Automatic generation of absolute myocardial blood flow images using [15O]H2O and a clinical PET/CT scanner

PURPOSE: Parametric imaging of absolute myocardial blood flow (MBF) using [(15)O]H(2)O enables determination of MBF with high spatial resolution. The aim of this study was to develop a method for generating reproducible, high-quality and quantitative parametric MBF images with minimal user intervention. METHODS: Nineteen patients referred for evaluation of MBF underwent rest and adenosine stress [(15)O]H(2)O positron emission tomography (PET) scans. Ascending aorta and right ventricular (RV) cavity volumes of interest (VOIs) were used as input functions. Implementation of a basis function method (BFM) of the single-tissue model with an additional correction for RV spillover was used to generate parametric images. The average segmental MBF derived from parametric images was compared with MBF obtained using nonlinear least-squares regression (NLR) of VOI data. Four segmentation algorithms were evaluated for automatic extraction of input functions. Segmental MBF obtained using these input functions was compared with MBF obtained using manually defined input functions. RESULTS: The average parametric MBF showed a high agreement with NLR-derived MBF [intraclass correlation coefficient (ICC) = 0.984]. For each segmentation algorithm there was at least one implementation that yielded high agreement (ICC > 0.9) with manually obtained input functions, although MBF calculated using each algorithm was at least 10% higher. Cluster analysis with six clusters yielded the highest agreement (ICC = 0.977), together with good segmentation reproducibility (coefficient of variation of MBF <5%). CONCLUSION: Parametric MBF images of diagnostic quality can be generated automatically using cluster analysis and a implementation of a BFM of the single-tissue model with additional RV spillover correction. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00259-011-1730-3) contains supplementary material, which is available to authorized users

Advanced imaging techniques for cardiovascular research

According to the World Health Organization, cardiovascular diseases (CVDs) are the first cause of death globally. CVDs are a cluster of disorders that involve heart and blood vessels. Among them, coronary artery disease (CAD) is the most important disease in terms of mortality, causing more than 50% of the annual deaths. Over the last decades, many recognized international organisms, such as the World Health Organization and the American College of Cardiology have done great efforts to reduce the mortality and morbidity of CAD. In this line, accurate diagnosis and cost-effective management of CAD have revealed to be of utmost importance. Several imaging techniques are currently used in the clinical practice to provide a diagnosis and clinical assessment of the disease. Among them, Positron Emission Tomography (PET) is considered to be the “gold standard” for non invasive assessment of myocardial perfusion and viability, the two most relevant physiological parameters used to diagnose and manage patients with known or suspected CAD..

