251 research outputs found
Coronary Artery Segmentation and Motion Modelling
Conventional coronary artery bypass surgery requires invasive sternotomy and the
use of a cardiopulmonary bypass, which leads to long recovery period and has high
infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery
based on image guided robotic surgical approaches have been developed to allow the
clinicians to conduct the bypass surgery off-pump with only three pin holes incisions
in the chest cavity, through which two robotic arms and one stereo endoscopic camera
are inserted. However, the restricted field of view of the stereo endoscopic images leads
to possible vessel misidentification and coronary artery mis-localization. This results
in 20-30% conversion rates from TECAB surgery to the conventional approach.
We have constructed patient-specific 3D + time coronary artery and left ventricle
motion models from preoperative 4D Computed Tomography Angiography (CTA)
scans. Through temporally and spatially aligning this model with the intraoperative
endoscopic views of the patient's beating heart, this work assists the surgeon to identify
and locate the correct coronaries during the TECAB precedures. Thus this work has
the prospect of reducing the conversion rate from TECAB to conventional coronary
bypass procedures.
This thesis mainly focus on designing segmentation and motion tracking methods
of the coronary arteries in order to build pre-operative patient-specific motion models.
Various vessel centreline extraction and lumen segmentation algorithms are presented,
including intensity based approaches, geometric model matching method and
morphology-based method. A probabilistic atlas of the coronary arteries is formed
from a group of subjects to facilitate the vascular segmentation and registration procedures.
Non-rigid registration framework based on a free-form deformation model
and multi-level multi-channel large deformation diffeomorphic metric mapping are
proposed to track the coronary motion. The methods are applied to 4D CTA images
acquired from various groups of patients and quantitatively evaluated
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
Anatomical Modeling of Cerebral Microvascular Structures: Application to Identify Biomarkers of Microstrokes
Les rĂ©seaux microvasculaires corticaux sont responsables du transport de lâoxygĂšne et des substrats Ă©nergĂ©tiques vers les neurones. Ces rĂ©seaux rĂ©agissent dynamiquement aux demandes Ă©nergĂ©tiques lors dâune activation neuronale par le biais du couplage neurovasculaire. Afin dâĂ©lucider le rĂŽle de la composante microvasculaire dans ce processus de couplage, lâutilisation de la modĂ©lisation in-formatique pourrait se rĂ©vĂ©ler un Ă©lĂ©ment clĂ©. Cependant, la manque de mĂ©thodologies de calcul appropriĂ©es et entiĂšrement automatisĂ©es pour modĂ©liser et caractĂ©riser les rĂ©seaux microvasculaires reste lâun des principaux obstacles. Le dĂ©veloppement dâune solution entiĂšrement automatisĂ©e est donc important pour des explorations plus avancĂ©es, notamment pour quantifier lâimpact des mal-formations vasculaires associĂ©es Ă de nombreuses maladies cĂ©rĂ©brovasculaires. Une observation courante dans lâensemble des troubles neurovasculaires est la formation de micro-blocages vascu-laires cĂ©rĂ©braux (mAVC) dans les artĂ©rioles pĂ©nĂ©trantes de la surface piale. De rĂ©cents travaux ont dĂ©montrĂ© lâimpact de ces Ă©vĂ©nements microscopiques sur la fonction cĂ©rĂ©brale. Par consĂ©quent, il est dâune importance vitale de dĂ©velopper une approche non invasive et comparative pour identifier leur prĂ©sence dans un cadre clinique.
