420 research outputs found

    Clinical validation of a software for quantitative follow-up of abdominal aortic aneurysm maximal diameter and growth by CT angiography

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    Purpose To compare the reproducibility and accuracy of abdominal aortic aneurysm (AAA) maximal diameter (D-max) measurements using segmentation software, with manual measurement on double-oblique MPR as a reference standard. Materials and methods The local Ethics Committee approved this study and waived informed consent. Forty patients (33 men, 7 women; mean age, 72 years, range, 49–86 years) had previously undergone two CT angiography (CTA) studies within 16 ± 8 months for follow-up of AAA ≥35 mm without previous treatment. The 80 studies were segmented twice using the software to calculate reproducibility of automatic D-max calculation on 3D models. Three radiologists reviewed the 80 studies and manually measured D-max on double-oblique MPR projections. Intra-observer and inter-observer reproducibility were calculated by intraclass correlation coefficient (ICC). Systematic errors were evaluated by linear regression and Bland–Altman analyses. Differences in D-max growth were analyzed with a paired Student's t-test. Results The ICC for intra-observer reproducibility of D-max measurement was 0.992 (≥0.987) for the software and 0.985 (≥0.974) and 0.969 (≥0.948) for two radiologists. Inter-observer reproducibility was 0.979 (0.954–0.984) for the three radiologists. Mean absolute difference between semi-automated and manual D-max measurements was estimated at 1.1 ± 0.9 mm and never exceeded 5 mm. Conclusion Semi-automated software measurement of AAA D-max is reproducible, accurate, and requires minimal operator intervention

    Computational estimation of haemodynamics and tissue stresses in abdominal aortic aneurysms

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    'o e Abdominal aortic aneurysm is a vascular disease involving a focal dilation of the aorta. The exact cause is unknown but possibilities include infection and weakening of the connective tissue. Risk factors include a history of atherosclerosis, current smoking and a close relative with the disease. Although abdominal aortic aneurysm can affect anyone, it is most often seen in older men, and may be present in up to 5.9 % of the population aged 80 years. Biomechanical factors such as tissue stresses and shear stresses have been shown to play a part in aneurysm progression, although the specific mechanisms are still to be determined. The growth rate of the abdominal aortic aneurysm has been found to correlate with the peak stress in the aneurysm wall and the blood flow is thought to influence disease development. In order to resolve the connections between biology and biomechanics, accurate estimations of the forces involved are required. The first part of this thesis assesses the use of computational fluid dynamics for modelling haemodynamics in abdominal aortic aneurysms. Boundary conditions from the literature o

    Improving patient-specific assessments of regional aortic mechanics via quantitative magnetic resonance imaging with early applications in patients at elevated risk for thoracic aortopathy

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    Unstable aortic aneurysms and dissections are serious cardiovascular conditions associated with high mortality. The current gold standards for assessment of stability, however, rely on simple geometric measurements, like cross-sectional area or increased diameter between follow-up scans, and fail to incorporate information about underlying aortic mechanics. Displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) has been used previously to determine heterogeneous circumferential strain patterns in the aortas of healthy volunteers. Here, I introduce technical improvements to DENSE aortic analysis and early pilot application in patients at higher risk for the development of aortopathies. Modifications to the DENSE aortic postprocessing method involving the separate spatial smoothing of the inner and outer layers of the aortic wall allowed for the preservation of radial and shear strains without impacting circumferential strain calculations. The implementation of a semiautomatic segmentation approach utilizing the intrinsic kinematic information provided by DENSE MRI reduced lengthy post-processing times while generating circumferential strain distributions with good agreement to a manually generated benchmark. Finally, a new analysis pipeline for the combined use and spatial correlation of 4D phase-contrast MRI alongside DENSE MRI to quantify both regional fluid and solid mechanics in the descending aorta is explored in a limited pilot study

