Dissertationen zum Thema „Water-fat MRI“

The separation of water and fat from multi-echo images is a classic problem in magnetic resonance imaging (MRI) with a wide range of important clinical applications. For example, removal of fat signal can provide better visualization of other signal of interest in MRI scans. In other cases, the fat distribution map can be of great importance in diagnosis. Although many methods have been proposed over the past three decades, robust fat water separation remains a challenge as radiological technology and clinical expectation continue to grow. The problem presents three key difficulties: a) the presence of B0 field inhomogeneities, often large in the state-of-the-art research and clinical settings, which makes the problem non-linear and ill-posed; b) the ambiguity of signal modeling in locations with only one metabolite (either fat or water), which can manifest as spurious fat water swaps in the separation; c) the computational expenditure in fat water separation as the size of the data is increasing along with evolving MRI hardware, which hampers the clinical applicability of the fat water separation. The main focus of this thesis is to develop novel graph based algorithms to estimate the B0 field inhomogeneity maps and separate fat water signals with global accuracy and computational efficiency. We propose a new smoothness constrained framework for the GlObally Optimal Surface Estimation (GOOSE), in which the spatial smoothness of the B0 field is modeled as a finite constraint between adjacent voxels in a uniformly discretized graph. We further develop a new non-equidistant graph model that enables a Rapid GlObally Optimal Surface Estimation (R-GOOSE) in a subset of the fully discretized graph in GOOSE. Extensions of the above frameworks are also developed to achieve high computational efficiency for processing large 3D datasets. Global convergence of the optimization formulation is proven in all frameworks. The developed methods have also been extensively compared to the existing state-of-the-art fat water separation methods on a variety of datasets with consistent performance of high accuracy and efficiency.

n MRI, water and fat signal separation with robust techniques are often helpful in the diagnosis using MRI. Reliable separation of water and fat will help the doctor to get accurate diagnoses such as the size of a tumour. Moreover, fat images can also help in diagnosing the liver and heart condition. To perform water and fat separation, multiple echoes, i.e. measurements of the raw MR signal at different time points, are required. By utilizing the knowledge of the expected signal evolution, it is possible to perform the separation. A main magnetic field is used in MRI. This field is not perfectly homogeneous. Estimating the non-homogeneities is crucial for correcting the separation signal. This thesis used the method of "Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation" (IDEAL). The aims of the thesis are developed a method which reconstruct fat or water MRI images from raw multi-coil image data and evaluate the method’s accuracy and speed by comparing with an available, implemented reconstruction method. In particular, the stability to so called swap artefacts will be analysed. Estimated field maps or inhomogeneity fields are one important and essential step, but there exist multiple local minima. To avoid choosing the incorrect minima, the initial estimation of the field map had to be close to the actual field map value. Neighbouring pixels would have a similar field map values, since the inhomogeneity field was smoothly varying. As such, we carried out the combination of IDEAL algorithms with a region growing method. We implemented the method to do the water and fat separation from a raw image consisting of multi-coil data and multi- echo. The proposed method was tested and the region growing method shows a significantly improved separation of water and fat, when compared to the traditional method without region growing.

Magnetic resonance imaging (MRI) is an important medical imaging technique for visualizing soft tissue structures in the body. It has the advantages of being noninvasive and, unlike x-ray, does not rely on ionizing radiation for imaging. In traditional hydrogen-based MRI, the strongest measured signals are generated from the hydrogen nuclei contained in water and fat molecules.Reliable and uniform water fat separation can be used to improve medical diagnosis. In many applications the water component is the primary signal of interest, while the fat component represents a signal which can obscure the underlying pathology or other features of interest. In other applications the fat signal is the signal of interest. There currently exist many techniques for water fat separation. Dixon reconstruction techniques take multiple images acquired at select echo times with specific phase properties. Linear combinations of these images produce separate water and fat images. In MR imaging, images with high signal-to-noise ratio (SNR), that can be generated in a short time, are desired. Balanced steady-state free precession (bSSFP) MRI is a technique capable of producing images with high SNR in a short imaging time but suffers from signal voids or banding artifacts due to magnetic field inhomogeneity and susceptibly variations. These signal voids degrade image quality. Several methods have been developed to remove these banding effects. The simplest methods combine images across multiple bSSFP image acquisitions. This thesis describes a technique in water fat separation I developed which combines the advantages of bSSFP with Dixon reconstruction in order to produce robust water fat decomposition with high SNR in a short imaging time, while simultaneously reducing banding artifacts which traditionally degrade image quality. This algorithm utilizes four phased-cycled bSSFP acquisitions at specific echo times. Phase sensitive post-processing and a field map are used to prepare the data and reduce the effects of field inhomogeneities. Dixon reconstruction is then used to generate separate water and fat images.

