Developing advanced mathematical models for detecting abnormalities in 2D/3D medical structures.

Detecting abnormalities in two-dimensional (2D) and three-dimensional (3D) medical structures is among the most interesting and challenging research areas in the medical imaging field. Obtaining the desired accurate automated quantification of abnormalities in medical structures is still very challenging. This is due to a large and constantly growing number of different objects of interest and associated abnormalities, large variations of their appearances and shapes in images, different medical imaging modalities, and associated changes of signal homogeneity and noise for each object. The main objective of this dissertation is to address these problems and to provide proper mathematical models and techniques that are capable of analyzing low and high resolution medical data and providing an accurate, automated analysis of the abnormalities in medical structures in terms of their area/volume, shape, and associated abnormal functionality. This dissertation presents different preliminary mathematical models and techniques that are applied in three case studies: (i) detecting abnormal tissue in the left ventricle (LV) wall of the heart from delayed contrast-enhanced cardiac magnetic resonance images (MRI), (ii) detecting local cardiac diseases based on estimating the functional strain metric from cardiac cine MRI, and (iii) identifying the abnormalities in the corpus callosum (CC) brain structure—the largest fiber bundle that connects the two hemispheres in the brain—for subjects that suffer from developmental brain disorders. For detecting the abnormal tissue in the heart, a graph-cut mathematical optimization model with a cost function that accounts for the object’s visual appearance and shape is used to segment the the inner cavity. The model is further integrated with a geometric model (i.e., a fast marching level set model) to segment the outer border of the myocardial wall (the LV). Then the abnormal tissue in the myocardium wall (also called dead tissue, pathological tissue, or infarct area) is identified based on a joint Markov-Gibbs random field (MGRF) model of the image and its region (segmentation) map that accounts for the pixel intensities and the spatial interactions between the pixels. Experiments with real in-vivo data and comparative results with ground truth (identified by a radiologist) and other approaches showed that the proposed framework can accurately detect the pathological tissue and can provide useful metrics for radiologists and clinicians. To estimate the strain from cardiac cine MRI, a novel method based on tracking the LV wall geometry is proposed. To achieve this goal, a partial differential equation (PDE) method is applied to track the LV wall points by solving the Laplace equation between the LV contours of each two successive image frames over the cardiac cycle. The main advantage of the proposed tracking method over traditional texture-based methods is its ability to track the movement and rotation of the LV wall based on tracking the geometric features of the inner, mid-, and outer walls of the LV. This overcomes noise sources that come from scanner and heart motion. To identify the abnormalities in the CC from brain MRI, the CCs are aligned using a rigid registration model and are segmented using a shape-appearance model. Then, they are mapped to a simple unified space for analysis. This work introduces a novel cylindrical mapping model, which is conformal (i.e., one to one transformation and bijective), that enables accurate 3D shape analysis of the CC in the cylindrical domain. The framework can detect abnormalities in all divisions of the CC (i.e., splenium, rostrum, genu and body). In addition, it offers a whole 3D analysis of the CC abnormalities instead of only area-based analysis as done by previous groups. The initial classification results based on the centerline length and CC thickness suggest that the proposed CC shape analysis is a promising supplement to the current techniques for diagnosing dyslexia. The proposed techniques in this dissertation have been successfully tested on complex synthetic and MR images and can be used to advantage in many of today’s clinical applications of computer-assisted medical diagnostics and intervention

Echocardiography

The book "Echocardiography - New Techniques" brings worldwide contributions from highly acclaimed clinical and imaging science investigators, and representatives from academic medical centers. Each chapter is designed and written to be accessible to those with a basic knowledge of echocardiography. Additionally, the chapters are meant to be stimulating and educational to the experts and investigators in the field of echocardiography. This book is aimed primarily at cardiology fellows on their basic echocardiography rotation, fellows in general internal medicine, radiology and emergency medicine, and experts in the arena of echocardiography. Over the last few decades, the rate of technological advancements has developed dramatically, resulting in new techniques and improved echocardiographic imaging. The authors of this book focused on presenting the most advanced techniques useful in today's research and in daily clinical practice. These advanced techniques are utilized in the detection of different cardiac pathologies in patients, in contributing to their clinical decision, as well as follow-up and outcome predictions. In addition to the advanced techniques covered, this book expounds upon several special pathologies with respect to the functions of echocardiography

