate three-dimensional reconstructions of the fetal brain according to the local intensity gradient. References: [1] Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau, Acad. Rad. 13(9), 2006. [3] Jiang, IEEE TMI 2007. [4] Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio. Eng. 51(4) 2004. [6] Habas, MICCAI 2008. [7] Bertelsen, ISMRM 2009. [8] Habas, Neuroimage 53(2) 2010. [9] Bach Cuadra, IADB, MICCAI 2009. [10] Styner, IEEE TMI 19(39 (2000). [11] Lee, IEEE Trans. Visual. And Comp. Graph. 3(3), 1997. [12] Bach Cuadra, ISMRM 2010.