A New Approach for Deep Gray Matter Analysis Using Partial-Volume Estimation.

INTRODUCTION: The existence of partial volume effects in brain MR images makes it challenging to understand physio-pathological alterations underlying signal changes due to pathology across groups of healthy subjects and patients. In this study, we implement a new approach to disentangle gray and white matter alterations in the thalamus and the basal ganglia. The proposed method was applied to a cohort of early multiple sclerosis (MS) patients and healthy subjects to evaluate tissue-specific alterations related to diffuse inflammatory or neurodegenerative processes. METHOD: Forty-three relapsing-remitting MS patients and nineteen healthy controls underwent 3T MRI including: (i) fluid-attenuated inversion recovery, double inversion recovery, magnetization-prepared gradient echo for lesion count, and (ii) T1 relaxometry. We applied a partial volume estimation algorithm to T1 relaxometry maps to gray and white matter local concentrations as well as T1 values characteristic of gray and white matter in the thalamus and the basal ganglia. Statistical tests were performed to compare groups in terms of both global T1 values, tissue characteristic T1 values, and tissue concentrations. RESULTS: Significant increases in global T1 values were observed in the thalamus (p = 0.038) and the putamen (p = 0.026) in RRMS patients compared to HC. In the Thalamus, the T1 increase was associated with a significant increase in gray matter characteristic T1 (p = 0.0016) with no significant effect in white matter. CONCLUSION: The presented methodology provides additional information to standard MR signal averaging approaches that holds promise to identify the presence and nature of diffuse pathology in neuro-inflammatory and neurodegenerative diseases

Effects of MP2RAGE B\u3csub\u3e1\u3c/sub\u3e\u3csup\u3e+\u3c/sup\u3e sensitivity on inter-site T\u3csub\u3e1\u3c/sub\u3e reproducibility and hippocampal morphometry at 7T

Most neuroanatomical studies are based on T -weighted MR images, whose intensity profiles are not solely determined by the tissue\u27s longitudinal relaxation times (T ), but also affected by varying non-T contributions, hampering data reproducibility. In contrast, quantitative imaging using the MP2RAGE sequence, for example, allows direct characterization of the brain based on the tissue property of interest. Combined with 7 Tesla (7T) MRI, this offers unique opportunities to obtain robust high-resolution brain data characterized by a high reproducibility, sensitivity and specificity. However, specific MP2RAGE parameter choices – e.g., to emphasize intracortical myelin-dependent contrast variations – can substantially impact image quality and cortical analyses through remnants of B -related intensity variations, as illustrated in our previous work. To follow up on this: we (1) validate this protocol effect using a dataset acquired with a particularly B insensitive set of MP2RAGE parameters combined with parallel transmission excitation; and (2) extend our analyses to evaluate the effects on hippocampal morphometry. The latter remained unexplored initially, but can provide important insights related to generalizability and reproducibility of neurodegenerative research using 7T MRI. We confirm that B inhomogeneities have a considerably variable effect on cortical T estimates, as well as on hippocampal morphometry depending on the MP2RAGE setup. While T differed substantially across datasets initially, we show the inter-site T comparability improves after correcting for the spatially varying B field using a separately acquired Sa2RAGE B map. Finally, removal of B residuals affects hippocampal volumetry and boundary definitions, particularly near structures characterized by strong intensity changes (e.g. cerebral spinal fluid). Taken together, we show that the choice of MP2RAGE parameters can impact T comparability across sites and present evidence that hippocampal segmentation results are modulated by B inhomogeneities. This calls for careful (1) consideration of sequence parameters when setting acquisition protocols, as well as (2) acquisition of a B map to correct MP2RAGE data for potential B variations to allow comparison across datasets. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 + + + + + + + +

Longitudinal automated detection of white-matter and cortical lesions in relapsing-remitting multiple sclerosis

Magnetic Resonance Imaging(MRI) plays an important role for lesion assessment in early stages of Multiple Sclerosis(MS). This work aims at evaluating the performance of an automated tool for MS lesion detection, segmentation and tracking in longitudinal data, only for use in this research study. The method was tested with images acquired using both a "clinical" and an "advanced" imaging protocol for comparison. The validation was conducted in a cohort of thirty-two early MS patients through a ground truth obtained from manual segmentations by a neurologist and a radiologist. The use of the "advanced protocol" significantly improves lesion detection and classification in longitudinal analyses

Étude des effets de volume partiel en IRM cérébrale pour l'estimation d'épaisseur corticale