Advanced Imaging Techniques for Cardiovascular Research

Objectives: In this thesis we addressed some of those difficulties by exploring new applications of a 68Galabeled radiotracer (68Ga-DOTA). 68Ga can be obtained from a 68Ge/68Ga generator and has a half-life of 68 minutes, which makes it a convenient candidate for its widespread clinical use. We proposed and validated the use of 68Ga-DOTA as a radiotracer for assessment of myocardial blood flow (MBF), myocardial viability and pulmonary blood flow (PBF). Additionally, we introduced a new methodology to perform a PET scan in which this tracer could be coinjected simultaneously with some other radiotracers such as 18FDG (multi-tracer PET). Lastly, we developed an automatic detector able to perform blood spectroscopy analysis, which offered the possibility to perform multi-tracer PET with minimal human intervention. Methods To test the capability of 68Ga-DOTA to measure MBF, viability and PBF, different groups of Large White pigs underwent PET/CT scans using 68Ga-DOTA as the injected radiotracer. For PBF studies, a group of healthy pigs (n = 4) were scanned under rest conditions. For MBF studies, a group of 8 pigs were scanned under rest and pharmacologically-induced stress in order to perform rest/stress tests, as it is done for humans in clinical routine. Additionally, a group of 5 pigs were scanned 7 days after the induction of a myocardial infarction (MI) to assess viability and MBF in a MI model. MBF, extracellular volume fraction (ECV, for viability assessment) and PBF maps were obtained after fitting the dynamic PET images to the corresponding pharmacokinetic model followed by 68Ga-DOTA in each tissue under study. Global and regional perfusion maps for the myocardial tissue (MBF) and lungs (PBF) were obtained. For validation purposes, the “goldstandard” technique used in tissue perfusion quantification (fluorescent-labeled microspheres (MS)) was simultaneosly performed along with the PET/CT scans. The blood sampling spectroscopic methodology was evaluated and calibrated in vitro using different 68Ga/18F mixtures. Then, it was tested in pigs (n = 3) injected with 68Ga-DOTA and 18FDG in the same acquisition. The activity concentration of each radiotracer in myocardial tissue was subsequently measured ex vivo. The automatic blood sampling detector was built from scratch and characterized using a catheter filled with different 68Ga/18F mixtures. Finally, it was additionally evaluated in vivo in n = 3 pigs under conditions resembling to those encountered in clinical routine. Results Regarding MBF quantification and validation with 68Ga-DOTA-PET, a strong correlation (r = 0.91) between MBF measured with PET and MS was obtained (slope = 0.96 ± 0.10, y-intercept = 0.11 ± 0.19 ml·min−1·g−1). For the myocardial infarction model, MBF values obtained with 68Ga-DOTA-PET in the infarcted area (LAD, left anterior descendant) were significantly reduced in comparison to remote ones LCX (left circumflex artery, p < 0.0001) and RCA (right coronary artery, p < 0.0001). In addition, 68Ga-DOTA-PET detected a significant ECV increase in the infarcted area (p < 0.0001). The correlation evaluation between 68Ga-DOTA-PET and MS as a PBF radiotracer also showed a good and significant correlation (r = 0.74, p < 0.0001). The gamma spectroscopic analysis on blood samples proposed for multi-tracer PET imaging was also succesfully validated, showing a correlation of r = 0.95 (p < 0.0001) for 18FDG concentration in myocardium measured with multi-tracer PET and by ex vivo validation. The blood sampling detector was able to measure the arterial input function in pigs in an experimental setup under realistic conditions. Discussion and conclusions 68Ga-DOTA-PET allowed accurate non-invasive assessment of MBF and ECV in pigs with myocardial infarction and under rest-stress conditions. This technique could provide wide access to quantitative measurement of both MBF and ECV with PET imaging. 68Ga-DOTA-PET was also demonstrated to be a potential inexpensive method for measuring PBF in clinical settings. As for multi-tracer PET imaging, the proposed methodology allowed explicit measurement of separate arterial input functions, offering very similar results to those obtained as a reference from the ex vivo analysis of the tissue under evaluation. Finally, a novel blood sampling device was developed and characterized, showing performance parameters similar to other devices in the literature. Noteworthy, this detector has the additional and unique feature of allowing us to perform multi-tracer PET by means of a gamma spectroscopic analysis of the blood flowing between its detection blocks. All the results summarized in this abstract may contribute to spread the use of PET in clinical routine, either by the clinical use of 68Ga-DOTA as an inexpensive but accurate radiotracer for MBF, PBF or viability assessment, or by the implementation of multi-tracer PET, which could lead to cost reduction of PET examinations by shortening the scanning time and eliminating misalignment inaccuracies. This multi-tracer PET methodology could also be safely implemented using our proposed automated device that permits to perform the gamma spectroscopic analysis on blood samples with minimal human intervention

Contributions to the quantitative analysis of dynamic PET studies using clustering approaches