L'obésité est associée à une augmentation de la morbidité et de la mortalité liée à de nombreuses maladies, y compris le diabète de type 2, l'hypertension et des pathologies hépatiques menant à une surcharge lipidique d’origine non alcoolique. Récemment, l’imagerie par résonance magnétique (IRM) est devenue la méthode de choix pour la quantification non invasive de la graisse. Dans cette thèse, les méthodes d'IRM ont été étudiées sur un scanner préclinique de 4.7T in vitro (fantômes MR) et in vivo (souris). Deux algorithmes de quantifications de la graisse -la méthode de Dixon et l’algorithme IDEAL- ont été considérés. Les performances de l'algorithme IDEAL ont été analysées en fonction de propriétés des tissus (T2*, fraction de graisse et modèle spectral de la graisse), de paramètres d'acquisition IRM (temps d’écho, nombre d'échos) et de paramètres expérimentaux (SNR et carte de champ). Sur les fantômes, l'approche standard single-T2* IDEAL a montré certaines limites qui pourraient être surmontées en optimisant le nombre d'échos. Une nouvelle méthode, pour déterminer les valeurs de vérité terrain pour T2* de l'eau et pour T2* de la graisse, a été proposée. Pour les mesures in vivo, différentes analyses ont été effectuées en utilisant l'algorithme IDEAL sur le foie et les muscles. L'analyse statistique sur les mesures de ROI a montré que le choix optimal du nombre d'échos est égal à trois pour la quantification de la graisse et six ou plus pour la quantification du T2*. Les valeurs de la fraction de graisse, calculées avec l'algorithme IDEAL, étaient statistiquement comparables aux valeurs obtenues avec la méthode de Dixon. Enfin, un procédé pour générer des signaux de référence mimant les systèmes eau-graisse (Fat Virtual Phantom MRI), sans l'aide d'objets physiques, a été proposé. Ces fantômes virtuels, qui présentent des caractéristiques de bruit réalistes, représentent une alternative intéressante aux fantômes physiques pour fournir un signal de référence dans les mesures IRM
Obesity is associated with increased morbidity and mortality linked to many diseases, including type 2 diabetes, hypertension and disease nonalcoholic fatty liver. Recently, 1H magnetic resonance imaging (MRI) has emerged as the method of choice for non-invasive fat quantification. In this thesis, MRI methodologies were investigated for in vitro (MR phantoms) and in vivo (mice) measurements on a 4.7T preclinical scanner. Two algorithms of fat quantifications – the Dixon’s method and IDEAL algorithm – were considered. The performances of the IDEAL algorithm were analyzed as a function of tissue properties (T2*, fat fraction and fat spectral model), MRI acquisition parameters (echo times, number of echoes) and experimental parameters (SNR and field map). In phantoms, the standard approach of single-T2* IDEAL showed some limitations that could be overcome by optimizing the number of echoes. A novel method to determine the ground truth values of T2* of water and T2* of fat was here proposed. For in vivo measurements, different analyses were performed using the IDEAL algorithm in liver and muscle. Statistical analysis on ROI measurements showed that the optimal choice of the number of echoes was equal to three for fat quantification and six or more for T2* quantification. The fat fraction values, calculated with IDEAL algorithm, were statistically similar to the values obtained with Dixon’s method. Finally, a method for generating reference signals mimicking fat-water systems (Fat Virtual Phantom MRI), without using physical objects, was proposed. These virtual phantoms, which display realistic noise characteristics, represent an attractive alternative to physical phantoms for providing a reference signal in MRI measurements

