In certain neuro-degenerative diseases likemultiple sclerosis (MS), the rate of brain atrophy can be measured by monitoring the brain parenchymal fraction (BPF) in such patients. The BPF is defined as the ratio of brain parenchymal volume (BPV, defined as the total volume of gray matter tissue, white matter tissue and other unidentified tissue) and intracranial volume (ICV, the total volume of the skull). It can be represented by the formula in equation 1: <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Csmall%20BPF%20=%20%5Cfrac%20%7BPBV%7D%7BICV%7D%20%5C;%20%5C;%20%5C;%20%5C;%20(1)" /> A complication with this measure is that the BPF is affected by the presence of edema in the brain, which leads to swelling and hence may obscure the true rate of brain atrophy. This leads to uncertainty when establishing “normal values” of BPF when analyzing different magnetic resonance imaging (MRI) scans of the same patient. Another problem is that different MRI scans of the same patient cannot be compared directly, due to the fact that the head of the patient will be in a different position for every scan. The SyMRI software used in this master thesis has the functionality to perform brain tissue characterization and measurement of brain volume, given a number of MR images of a patient. Using tissue properties such as longitudinal relaxation time (T1), transverse relaxation time (T2) and proton density (PD), each voxel in a volume can be classified to belong to a certain tissue type. From these measurements, the intracranial volume, brain volume, white matter, gray matter and cerebrospinal fluid volumes can easily be estimated. In this master thesis, the BPF of several patients were analyzed based on quantitative MRI (qMRI) images, in order to identify the change of BPF due to the presence of edema over time. Volumes obtained from the same patients at different time points were aligned (registered), such that the BPF can be easily compared between years. A correlation analysis between the BPF and R1, R2 and PD was performed (R1 is the longitudinal relaxation rate defined as 1/T1 relaxation time and R2 Is transverse relaxation rate defined as 1/T2 relaxation time) to investigate if any of these variables can explain the change in BPF. The results show that due to image registration, and removing some of the slices from the top and bottom of the head, the BPF of the patients was corrected to a certain extent. The change in the mean BPF of each patient over four years was less than 1% post registration and slice removal. However, the decrease in standard deviation was between 6.9% to 52% after registration and removing of slices. The BPF of the follow-up years also came closer to the initial BPF value measured in the first year. The statistical analysis of the BPF and R1, R2 and PD, showed a very low correlation (0.1) between BPF and PD, and intermediate correlations between BPF and R1, R2 (0.385 and -0.51, respectively). Future work will focus on understanding how these results relate to edema.

Yes / To assess whether magnetic resonance imaging (MRI)-based measurements of T2, fat fraction, diffusion tensor imaging, and muscle volume can detect differences between the muscles of myositis patients and healthy controls, and to identify how they compare with semi-quantitative MRI diagnosis. Sixteen myositis patients and 16 age- and gender-matched healthy controls underwent MRI of their thigh. Quantitative MRI measurements and radiologists' semi-quantitative scores were assessed. Strength was assessed using an isokinetic dynamometer. Fat fraction and T2 values were higher in myositis patients whereas muscle volume was lower compared to healthy controls. There was no difference in diffusion. Muscle strength was lower in myositis patients compared to healthy controls. In a subgroup of eight patients, scored as unaffected by radiologists, T2 values were still significantly higher in myositis patients. Quantitative MRI measurements can detect differences between myositis patients and healthy controls. Changes in the muscles of myositis patients, undetected by visual, semi-quantitative scoring, can be detected using quantitative T2 measurements. This suggests that MRI T2 values may be useful for the management of myositis patients. / National Institute for Health Research (NIHR) Leeds (BRC) and Health Education England