    Computational fluid dynamics indicators to improve cardiovascular pathologies

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    In recent years, the study of computational hemodynamics within anatomically complex vascular regions has generated great interest among clinicians. The progress in computational fluid dynamics, image processing and high-performance computing haveallowed us to identify the candidate vascular regions for the appearance of cardiovascular diseases and to predict how this disease may evolve. Medicine currently uses a paradigm called diagnosis. In this thesis we attempt to introduce into medicine the predictive paradigm that has been used in engineering for many years. The objective of this thesis is therefore to develop predictive models based on diagnostic indicators for cardiovascular pathologies. We try to predict the evolution of aortic abdominal aneurysm, aortic coarctation and coronary artery disease in a personalized way for each patient. To understand how the cardiovascular pathology will evolve and when it will become a health risk, it is necessary to develop new technologies by merging medical imaging and computational science. We propose diagnostic indicators that can improve the diagnosis and predict the evolution of the disease more efficiently than the methods used until now. In particular, a new methodology for computing diagnostic indicators based on computational hemodynamics and medical imaging is proposed. We have worked with data of anonymous patients to create real predictive technology that will allow us to continue advancing in personalized medicine and generate more sustainable health systems. However, our final aim is to achieve an impact at a clinical level. Several groups have tried to create predictive models for cardiovascular pathologies, but they have not yet begun to use them in clinical practice. Our objective is to go further and obtain predictive variables to be used practically in the clinical field. It is to be hoped that in the future extremely precise databases of all of our anatomy and physiology will be available to doctors. These data can be used for predictive models to improve diagnosis or to improve therapies or personalized treatments.En els últims anys, l'estudi de l'hemodinàmica computacional en regions vasculars anatòmicament complexes ha generat un gran interès entre els clínics. El progrés obtingut en la dinàmica de fluids computacional, en el processament d'imatges i en la computació d'alt rendiment ha permès identificar regions vasculars on poden aparèixer malalties cardiovasculars, així com predir-ne l'evolució. Actualment, la medicina utilitza un paradigma anomenat diagnòstic. En aquesta tesi s'intenta introduir en la medicina el paradigma predictiu utilitzat des de fa molts anys en l'enginyeria. Per tant, aquesta tesi té com a objectiu desenvolupar models predictius basats en indicadors de diagnòstic de patologies cardiovasculars. Tractem de predir l'evolució de l'aneurisma d'aorta abdominal, la coartació aòrtica i la malaltia coronària de forma personalitzada per a cada pacient. Per entendre com la patologia cardiovascular evolucionarà i quan suposarà un risc per a la salut, cal desenvolupar noves tecnologies mitjançant la combinació de les imatges mèdiques i la ciència computacional. Proposem uns indicadors que poden millorar el diagnòstic i predir l'evolució de la malaltia de manera més eficient que els mètodes utilitzats fins ara. En particular, es proposa una nova metodologia per al càlcul dels indicadors de diagnòstic basada en l'hemodinàmica computacional i les imatges mèdiques. Hem treballat amb dades de pacients anònims per crear una tecnologia predictiva real que ens permetrà seguir avançant en la medicina personalitzada i generar sistemes de salut més sostenibles. Però el nostre objectiu final és aconseguir un impacte en l¿àmbit clínic. Diversos grups han tractat de crear models predictius per a les patologies cardiovasculars, però encara no han començat a utilitzar-les en la pràctica clínica. El nostre objectiu és anar més enllà i obtenir variables predictives que es puguin utilitzar de forma pràctica en el camp clínic. Es pot preveure que en el futur tots els metges disposaran de bases de dades molt precises de tota la nostra anatomia i fisiologia. Aquestes dades es poden utilitzar en els models predictius per millorar el diagnòstic o per millorar teràpies o tractaments personalitzats.Postprint (published version

    Optimization of CT scanning protocol of Type B aortic dissection follow-up through 3D printed model

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    This research aims to develop and evaluate a human tissue-like material 3D printed model used as a phantom in determining optimized scanning parameters to reduce the radiation dose for Type B aortic dissection patients after thoracic endovascular aortic repair. The results show that radiation risk for follow-up Type B aortic dissection patients can be potentially reduced. Further, the value of using 3D printed model in studying CT scanning protocols was further validated

    Tuning of boundary conditions parameters for hemodynamics simulation using patient data

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    This thesis describes an engineering workflow, which allows specification of boundary conditions and 3D simulation based on clinically available patient-specific data. A review of numerical models used to describe the cardiovascular system is provided, with a particular focus on the clinical target disease chosen for the toolkit, aortic coarctation. Aorta coarctation is the fifth most common congenital heart disease, characterized by a localized stenosis of the descending thoracic aorta. Current diagnosis uses invasive pressure measurement with rare but potential complications. The principal objective of this work was to develop a tool that can be translated into the clinic, requiring minimum operator input and time, capable of returning meaningful results from data typically acquired in clinical practice. Linear and nonlinear 1D modelling approaches are described, tested against full 3D solutions derived for idealized geometries of increasing complexityand for a patient-specific aortic coarctation. The 1D linear implementation is able to represent the fluid dynamic in simple idealized benchmarks with a limited effort in terms of computational time, but in a more complex case, such as a mild aortic coarctation, it is unable to predict well 3D fluid dynamic features. On the other side, the 1D nonlinear implementation showed a good agreement when compared to 3D pressure and flow waveforms, making it suitable to estimate outflow boundary conditions for subject-specific models. A cohort of 11 coarctation patients was initially used for a preliminary analysis using 0D models of increasing complexity to examine parameters derived when tuning models of the peripheral circulation. The first circuit represents the aortic coarctation as a nonlinear resistance, using the Bernoulli pressure drop equation, without considering the effect of downstream circulation. The second circuit include a peripheral resistance and compliance, and separate ascending and descending aortic pressure responses. In the third circuit a supra-aortic Windkessel model was added in order to include the supra-aortic circulation. The analysis detailed represents a first attempt to assess the interaction between local aortic haemodynamics and subject-specific parameterization of windkessel representations of the peripheral and supra-aortic circulation using clinically measured data. From the analysis of these 0D models, it is clear that the significance of the coarctation becomes less from the simple two resistance model to the inclusion of both the peripheral and supra-aortic circulation. These results provide a context within which to interpret outcomes of the tuning process reported for a more complex model of aortic haemodynamics using 1D and 3D model approaches. Earlier developments are combined to enable a multi-scale modelling approach to simulate fluid-dynamics. This includes non-linear 1D models to derive patient-specific parameters for the peripheral and supra-aortic circulation followed by transient analysis of a coupled 3D/0D system to estimate the coarctation pressure augmentation. These predictions are compared with invasively measured catheter data and the influence of uncertainty in measured data on the tuning process is discussed. This study has demonstrated the feasibility of constructing a workflow using non-invasive routinely collected clinical data to predict the pressure gradient in coarctation patients using patient specific CFD simulation, with relatively low levels of user interaction required. The results showed that the model is not suitable for the clinical use at this stage, thus further work is required to enhance the tuning process to improve agreement with measured catheter data. Finally, a preliminary approach for the assessment of change in haemodynamics following coarctation repair, where the coarctation region is enlarged through a virtual intervention process. The CFD approach reported can be expanded to explore the sensitivity of the peak ascending aortic pressure and descending aortic flow to the aortic diameter achieved following intervention, such an analysis would provide guidance for surgical intervention to target the optimal diameter to restore peripheral perfusion and reduce cerebral hypertension