The work developed in this thesis is within the scope of magnetic resonance imaging (MRI) acquisition and image processing for the automated analysis of brain structures. The measurement of structural modifications with time such as cortical atrophy requires the application of image processing algorithms. They must compensate for MRI artifacts such as intensity inhomogeneities or partial volume (PV) effects to allow for brain tissues segmentation then cortical thickness estimation. We suggest a new PV model relying on the physics of acquisition named bi-exponential model that differs from the commonly used linear model by modelling brain tissues and image acquisition. It requires the use of two differently contrasted and perfectly coregistered images. This model has been validated with simulations and physical and digital phantoms in a first place. In parallel, the recent MP2RAGE sequence provides two coregistered images and their combination results in a bias-field corrected image as well as a T1 map of the scanned tissues. We tested our model with in vivo MP2RAGE data and demonstrated that using the linear PV model leads to a systematic gray matter proportion underestimation in PV voxels. These errors result in cortical thickness underestimation. Our results favor the following assumption: PV modelling with MP2RAGE images must differ from the usual linear PV model applied for images obtained from more classic sequences. The bi-exponential model is an adapted solution to this particular sequence.Les travaux réalisés dans cette thèse se situent à l'interface des domaines de l'acquisition en imagerie par résonance magnétique (IRM) et du traitement d'image pour l'analyse automatique des structures cérébrales. La mesure de modifications structurelles telles que l'atrophie corticale nécessite l'application d'algorithmes de traitement d'image. Ceux-ci doivent compenser les artefacts en IRM tels que l'inhomogénéité du signal ou les effets de volume partiel (VP) pour permettre la segmentation des tissus cérébraux puis l'estimation d'épaisseur corticale. Nous proposons une nouvelle modélisation de VP proche de la physique de l'acquisition baptisée modèle bi-exponentiel qui vient concurrencer le traditionnel modèle linéaire. Il nécessite l'utilisation de deux images de contrastes différents parfaitement recalées. Ce modèle a été validé sur des simulations et des fantômes physique et numérique dans un premier temps. Parallèlement, la récente séquence MP2RAGE permet d'acquérir deux images co-recalées par acquisition et leur combinaison aboutit à l'obtention d'une image insensible aux inhomogénéités du signal et d'une carte de T1 des tissus imagés. Nous avons testé notre modèle sur des données in vivo MP2RAGE et avons montré que l'application du modèle linéaire de VP conduit à une sous-estimation systématique de la substance grise à l'échelle du voxel. Ces erreurs se propagent à l'estimation d'épaisseur corticale, biomarqueur très sensible aux effets de VP. Nos résultats plaident en faveur de l'hypothèse suivante : la modélisation de VP pour les images MP2RAGE doit être différente de celle employée pour des images obtenues avec des séquences plus classiques. Le modèle bi-exponentiel est une solution adaptée à cette séquence particulière

