Magnetic Resonance Imaging of the Brain in Moving Subjects. Application of Fetal, Neonatal and Adult Brain Studies

Imaging in the presence of subject motion has been an ongoing challenge for magnetic resonance imaging (MRI). Motion makes MRI data inconsistent, causing artifacts in conventional anatomical imaging as well as invalidating diffusion tensor imaging (DTI) reconstruction. In this thesis some of the important issues regarding the acquisition and reconstruction of anatomical and DTI imaging of moving subjects are addressed; methods to achieve high resolution and high signalto- noise ratio (SNR) volume data are proposed. An approach has been developed that uses multiple overlapped dynamic single shot slice by slice imaging combined with retrospective alignment and data fusion to produce self consistent 3D volume images under subject motion. We term this method as snapshot MRI with volume reconstruction or SVR. The SVR method has been performed successfully for brain studies on subjects that cannot stay still, and in some cases were moving substantially during scanning. For example, awake neonates, deliberately moved adults and, especially, on fetuses, for which no conventional high resolution 3D method is currently available. Fine structure of the in-utero fetal brain is clearly revealed for the first time with substantially improved SNR. The SVR method has been extended to correct motion artifacts from conventional multi-slice sequences when the subject drifts in position during data acquisition. Besides anatomical imaging, the SVR method has also been further extended to DTI reconstruction when there is subject motion. This has been validated successfully from an adult who was deliberately moving and then applied to inutero fetal brain imaging, which no conventional high resolution 3D method is currently available. Excellent fetal brain 3D apparent diffusion coefficient (ADC) maps in high resolution have been achieved for the first time as well as promising fractional Anisotropy (FA) maps. Pilot clinical studies using SVR reconstructed data to study fetal brain development in-utero have been performed. Growth curves for the normally developing fetal brain have been devised by the quantification of cerebral and cerebellar volumes as well as some one dimensional measurements. A Verhulst model is proposed to describe these growth curves, and this approach has achieved a correlation over 0.99 between the fitted model and actual data

Mri Methods For Imaging The Feto-Placental Vasculature And Blood

Fetal magnetic resonance imaging (MRI) in recent times has become a well-established adjunct to ultrasound (US) in routine clinical prenatal care and diagnostics. The majority of fetal MRI is restricted to T2-weighted scans, where the diagnosis is based on the appearance of normal and abnormal tissue. Although there have been many advancements in MRI and a plethora of sequences, that probe different anatomical and different physiological process, the adaptation of these in fetal imaging has been rather slow. Many of these can extract quantitative parameters that can throw light on the underlying tissue’s normal/patho-physiology. But the use of such quantitative MRI methods has been extremely limited in fetal imaging due to its unique and dynamic physiological milieu that pose several technical challenges including low signal to noise and/or resolution, artifacts associated with abdominal imaging and most importantly fetal motion. These limitations are expected to be overcome by (a) optimizing and (b) developing novel MR imaging sequences, both of which constitute the primary aim of my work. This work develops a framework that allows for vascular imaging in the fetus and placenta. This includes both qualitative vascular imaging and blood flow quantification. Towards this, three broad directions were explored (a) Moving to higher field imaging, while optimizing parameters for low energy deposition and (b) application of non-gated phase contrast MRI and (c) optimization of conventional time-of-flight angiography for fetal applications

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

Diffusion Weighted Imaging of the Neonatal Brain

Although in the last decades advances in fetal and neonatal medicine have reduced mortality in neonatal intensive care units in the Western world, the morbidity due to brain injury remains high. Patterns of neonatal brain injury can be roughly divided in (1) term and (2) preterm patterns. Table 1 shows the number of infants admitted to the NICU in the Sophia Children’s Hospital between March 2008 and March 2010 with a typical ‘neurological’ diagnosis. The table highlights differences in diagnoses between preterm and term infants in relation to gender. In preterm infants the most common diagnoses are: persistent flaring (hypersignal intensity seen in periventricluar white matter using cranial ultrasound), intraventricular haemorrhage and venous infarction. In term infants perinatal asphyxia and perinatal stroke are most often reported

Exploring the developing preterm brain with diffusion tensor magnetic resonance imaging

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