Introdução: A doença arterial coronária (DAC) é avaliada através dos aspectos anatômicos da placa aterosclerótica ou a partir da repercussão funcional da estenose, por métodos diagnósticos diversos. O ultrassom intravascular (IVUS) fornece uma avaliação anatômica precisa do lúmen e da parede do vaso, tendo sido validado como uma ferramenta útil para guiar a intervenção coronária percutânea (ICP). No entanto, do ponto de vista diagnóstico, o IVUS representa mal o estado funcional (isto é, informação relacionada ao comprometimento de fluxo) do vaso interrogado. A reserva de fluxo fracionada (FFR) é método importante para identificação de isquemia, discriminando as estenoses coronárias que podem se beneficiar de ICP. Objetivamos desenvolver e avaliar o desempenho diagnóstico de um novo algoritmo computacional para estimar a FFR à partir das imagens do IVUS tridimensional (IVUSFR), comparando-o com o método padrão ouro para estimação de fluxo coronário invasivo (FFRPW). Métodos: Pacientes com DAC estável conhecida ou suspeita encaminhados para cateterismo cardíaco eletivo foram submetidos a avaliação complementar com medida de fluxo coronário pelo FFRPW e com imagem intravascular pelo IVUS, no mesmo procedimento, a fim de avaliar lesões intermediárias. As imagens do IVUS foram processadas para gerar uma malha computacional tridimensional que condensa as características geométricas do vaso. O IVUSFR foi obtido utilizando dinâmica de fluido computacional, configurando-se as condições de contorno a partir de características específicas do paciente e do território coronário irrigado. As medidas de FFRPW foram dicotomizadas no limiar de 0,80 para definir lesões hemodinamicamente significativas e avaliar o desempenho diagnóstico do IVUSFR. Resultados: Um total de 34 artérias coronárias de 24 pacientes foi analisado. A área luminal mínima média avaliada pelo IVUS de 4,14 ± 1,74 mm2, e carga de placa média de 66±10% caracterizam o grau intermediário das lesões. O IVUSFR correlacionou significativamente (r = 0,79; p < 0,001) e mostrou boa concordância com a FFRPW, apresentando diferença média de -0,008 ± 0,067 (p = 0,47). O IVUSFR apresentou acurácia, sensibilidade, especificidade, valor preditivo positivo e valor preditivo negativo de 91%, 89%, 92%, 80% e 96%, respectivamente, para detectar estenoses hemodinamicamente significativas. Conclusão: O processamento computacional do IVUSFR é um novo método que permite a avaliação funcional da estenose coronária intermediária de forma acurada, enriquecendo as informações anatômicas do IVUS / Introduction: Coronary artery disease (CAD) is assessed through the anatomical aspects of the atherosclerotic plaque or through the functional impairment of the stenosis, by different diagnostic methods. Intravascular ultrasound (IVUS) provides accurate anatomic assessment of lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention (PCI). However, from the diagnostic point of view, IVUS poorly represents the functional status (i.e. flow-related information) of the imaged vessel. Fractional flow reserve (FFR) is an important tool to identify ischemia, discriminating coronary stenosis that may benefit from PCI. We aimed to develop and evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional IVUS imaging in estimating fractional flow reserve (IVUSFR), compared to gold-standard invasive measurements (FFRPW). Methods: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRPW measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Through computational fluid dynamics, IVUSFR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFRPW measurements were dichotomized at the 0.80 thresholds to define hemodynamically significant lesions and evaluate diagnostic performance of IVUSFR. Results: A total of 24 patients with 34 vessels were analyzed. The mean minimum luminal area assessed by IVUS was 4.14 ± 1.74 mm2, and mean plaque burden was 66 ± 10%, characterizing intermediate lesions. IVUSFR significantly correlated (r = 0.79; p < 0.001) and showed good agreement with FFRPW, with a mean difference of -0.008 ± 0.067 (p = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96% respectively to detect significant stenosis. Conclusion: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of IVUS

