Magnetic Resonance Imaging of the Neonatal Cardiovascular System : Impact of Patent Ductus Arteriosus

The incidence of premature birth is increasing in absolute number and as a proportion of all births around the world. Many pathologies seen in this cohort are related to abnormal blood supply. Fetal and premature cardiovascular systems differ greatly as to maintain adequate blood flow to the developing organs in the uterine and extra-uterine environments require very different circulations. Subsequently following preterm birth the immature cardiovascular system undergoes abrupt adaptations, often resulting in the prolonged patency of the fetal shunt, ductus arteriosus. The impact of a patent ductus arteriosus (PDA) is poorly understood. However it is thought that large ductal shunt volumes may result in congestive cardiac failure and systemic hypo-­‐perfusion. Cardiac MRI has contributed greatly to the understanding of many cardiovascular diseases and congenital defects in paediatric and adult patients. Translating these imaging techniques to assess the preterm cardiovascular system requires careful optimization due to their condition, size and significantly increased heart rate. The work presented in this thesis employs multiple functional CMR techniques to investigate the preterm cardiovascular system in the presence and absence of PDA and the resultant cardiac function. A novel technique utilizing PC MRI to quantify PDA shunt volume and its impact on flow distribution is presented. Despite large shunt volumes, systemic circulation remained within normal range, although slight reduction is detectable when assessed at group level. Subsequently the impact of PDA and associated increased work load on left ventricular dimensions and function was then investigated using SSFP imaging. Results indicated that cardiac function was maintained even in the presence of large shunt volumes. Finally 4D PC sequences were employed to evaluate pulse wave velocity and flow regime within the preterm aorta, demonstrating the feasibility of hemodynamic assessment in this cohort. The findings of these studies provide insight into the impact of PDA. The reliable measurement and assessment of preterm cardiovascular system provides the potential to improve the understanding of the development and effects of certain pathologies seen in this cohort.Open Acces

Deep learning tools for outcome prediction in a trial fibrilation from cardiac MRI

Tese de mestrado integrado em Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica), Universidade de Lisboa, Faculdade de Ciências, 2021Atrial fibrillation (AF), is the most frequent sustained cardiac arrhythmia, described by an irregular and rapid contraction of the two upper chambers of the heart (the atria). AF development is promoted and predisposed by atrial dilation, which is a consequence of atria adaptation to AF. However, it is not clear whether atrial dilation appears similarly over the cardiac cycle and how it affects ventricular volumes. Catheter ablation is arguably the AF gold standard treatment. In their current form, ablations are capable of directly terminating AF in selected patients but are only first-time effective in approximately 50% of the cases. In the first part of this work, volumetric functional markers of the left atrium (LA) and left ventricle (LV) of AF patients were studied. More precisely, a customised convolutional neural network (CNN) was proposed to segment, across the cardiac cycle, the LA from short axis CINE MRI images acquired with full cardiac coverage in AF patients. Using the proposed automatic LA segmentation, volumetric time curves were plotted and ejection fractions (EF) were automatically calculated for both chambers. The second part of the project was dedicated to developing classification models based on cardiac MR images. The EMIDEC STACOM 2020 challenge was used as an initial project and basis to create binary classifiers based on fully automatic classification neural networks (NNs), since it presented a relatively simple binary classification task (presence/absence of disease) and a large dataset. For the challenge, a deep learning NN was proposed to automatically classify myocardial disease from delayed enhancement cardiac MR (DE-CMR) and patient clinical information. The highest classification accuracy (100%) was achieved with Clinic-NET+, a NN that used information from images, segmentations and clinical annotations. For the final goal of this project, the previously referred NNs were re-trained to predict AF recurrence after catheter ablation (CA) in AF patients using pre-ablation LA short axis in CINE MRI images. In this task, the best overall performance was achieved by Clinic-NET+ with a test accuracy of 88%. This work shown the potential of NNs to interpret and extract clinical information from cardiac MRI. If more data is available, in the future, these methods can potentially be used to help and guide clinical AF prognosis and diagnosis

