Level-Set Based Artery-Vein Separation in Blood Pool Agent CE-MR Angiograms

Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved

Contrast-enhanced magnetic resonance angiography.

Contrast-enhanced magnetic resonance angiography (CE-MRA) is a diagnostic method for imaging of vascular structures based on nuclear magnetic resonance. Vascular enhancement is achieved by injection of a contrast medium (CM). Studies were performed using two different types of CM: conventional paramagnetic CM, and a new type of CM based on hyperpolarized (HP) nuclei. The effects of varying CM concentration with time during image acquisition were studied by means of computer simulations using two different models. It was shown that a rapid concentration variation during encoding of the central parts of k-space could result in signal loss and severe image artifacts. The results were confirmed qualitatively with phantom experiments. A postprocessing method was developed to address problems with simultaneous enhancement of arteries and veins in CE-MRA of the lower extremities. The method was based on the difference in flow-induced phase in the two vessel types. Evaluation of the method was performed with flow phantom measurements and with CE-MRA in two volunteers using standard pulse sequences. The flow-induced phase in the vessels of interest was sufficient to distinguish arteries from veins in the superior-inferior direction. Using this method, the venous enhancement could be extinguished. The possibility of using HP nuclei as CM for CE-MRA was evaluated. Signal expressions for a flow of HP CM imaged with a gradient echo sequence were derived. These signal expressions were confirmed in phantom experiments using HP 129Xe dissolved in ethanol. Studies were also performed with a new CM based on HP 13C. The CM had very long relaxation times (T1,in vivo/T2,in vivo≈ 38/1.3 s). The long relaxation times were utilized in imaging with a fully balanced steady-state free precession pulse sequence (trueFISP), where the optimal flip angle was found to be 180°. CE-MRA with the 13C-based CM in rats resulted in images with high vascular SNR (~500). CE-MRA is a useful clinical tool for diagnosing vascular disease. With the development of new contrast media, based on hyperpolarized nuclei for example, there is a potential for further improvement in the signal levels that can be achieved, enabling a standard of imaging of vessels that is not possible today

Dynamic magnetic resonance angiography of the arteries of the hand. A comparison between an extracellular and an intravascular contrast agent

The purpose of this study was to compare the image quality of the intravascular contrast agent gadofosveset with the extracellular contrast agent gadoterate meglumine in time-resolved three-dimensional magnetic resonance (MR) angiography of the human arteries of the hand. The value of cuff compression technique for suppression of venous enhancement for both contrast agents was also investigated. Three-dimensional MR angiograms of both hands of 11 healthy volunteers were acquired for each contrast agent at 1.5-T, while subsystolic cuff compression was applied at one side. Quantitative and qualitative evaluation were performed and analyzed with Student's t-test. Visualization of vessels was superior in the images acquired with gadofosveset, especially in the late phases. Quantitative and qualitative evaluation showed significantly higher values for gadofosveset. The cuff compression at the lower arm proved to be an effective method to enhance arterial vessels. In conclusion the blood pool agent gadofosveset is superior for the dynamic imaging of the vessels of the hand when compared with the extracellular contrast agent gadoterate meglumine. To fully utilize the advantages of intravascular contrast agents, venous overlay has to be delayed or reduced, which can be achieved effectively by subsystolic lower arm cuff compressio

Improved 3D MR Image Acquisition and Processing in Congenital Heart Disease

Congenital heart disease (CHD) is the most common type of birth defect, affecting about 1% of the population. MRI is an essential tool in the assessment of CHD, including diagnosis, intervention planning and follow-up. Three-dimensional MRI can provide particularly rich visualization and information. However, it is often complicated by long scan times, cardiorespiratory motion, injection of contrast agents, and complex and time-consuming postprocessing. This thesis comprises four pieces of work that attempt to respond to some of these challenges. The first piece of work aims to enable fast acquisition of 3D time-resolved cardiac imaging during free breathing. Rapid imaging was achieved using an efficient spiral sequence and a sparse parallel imaging reconstruction. The feasibility of this approach was demonstrated on a population of 10 patients with CHD, and areas of improvement were identified. The second piece of work is an integrated software tool designed to simplify and accelerate the development of machine learning (ML) applications in MRI research. It also exploits the strengths of recently developed ML libraries for efficient MR image reconstruction and processing. The third piece of work aims to reduce contrast dose in contrast-enhanced MR angiography (MRA). This would reduce risks and costs associated with contrast agents. A deep learning-based contrast enhancement technique was developed and shown to improve image quality in real low-dose MRA in a population of 40 children and adults with CHD. The fourth and final piece of work aims to simplify the creation of computational models for hemodynamic assessment of the great arteries. A deep learning technique for 3D segmentation of the aorta and the pulmonary arteries was developed and shown to enable accurate calculation of clinically relevant biomarkers in a population of 10 patients with CHD