The claustrum (Cl) is a subcortical gray-matter structure housed between the external capsule medially and the extreme capsule laterally. Due to its extensive reciprocal connections throughout the brain, it has been implicated in consciousness and other higher order functions including linking behavior and emotion. Such linkage may be important in understanding the neurobiology of autism since other cortical and subcortical regions including the spatially and ontologically related basal ganglia, as well as limbic structures, have been implicated in the disorder. Participants were males with autism (n=16) and typically developing (TD; n=14) matched for head circumference and age. The Cl and other structures were identified in 3-Tesla MRI scans using ANALYZE®, then segmented and volume quantified. Four Cl volumes were traced (i.e., right, left, right ventral, left ventral) first in axial plane then in coronal plane for entire Cl visualization. Two-tailed single sample t-tests revealed significant differences in the right claustrum (p=.014), left claustrum (p = .041), right total claustrum (p = .018) and left total claustrum (p=.044). Right Cl volume was found to be significantly larger than left within each of the groups (Autism, p=.021; TD, p=.033). These preliminary results demonstrate that the Cl can be consistently identified in vivo using ROI tracing with apparent right-versus-left asymmetry documented. Smaller claustral volumes in autism support theories of a disconnect in long-range circuitry associated with autism.

The development of a child can be monitored by studying the changes in physical appearance or the development of capabilities e.g. walking and talking. But is it possible to find a quantitative measure for brain development? The aim of this thesis work is to investigate that possibility using quantitative magnetic resonance imaging (qMRI) images by answering the following questions: Can brain development be determined using qMRI? If so, what properties of the brain can be used? Can the age of a child be automatically detected with an algorithm? If so, how can this algorithm function? With what accuracy? Previous studies have shown that it is possible to detect properties in the brain changing with age, based on MRI images. These properties have e.g. been changes in T1 and T2 relaxation time, i.e. properties in water signal behavior that can be measured using multiple MR acquisitions. In the literature this was linked to a rapid myelination process that occurs after birth. Furthermore the organization and growth of the brain is a property that can be measured and monitored. This thesis have investigated several different properties in the brain based on qMRI images in order to identify those who have a strong correlation with age in the range 0-20 years. The properties that were found to have a high correlation were: Position of the first histogram peak in T1 weighted qMRI images, Fraction of white matter in the brain, Mean pixel value of PD weighted qMRI images, Volume of white matter in the brain, Curves on the form f(x) = ae^(-bx) +c are fitted to the data sets and confidence intervals are calculated to frame the statistical insecurity of the curve. The mean error in percent for the different properties can be seen in the list below: Property, Mean error [%] 0-20 years, Mean error [%] 0-3 years Peak position: 53.84, 98.17 Fraction of WM: 118.97, 71.67 Mean pixel value: 200.89, 126.28 Volume of WM: 241.72, 72.58 The conclusions drawn based on the presented results are that there are properties in the brain that correlates well to aging, but the error is too large for making a valid prediction of age over the entire range of 0-20 years. When decreasing the age range to 0-3 years the mean error becomes smaller, but it is still too large. More data is needed to evaluate and improve this result.

The purpose of this thesis was to implement and quantitatively test a quantitative MRI (qMRI) method, from which synthetic MR images are created and also evaluated. The parameter maps of T1, T2*, and effective proton density (PD*) were tested with reference tubes containing different relaxation times, and concentrations of water (H2O) and heavy water (D2O). Two normal volunteers were also used to test qMRI method, by performing regional analysis on the parameter maps of the volunteers. The synthetic FLASH MR images were evaluated by: using the relative standard deviation of a region of interest (ROI) as a measure for the signal-to-noise ratio (SNR), implanting artificial multiple sclerosis (MS) lesions in the parameter maps used to create the synthetic images, and an MRI radiologist opinion of the images. All MRI measurements were conducted on a 3.0 Tesla scanner (Siemens MAGNETOM Skyrafit). The results from reference tube testing, shows that the implementation was reasonably successful, although the T2* maps can not display values on voxels which have T2 exceeding 100 ms. In vivo parameter map ROI values were consistent between volunteers. The SNR and contrast-to-noise ratio of synthetic images are comparable to their measured counterparts depending on TE. The artificial MS lesions were distinguishable from normal appearing tissue in a T1-weighted synthetic FLASH. The radiologist thought the a synthetic T2*-weighted FLASH was somewhat promising for clinical use after further research and development, however a synthetic T1-weighted FLASH had clinical value. / Syftet med detta arbete var att implementera och kvantitativt undersöka en kvantitativ MR (qMRI) metod, för att sedan skapa och utvärdera syntetiska MR-bilder. qMRI-metodens parameterkartor (T1, T2* och effektiv proton densitets PD*) undersöktes med olika typer av referensprover. Dessa prover innehöll skilda relaxationstider, samt olika koncentrationer av vatten (H2O) och tungt vatten (D2O). In vivo parameterkartor från frivilliga granskades genom att jämföra T1, T2* och PD* värdena på intresseområden (ROIs) mellan frivilliga och publicerade värden. Syntetiska FLASH MR-bilder utvärderades genom att: använda relativa standardavvikelsen av ett intresseområde (ROI) som ett mått på signal-brusförhållande (SNR), implantera artificiell multipel skleros (MS) lesioner i de frivilligas parameterkartor för att se ifall dessa kan identifieras i de syntetiska MR-bilder, och slutligen utvärderade en MR-radiolog bilderna. MR-mätningarna utfördes på 3.0 Tesla MR-kamera (Siemens MAGNETOM Skyrafit). Resultaten från referensproverna visar att implementeringen var rimligen framgångsrik, även om beräknade T2* för voxlar som har T2 över 100 ms inte är pålitliga. Frivilligas parameterkartor visade på bra överensstämmelse, dessvärre inte med publicerade. SNR och kontrast-till-brus-förhållandet (CNR) för syntetiska bilder är jämförbara med deras uppmätta motsvarigheter, beroende på TE. De artificiella MS-lesionerna kunde tydligt skiljas från normal omgivande vävnad i en T1-viktad syntetisk FLASH. Radiologen tyckte att en syntetisk T2*-viktad FLASH var något lovande för klinisk användning efter ytterligare förbättringar, medan en syntetisk T1-viktad FLASH hade kliniskt värde.