Texture Analysis of Late Gadolinium Enhanced Cardiac Magnetic Resonance Images for Characterizing Myocardial Fibrosis and Infarction

Le tiers de la population aux États-Unis est affecté par des cardiomyopathies. Lorsque le muscle du coeur, le myocarde, est altéré par la maladie, la santé du patient est détériorée et peut même entrainer la mort. Les maladies ischémiques sont le résultat d’artères coronariennes bloquées (sténose), limitant l’apport sanguin vers le myocarde. Les cardiomyopathies non-ischémiques sont les maladies dues à d’autres causes que des sténoses. Les fibres de collagène (fibrose) s’infiltrent dans le muscle cardiaque dans le but de maintenir la forme et les fonctions cardiaques lorsque la structure du myocarde est affectée par des cardiomyopathies. Ce principe, nécessaire au fonctionnement du coeur en présence de maladies, devient mal adapté et mène à des altérations du myocarde aux conséquences négatives, par exemple l’augmentation de la rigidité du myocarde. Une partie du diagnostic clinique lors de cardiomyopathies consiste à évaluer la fibrose dans le coeur avec différentes modalités d’imagerie. Les fibres de collagène s’infiltrent et s’accumulent dans la zone extracellulaire du myocarde ou peuvent remplacer progressivement les cardiomyocytes compromises. L’infiltration de fibrose dans le myocarde peut possiblement être réversible, ce qui rend sa détection particulièrement importante pour le clinicien. Différents tests diagnostiques existent pour aider le clinicien à établir l’état du patient en présence de cardiomyopathies. L’imagerie par résonance magnétique (IRM) est une modalité d’imagerie qui offre une haute résolution pour la visualisation du myocarde. Parmi les séquences disponibles avec cette modalité, l’imagerie par rehaussement tardif (RT) augmente le contraste du signal existant entre les tissus sains et les tissues malades du myocarde. Il s’agit d’images en pondération T1 avec administration d’agent de contraste qui se propage dans la matrice extracellulaire et résulte en un rehaussement du signal à cet endroit. Les images IRM RT permettent d’évaluer la présence et l’étendue des dommages au myocarde. Le clinicien peut évaluer la sévérité des cardiomyopathies et poser un pronostique à l’aide de ces images. La détection de fibrose diffuse dans ces images peut informer le clinicien sur l’état du patient et est un important marqueur de cardiomyopathies. Il est important d’établir l’occurrence de l’infarctus en présence de maladies ischémiques. En effet, l’approche interventionnelle varie selon que le clinicien fait face à une ischémie aigue ou chronique. Lors du diagnostic, Il serait donc bénéfique de différencier les infarctus du myocarde aigu de ceux chronique. Ceci s’est avéré difficile à l’aide des images IRM RT où l’intensité du signal ou la taille des régions sont similaires dans les deux types d’ischémie. Le but de la présente thèse est donc d’appliquer les méthodes d’analyse de texture à des images IRM RT afin de détecter la présence de fibrose diffuse dans le myocarde et de plus de déterminer l’âge de l’infarctus du myocarde. La première étude portait sur la détection de fibrose diffuse dans le myocarde à l’aide de l’analyse de texture appliquée à des images IRM RT afin d’établir si un lien existe entre la variation du signal d’intensité et la structure sous-jacente du myocarde. La présence de collagène dans le myocarde augmente avec l’âge et nous avons utilisé un modèle animal de rats jeunes et âgés. Nous avons fait une étude ex-vivo afin d’obtenir des images IRM RT de haute résolution avec absence de mouvement et ainsi permettre une comparaison des images avec des coupes histologiques des coeurs imagés. Des images IRM RT ont été acquises sur vingt-quatre animaux. Les coupes histologiques ont été traitées avec la méthode utilisant un marqueur ‘picrosirius red’ qui donne une teinte rouge au collagène. La quantification de la fibrose obtenue avec les images IRM RT a été comparée à la quantification obtenue sur les coupes histologiques. Ces quantifications ont de plus été comparées à l’analyse de texture appliquée aux images IRM RT. La méthode de texture a été appliquée en créant des cartes de texture basées sur la valeur de Contraste, cette mesure étant obtenue par des calculs statistiques sur la matrice de cooccurrence. Les régions montrant une plus grande complexité de signal d’intensité sur les images IRM RT ont été rehaussées avec les cartes de textures. Un calcul de régression linéaire a permis d’étudier le lien entre les différentes méthodes de quantification. Nous avons trouvés que la quantification de fibrose dans le myocarde à l’aide de l’analyse de texture appliquée sur des images IRM RT concordait avec le niveau de collagène identifié avec les images IRM et avec les coupes histologiques. De plus, nous avons trouvés que l’analyse de texture rehausse la présence de fibrose diffuse dans le myocarde. La seconde étude a pour but de discriminer les infarctus aigus du myocarde de ceux qui sont chroniques sur des images IRM RT de patients souffrant de cardiomyopathies ischémiques. Vingt-deux patients ont subi l’imagerie IRM (12 avec infarctus aigu du myocarde et 12 avec infarctus chronique). Une segmentation des images a permis d’isoler les différentes zones du