Mención Internacional en el título de doctorDynamic positron emission tomography (PET) is a widespread medical imaging technique that allows the quantification of different physiological parameters within the body and yields more information that the one provided by a single, static image. Quantification of these studies involves obtaining the input function, that is, the amount of tracer present in arterial blood at any given point in time, and the tissue time-activity curve (TAC) for the tissue or organ under study. The subjacent biological processes are modelled as the tracer exchange rates between the arterial activity source and a compartmental model; this mathematical approach allows to quantify different biological aspects (metabolic rates, blood flow, specific receptor binding) in a non-invasive way. Typically, arterial and tissue TACs are extracted from the image data by drawing a ROI over the areas of interest, either over the PET image or over some anatomical imaging modality, such as CT, and in some cases acquire some blood samples to correct the input function for metabolites, partial volume effects or other different sources of distortion that may bias the final result. While this ROI delineation is done normally by an experienced operator, this process is very slow and, more importantly, subjective and non-replicable. Furthermore, ROI delineation over registered anatomical images may group together regions that look identical in the CT image but have different underlying kinetics. These reasons have motivated the development of automatic segmentation or TAC extraction algorithms, of which there are several examples in the medical imaging literature. Most of the proposed methods involve the use of unsupervised machine learning algorithms or the direct application of dimensionality reduction techniques, such as PCA or SVD. This thesis studies the feasibility of supervised algorithms to extract the activity curves of dynamic studies based solely on the knowledge acquired about the kinetics of similar ones. Our experiments on three swine studies showed that the segmentation was successful and the obtained TACs allowed the computation of the kinetic analysis and obtained smaller errors in the kinetic parameters obtained from the mathematical model than the manual segmentations. Said supervised algorithms are not common in the literature but we have shown that they can be a viable option for very specific subset of cases. One of the problems of the published automatic segmentation algorithms is the general lack of published source codes or even binary distributions. As has been studied in the literature, this presents a problem by itself, as it forces other researchers to re-implement said algorithms. This work presents the development of an open framework for dynamic imaging clustering that includes the most commonly used algorithms and that can be easily extended by third parties through the use of its public API. The code for said framework has been published with a free software license to allow it to be modified by external researchers and adapt it to their needs. It has been developed as an ImageJ plugin to take advantage to all the imaging analysis functionalities already presented in said platform. Using this framework, we also present an improvement of the classical leader-follower algorithm. This unsupervised algorithm groups image voxels with similar TACs according to a threshold set by the user and creates as many clusters as necessary to form homogeneous regions. Due to the nature of the partial volume distortions that need to be removed from the final TACs as much as possible, the proposed method implements a two-step leader-follower modification. In this case, the image voxels are clustered according to both a similarity metric and a distance metric; particularly, the cosine similarity and the Euclidean distance were chosen for our tests. This algorithm successfully segmented all of the evaluated 24 mice imaging studies, yielding quantitative parameters after the kinetic modelling that were not significantly different from those obtained via manual delineation and maintained the differences between the three tracers used in this experiment. --------------------------------------------------------La tomografía por emisión de positrones (PET) es una técnica de imagen médica ampliamente utilizada que permite la cuantificación de diferentes parámetros fisiológicos dentro del cuerpo y arroja más información que la que puede obtenerse mediante una única imagen estática. La cuantificación de estos estudios necesita la obtención de la función de entrada, esto es, la cantidad de trazador presente en sangre arterial a lo largo del tiempo, y la curva de actividad (TAC) del tejido u órgano bajo estudio. Los procesos biológicos subyacentes se modelan como las velocidades de intercambio de trazador entre la fuente de actividad arterial y un modelo compartimental; esta aproximación matemática permite cuantificar diferentes aspectos biológicos (metabolismo, flujo sanguíneo, fijación a receptores específicos) de una forma no invasiva. Típicamente, la función de entrada y la TAC de los tejidos se extraen directamente de la imagen mediante el trazado de una región de interés (ROI), bien sobre la imagen PET directamente o sobre alguna modalidad de imagen que presente información anatómica, como el CT, y en algunos casos requiere la obtención de muestras de sangre para corregir en la función de entrada el efecto de metabolitos, efectos de volumen parcial u otras fuentes de distorsión que pueden sesgar el resultado final. Aunque este proceso de delineación lo realiza habitualmente un operador experimentado, este proceso es lento, subjetivo y no replicable. Además, la delineación de ROIs sobre imágenes anatómicas registradas puede agrupar regiones que aparecen idénticas en la imagen de CT pero tienen diferentes comportamientos cinéticos. Estas razones han motivado el desarrollo de algoritmos de segmentación automática o extracción de TAC, de los cuales hay múltiples ejemplos en la literatura de imagen médica. La mayoría de los métodos propuestos son implementaciones de algoritmos de unsupervised machine learning, o aprendizaje máquina no supervisado, o la aplicación directa de técnicas de reducción de dimensionalidad, como análisis de componentes principales (PCA) o descomposición en valores singulares (SVD). Esta tesis doctoral estudia la posibilidad de emplear algoritmos supervisados para extraer las curvas de actividad de estudios dinámicos basándose únicamente en el conocimiento adquirido en la cinética de estudios similares. La experimentación con tres estudios porcinos mostró que la obtención de las TACs fue exitosa, y estos datos permitieron el cálculo de los parámetros cinéticos, obteniendo errores en el ajuste matemático menores que los obtenidos mediante una segmentación manual. Este tipo de algoritmos supervisados no son comunes en la literature pero hemos demostrado que pueden ser una opción viable para un subconjunto de casos específico. Uno de los problemas de los algoritmos de segmentación automática publicados en la literatura es la carencia general de código fuente o incluso distribuciones binarias. Como ya se ha estudiado en la literature, esto presenta un problema, al forzar a investigadores de otras instituciones a reimplementar dichos algoritmos. Este trabajo presenta un marco de desarrollo para algoritmos de clustering aplicados a imagen médica dinámica que incluye los algoritmos más comúnmente utilizados y que puede ser extendido fácilmente mediante terceros a través del uso de su interfaz de programación (API) pública. El código para dicho marco de desarrollo ha sido publicado con una licencia libre para permitir su modificación por investigadores externos y su adaptación a sus necesidades. Se ha programado como un plugin de la plataforma de análisis de imagen ImageJ para aprovechar todas las ventajas y funcionalidades de análisis ya presentes en dicha plataforma. Empleando este marco de desarrollo, finalmente presentamos una mejora sobre un algoritmo clásico leader-follower. Este algoritmo no supervisado agrupa vóxeles de la imagen con TACs similares de acuerdo a un umbral establecido por el usuario, y crea tantos clusters, o grupos, necesaarios para formar regiones homogéneas. Debido a los efectos de volumen parcial, que deben ser eliminados de las TACs finales lo máximo posible, el método propuesto implementa una modificación del leader-follower en dos pasos. En este caso, los vóxeles de la imagen se agrupan de acuerdo a una métrica de similitud (coseno) y una métrica de distancia (Euclídea). El algoritmo segmentó con éxito 24 imágenes dinámicas de ratón, ofreciendo parámetros cuantitativos tras el modelado cinético que no fueron diferentes de forma significativa de los obtenidos a través de la delineación manual y manteniendo las diferencias observadas entre los tres trazadores empleados en este experimento.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: María Jesús Ledesma Carbayo; Secretario: Jorge Ripoll Lorenzo; Vocal: Stephen L. Bacharac