Dans cette thĂšse,un pipeline de traitement entiĂšrement automatisĂ© est proposĂ© pour aborder le prob-lĂšme de la modĂ©lisation anatomique microvasculaire. La mĂ©thode de modĂ©lisation consiste en un rĂ©seau de neurones entiĂšrement convolutif pour segmenter les capillaires sanguins, un gĂ©nĂ©rateur de modĂšle de surface 3D et un algorithme de contraction de la gĂ©omĂ©trie pour produire des mod-Ăšles graphiques vasculaires ne comportant pas de connections multiples. Une amĂ©lioration de ce pipeline est dĂ©veloppĂ©e plus tard pour allĂ©ger lâexigence de maillage lors de la phase de reprĂ©sen-tation graphique. Un nouveau schĂ©ma permettant de gĂ©nĂ©rer un modĂšle de graphe est dĂ©veloppĂ© avec des exigences dâentrĂ©e assouplies et permettant de retenir les informations sur les rayons des vaisseaux. Il est inspirĂ© de graphes gĂ©omĂ©triques dĂ©formants construits en respectant les morpholo-gies vasculaires au lieu de maillages de surface. Un mĂ©canisme pour supprimer la structure initiale du graphe Ă chaque exĂ©cution est implĂ©mentĂ© avec un critĂšre de convergence pour arrĂȘter le pro-cessus. Une phase de raffinement est introduite pour obtenir des modĂšles vasculaires finaux. La modĂ©lisation informatique dĂ©veloppĂ©e est ensuite appliquĂ©e pour simuler les signatures IRM po-tentielles de mAVC, combinant le marquage de spin artĂ©riel (ASL) et lâimagerie multidirectionnelle pondĂ©rĂ©e en diffusion (DWI). LâhypothĂšse est basĂ©e sur des observations rĂ©centes dĂ©montrant une rĂ©orientation radiale de la microvascularisation dans la pĂ©riphĂ©rie du mAVC lors de la rĂ©cupĂ©ra-tion chez la souris. Des lits capillaires synthĂ©tiques, orientĂ©s alĂ©atoirement et radialement, et des angiogrammes de tomographie par cohĂ©rence optique (OCT), acquis dans le cortex de souris (n = 5) avant et aprĂšs lâinduction dâune photothrombose ciblĂ©e, sont analysĂ©s. Les graphes vasculaires informatiques sont exploitĂ©s dans un simulateur 3D Monte-Carlo pour caractĂ©riser la rĂ©ponse par rĂ©sonance magnĂ©tique (MR), tout en considĂ©rant les effets des perturbations du champ magnĂ©tique causĂ©es par la dĂ©soxyhĂ©moglobine, et lâadvection et la diffusion des spins nuclĂ©aires.
Le pipeline graphique proposĂ© est validĂ© sur des angiographies synthĂ©tiques et rĂ©elles acquises avec diffĂ©rentes modalitĂ©s dâimagerie. ComparĂ© Ă dâautres mĂ©thodes effectuĂ©es dans le milieu de la recherche, les expĂ©riences indiquent que le schĂ©ma proposĂ© produit des taux dâerreur gĂ©omĂ©triques et topologiques amoindris sur divers angiogrammes. LâĂ©valuation confirme Ă©galement lâefficacitĂ© de la mĂ©thode proposĂ©e en fournissant des modĂšles reprĂ©sentatifs qui capturent tous les aspects anatomiques des structures vasculaires. Ensuite, afin de trouver des signatures de mAVC basĂ©es sur le signal IRM, la modĂ©lisation vasculaire proposĂ©e est exploitĂ©e pour quantifier le rapport de perte de signal intravoxel minimal lors de lâapplication de plusieurs directions de gradient, Ă des paramĂštres de sĂ©quence variables avec et sans ASL. Avec lâASL, les rĂ©sultats dĂ©montrent une dif-fĂ©rence significative (p <0,05) entre le signal calculĂ© avant et 3 semaines aprĂšs la photothrombose. La puissance statistique a encore augmentĂ© (p <0,005) en utilisant des angiogrammes capturĂ©s Ă la semaine suivante. Sans ASL, aucun changement de signal significatif nâest trouvĂ©. Des rapports plus Ă©levĂ©s sont obtenus Ă des intensitĂ©s de champ magnĂ©tique plus faibles (par exemple, B0 = 3) et une lecture TE plus courte (<16 ms). Cette Ă©tude suggĂšre que les mAVC pourraient ĂȘtre carac-tĂ©risĂ©s par des sĂ©quences ASL-DWI, et fournirait les informations nĂ©cessaires pour les validations expĂ©rimentales postĂ©rieures et les futurs essais comparatifs.----------ABSTRACT
Cortical microvascular networks are responsible for carrying the necessary oxygen and energy substrates to our neurons. These networks react to the dynamic energy demands during neuronal activation through the process of neurovascular coupling. A key element in elucidating the role of the microvascular component in the brain is through computational modeling. However, the lack of fully-automated computational frameworks to model and characterize these microvascular net-works remains one of the main obstacles. Developing a fully-automated solution is thus substantial for further explorations, especially to quantify the impact of cerebrovascular malformations associ-ated with many cerebrovascular diseases. A common pathogenic outcome in a set of neurovascular disorders is the formation of microstrokes, i.e., micro occlusions in penetrating arterioles descend-ing from the pial surface. Recent experiments have demonstrated the impact of these microscopic events on brain function. Hence, it is of vital importance to develop a non-invasive and translatable approach to identify their presence in a clinical setting.