Dual contrast microvascular MRI

Department of Biomedical EngineeringThe fundamental magnetic resonance angiography (MRA) has been used for obtaining vascular information, such as vessel size and structure. For many decades, MRA techniques with contrast agent have been developed and implemented in research and the clinical area for in vivo applications. Especially, the longitudinal (T1) and transverse (T2 or T2*) contrasts in MRA provide diverse and different information of same subject???s vasculature. The assessments of vascular structure and function by using two types of contrast are important for monitoring vascular behavior. Generally, the two types of contrast agent are T1- and T2-contrast agents. In recent years, several efforts have been focusing on synthesizing hybrid nanoparticles to achieve T1- and T2-contrast, simultaneously. The MR images with both positively and negatively enhanced contrast over the same anatomical region offer complementary information. The benefits of dual contrast with a single agent for in vivo experiments are obvious. In this study, instead of synthesized hybrid contrast agents or multiple contrast agents, simultaneous acquisitions of in vivo dual contrast with size-controlled superparamagnetic iron oxide nanoparticles (SPION) in MRA were obtained and evaluated. As this method is successful for preclinical investigations, dual contrast has a great potential to directly help to compensate vascular information by positively and negatively enhanced contrast. The results of obtained dual contrast in in vivo images were apparent, the smaller vessels in the head region of rodents were distinctively visible from negatively enhanced contrast MRA, while positively enhanced contrast MRA eliminated false contrasts in regions of airways and bone from negatively enhanced contrast MRA. Based on advantages of dual contrast in in vivo MRA, we systematically compared the strengths and weaknesses of dual contrast-enhanced MRAs with SPION in cerebral micro-vessels of the rodent brain. The vasculatures in rodent brain with positively enhanced contrast were visualized well without any artifact, but smaller vessels than given spatial resolution were hardly detected. On the other hand, negatively enhanced contrast based MRA provided good sensitivity for micro-vessels. However, negatively enhanced vessels and specific regions suffered from susceptibility-induced artifacts. Consequently, dual contrast enhanced MRAs were combined for compensation of those short-comings and visualization of whole-brain micro-MRA. The other subject of this thesis is a feasibility evaluation of newly developed contrast agent for in vivo applications at high magnetic field. From MR perspective, the behavior of higher magnetic field (> 7T) is attractive, as it is expected to drastically increase SNR, resolution and susceptibility contrast, which improves lesion detection and quantifications. Also the reduction of inherent T1 relaxation time of contrast agent at high magnetic field is important to increase positively enhanced contrast with limited MR acquisition parameters. The developed contrast agent used in this study was observed to maintain its favorable positive relaxivity even at 7 T magnetic field without drastic reductions of r1 relaxivity. The developed contrast agent was characterized by this phantom and in vivo experiments. The results of 3D MRA proved the feasibility of vascular imaging within 2 hours after intravenous injection of the contrast agent. And a significant reduction of T1 values was observed in the tumor region 7 hours after contrast agent injection in the tumor mouse model.ope

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

A novel MRA-based framework for the detection of changes in cerebrovascular blood pressure.

Background: High blood pressure (HBP) affects 75 million adults and is the primary or contributing cause of mortality in 410,000 adults each year in the United States. Chronic HBP leads to cerebrovascular changes and is a significant contributor for strokes, dementia, and cognitive impairment. Non-invasive measurement of changes in cerebral vasculature and blood pressure (BP) may enable physicians to optimally treat HBP patients. This manuscript describes a method to non-invasively quantify changes in cerebral vasculature and BP using Magnetic Resonance Angiography (MRA) imaging. Methods: MRA images and BP measurements were obtained from patients (n=15, M=8, F=7, Age= 49.2 ± 7.3 years) over a span of 700 days. A novel segmentation algorithm was developed to identify brain vasculature from surrounding tissue. The data was processed to calculate the vascular probability distribution function (PDF); a measure of the vascular diameters in the brain. The initial (day 0) PDF and final (day 700) PDF were used to correlate the changes in cerebral vasculature and BP. Correlation was determined by a mixed effects linear model analysis. Results: The segmentation algorithm had a 99.9% specificity and 99.7% sensitivity in identifying and delineating cerebral vasculature. The PDFs had a statistically significant correlation to BP changes below the circle of Willis (p-value = 0.0007), but not significant (p-value = 0.53) above the circle of Willis, due to smaller blood vessels. Conclusion: Changes in cerebral vasculature and pressure can be non-invasively obtained through MRA image analysis, which may be a useful tool for clinicians to optimize medical management of HBP

Respiratory Motion Compensation in Coronary Magnetic Resonance Angiography: Analysis and Optimization of Self-Navigation

Coronary Magnetic Resonance Imaging requires prolonged acquisition times; for this reason, respiratory movements of the heart have a great impact on the final image quality. The aim of this thesis was to provide possible optimization of the "self-navigation" approach to compensate this type of motion. Two developed methods were tested in 11 volunteer, thus providing statistically significant results. The purposed solutions provided optimal image quality in individal cases