KSNM60 in Cardiology: Regrowth After a Long Pause

The Korean Society of Nuclear Medicine (KSNM) is celebrating its 60th anniversary in honor of the nuclear medicine professionals who have dedicated their efforts towards research, academics, and the more comprehensive clinical applications and uses of nuclear imaging modalities. Nuclear cardiology in Korea was at its prime time in the 1990s, but its growth was interrupted by a long pause. Despite the academic and practical challenges, nuclear cardiology in Korea now meets the second leap, attributed to the growth in molecular imaging tailored for many non-coronary diseases and the genuine values of nuclear myocardial perfusion imaging. In this review, we describe the trends, achievements, challenges, and perspectives of nuclear cardiology throughout the 60-year history of the KSNM.ope

Técnicas de imagen avanzada aplicadas a la investigación cardiovascular

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, leída el 05-11-2019According to the World Health Organization, cardiovascular diseases (CVDs) are the first cause of death globally. CVDs are a cluster of disorders that involve heart and blood vessels. Among them, coronary artery disease (CAD) is the most important disease in terms of mortality, causing more than 50% of the annual deaths. Over the last decades, many recognized international organisms, such as the World Health Organization and the American College of Cardiology have done great efforts to reduce the mortality and morbidity of CAD. In this line, accurate diagnosis and cost-effective management of CAD have revealed to be of utmost importance. Several imaging techniques are currently used in the clinical practice to provide a diagnosis and clinical assessment of the disease. Among them, Positron Emission Tomography (PET) is considered to be the “gold standard” for non invasive assessment of myocardial perfusion and viability, the two most relevant physiological parameters used to diagnose and manage patients with known or suspected CAD...Según la Organización Mundial de la Salud (OMS), las enfermedades cardiovasculares son, cada año, la primera causa de muerte en el mundo. De ellas, más de la mitad son causadas por la enfermedad de las arterias coronarias. En las últimas décadas, numerosos organismos internacionales de reconocido prestigio, como la propia OMS o el Colegio Americano de Cardiología,han centrado sus esfuerzos en reducir la mortalidad y la morbilidad de esta enfermedad y han establecido como factores clave el diagnóstico preciso y el tratamiento eficaz y económico de la enfermedad. En la actualidad, existen diversas técnicas de diagnóstico por imagen que nos permiten evaluar clínicamente esta enfermedad. De entre todas ellas, la tomografía por emisión de positrones (PET por sus siglas en inglés) destaca como la técnica de referencia para la evaluación de la perfusión y viabilidad del miocardio, que son dos de los parámetros fisiológicos más importantes a la hora de diagnosticar y tratar a pacientes de los que se sabe o se sospecha que pueden padecerla enfermedad de las arterias coronarias...Fac. de Ciencias FísicasTRUEunpu

Mapping the Impact and Plasticity of Cortical-Cardiovascular Interactions in Vascular Disease Using Structural and Functional MRI