Introdução: A extensão da doença arterial coronariana (DAC) é um dos mais fortes preditores de eventos cardiovasculares adversos. Estratégias capazes de quantificar acuradamente a gravidade da doença coronária podem implicar em melhora na avalição prognóstica, na orientação terapêutica e na avaliação da progressão da doença. O ultrassom intracoronário (USIC) tornou-se o método padrão-ouro para quantificação da aterosclerose devido à sua habilidade em avaliar diretamente as placas ateroscleróticas. A angiotomografia coronária tem surgido como uma útil alternativa não invasiva ao USIC para avaliação de pacientes com DAC. Entretanto, pouco se sabe a respeito da sua habilidade em estimar, de modo acurado, a carga aterosclerótica coronariana global. Objetivo: Comparar diversos escores angiotomográficos que avaliam a extensão da DAC utilizando o USIC multivascular como padrão-ouro. Métodos: Pacientes com doença coronariana diagnosticada, em programação para intervenção percutânea foram incluídos prospectivamente. Pelo menos uma de três características de alto risco era necessária para inclusão: doença multiarterial, diabetes melitus e/ou síndrome coronária aguda à admissão. Todos os pacientes foram submetidos a ultrassom intracoronário multivascular e angiotomografia coronária. Escore de cálcio e cinco outros escores previamente descritos foram calculados com base na imagem da angiotomografia coronária e comparados com o volume percentual de ateroma (VPA) médio derivado do USIC. Um novo escore angiotomográfico foi criado e também comparado ao USIC. Resultados: Um total de 62 pacientes foram incluídos. Todos com exceção de um escore apresentaram baixa a moderada correlação, estatisticamente significante, com o VPA derivado do USIC. O novo escore angiotomográfico criado demonstrou a mais forte correlação com o VPA ao USIC (&#961;=0,73, p < 0,001) e a maior área sob a curva ROC (estatística-C = 0,90) para predizer um VPA médio dicotomizado alto. Conclusões: Enquanto escores angiotomográficos foram capazes de estimar a carga aterosclerótica coronária global, um recém criado escore pode ser uma ferramenta útil para a quantificação da extensão da DAC em pacientes de alto risco. / Background: The extent of coronary artery disease (CAD) is one the most powerful predictors of cardiovascular outcomes. Strategies that accurately quantify coronary artery disease severity are expected to improve prognosis assessment, treatment guidance and evaluation of disease progression. Intravascular ultrasound (IVUS) has become the gold-standard method to quantify atherosclerosis due to its ability to directly analyze atherosclerotic plaques. Coronary computed tomography angiography (CTA) has emerged as a useful non-invasive alternative to IVUS for assessing patients with CAD. Nevertheless, little is known about its ability to accurately estimate global atherosclerotic burden. Objective: To compare several coronary CTA scoring systems assessing CAD extent with gold-standard multivessel intravascular ultrasound. Methods: Patients with diagnosed coronary disease scheduled for percutaneous intervention were prospectively enrolled. For all patients, coronary CTA and multivessel IVUS were obtained. Calcium score and 5 previously reported scores were calculated from coronary CTA imaging and compared to average IVUS-derived percent atheroma volume (PAV). A novel coronary CTA score was constructed and also compared to IVUS. Results: A total of 62 patients were included. All but one previously described scoring system showed a significant low-to-moderate association with IVUS-derived PAV. The newly developed \"soft plaque\" coronary CTA score demonstrated the strongest correlation with IVUS-PAV (&#961;=0.73, p&lt;0.001) and the greatest area under the ROC curve (C-statistic = 0.90) to predict a high dichotomized PAV. Conclusions: While coronary CTA scores were able to assess total atherosclerotic burden in patients with coronary disease, a newly described CTA scoring system may be a promising non-invasive tool to quantify disease extent in high-risk patients with known CAD.