myocarde, soit la zone d’infarctus, la zone grise au rebord de l’infarctus et la zone du myocarde sain, dans les deux groupes de patients. L’analyse de texture s’est faite dans ces régions en comparant les valeurs obtenues dans les deux groupes. Nous avons obtenu plus de valeurs de texture discriminantes dans la zone grise, en comparaison avec la région du myocarde sain, où aucune valeur de texture n’était significativement différente, et à la zone d’infarctus, où seule la valeur de texture statistique Moyenne était différentes dans les deux groupes. La zone grise a déjà fait l’objet d’études ayant établis cette région comme composée de cardiomyocytes sains entremêlés avec des fibres de collagène. Notre étude montre que cette région peut exhiber des différences structurelles entre les infarctus aigus du myocarde et ceux qui sont chroniques et que l’analyse de texture a réussi à les détecter. L’étude de la présence de collagène dans le myocarde est importante pour le clinicien afin qu’il puisse faire un diagnostic adéquat du patient et pour qu’il puisse faire un choix de traitement approprié. Nous avons montrés que l’analyse de texture sur des images IRM RT de patients peut différencier et même permettre la classification des ischémies aigues des ischémies chroniques, ce qui n’était pas possible avec uniquement ce type d’images. Nous avons de plus démontrés que l’analyse de texture d’images IRM RT permettait d’évaluer le contenu de fibrose diffuse dans un modèle animal de haute résolution avec validation histologique. Une telle relation entre les résultats d’analyse de texture d’images IRM RT et la structure sous-jacente du myocarde n’avait pas été étudiée dans la littérature. Notre méthode pourra être améliorée en effectuant d’autres calculs statistiques sur la matrice de cooccurrence, en testant d’autres méthodes d’analyse de texture et en appliquant notre méthode à de nouvelles séquences d’acquisition IRM, tel les images en pondération T1. D’autres améliorations possibles pourraient porter sur une évaluation de matrice de cooccurrence avec voisinage circulaire suivant la forme du myocarde sur les tranches d’images IRM RT. Plusieurs matrice de cooccurrence pourraient aussi être évaluées en fonction de la position dans l’espace du voisinage afin d’intégrer une composante directionnelle dans les calculs de texture. D’autres études sont nécessaires afin d’établir si une analyse de texture des images IRM RT pourrait différencier le stade de la fibrose pour un même patient lors d’une étude de suivi. De même, d’autres études sont nécessaires afin de valider l’utilisation de texture sur des scanners IRM différents. Établir l’âge de l’infarctus du myocarde permettra de planifier les interventions thérapeutiques et d’évaluer le pronostique pour le patient.----------ABSTRACT A third of the United States population is affected by cardiomyopathies. Impairment of the heart muscle, the myocardium, puts the patient’s health at risk and could ultimately lead to death. Ischemic cardiomyopathies result from lack of blood (ischemia) reaching the myocardium from blocked coronary arteries. Non-ischemic cardiomyopathies are diseases from other etiology than ischemia. Often collagen fibers infiltrate the heart (fibrosis), as a means to maintain its shape and function in the presence of disease that affects the myocardial cellular structure. This necessary phenomenon ultimately becomes maladaptive and results in the heart’s impairment. Part of the heart’s involvement in disease can be assessed through the analysis of myocardial fibrosis. Cardiomyopathy diagnosis involves the investigation of the presence of myocardial fibrosis, either infiltrative, defined as the increased presence of collagen protein in the extracellular space, or replacement fibrosis, when collagen fibers progressively replace diseased cardiomyocytes. The infiltrative fibrosis is believed to be reversible in some instances and consequently, myocardial fibrosis analysis has decisional impact on the interventional procedure that would benefit the health of the patient. The heart contracts and relaxes as it pumps blood to the rest of the body, an action directly impaired by myocardial damage. Any myocardial involvement should be assessed by the clinician to identify the severity of the myocardial damage, establish a prognosis and plan therapeutic intervention. Different diagnostic tests are required to image the myocardium and help the clinician in the diagnostic process. Cardiac magnetic resonance (CMR) imaging has emerged as a high resolution imaging modality that offers precise structural analysis of the heart. Among the different imaging sequences available with CMR, late gadolinium enhancement (LGE) shows the myocardium and enhances any impairments that may exist with the use of a contrast agent. It is a T1-weighted image with extracellular contrast agent (CA) administration. Increased signal intensity in the infarct scar is created from the CA dynamics. LGE CMR imaging offers information on the scar size and its location. The clinician can estimate the severity of the disease and establish prognosis with LGE CMR images. In ischemic cardiomyopathy, it is important to establish the occurrence of the infarction and know the age of the infarct to plan surgical