There is growing interest in the role of vascular disease in accelerating age-related decline in cerebrovascular structural and functional integrity. Since an increased number of older adults are surviving chronic diseases, of which cardiovascular disease (CVD) is prevalent, there is an urgent need to understand relationships between cardiovascular dysfunction and brain health. It is unclear if CVD puts the brains of older adults, already experiencing natural brain aging, at greater risk for degeneration. In this thesis, the role of CVD in accelerating brain aging is explored. Because physical activity is known to provide neuroprotective benefits to brains of older adults, the role of physical activity in mediating disease effects were also explored. Using novel neuroimaging techniques, measures of gray matter volume and cerebrovascular hemodynamics were compared between groups of coronary artery disease patients and age-matched controls, to describe regional effects of CVD on the brain. In a sub-set of patients, imaging measures were repeated after completion of a 6-month exercise training, part of a cardiac rehabilitation program, to examine exercise effects. Differences in cerebrovascular hemodynamics were measured as changes in resting cerebral blood flow (CBF) and changes in cerebrovascular reactivity (CVR) to hypercapnia (6% CO2) using a non-invasive perfusion magnetic resonance imaging technique, arterial spin labelling (ASL). We found decreased brain volume, CBF and CVR in several regions of the brains of coronary artery disease patients compared to age-matched healthy controls. The reductions in CBF and CVR were independent of underlying brain atrophy, suggesting that changes in cerebrovascular function could precede changes in brain structure. In addition, increase in brain volume and CBF were observed in some regions of the brain after exercise training, indicating that cardiac rehabilitation programs may have neurorehabiliation effects as well. Since, CBF measured with ASL is not the [gold] standard measure of functional brain activity, we examined the regional correlation of ASL-CBF to glucose consumption rates (CMRglc) measured with positron emission tomography (PET), a widely acceptable marker of brain functional activity. Simultaneous measurements of ASL-CBF and PET-CMRglc were performed in a separate study in a group of older adults with no neurological impairment. Across brain regions, ASL-CBF correlated well with PET-CMRglc, but variations in regional coupling were found and demonstrate the role of certain brain regions in maintaining higher level of functional organization compared to other regions. In general, the results of the thesis demonstrate the impact of CVD on brain health, and the neurorehabiliation capacity of cardiac rehabilitation. The work presented also highlights the ability of novel non-invasive neuroimaging techniques in detecting and monitoring subtle but robust changes in the aging human brain

ADVANCEMENTS IN QUANTITATIVE PERFUSION MAGNETIC RESONANCE IMAGING (MRI) OF DEMENTIA

Alzheimer's disease (AD) affects a considerable, and increasing, part of the population. Early diagnosis of AD is very important to permit effective therapy, and minimize AD's social and economic burden. The goal of our research is to evaluate the changes of cerebral perfusion (i.e., blood flow) in the early stages of AD and the effects from hypertension.We studied volunteers with Mild Cognitive Impairment (MCI) and early AD from the Pittsburgh cohort of the Cardiovascular Health Study (CHS) Cognitive Study during a four-year follow-up. Previously, studies used referral patients who typically have more advanced AD. No perfusion data concerning the early and transitional disease stages are currently available from population studies (i.e., subjects who have been monitored longitudinally in time). There are no common techniques for perfusion quantification and image analysis so that inconsistencies are observed between/within studies, modalities, and researchers. Several advancements were achieved in preparation for the cohort study. First, we improved the accuracy and speed of brain perfusion quantification. Second, we improved the accuracy of image registration to a reference brain using quantitative validation of a registration method and performance comparison with a popular registration method. Third, we improved the method of statistical analysis for evaluating the changes of perfusion between groups. Fourth, we evaluated the changes of cerebral perfusion between cognitive groups (controls, MCIs, ADs), and hypertension and normo-tensive subgroups.Individual perfusion maps were improved by measuring and incorporating individual arrival time, saturation effects, and individual inversion efficiency. A fully deformable registration technique was shown to be more accurate than standard techniques like statistical parametric mapping to detect local perfusion changes. All of the published literature for perfusion up-to-date reported decreased perfusion in AD, but we found hyperperfusion in some regions. The regional findings imply that a hemodynamic process, at the capillary level, accompanied the neurodegenerative process. Hypertensive normal cognitive controls demonstrated hypoperfusion in regions usually involved in AD pathology. However, the effect of hypertension was attenuated after the onset of the pathological cognitive process

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