Yes / Introduction : Rheumatoid arthritis (RA) affects 1% of the population and is principally associated with joint inflammation. It is suggested however that muscle involvement may be one of the earliest clinical features of RA. It is therefore important that techniques exist to accurately assess muscle health in those with RA to enable successful treatment. This study assesses the inter-rater and intra-rater repeatability of Diffusion Tensor MRI (DTI), 2-Point Dixon fat fraction, and T2 relaxation of the thigh muscle in patients with RA using manual regions of interest (ROI). Methods: Nineteen patients (10/19 males; mean age 59; range 18-85) diagnosed with RA had an MRI scan of their hamstrings and quadriceps muscles to obtain fat fraction (FF), mean diffusivity (MD), fractional anisotropy (FA), and T2 quantitative measurements. Two raters (R#1 & R#2) (initials removed for review) independently contoured ROIs for each patient. R#1 repeated the ROI for the same 19 patients after a 6-month hiatus to assess intra-rater repeatability. Inter-rater and intra-rater repeatability for the ROI measurements were compared using Inter Class Correlation (ICC) and Bland-Altman plots. Results: There was excellent agreement for both inter-rater and intra-rater repeatability. ICC results ranged from 0.900-0.998 (P<0.001), and intra-rater ICC results ranged from 0.977-0.999 (P<0.001). Bland-Altman plots also showed excellent agreement. Conclusions: ICC measurements and Bland-Altman plots showed excellent repeatability and agreement with no statistically significant differences when assessing the inter-rater and intra-rater repeatability of FF, MD, FA, and T2 relaxation of the thigh muscle using manual regions of interest in patients with RA. Implications for practice: Manual ROI drawing does not introduce significant errors obtaining FF, MD, FA, and T2 MRI measurements in an RA population. / This research is funded by the NIHR infrastructure at Leeds.