Introdução: A doença arterial coronária (DAC) é avaliada através dos aspectos anatômicos da placa aterosclerótica ou a partir da repercussão funcional da estenose, por métodos diagnósticos diversos. O ultrassom intravascular (IVUS) fornece uma avaliação anatômica precisa do lúmen e da parede do vaso, tendo sido validado como uma ferramenta útil para guiar a intervenção coronária percutânea (ICP). No entanto, do ponto de vista diagnóstico, o IVUS representa mal o estado funcional (isto é, informação relacionada ao comprometimento de fluxo) do vaso interrogado. A reserva de fluxo fracionada (FFR) é método importante para identificação de isquemia, discriminando as estenoses coronárias que podem se beneficiar de ICP. Objetivamos desenvolver e avaliar o desempenho diagnóstico de um novo algoritmo computacional para estimar a FFR à partir das imagens do IVUS tridimensional (IVUSFR), comparando-o com o método padrão ouro para estimação de fluxo coronário invasivo (FFRPW). Métodos: Pacientes com DAC estável conhecida ou suspeita encaminhados para cateterismo cardíaco eletivo foram submetidos a avaliação complementar com medida de fluxo coronário pelo FFRPW e com imagem intravascular pelo IVUS, no mesmo procedimento, a fim de avaliar lesões intermediárias. As imagens do IVUS foram processadas para gerar uma malha computacional tridimensional que condensa as características geométricas do vaso. O IVUSFR foi obtido utilizando dinâmica de fluido computacional, configurando-se as condições de contorno a partir de características específicas do paciente e do território coronário irrigado. As medidas de FFRPW foram dicotomizadas no limiar de 0,80 para definir lesões hemodinamicamente significativas e avaliar o desempenho diagnóstico do IVUSFR. Resultados: Um total de 34 artérias coronárias de 24 pacientes foi analisado. A área luminal mínima média avaliada pelo IVUS de 4,14 ± 1,74 mm2, e carga de placa média de 66±10% caracterizam o grau intermediário das lesões. O IVUSFR correlacionou significativamente (r = 0,79; p < 0,001) e mostrou boa concordância com a FFRPW, apresentando diferença média de -0,008 ± 0,067 (p = 0,47). O IVUSFR apresentou acurácia, sensibilidade, especificidade, valor preditivo positivo e valor preditivo negativo de 91%, 89%, 92%, 80% e 96%, respectivamente, para detectar estenoses hemodinamicamente significativas. Conclusão: O processamento computacional do IVUSFR é um novo método que permite a avaliação funcional da estenose coronária intermediária de forma acurada, enriquecendo as informações anatômicas do IVUS / Introduction: Coronary artery disease (CAD) is assessed through the anatomical aspects of the atherosclerotic plaque or through the functional impairment of the stenosis, by different diagnostic methods. Intravascular ultrasound (IVUS) provides accurate anatomic assessment of lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention (PCI). However, from the diagnostic point of view, IVUS poorly represents the functional status (i.e. flow-related information) of the imaged vessel. Fractional flow reserve (FFR) is an important tool to identify ischemia, discriminating coronary stenosis that may benefit from PCI. We aimed to develop and evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional IVUS imaging in estimating fractional flow reserve (IVUSFR), compared to gold-standard invasive measurements (FFRPW). Methods: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRPW measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Through computational fluid dynamics, IVUSFR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFRPW measurements were dichotomized at the 0.80 thresholds to define hemodynamically significant lesions and evaluate diagnostic performance of IVUSFR. Results: A total of 24 patients with 34 vessels were analyzed. The mean minimum luminal area assessed by IVUS was 4.14 ± 1.74 mm2, and mean plaque burden was 66 ± 10%, characterizing intermediate lesions. IVUSFR significantly correlated (r = 0.79; p < 0.001) and showed good agreement with FFRPW, with a mean difference of -0.008 ± 0.067 (p = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96% respectively to detect significant stenosis. Conclusion: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of IVUS

