A DETERMINISTIC AND DUCTILE SEGMENTATION ALGORITHMFOR MORPHOLOGIC MRI AND CTA IMAGES AND QUANTITATIVE ANALYSISOF DYNAMIC SUSCEPTIBILITY-CONTRAST MAGNETIC RESONANCE IMAGING DATA
Manfredo Atzori · 2010
The work that is described in this thesis has been performed in collaboration with the Research Unit in Brain Imaging and Neuropsychology (RUBIN) of the Inter University Centre for Behavioural Neurosciences of Udine and Verona (ICBN). The research group studies morphological and functional alterations of the Brain in patients affected by psychiatric diseases as schizophrenia. Several studies have been realized to investigate morphologic and functional alterations in the Brain of patients affected by schizophrenia. Those studies are usually performed on scans of the head acquired using structural Magnetic Resonance Imaging (MRI) or functional MRI. The morphological and functional differences described in scientific literature between patients affected by schizophrenia and healthy controls are usually very small and characterized by high variability. This fact depends on the high inter-subject variability of the human brain, on the use of drugs by the patients (that can affect the parameters), and on the diagnosis criteria of schizophrenia, that include many different symptoms. The implementation of procedures able to identify and analyze with high accuracy and sensitivity the small differences that exist between patients affected by schizophrenia and the healthy controls is a challenging problem at the state of the art. The first aim of the work described in this thesis is the ideation, the implementation and the characterization of a fully automatic, robust, accurate and ductile algorithm for the segmentation of the Brain, Cerebro Spinal Fluid, Grey Matter and White Matter in T1 MRI of the head. In medical imaging, segmentation can be defined as the identification of the boundaries of different anatomical structures in the images. Segmentation algorithms are a key component in medical imaging since they play a vital role in numerous biomedical imaging applications. Depending on the state of the art that the processes have reached, various methods have been realized to segment specific anatomical structures. The procedures to segment the Brain, Cerebro Spinal Fluid, Grey Matter and White Matter in order to analyze the morphological alterations that are related to psychiatric disease need to be very sensitive and accurate. Moreover, the procedures need to be easy modified according to specific needs of the research. The Research Unit in Brain Imaging and Neuropsychology decided to undertake the way of realizing a segmentation algorithm, rather than using one of the available software, because those are considered unsatisfactory for the research field. Moreover, the RUBIN desired to have an instrument of its own, well known and easy to be modified according to specific needs. Ductility is therefore a fundamental characteristic for the algorithm. The realized algorithm is named Orao, it is fully automatic and is based on iterative analyses of global and local intensity distributions, the application of morphologic operators and the analysis of connectivity properties. It shows excellent results in quantitative validation and comparison with the procedures that are most used at the state of the art. The second aim of the work is to test the ductility of the segmentation algorithm through its application to various anatomical structures and medical imaging acquisition techniques. The studied anatomical structures include the Skull, Heart, Kidneys, Urinary Bladder, Urinary Tracts, Bone and a tumour of the Brain. The studied medical imaging acquisition techniques include T1 and T2 weighted MRI of the head and Computed Tomography Angiography of the chest. Those applications are automatic or semiautomatic, depending on the specific case, but it shall be noticed that the semi-automatic applications are ideated in order to be easily automated. The third aim of this work is the ideation, the implementation and the characterization of a procedure to perform voxel by voxel analysis of Dynamic Susceptibility Contrast MRI (DSC MRI). DSC MRI is a technique to perform perfusion magnetic resonance using an exogenous tracer, such as gadolinium, and is one of the most interesting techniques for the quantitative study of the brain hemodynamics. The DSC MRI allows to quantify important hemodynamic parameters that play an important role in the study of several pathologies, such as cerebral tumours, ischemia or infarction, epilepsy, but preliminary works suggest that this technique may provide important clinical information on neuropsychiatric disorders, especially dementia and schizophrenia. Procedures that can compare voxel by voxel the brains of patients with the ones of the healthy controls are still needed in Dynamic Susceptibility Contrast MRI. A technique to perform DSC MRI analysis voxel by voxel could lead to the identification of the anatomic regions majorly involved in various pathologies as schizophrenia. The fourth aim of the work is the analysis of local and global, morphological and functional, alterations of the Brain, Grey Matter, White Matter and Cerebro Spinal Fluid (CSF) in patients affected by schizophrenia using the procedures realized. First morphological alterations are studied through the analysis of the volumes of the segmented Brain, Grey Matter, White Matter and CSF. Then, functional alterations are studied using statistical parametric DSC MRI mapping.