Osteoarthritis (OA) is one of the leading causes of disability world-wide. It affects 12% of all Americans ages 25-74 [1]. One of the challenges with OA, is that there are currently no clinically viable methods to measure the health of the cartilage before cartilage loss. There are no ways to replace or heal the cartilage after it has been lost. It is known that the early stages of OA involve a decrease in the amount of glycosaminoglycans (GAG), one of the main molecules in cartilage. This decrease in GAG leads to a change in the fixed charge density of the cartilage and a higher water content with higher diffusivity. The development of techniques to measure the PG content in the cartilage could lead to early diagnosis and the development of effective preventative treatments.One of the suggested methods for measuring the PG content is through quantitative magnetic resonance imaging (MRI). MRI is a non-invasive medical imaging technique known for it's ability to image soft tissue. MRI measures the reaction of the nuclear spin in a magnetic field to a radio frequency (RF) pulse. These spins, and the signal they produce, are sensitive to magnetic fields. This makes it possible to measure small changes in anatomical structure, like a decrease in PG content, because the magnetic spins are sensitive to the local magnetic environment. There are several MRI techniques that are able to measure the PG content in the cartilage.The behavior of the MR signal can be affected by changes in the molecular environment. This effect can by measured through changes in the MR signal parameters T1r and T2. More complex MRI techniques such as chemical exchange saturation transfer (CEST) can be used to directly measure the amount of GAG by taking advantage of the transfer of proton magnetization between the GAG molecules and the surrounding fluids. There are even MRI techniques such as balanced steady state free precession (bSSFP) which makes it possible to measure high resolution morphological images, making it easier to interpret the quantitative scans.This thesis will describe methods employed to improve MRI imaging of cartilage. One method is the developing and testing a new technique for creating maps of the local magnetic field. These field maps can help scans that are particularly sensitive to non-homogeneities in the field. Another method is improving the parameter estimation algorithms which make it easier to more accurately predict values of signal parameters like T1r and T2. This thesis will also describe ongoing efforts to create, and optimize a clinically viable whole-joint cartilage imaging protocol that can be used for early OA detection and diagnosis.

L'évaluation non-invasive de la myéline dans la substance blanche du système nerveux central est fondamentale pour le suivi de pathologies telles que la sclérose en plaques. La myéline est majoritairement constituée de lipides et de protéines : du fait des nombreuses interactions dans ces macromolécules, les temps de relaxation transversale sont très courts (T2 < 1 ms), rendant indétectables ces signaux par des séquences conventionnelles. Les méthodes standards d’imagerie par RMN pour la caractérisation de la myéline reposent sur la modélisation des interactions entre les protons aqueux et la structure myélinisée. Néanmoins, la sélectivité et la robustesse de ces méthodes indirectes peuvent être remises en cause. Les séquences à temps d’écho ultracourt (UTE – TE < 1 ms) permettraient de faire l’acquisition directe des signaux issus de la matrice semi-solide de la myéline. Le développement de telles méthodes pour la mise en contraste positif et sélectif de la myéline sur système préclinique est l’objet de cette thèse. La validation de chacune des méthodes a été menée sur modèle murin ex vivo en confrontant des animaux sains et démyélinisés. Les résultats à partir des méthodes UTE montrent une sélectivité significative à la démyélinisation, suggérant l’adéquation de la technique pour l'évaluation de la myéline dans la substance blanche. / Non-invasive evaluation of white matter myelin in the central nervous system is essential for the monitoring of pathologies such as multiple sclerosis. Myelin is essentially composed of lipids and proteins: because of the numerous interactions between these macromolecules, the transverse relaxation times are very short (T2 < 1 ms), and their signals are undetectable using conventional sequences. Standard MRI methods for the characterization of myelin rely on the modeling of the interactions of aqueous protons with myelinated structures. Nonetheless, the selectivity and robustness of such indirect methods are questionable. Ultrashort echo time sequences (UTE – TE < 1 ms) may allow to directly detect the signals arising from the semi-solid spin pool of myelin. The main objective of this thesis consists in developing such methods in order to generate a positive and selective contrast of myelin using a preclinical imaging system. Validation of each method was carried out using an ex vivo murine model by confronting healthy and demyelinated animals. Results show a significant selectivity of the UTE methods to demyelination, suggesting that the technique is promising for white matter myelin monitoring.

This thesis investigates if support vector machine classification is a suitable approach when performing automatic segmentation of knee cartilage using quantitative magnetic resonance imaging data. The data sets used are part of a clinical project that investigates if patients that have suffered recent knee damage will develop cartilage damage. Therefore the thesis also investigates if the segmentation results can be used to predict the clinical outcome of the patients. Two methods that perform the segmentation using support vector machine classification are implemented and evaluated. The evaluation indicates that it is a good approach for the task, but the implemented methods needs to be further improved and tested on more data sets before clinical use. It was not possible to relate the cartilage properties to clinical outcome using the segmentation results. However, the investigation demonstrated good promise of how the segmentation results, if they are improved, can be used in combination with quantitative magnetic resonance imaging data to analyze how the cartilage properties change over time or vary between knees.

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