intervention. Differentiation of acute from chronic MI is therefore important in the diagnostic process. In LGE CMR the level of signal intensity or the size of infarction are both similar in acute or in chronic MI. It has therefore been challenging to distinguish acute MI from chronic MI scars with LGE CMR images alone. The aim of this thesis was to investigate texture analysis of LGE CMR images to determine if acute MI could be distinguished from chronic MI and to detect increased presence of diffuse myocardial fibrosis in the myocardium. The first study was performed to investigate if texture analysis of LGE CMR images could detect variations in the presence of diffuse myocardial fibrosis and if the underlying myocardial structure could be related to the texture measures. Collagen content increased with aging and we used an animal model of young versus old rat. An ex-vivo animal model was necessary to allow for higher image resolution in LGE CMR images and to perform validation of our texture measures with histology images. Twenty four animals were scanned for LGE CMR images and texture analysis was applied to the heart images. Histology slices were stained with picrosirius red and collagen fibers were isolated based on their color content. LGE CMR quantification was compared to histological slices of the heart stained with the picrosirius red method. Texture analysis of LGE CMR images was also compared to the original LGE CMR image quantification and to histology. Texture analysis was done by creating contrast texture maps extracted from Haralick’s gray level co-occurrence matrix (GLCM). Regions of complex signal intensity combination were enhanced in LGE CMR images and in contrast texture maps. Regression analysis was performed to assess the level of agreement between the different analysis methods. We found that LGE CMR images could assess the different levels of collagen content in the different aged animal model, and that moreover texture analysis enhanced those differences. The location of enhancement from texture analysis images corresponded to location of increased collagen content in the old compared to the young rat hearts. Histological validation was shown for texture analysis applied to LGE CMR images to assess myocardial fibrosis. Our second study aimed at discriminating acute versus chronic MI from LGE CMR patient images alone through the use of texture analysis. Twenty two patients who had LGE CMR images were included in our study (12 acute and 12 chronic MI). Regional segmentation was performed and texture features were compared in those regions between both groups of patient. Texture analysis resulted in significantly different values between the two groups. More specifically the peri-infarct zone had the most number of discriminative features compared to the remote myocardium which had none and to the infarct core where only the mean features was significantly different. The border zone has been shown to be composed of healthy cardiomyocytes intermingled with the scar’s collagen fibers. Our study indicates this region might exhibit structural differences in the myocardium in acute from chronic MI patients that texture analysis of LGE CMR images can detect. Characterization of myocardial collagen content is important while clinicians analyze the state of the patient since it influences the course of action required to treat cardiomyopathies. LGE CMR images have been thoroughly used and validated to characterize focal myocardial scar, however it was limited in characterizing the age of infarction or quantifying diffuse collagen content. We have shown texture analysis of LGE CMR images alone can differentiate and even classify, acute from chronic MI patients, which was not previously possible. Characterization of myocardial infarction according to age will prove important in planning therapeutic interventions in clinical practice. Moreover, we have established texture analysis as a means to characterize the myocardium and detect variation in fibrosis content from high resolution LGE CMR images with histology validation. To our knowledge, such a relation between texture analysis of LGE CMR images and the underlying myocardial structure had not been done previously. Improvements could be done to our method, as we can increase the number of texture features that were analyzed from the GLCM, include other texture analysis methods such as the run-length matrix, and apply our method to other CMR imaging sequences such as T1 mapping. Adapting the GLCM to the heart could also be investigated, such as considering circular GLCM computation to consider the round shape of the myocardium in the short axis LGE CMR image slices. Directional GLCM could also be computed individually and analyzed for any myocardial or collagen fiber orientation indication. Further analysis is also required to establish if texture analysis could differentiate the age of MI in the same individual through a follow-up study. The measures of texture analysis from LGE CMR images obtained through different CMR scanners remains to be investigated as well. Knowing the age of infarct and evaluating the presence of diffuse myocardial fibrosis will help the clinician plan therapeutic interventions and establish a prognosis for the patient