Na prática intervencionista, a ultrassonografia intravascular (USIV) é usada para se obter informações quantitativas e qualitativas do acometimento aterosclerótico, de forma complementar à angiografia. Esta tese teve como objetivos explorar a característica tomográfica do exame de USIV, bem como sua dinâmica dentro do ciclo cardíaco. Para isso, desenvolvemos técnicas de processamento de imagens médicas. Primeiramente, investigamos a reconstrução tridimensional da coronária baseando-nos apenas nas imagens de USIV, ou seja, sem a angiografia, como é feita a reconstrução atualmente. Na análise da dinâmica, fizemos um estudo para dispor volumes da coronária em diferentes fases do ciclo cardíaco de forma que estivessem alinhados espacialmente. Como consequência dos tratamentos propostos anteriormente, realizamos estudos sobre a quantificação de propriedades mecânicas dentro das condições oferecidas no intervalo de um ciclo cardíaco. As metodologias propostas foram aplicadas em simulações numéricas desenvolvidas neste trabalho e em exames reais. Obtivemos resultados compatíveis com os objetivos iniciais para reconstrução tridimensional da USIV em simulações numéricas. Na análise da dinâmica, a reconstrução de volumes em diferentes fases do ciclo e o alinhamento espacial possibilitaram a quantificação da variação setorial de volume da luz do vaso durante o ciclo cardíaco / In percutaneous coronary interventions, intravascular ultrasound (IVUS) examination is used to retrieve quantitative and qualitative information about the atherosclerotic plaque progression, complementary to angiography examination. This thesis has as objectives to explore the tomographic characteristic of the IVUS examination, as well as its dynamics within a cardiac cycle. For that purpose, medical image processing techniques were developed. Firstly, we have investigated how to reconstruct the tridimensional coronary based only on IVUS images, that is, without angiography, as it is done nowadays. Regarding dynamic analysis, we have studied models to build volumes of the coronary in distinct phases of the cardiac cycle in a spatial aligned way. Conversantly, as a consequence of the previous image processing methods, we have studied the quantification of mechanical properties of the vessel wall within a cardiac cycle. The methodologies proposed were applied in numeric phantoms developed in this work and also in real IVUS examinations. As result, tridimensional reconstruction was successful in the numeric phantom approach. In dynamics analysis, the reconstruction in distinct cardiac phases and volumes spatial alignment enabled the quantification of lumen volume variation during the cardiac cycle

L'imagerie intravasculaire ultrasonore (IVUS) est une technologie médicale par cathéter qui produit des images de coupe des vaisseaux sanguins. Elle permet de quantifier et d'étudier la morphologie de plaques d'athérosclérose en plus de visualiser la structure des vaisseaux sanguins (lumière, intima, plaque, média et adventice) en trois dimensions. Depuis quelques années, cette méthode d'imagerie est devenue un outil de choix en recherche aussi bien qu'en clinique pour l'étude de la maladie athérosclérotique. L'imagerie IVUS est par contre affectée par des artéfacts associés aux caractéristiques des capteurs ultrasonores, par la présence de cônes d'ombre causés par les calcifications ou des artères collatérales, par des plaques dont le rendu est hétérogène ou par le chatoiement ultrasonore (speckle) sanguin. L'analyse automatisée de séquences IVUS de grande taille représente donc un défi important. Une méthode de segmentation en trois dimensions (3D) basée sur l'algorithme du fast-marching à interfaces multiples est présentée. La segmentation utilise des attributs des régions et contours des images IVUS. En effet, une nouvelle fonction de vitesse de propagation des interfaces combinant les fonctions de densité de probabilité des tons de gris des composants de la paroi vasculaire et le gradient des intensités est proposée. La segmentation est grandement automatisée puisque la lumière du vaisseau est détectée de façon entièrement automatique. Dans une procédure d'initialisation originale, un minimum d'interactions est nécessaire lorsque les contours initiaux de la paroi externe du vaisseau calculés automatiquement sont proposés à l'utilisateur pour acceptation ou correction sur un nombre limité d'images de coupe longitudinale. La segmentation a été validée à l'aide de séquences IVUS in vivo provenant d'artères fémorales provenant de différents sous-groupes d'acquisitions, c'est-à-dire pré-angioplastie par ballon, post-intervention et à un examen de contrôle 1 an suivant l'intervention. Les résultats ont été comparés avec des contours étalons tracés manuellement par différents experts en analyse d'images IVUS. Les contours de la lumière et de la paroi externe du vaisseau détectés selon la méthode du fast-marching sont en accord avec les tracés manuels des experts puisque