    Deep Learning-based Automated Aortic Area and Distensibility Assessment: The Multi-Ethnic Study of Atherosclerosis (MESA)

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    This study applies convolutional neural network (CNN)-based automatic segmentation and distensibility measurement of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging (PC-cine MRI) within the large MESA cohort with subsequent assessment on an external cohort of thoracic aortic aneurysm (TAA) patients. 2D PC-cine MRI images of the ascending and descending aorta at the pulmonary artery bifurcation from the MESA study were included. Train, validation, and internal test sets consisted of 1123 studies (24282 images), 374 studies (8067 images), and 375 studies (8069 images), respectively. An external test set of TAAs consisted of 37 studies (3224 images). A U-Net based CNN was constructed, and performance was evaluated utilizing dice coefficient (for segmentation) and concordance correlation coefficients (CCC) of aortic geometric parameters by comparing to manual segmentation and parameter estimation. Dice coefficients for aorta segmentation were 97.6% (CI: 97.5%-97.6%) and 93.6% (84.6%-96.7%) on the internal and external test of TAAs, respectively. CCC for comparison of manual and CNN maximum and minimum ascending aortic areas were 0.97 and 0.95, respectively, on the internal test set and 0.997 and 0.995, respectively, for the external test. CCCs for maximum and minimum descending aortic areas were 0.96 and 0. 98, respectively, on the internal test set and 0.93 and 0.93, respectively, on the external test set. We successfully developed and validated a U-Net based ascending and descending aortic segmentation and distensibility quantification model in a large multi-ethnic database and in an external cohort of TAA patients.Comment: 25 pages, 5 figure

    Dynamic motion analysis of aorta : image processing methods for MDCT and Cine-MR image

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    Dept. of Biomedical Engineering/박사This dissertation was to study on image processing method for dynamic motion analysis of aorta using sequential images. The visualization of blood vessel motion and imaging protocols for cross-sectional aorta images are proposed.To accomplish assess the aorta motion, muti-steps image processing strategy was applied. First, the image pre-processing was applied to image enlargement and segmentation of aorta. Second, the intensity profile of aorta was used for wall boundary extraction. Third, semi-automatic extraction of target aorta boundary tracing over first frame is then automatically tracked throughout the image frames. The visualization of aorta motion in the sequential images provides a quantitative source of their motion in space. In order to visualize the blood vessel wall motion, velocity vector mapping was applied to the sequential images. It provided the information of aorta wall movement velocity and aortic displacement.To evaluate the proposed methods, clinical validation have been designed using MDCT and Cine-MR images.The aortic wall movement property, the movement profiles on aorta calcification, aortic displacement, and relations between wall movement and age were assessed using MDCT images. The number of subjects (14 men, 16 women; mean age, 55.9 ± 14.99 years; range, 31-80 years) were 30 and have valvular heart disease. The correlation between wall movement at three different position of thoracic aorta and entire study population group was -0.63 (p < 0.001), -0.51 (p < 0.05) and -0.45 (p < 0.05) respectively. The profiles of wall variation in aorta calcification indicate dyssynchoronous aorta expansion. The clusters which are include the calcification point showed low variation throughout the image samples.The aortic wall movement of Turner syndrome group were also assessed using Cine-MR images. The number of subjects (17 women; mean age, 21.6 ± 6.6 years; range, 11-38 years) were 17. The wall movement data of total subjects were presented as mean ± standard deviation. The movement of descending aorta at three different position were 0.79 ± 0.25, 0.59 ± 0.15 and 0.53 ± 0.15 respectively.There was a significant decrease of the aortic wall motion at all thoracic levels throughout the ages. Although specific assessment of vascular aging was not available for the diseased subjects, a potential distinction on the aorta aging at the different ages was possible.In contrast to the ascending aorta, the descending segments presented a significantly lesser magnitude of displacement and appear rather fixed at their thoracic position.The results of this dissertation provide the fundamental characteristics of blood vessel motion and could be used not only clinical researches also clinical applications, such as vascular aging, assessment of vascular disease, and early detection of vascular abnormalityope
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