In this thesis, a fully automatic processing pipeline to address the problem of microvascular anatom-ical modeling is proposed. The modeling scheme consists of a fully-convolutional neural network to segment microvessels, a 3D surface model generator and a geometry contraction algorithm to produce vascular graphical models with a single connected component. An improvement on this pipeline is developed later to alleviate the requirement of water-tight surface meshes as inputs to the graphing phase. The novel graphing scheme works with relaxed input requirements and intrin-sically captures vessel radii information, based on deforming geometric graphs constructed within vascular boundaries instead of surface meshes. A mechanism to decimate the initial graph struc-ture at each run is formulated with a convergence criterion to stop the process. A refinement phase is introduced to obtain final vascular models. The developed computational modeling is then ap-plied to simulate potential MRI signatures of microstrokes, combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). The hypothesis is driven based on recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially oriented, and op-tical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n=5) before and after inducing targeted photothrombosis, are analyzed. The computational vascular graphs are exploited within a 3D Monte-Carlo simulator to characterize the magnetic resonance (MR) re-sponse, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins.
The proposed graphing pipeline is validated on both synthetic and real angiograms acquired with different imaging modalities. Compared to other efficient and state-of-the-art graphing schemes, the experiments indicate that the proposed scheme produces the lowest geometric and topological error rates on various angiograms. The evaluation also confirms the efficiency of the proposed scheme in providing representative models that capture all anatomical aspects of vascular struc-tures. Next, searching for MRI-based signatures of microstokes, the proposed vascular modeling is exploited to quantify the minimal intravoxel signal loss ratio when applying multiple gradient di-rections, at varying sequence parameters with and without ASL. With ASL, the results demonstrate a significant difference (p<0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p<0.005) using angiograms captured at week 4. Without ASL, no reliable signal change is found. Higher ratios with improved significance are achieved at low magnetic field strengths (e.g., at 3 Tesla) and shorter readout TE (<16 ms). This study suggests that microstrokes might be characterized through ASL-DWI sequences, and provides necessary insights for posterior experimental validations, and ultimately, future transla-tional trials
Computer Vision Techniques for Transcatheter Intervention
Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area
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
Automatic Spatiotemporal Analysis of Cardiac Image Series
RĂSUMĂ
Ă ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de
dĂ©cĂšs en AmĂ©rique du Nord. Chez lâadulte et au sein de populations de plus en plus jeunes,
la soi-disant Ă©pidĂ©mie dâobĂ©sitĂ© entraĂźnĂ©e par certaines habitudes de vie tels que la mauvaise
alimentation, le manque dâexercice et le tabagisme est lourde de consĂ©quences pour les personnes
affectées, mais aussi sur le systÚme de santé. La principale cause de morbidité et de
mortalitĂ© chez ces patients est lâathĂ©rosclĂ©rose, une accumulation de plaque Ă lâintĂ©rieur des
vaisseaux sanguins à hautes pressions telles que les artÚres coronaires. Les lésions athérosclérotiques
peuvent entraĂźner lâischĂ©mie en bloquant la circulation sanguine et/ou en provoquant
une thrombose. Cela mĂšne souvent Ă de graves consĂ©quences telles quâun infarctus. Outre les
problÚmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la
rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population
pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de
Kawasaki. Il sâagit dâune vasculite aigĂŒe pouvant affecter lâintĂ©gritĂ© structurale des parois des
artĂšres coronaires et mener Ă la formation dâanĂ©vrismes. Dans certains cas, ceux-ci entravent
lâhĂ©modynamie artĂ©rielle en engendrant une perfusion myocardique insuffisante et en activant
la formation de thromboses.
Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectuĂ©s Ă lâaide
dâangiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de
projections radiographiques sont acquises en sĂ©ries suite Ă lâinfusion artĂ©rielle dâun agent de
contraste. Ces images révÚlent la lumiÚre des vaisseaux sanguins et la présence de lésions
potentiellement pathologiques, sâil y a lieu. Parce que les sĂ©ries acquises contiennent de lâinformation
trĂšs dynamique en termes de mouvement du patient volontaire et involontaire (ex.
battements cardiaques, respiration et dĂ©placement dâorganes), le clinicien base gĂ©nĂ©ralement
son interprĂ©tation sur une seule image angiographique oĂč des mesures gĂ©omĂ©triques sont effectuĂ©es
manuellement ou semi-automatiquement par un technicien en radiologie. Bien que
lâangiographie par fluoroscopie soit frĂ©quemment utilisĂ© partout dans le monde et souvent
considĂ©rĂ© comme lâoutil de diagnostic âgold-standardâ pour de nombreuses maladies vasculaires,
la nature bidimensionnelle de cette modalitĂ© dâimagerie est malheureusement trĂšs
limitante en termes de spécification géométrique des différentes régions pathologiques. En effet,
la structure tridimensionnelle des stĂ©noses et des anĂ©vrismes ne peut pas ĂȘtre pleinement
appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de
lâimageur. De plus, la prĂ©sence de lĂ©sions affectant les artĂšres coronaires peut ne pas reflĂ©ter
la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT
Cardiovascular disease continues to be the leading cause of death in North America. In adult
and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by
lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses
on the healthcare system. The primary cause of serious morbidity and mortality for these
patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary
arteries. These lesions can lead to ischemic disease and may progress to precarious blood
flow blockage or thrombosis, often with infarction or other severe consequences. Besides
the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased
stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the
most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis
may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions.
These can hinder the blood flowâs hemodynamics, leading to inadequate downstream
perfusion, and may activate thrombus formation which may lead to precarious prognosis.
Diagnosing these two prominent coronary artery diseases is traditionally performed using
fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective
arterial infusion of a radiodense contrast agent, which reveals the vesselsâ luminal
area and possible pathological lesions. The acquired series contain highly dynamic information
on voluntary and involuntary patient movement: respiration, organ displacement and
heartbeat, for example. Current clinical analysis is largely limited to a single angiographic
image where geometrical measures will be performed manually or semi-automatically by a
radiological technician. Although widely used around the world and generally considered
the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of
this imaging modality is limiting in terms of specifying the geometry of various pathological
regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated
in 2D because their observable features are dependent on the angular configuration of
the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not
reflect the true health of the myocardium, as natural compensatory mechanisms may obviate
the need for further intervention. In light of this, cardiac magnetic resonance perfusion
imaging is increasingly gaining attention and clinical implementation, as it offers a direct
assessment of myocardial tissue viability following infarction or suspected coronary artery
disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic
imaging. This issue predisposes clinicians to laborious manual intervention in order
to align anatomical structures in sequential perfusion frames, thus hindering automation o
Automatic Spatiotemporal Analysis of Cardiac Image Series
RĂSUMĂ
Ă ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de
dĂ©cĂšs en AmĂ©rique du Nord. Chez lâadulte et au sein de populations de plus en plus jeunes,
la soi-disant Ă©pidĂ©mie dâobĂ©sitĂ© entraĂźnĂ©e par certaines habitudes de vie tels que la mauvaise
alimentation, le manque dâexercice et le tabagisme est lourde de consĂ©quences pour les personnes
affectées, mais aussi sur le systÚme de santé. La principale cause de morbidité et de
mortalitĂ© chez ces patients est lâathĂ©rosclĂ©rose, une accumulation de plaque Ă lâintĂ©rieur des
vaisseaux sanguins à hautes pressions telles que les artÚres coronaires. Les lésions athérosclérotiques
peuvent entraĂźner lâischĂ©mie en bloquant la circulation sanguine et/ou en provoquant
une thrombose. Cela mĂšne souvent Ă de graves consĂ©quences telles quâun infarctus. Outre les
problÚmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la
rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population
pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de
Kawasaki. Il sâagit dâune vasculite aigĂŒe pouvant affecter lâintĂ©gritĂ© structurale des parois des
artĂšres coronaires et mener Ă la formation dâanĂ©vrismes. Dans certains cas, ceux-ci entravent
lâhĂ©modynamie artĂ©rielle en engendrant une perfusion myocardique insuffisante et en activant
la formation de thromboses.
Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectuĂ©s Ă lâaide
dâangiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de
projections radiographiques sont acquises en sĂ©ries suite Ă lâinfusion artĂ©rielle dâun agent de
contraste. Ces images révÚlent la lumiÚre des vaisseaux sanguins et la présence de lésions
potentiellement pathologiques, sâil y a lieu. Parce que les sĂ©ries acquises contiennent de lâinformation
trĂšs dynamique en termes de mouvement du patient volontaire et involontaire (ex.
battements cardiaques, respiration et dĂ©placement dâorganes), le clinicien base gĂ©nĂ©ralement
son interprĂ©tation sur une seule image angiographique oĂč des mesures gĂ©omĂ©triques sont effectuĂ©es
manuellement ou semi-automatiquement par un technicien en radiologie. Bien que
lâangiographie par fluoroscopie soit frĂ©quemment utilisĂ© partout dans le monde et souvent
considĂ©rĂ© comme lâoutil de diagnostic âgold-standardâ pour de nombreuses maladies vasculaires,
la nature bidimensionnelle de cette modalitĂ© dâimagerie est malheureusement trĂšs
limitante en termes de spécification géométrique des différentes régions pathologiques. En effet,
la structure tridimensionnelle des stĂ©noses et des anĂ©vrismes ne peut pas ĂȘtre pleinement
appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de
lâimageur. De plus, la prĂ©sence de lĂ©sions affectant les artĂšres coronaires peut ne pas reflĂ©ter
la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT
Cardiovascular disease continues to be the leading cause of death in North America. In adult
and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by
lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses
on the healthcare system. The primary cause of serious morbidity and mortality for these
patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary
arteries. These lesions can lead to ischemic disease and may progress to precarious blood
flow blockage or thrombosis, often with infarction or other severe consequences. Besides
the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased
stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the
most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis
may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions.
These can hinder the blood flowâs hemodynamics, leading to inadequate downstream
perfusion, and may activate thrombus formation which may lead to precarious prognosis.