Computer aided diagnosis of coronary artery disease, myocardial infarction and carotid atherosclerosis using ultrasound images: a review

The diagnosis of Coronary Artery Disease (CAD), Myocardial Infarction (MI) and carotid atherosclerosis is of paramount importance, as these cardiovascular diseases may cause medical complications and large number of death. Ultrasound (US) is a widely used imaging modality, as it captures moving images and image features correlate well with results obtained from other imaging methods. Furthermore, US does not use ionizing radiation and it is economical when compared to other imaging modalities. However, reading US images takes time and the relationship between image and tissue composition is complex. Therefore, the diagnostic accuracy depends on both time taken to read the images and experience of the screening practitioner. Computer support tools can reduce the inter-operator variability with lower subject specific expertise, when appropriate processing methods are used. In the current review, we analysed automatic detection methods for the diagnosis of CAD, MI and carotid atherosclerosis based on thoracic and Intravascular Ultrasound (IVUS). We found that IVUS is more often used than thoracic US for CAD. But for MI and carotid atherosclerosis IVUS is still in the experimental stage. Furthermore, thoracic US is more often used than IVUS for computer aided diagnosis systems

Doctor of Philosophy

dissertationImage-based biomechanics, particularly numerical modeling using subject-specific data obtained via imaging, has proven useful for elucidating several biomechanical processes, such as prediction of deformation due to external loads, applicable to both normal function and pathophysiology of various organs. As the field evolves towards applications that stretch the limits of imaging hardware and acquisition time, the information traditionally expected as input for numerical routines often becomes incomplete or ambiguous, and requires specific acquisition and processing strategies to ensure physical accuracy and compatibility with predictive mathematical modeling. These strategies, often derivatives or specializations of traditional mechanics, effectively extend the nominal capability of medical imaging hardware providing subject-specific information coupled with the option of using the results for predictive numerical simulations. This research deals with the development of tools for extracting mechanical measurements from a finite set of imaging data and finite element analysis in the context of constructing structural atlases of the heart, understanding the biomechanics of the venous vasculature, and right ventricular failure. The tools include: (1) application of Hyperelastic Warping image registration to displacement-encoded MRI for reconstructing absolute displacement fields, (2) combination of imaging and a material parameter identification approach to measure morphology, deformation, and mechanical properties of vascular tissue, and (3) extrapolation of diffusion tensor MRI acquired at a single time point for the prediction the structural changes across the cardiac cycle with mechanical simulations. Selected tools were then applied to evaluate structural changes in a reversible animal model for right ventricular failure due to pressure overload