Abstract The purpose of this study was to evaluate the value of 0.23T low-field magnetic resonance imaging (MRI) and nanocolloid (NC) scintigraphy in assessing joint pathology associated with rheumatoid arthritis (RA). Fat suppression methods combined with contrast media enhancement aid in distinguishing enhancing inflamed tissue from the surrounding fat, especially in the imaging of arthritic joints. The feasibility and image quality of a phase-shift water-fat MRI method for fat suppression at low-field 0.23T open configuration MR scanner was evaluated. The technique was combined with contrast-enhanced imaging to assess the conspicuity of synovial hypertrophy in the joints of 30 RA patients. Improved conspicuity and delineation of synovitis was detected with this method. However, because of a great amount of manual post processing, future development is needed to make this method more feasible. Contrast-enhanced MRI and NC scintigraphy may provide objective and quantitative information about the inflammatory activity in arthritic joints. The value of quantitative and semiquantitative measures of inflammation derived from NC scintigraphy and low-field MRI of the wrist joint of 28 early RA patients was evaluated. Furthermore, it was investigated whether these parameters have predictive value of further erosive development during two years of follow-up. Strong correlations were detected between the NC scintigraphy and MRI measures, and these parameters were associated with laboratory markers of inflammation. During the two-year follow-up, the initial MRI and NC scintigraphy measures were closely related with the progression of wrist joint erosions. Small erosive-like bone defects can occasionally be found in wrist MRI of patients without clinically overt arthritis. The prevalence of these lesions was studied in bilateral wrist MRI examinations of 31 healthy persons. Small lesions resembling erosions were detected in 14 out of 31 subjects. Altogether 24 of the 930 wrist bones evaluated showed such lesions (3%). Thus small changes resembling erosions can be found in the wrist MRI of healthy subjects; the significance of these findings must always be interpreted with reference to the clinical picture. In conclusion, early RA patients with high local inflammatory activity, as detected by NC scintigraphy and MRI are at risk of developing further bone damage. Furthermore, in the follow-up of early RA patients, if clinically sustained response is not achieved, these methods help to identify patients who need more intensive drug treatment.

Magnetic resonance imaging (MRI) is one of the most important diagnostic tools of modern healthcare. The signal in medical MRI predominantly originates from water and fat molecules. Separation of the two components into water-only and fat-only images can improve diagnosis, and is the premier non-invasive method for measuring the amount and distribution of fatty tissue. Fat-water imaging (FWI) enables fast fat/water separation by model-based estimation from chemical shift encoded data, such as multi-echo acquisitions. Qualitative FWI is sufficient for visual separation of the components, while quantitative FWI also offers reliable estimates of the fat percentage in each pixel. The major problems of current FWI methods are long acquisition times, long reconstruction times, and reconstruction errors that degrade image quality. In this thesis, existing FWI methods were reviewed, and novel fully automatic methods were developed and evaluated, with a focus on fast 3D image reconstruction. All MRI data was acquired on standard clinical scanners. A triple-echo qualitative FWI method was developed for the specific application of 3D whole-body imaging. The method was compared with two reference methods, and demonstrated superior image quality when evaluated in 39 volunteers. The problem of qualitative FWI by dual-echo data with unconstrained echo times was solved, allowing faster and more flexible image acquisition than conventional FWI. Feasibility of the method was demonstrated in three volunteers and the noise performance was evaluated. Further, a quantitative multi-echo FWI method was developed. The signal separation was based on discrete whole-image optimization. Fast 3D image reconstruction with few reconstruction errors was demonstrated by abdominal imaging of ten volunteers. Lastly, a method was proposed for quantitative mapping of average fatty acid chain length and degree of saturation. The method was validated by imaging different oils, using gas-liquid chromatography (GLC) as the reference. The degree of saturation agreed well with GLC, and feasibility of the method was demonstrated in the thigh of a volunteer. The developed methods have applications in clinical settings, and are already being used in several research projects, including studies of obesity, dietary intervention, and the metabolic syndrome.