Clinical translation of quantitative MRI techniques in Neuroradiology

The overall objective of the present work is the translation of advanced qMRI techniques from the research environment into the field of clinical neuroimaging. In this context, qMRI is defined as the application of absolute quantitative measures that are extracted from in vivo MRI data. These can be used to describe biophysical characteristics and processes and thereby enhance the diagnostic power of qualitative, “weighted” imaging that is primarily used in the clinical setting. The feasibility, usefulness, and limitations of five qMRI techniques were investigated in different CNS pathologies (brain tumours, ischaemic stroke, migraine, brain/skull malformations) and in the description of normal brain maturation in infants and young children. The translation of new imaging methods from “bench to bedside” involves several steps, and the presented studies are located at different stages in this process. Studies 1 and 2 are examples of a relatively early stage. At the time of publication, pH-weighted APT imaging had been tested preclinically and in smaller cohorts of patients, but not in acute stroke, where anaerobic glycolysis and tissue acidosis is highly prevalent. In study 1, it was postulated that APT imaging could be a novel approach to demonstrate oligaemia in hyperacute stroke, allowing a more detailed description of tissue at risk. For acceleration purposes, sequence parameters were optimised by using computer simulations and subsequently validated in healthy subjects. Ten acute stroke patients were included (7 < 4 hours, 3 < 24 hours after symptom onset). As expected, the APT effect was significantly decreased in ischaemic regions compared to normal white matter (p=0.03) and APT values tended to be lower in the final infarct volume (p=0.10). In study 2, APT imaging was moved to a different pathology, also characterised by hypoperfusion, tissue hypoxia, and anaerobic glycolysis. Here, the metabolic changes during the migraine aura of a patient with FHM were investigated for the first time using APT imaging. The patient developed clear tissue acidosis and blood flow disturbances in the absence of ischaemia in the affected cerebral hemisphere, possibly caused by CSD, i.e. the state of neuronal inhibition that is supposed to be the pathophysiological basis of migraine aura. The studies were not designed to provide a statistical conclusion, but to identify technical strengths and weaknesses of this imaging technique. Study 6 also represents an early phase of clinical translation. Here, a new postprocessing approach was developed to achieve absolute metrics for the measurement of dynamic processes on CINE MRI, a time-resolved method to visualise moving structures in vivo, e.g. in cardiac, bowel, or foetal imaging. Usually movement is evaluated qualitatively and to date objective quantitative approaches are missing. In this study, a measuring method (voxel intensity distribution method, VIDM) for subtle movements was developed and applied in 27 children with Chiari and other brain/skull malformations, where cerebellar tissue herniates dynamically through the foramen magnum following CSF pulsatility. The degree of movement was compared using VIDM and visually derived, clinically accepted linear measurements on CINE sequences. In 85% of the patients, VIDM showed significantly more cerebellar displacement (p=0.002) compared to simple visual assessments, although this did not correlate with the clinical outcome parameters (hydrocephalus or syringomyelia; Pearson’s correlation coefficient -0.28; p=0.16). It is suggested that VIDM might be a valuable tool to detect and measure subtle dynamic processes in the CNS, but extracranial applications are also very likely. Study 3 and 7 represent validation studies of methods that have been presented in clinical data before. In study 3, 2HG MRS was used in 35 patients suspected for cerebral gliomas to determine the IDH mutational status that today is an integral part of the WHO brain tumour classification system. For this study, a dedicated MRS sequence was used and the routine imaging protocol was extended by only 6 min. The sensitivity/specificity for determining the IDH mutational status was 89.5% and 81.3%, respectively. It could be concluded that 2HG MRS is an easily applicable supplement to standard imaging protocols that allows presurgical diagnostics and opens up for more detailed assessment during treatment. In study 7, T1 maps were generated from clinical MRI data using the MP2RAGE sequence, a technique extensively applied in neuroscience, but little in the clinical setting. The technical parameters were adapted to find a balance between short acquisition times, high signal-to-noise, and reliable T1 values to quantify myelin maturation in 94 children up to the age of 6 years. The assessment of adequate myelination is a central part of paediatric imaging diagnostics, but is to date done by evaluating images qualitatively. The aim was to validate the MP2RAGE-based T1 mapping technique for the assessment of normal myelination, and data were compared to those of children with various CNS pathologies. Additionally, the diagnostic power of the MP2RAGE was pointed out for the qualitative assessment of regular myelination and brain pathologies. The purpose of study 4 and 5 was to improve the diagnostic confidence of perfusion-weighted DCE maps. DCE is a well-established technique outside the CNS, but is used less in neuroimaging due to a number of technical issues. Here, postprocessing was addressed with the aim to reduce noise in the resultant parameter maps. Two curve-fitting methods, the Levenberg-Marquardt (LM) algorithm and a Baysian method (BM), were compared in digital phantoms and in 42 glioma patients applying two compartmental models (extended Toft’s, ETM, and 2-compartment- exchange model, 2CXM). The image quality was assessed with regard to tumour discrimination and overall impression of the images. Moreover, the diagnostic performance to differentiate high-grade from low-grade gliomas was investigated. The image quality of parameter maps generated by BM was significantly improved compared to LM (p<0.001), and the 2CXM- based maps were higher rated, regardless of the fitting method. The diagnostic performance to differentiate tumour grades was excellent for Ktrans and Vp (p<0.001). This was not affected by the fitting method for the leakage parameter Ktrans, whereas Vp was improved when using BM. These studies suggest that using BM to derive perfusion parameters from DCE data are superior to LM, hopefully leading to higher diagnostic confidence and acceptance in the clinical community. Clinical imaging diagnostics benefits without doubt from the integration of quantitative information gained by qMRI, thereby increasing reproducibility and reliability and enabling the objective comparison to normative and patient databases. Each step of the clinical translation process is essential to show opportunities, identify areas of optimisation, and to reveal challenges and limitations. After further development APT imaging is today available on standard MRI platforms, and BM-based curve fitting of perfusion data has been implemented in postprocessing software programmes. T1 maps of normal myelination in children are made publicly available and may be a first step towards an automated tool to detect myelination disorders more efficiently