Diagnosing these two prominent coronary artery diseases is traditionally performed using
fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective
arterial infusion of a radiodense contrast agent, which reveals the vesselsâ luminal
area and possible pathological lesions. The acquired series contain highly dynamic information
on voluntary and involuntary patient movement: respiration, organ displacement and
heartbeat, for example. Current clinical analysis is largely limited to a single angiographic
image where geometrical measures will be performed manually or semi-automatically by a
radiological technician. Although widely used around the world and generally considered
the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of
this imaging modality is limiting in terms of specifying the geometry of various pathological
regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated
in 2D because their observable features are dependent on the angular configuration of
the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not
reflect the true health of the myocardium, as natural compensatory mechanisms may obviate
the need for further intervention. In light of this, cardiac magnetic resonance perfusion
imaging is increasingly gaining attention and clinical implementation, as it offers a direct
assessment of myocardial tissue viability following infarction or suspected coronary artery
disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic
imaging. This issue predisposes clinicians to laborious manual intervention in order
to align anatomical structures in sequential perfusion frames, thus hindering automation o
Vascular Modeling from Volumetric Diagnostic Data: A Review
Reconstruction of vascular trees from digital diagnostic images is a challenging task in the development of tools for simulation and procedural planning for clinical use. Improvements in quality and resolution of acquisition modalities are constantly increasing the fields of application of computer assisted techniques for vascular modeling and a lot of Computer Vision and Computer Graphics research groups are currently active in the field, developing methodologies, algorithms and software prototypes able to recover models of branches of human vascular system from different kinds of input images. Reconstruction methods can be extremely different according to image type, accuracy requirements and level of automation. Some technologies have been validated and are available on medical workstation, others have still to be validated in clinical environments. It is difficult, therefore, to give a complete overview of the different approach used and results obtained, this paper just presents a short review including some examples of the principal reconstruction approaches proposed for vascular reconstruction, showing also the contribution given to the field by the Medical Application Area of CRS4, where methods to recover vascular models have been implemented and used for blood flow analysis, quantitative diagnosis and surgical planning tools based on Virtual Reality
Mri Assessment Of Maternal Uteroplacental Circulation In Pregnancy
Hypertensive pregnancy disorders (HPD) such as preeclampsia are highly associated with maternal vascular malperfusion of the placenta, an organ that exchanges nutrients and oxygen between the maternal circulation and the growing fetus. Adverse pregnancy outcomes are difficult to predict because there is insufficient understanding of how poor maternal arterial remodeling leads to disease. There is also a lack of reliable tools to evaluate these changes in early gestation.
The hypothesis of this dissertation was that magnetic resonance imaging (MRI) could noninvasively evaluate uteroplacental function in vivo through a combination of arterial spin labeling (ASL), 4D flow, and time-of-flight (TOF) techniques which were already effective in the evalution of other cardiovascular diseases. These flow and perfusion imaging studies were conducted on human pregnant volunteers in their second and third trimesters at 1.5T. Many of them were also examined by conventional Doppler ultrasound (US) and followed through delivery.
Flow-sensitive Alternating Inversion Recovery (FAIR) ASL MRI with background suppression was found to be feasible in detecting placental perfusion signal despite the presence of motion artifacts. An important consideration when studying placental ASL was the slow movement of maternal arterial blood in a large cavity called the intervillous space. This was a unique feature of placental anatomy which distinguished it from other organs containing capillaries. It became apparent that traditional models to estimate perfusion from MRI were no longer applicable. In this work, a statistical approach was first developed to filter out motion artifacts, followed by a coordinate transformation to better represent the lobular distribution of blood flow in the intervillous space of the placenta. The uterine arteries (UtAs) are the main maternal blood supply of the placenta and have also long been suspected to be involved in HPD, though US-based measurements have not yet been found to be highly predictive for widespread clinical use. In this work, 4D flow MRI enabled visualization of the tortuous UtAs while measuring volumetric flow rate. Its performance in predicting incidence of preeclampsia and small-for-gestational age births was comparable to Doppler US. When considering the innovative potential of 4D flow MRI to capture complex flow dynamics, this validation demonstrated the value of continuing technical development for improving HPD risk assessment. Furthermore, centerline extraction of the maternal pelvic arteries in TOF MRI, from the descending aorta to the UtAs and external iliac arteries, provided quantitative metrics to characterize the geometry including path length and curvature. Pulse wave velocity (PWV) was estimated using path length by TOF MRI and velocimetry by 2D phase contrast and 4D flow MRI with results showing sensitivity to differences between UtAs and external iliac arteries. These approaches provided physiological metrics to explore and characterize the remodeling process of the uteroplacental arteries. This dissertation demonstrates the feasibility of measuring structure and hemodynamics of the maternal vascular blood supply using non-contrast MRI that can lead to the more reliable biomarkers of adverse pregnancy outcomes needed to diagnose and treat HPD
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