A major health concern for subjects with diabetes is weaker bones and increased fracture risk. Current clinical assessment of the bone strength is performed by measuring Bone Mineral Density (BMD), where low BMD-values are associated with an increased risk of fracture. However, subjects with Type 2 Diabetes (T2D) have been shown to have normal or higher BMD-levels compared to healthy controls, which does not reflect the recognized bone fragility among diabetics. Thus, there is need for more research about diabetes-related bone fragility to find other factors of impaired bone health. One potential biomarker that has recently been studied is Bone Marrow Fat (BMF). The data in this project consisted of whole-body water-fat Magnetic Resonance Imaging (MRI) volumes from the UK Biobank Imaging study (UKBB). Each subject in this data has a water volume and a fat volume, allowing for a quantitative assessment of water and fat content in the body. To analyze and perform quantitative measurements of the bones specifically, a Deep Learning (DL) model was trained, validated, and tested for performing fully automated and objective skeleton segmentation, where six different bones were segmented: spine, femur, pelvis, scapula, clavicle and humerus. The model was trained and validated on 120 subjects with 6-fold cross-validation and tested on eight subjects. All ground-truth segmentations of the training and test data were generated using two semi-automatic pipelines. The model was evaluated for each bone separately as well as the overall skeleton segmentation and achieved varying accuracy, performing better on larger bones than on smaller ones. The final trained model was applied on a larger dataset of 9562 subjects (16% type 2 diabetics) and the BMF, as well as bone marrow volume (BMV) and cortical bone volume (CBV), were measured in the segmented bones of each subject. The results of the quantified biomarkers were compared between T2D and healthy subjects. The comparison revealed possible differences between healthy and diabetic subjects, suggesting a potential for new findings related to diabetes and associated bone fragility.

碩士
義守大學
資訊工程學系碩士在職專班
99
Fat suppression is a common MRI (Magnetic Resonance Imaging) technique routinely used to suppress the signal from adipose tissue. It may be used to reduce chemical shift artifacts, increase conspicuity of contrast-enhanced tumors, or improve tissue characterization. The purpose of this study is to compare the efficiency of various fat suppression techniques on water-fat phantom by using MRI. All scans were performed on a GE Signa HDxt 1.5T scanner. The home-made water-fat phantom consists of eleven homogeneous water-fat tubes been prepared in various fat fractions from 0% up to 100% with 10% increment. The phantom was imaged using six fat suppression pulse sequences, spin echo T1 fat saturation (SE T1 FS), spin echo T2 fat saturation (SE T21 FS), fast spin echo T1 fat saturation (FSE T1 FS), fast spin echo T2 fat saturation (FSE T2 FS), short TI inversion recovery (STIR), and iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL). The ROI (regions of interest) values of all tubes were measured using MATLAB. The ROI values and the fat fractions of tubes were correlated with linear regression for each technique using SPSS 18.0. Bland-Altman analyses were used to assess the correlation and consistency among all imaging methods. The ROI values were significantly correlated with phantom fractions for all imaging methods (p＜0.001). The regression lines related to phantom fractions for all methods were listed as follows, y = 0.921x + 8.318 (r2 = 0.879, SE T1 FS), y = 0.931x + 24.818 (r2 = 0.773, SE T2 FS), y = 0.962x + 1.545 (r2 = 0.923, FSE T1 FS), y = 1.003x + 7.409 (r2 = 0.938, FSE T2 FS), y = 1.002x + 5.182 (r2 = 0.971, STIR), and y = 0.931x + 8.000 (r2 = 0.945, IDEAL)。Bland–Altman plot revealed mean differences equal to 4.36% (SE T1 FS), 21.36% (SE T2 FS), -0.36% (FSE T1 FS), 7.55 % (FSE T2 FS), 5.27% (STIR), and 4.55% (IDEAL). The ROI values were significantly correlated when compared IDEAL with other imaging methods (p＜0.001). The regression lines related to IDEAL were listed as follows, y = 1.004x - 0.382 (r2 = 0.957, SE T1 FS), y = 1.065x + 13.297 (r2 = 0.926, SE T2 FS), y = 1.006x - 5.236 (r2＝ 0.926, FSE T1 FS), y = 1.072x - 0.915 (r2 = 0.983, FSE T2 FS), and y = 1.059x - 2.483 (r2 = 0.995, STIR). Bland–Altman plot revealed mean differences equal to -0.18% (SE T1 FS), 16.82% (SE T2 FS), -4.91% (FSE T1 FS), 3.00 % (FSE T2 FS), and 0.73% (STIR). It was found that STIR technique had the best linear relationship and lowest mean difference with IDEAL. This study demonstrated that STIR is the best choice to be used as an alternative method of IDEAL for fat suppression.