les mesures d'aire sont similaires et les différences point-à-point entre les contours sont faibles. De plus, la segmentation par fast-marching 3D s'est effectuée en un temps grandement réduit comparativement à l'analyse manuelle. Il s'agit de la première étude rapportée dans la littérature qui évalue la performance de la segmentation sur différents types d'acquisition IVUS. En conclusion, la segmentation par fast-marching combinant les informations des distributions de tons de gris et du gradient des intensités des images est précise et efficace pour l'analyse de séquences IVUS de grandes tailles. Un outil de segmentation robuste pourrait devenir largement répandu pour la tâche ardue et fastidieuse qu'est l'analyse de ce type d'images. / Intravascular ultrasound (IVUS) is a catheter based medical imaging technique that produces cross-sectional images of blood vessels. These images provide quantitative assessment of the vascular wall, information about the nature of atherosclerotic lesions as well as the plaque shape and size. Over the past few years, this medical imaging modality has become a useful tool in research and clinical applications, particularly in atherosclerotic disease studies. However, IVUS imaging is subject to catheter ring-down artifacts, missing vessel parts due to calcification shadowing or side-branches, heterogeneously looking plaques and ultrasonic speckle from blood. The automated analysis of large IVUS data sets thus represents an important challenge. A three-dimensional segmentation algorithm based on the multiple interface fast-marching method is presented. The segmentation is based on region and contour features of the IVUS images: a new speed fonction for the interface propagation that combines the probability density functions (PDFs) of the vessel wall components and the intensity gradients is proposed. The segmentation is highly automated with the detection of the lumen boundary that is fully automatic. Minimal interactions are necessary with a novel initialization procedure since initial contours of the external vessel wall border are also computed automatically on a limited number of longitudinal images and then proposed to the user for acceptance or correction. The segmentation method was validated with in-vivo IVUS data sets acquired from femoral arteries. This database contained 3 subgroups: pullbacks acquired before balloon angioplasty, after the intervention and at a 1 year follow-up examination. Results were compared with validation contours that were manually traced by different experts in IVUS image analysis. The lumen and external wall boundaries detected with the fast-marching method are in agreement with the experts' manually traced contours with similarly found area measurements and small point-to-point contour differences. In addition, the 3D fast-marching segmentation method dramatically reduced the analysis time compared to manual tracing. Such a valdiation study, with comparison between pre- and post-intervention data, has never been reported in the IVUS segmentation literature. In conclusion, the fast-marching method combining the information on the gray level distributions and intensity gradients of the images is precise and efficient to analyze large IVUS sequences. It is hoped that the fast-marching method will become a widely used tool for the fastidious and difficult task of IVUS image processing.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

L'imagerie intravasculaire ultrasonore (IVUS) est une technologie médicale par cathéter qui produit des images de coupe des vaisseaux sanguins. Elle permet de quantifier et d'étudier la morphologie de plaques d'athérosclérose en plus de visualiser la structure des vaisseaux sanguins (lumière, intima, plaque, média et adventice) en trois dimensions. Depuis quelques années, cette méthode d'imagerie est devenue un outil de choix en recherche aussi bien qu'en clinique pour l'étude de la maladie athérosclérotique. L'imagerie IVUS est par contre affectée par des artéfacts associés aux caractéristiques des capteurs ultrasonores, par la présence de cônes d'ombre causés par les calcifications ou des artères collatérales, par des plaques dont le rendu est hétérogène ou par le chatoiement ultrasonore (speckle) sanguin. L'analyse automatisée de séquences IVUS de grande taille représente donc un défi important. Une méthode de segmentation en trois dimensions (3D) basée sur l'algorithme du fast-marching à interfaces multiples est présentée. La segmentation utilise des attributs des régions et contours des images IVUS. En effet, une nouvelle fonction de vitesse de propagation