Intraoperative Quantification of Bone Perfusion in Lower Extremity Injury Surgery

Orthopaedic surgery is one of the most common surgical categories. In particular, lower extremity injuries sustained from trauma can be complex and life-threatening injuries that are addressed through orthopaedic trauma surgery. Timely evaluation and surgical debridement following lower extremity injury is essential, because devitalized bones and tissues will result in high surgical site infection rates. However, the current clinical judgment of what constitutes “devitalized tissue” is subjective and dependent on surgeon experience, so it is necessary to develop imaging techniques for guiding surgical debridement, in order to control infection rates and to improve patient outcome. In this thesis work, computational models of fluorescence-guided debridement in lower extremity injury surgery will be developed, by quantifying bone perfusion intraoperatively using Dynamic contrast-enhanced fluorescence imaging (DCE-FI) system. Perfusion is an important factor of tissue viability, and therefore quantifying perfusion is essential for fluorescence-guided debridement. In Chapters 3-7 of this thesis, we explore the performance of DCE-FI in quantifying perfusion from benchtop to translation: We proposed a modified fluorescent microsphere quantification technique using cryomacrotome in animal model. This technique can measure bone perfusion in periosteal and endosteal separately, and therefore to validate bone perfusion measurements obtained by DCE-FI; We developed pre-clinical rodent contaminated fracture model to correlate DCE-FI with infection risk, and compare with multi-modality scanning; Furthermore in clinical studies, we investigated first-pass kinetic parameters of DCE-FI and arterial input functions for characterization of perfusion changes during lower limb amputation surgery; We conducted the first in-human use of dynamic contrast-enhanced texture analysis for orthopaedic trauma classification, suggesting that spatiotemporal features from DCE-FI can classify bone perfusion intraoperatively with high accuracy and sensitivity; We established clinical machine learning infection risk predictive model on open fracture surgery, where pixel-scaled prediction on infection risk will be accomplished. In conclusion, pharmacokinetic and spatiotemporal patterns of dynamic contrast-enhanced imaging show great potential for quantifying bone perfusion and prognosing bone infection. The thesis work will decrease surgical site infection risk and improve successful rates of lower extremity injury surgery

Restored perfusion and reduced inflammation in the infarcted heart after grafting stem cells with a hyaluronan-based scaffold

The aim of this study is to investigate the blood perfusion and the inflammatory response of the myocardial infarct area after transplanting a hyaluronan-based scaffold (HYAFF\uae11) with bone marrow mesenchymal stem cells (MSCs). Nine-week-old female pigs were subjected to a permanent left anterior descending coronary artery ligation for 4 weeks. According to the kind of the graft, the swine subjected to myocardial infarction were divided into the HYAFF\uae11, MSCs, HYAFF\uae11/MSCs and untreated groups. The animals were killed 8 weeks after coronary ligation. Scar perfusion, evaluated by Contrast Enhanced Ultrasound echography, was doubled in the HYAFF\uae11/MSCs group and was comparable with the perfusion of the healthy, non-infarcted hearts. The inflammation score of the MSCs and HYAFF\uae11/MSCs groups was near null, revealing the role of the grafted MSCs in attenuating the cell infiltration, but not the foreign reaction strictly localized around the fibres of the scaffold. Apart from the inflammatory response, the native tissue positively interacted with the HYAFF\uae11/MSCs construct modifying the extracellular matrix with a reduced presence of collagene and increased amount of proteoglycans. The border-zone cardiomyocytes also reacted favourably to the graft as a lower degree of cellular damage was found. This study demonstrates that the transplantation in the myocardial infarct area of autologous MSCs supported by a hyaluronan-based scaffold restores blood perfusion and almost completely abolishes the inflammatory process following an infarction. These beneficial effects are superior to those obtained after grafting only the scaffold or MSCs, suggesting that a synergic action was achieved using the cell-integrated polymer construct

A novel myocardium segmentation approach based on neutrosophic active contour model

Automatic delineation of the myocardium in echocardiography can assist ra- diologists to diagnosis heart problems. However, it is still challenging to distinguish myocardium from other tissue due to a low signal-to-noise ratio, low contrast, vague boundary, and speckle noise