碩士
國立中山大學
生物醫學科學研究所
94
Hepatic steatosis is common in the general population and is present in 13.25% of donor organs. It can affect graft survival and recovery of the donor after partial hepatectomy. Liver biopsy is the standard method to measure the degree of hepatic steatosis, but it’s also an invasive procedure and may have sampling error. Non-invasive tools, such as computed tomography and magnetic resonance image, are generally utilized and developed. This study was designed to build a standard model for the quantification of the fat content in a fat-water mixed phantom model. Pork fat and pure water were mixed in different ratios by volume (from 0% fraction of fat to 100% fat in steps of 5%), and then measured for fat content in different concentrations of fat-water mixed phantom by using (1) CT number (Hounsfield unit; HU), (2) Dixon method (in-phase & opposed-phase), and (3) 1H spectroscopy (SVS30 & SVS136, without water suppression). The CT number decreased with increasing fat concentration. The Hounsfield units of pure fat were about -122 HU. At Dixon method, the fat image intensity increased to its maximum when the fat concentration reached 25% and then decreased. Fat concentration higher than 25% and lower than 25% both had the same value of the fat image intensity. Combined with SVS30 water/fat peak height ratio, the fat concentration could be estimated. Furthermore, the fat image could be utilized to observe the topographic distribution of hepatic steatosis. Then a rat fatty liver model fed with a choline deficient and iron supplemented L-amino acid defined (CDAA) diet was established. Fatty liver grade was evaluated by radiological and biochemical assessments. CT and MRS technique displayed the highest fat contents the same with histological examination in CDAA diet rats at 6 weeks. The results showed that MRS was a suitable method for quantifying fat to water concentration. As a result of this study, model of measurement scale can be established to measure fat concentration both in phanatoms and animal. Further study in human fatty liver was expected.

Numerous studies have shown that the combination of radiation therapy and hyperthermia, when delivered at moderate temperatures (40°-45°C) for sustained times (30-90 minutes), can help to provide palliative relief and augment tumor response, local control, and survival. However, the dependence of treatment success on achieved temperature highlights the need for accurate thermal dosimetry, so that the prescribed thermal dose can be delivered to the tumor. This can be achieved noninvasively with MR thermometry. However, there are many challenges to performing MR thermometry in the breast, where hyperthermia of locally advanced breast cancer can provide a benefit. These include magnetic field system drift, fatty tissue, and breathing motion.

The purpose of this research was to develop a system for the hyperthermia treatment of LABC while performing MR thermometry. A hardware system was developed for performing the hyperthermia treatment within the MR bore. Methods were developed to correct for magnetic field system drift and to correct for breath hold artifacts in MR thermometry of the tumor using measurement of field changes in fat references. Lastly, techniques were developed for measuring temperature in the fatty tissue using multi-echo fat water separation methods, reducing the error of performing MR thermometry in such tissues. All of these methods were characterized with phantom and in vivo experiments in a 1.5T MR system.

The results of this research can provide the means for successful hyperthermia treatment of LABC with MR thermometry. With this thermometry, accurate thermal doses can be obtained, potentially providing improved outcomes. However, these results are not only applicable in the breast, but can also be used for improved MR thermometry in other areas of the body, such as the extremities or abdomen.

Dissertation

碩士
國防醫學院
生物及解剖學研究所
106
Chronic kidney disease (CKD) is a global public health issue by progression loss of kidney function. Alternation of bone marrow perfusion may resulting from the atherosclerotic change caused by disturbances in calcium and phosphorus homeostasis of vessels. Our study aims to investigate the bone marrow perfusion with dynamic contrast enhanced (DCE)-MRI with pharmacokinetic model and meanwhile to measure the possible fat/water content and trabeculation change by using T2* mapping, MR spectroscopy (MRS) and micro computed tomography (μCT). Twelve rats were randomly separated into two groups. Group 1 was the normal control group. Group 2 was the CKD (subtotal nephrectomy) group. The lumbar spines of all rats were imaged and L5 vertebral body were monitored at 0, 8, 16, 24, 30, 38 and 43 weeks. After week 43, all rats were sacrificed and correlated the histologic changes with MRI and μCT results. The DCE-MRI demonstrate lower kel and kep values in CKD group as compare to control group. Increasing T2* values and decreasing fat content and trabeculation were also observed on T2* mapping, MRS and micro-CT results. Histopathology revealed sinusoidal dilatation and decreased adipocytes in vertebral bone marrow in the CKD group. As compared to the control group, the CKD group also demonstrated decreased fat content percentage in vertebral bone marrow. In conclusion, this study shows using quantitative MRI and μCT to assess the CKD-related arthropathic of vertebral body is feasible. Lumbar spine bone marrow perfusion deficiency in experimental CKD may be associated with decreased fat content, increased water content, and sparse trabeculation.