des interfaces combinant les fonctions de densité de probabilité des tons de gris des composants de la paroi vasculaire et le gradient des intensités est proposée. La segmentation est grandement automatisée puisque la lumière du vaisseau est détectée de façon entièrement automatique. Dans une procédure d'initialisation originale, un minimum d'interactions est nécessaire lorsque les contours initiaux de la paroi externe du vaisseau calculés automatiquement sont proposés à l'utilisateur pour acceptation ou correction sur un nombre limité d'images de coupe longitudinale. La segmentation a été validée à l'aide de séquences IVUS in vivo provenant d'artères fémorales provenant de différents sous-groupes d'acquisitions, c'est-à-dire pré-angioplastie par ballon, post-intervention et à un examen de contrôle 1 an suivant l'intervention. Les résultats ont été comparés avec des contours étalons tracés manuellement par différents experts en analyse d'images IVUS. Les contours de la lumière et de la paroi externe du vaisseau détectés selon la méthode du fast-marching sont en accord avec les tracés manuels des experts puisque les mesures d'aire sont similaires et les différences point-à-point entre les contours sont faibles. De plus, la segmentation par fast-marching 3D s'est effectuée en un temps grandement réduit comparativement à l'analyse manuelle. Il s'agit de la première étude rapportée dans la littérature qui évalue la performance de la segmentation sur différents types d'acquisition IVUS. En conclusion, la segmentation par fast-marching combinant les informations des distributions de tons de gris et du gradient des intensités des images est précise et efficace pour l'analyse de séquences IVUS de grandes tailles. Un outil de segmentation robuste pourrait devenir largement répandu pour la tâche ardue et fastidieuse qu'est l'analyse de ce type d'images. / Intravascular ultrasound (IVUS) is a catheter based medical imaging technique that produces cross-sectional images of blood vessels. These images provide quantitative assessment of the vascular wall, information about the nature of atherosclerotic lesions as well as the plaque shape and size. Over the past few years, this medical imaging modality has become a useful tool in research and clinical applications, particularly in atherosclerotic disease studies. However, IVUS imaging is subject to catheter ring-down artifacts, missing vessel parts due to calcification shadowing or side-branches, heterogeneously looking plaques and ultrasonic speckle from blood. The automated analysis of large IVUS data sets thus represents an important challenge. A three-dimensional segmentation algorithm based on the multiple interface fast-marching method is presented. The segmentation is based on region and contour features of the IVUS images: a new speed fonction for the interface propagation that combines the probability density functions (PDFs) of the vessel wall components and the intensity gradients is proposed. The segmentation is highly automated with the detection of the lumen boundary that is fully automatic. Minimal interactions are necessary with a novel initialization procedure since initial contours of the external vessel wall border are also computed automatically on a limited number of longitudinal images and then proposed to the user for acceptance or correction. The segmentation method was validated with in-vivo IVUS data sets acquired from femoral arteries. This database contained 3 subgroups: pullbacks acquired before balloon angioplasty, after the intervention and at a 1 year follow-up examination. Results were compared with validation contours that were manually traced by different experts in IVUS image analysis. The lumen and external wall boundaries detected with the fast-marching method are in agreement with the experts' manually traced contours with similarly found area measurements and small point-to-point contour differences. In addition, the 3D fast-marching segmentation method dramatically reduced the analysis time compared to manual tracing. Such a valdiation study, with comparison between pre- and post-intervention data, has never been reported in the IVUS segmentation literature. In conclusion, the fast-marching method combining the information on the gray level distributions and intensity gradients of the images is precise and efficient to analyze large IVUS sequences. It is hoped that the fast-marching method will become a widely used tool for the fastidious and difficult task of IVUS image processing.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

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