Inflammatory cardiomyopathy - diagnosis and risk stratification in myocarditis

Background: Acute myocarditis remains a challenging clinical diagnosis with limited epidemiological data and poorly defined markers of adverse risk. We sought to build a better understanding of myocarditis epidemiology and to integrate clinical, genetic and advanced imaging data to generate new insights into myocarditis pathobiology. Methods and Results: (1) Evaluation of population-level hospital admission data from NHS England from 1998-2017 revealed a rising incidence of myocarditis, at least two-fold greater than that reported from pathological registries, most commonly amongst men with median age 36 years and women aged 46 years, with distinct peaks over Winter and the greatest burden in London. (2) Cardiovascular magnetic resonance (CMR) phenotype study of a 114 prospectively recruited patients with acute myocarditis demonstrated the natural history of changes in left ventricular parameters over 12 months and revealed a correlation between change in myocardial mechanics, specifically circumferential strain, and extent of myocardial oedema by T2 mapping (R=-0.70, p=0.01). (3) Genetic sequencing of 231 unrelated patients recruited with acute myocarditis revealed the presence of truncating variants in key cardiomyopathy genes in 4.8% of the cohort, particularly linked to arrhythmogenic ventricular cardiomyopathy (AVC) with significant enrichment compared with 1054 healthy volunteers indicating a potential overlap between myocarditis and AVC (odds ratio 8.2; 95% CI 2.4-28.3; p=0.001). (4) Retrospective long-term clinical outcome study of 401 patients with mid-wall/subepicardial late gadolinium enhancement (LGE) but otherwise normal LV volumes and function suggestive of healed myocarditis demonstrated a low risk of actual or aborted sudden cardiac death over a median follow-up of 4.3 years (incidence rate per 100 patient-years of 0.05%). (5) Psychological study of post-traumatic stress disorder amongst 231 patients with acute myocarditis compared with 44 patients with acute myocardial infarction highlighted the profound and long-lasting psychological morbidity associated uniquely with myocarditis. Conclusion: Myocarditis is a heterogeneous disease that remains vastly underestimated in prevalence. Integration of advanced CMR techniques with genomic data may provide incremental value in early diagnosis, non-invasive surveillance and identification of high-risk individuals who may benefit from a more personalised approach with close monitoring and targeted therapy.Open Acces

Sensing and Signal Processing in Smart Healthcare

In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included

The airway microbiota of stable COPD : Association with exacerbation frequency and the risks associated with bronchoscopic data collection

Background: Acute exacerbations of COPD are an important cause of mortality and morbidity in patients with COPD. It is incompletely understood why some COPD patients experience frequent exacerbations, while others rarely or never exacerbate. Studies have suggested that the microbiome of the lungs is different in patients with different exacerbation frequencies. Most studies use sputum samples prone to contamination from the upper airway. Bronchoscopic sampling could improve the quality of the samples, but is a more invasive approach. Aims: The overall aim of the PhD project is to investigate if the airway microbiota in subjects with stable COPD is associated with exacerbation frequency and to assess the complications and discomforts (including rates and predictors) associated with bronchoscopic data collection in participants with and without COPD. Materials and Methods: For the first paper, we performed a systematic literature search on complications and discomfort of non-therapeutic bronchoscopy in PubMed. Titles and abstracts of retrieved search hits were sorted according to inclusion and exclusion criteria. The second and third paper uses data collected in the Bergen COPD Microbiome Study (MicroCOPD). Individuals with and without COPD underwent bronchoscopy including protected bronchoalveolar lavage (BAL) (in participants with FEV1 >30% of predicted), protected specimen brushes (PSB), small volume lavage, and in 1/3 of bronchoscopies, endobronchial biopsies. In addition to bronchoscopic sampling, participants provided oral wash samples. For each bronchoscopic procedure, there was one negative control sample of the phosphate-buffered-saline used for the microbial samples. Some participants underwent more than one bronchoscopy. Light sedation with alfentanil was offered to participants. Immediate complications, defined as any event requiring an unplanned intervention or early termination of the procedure, were recorded. Participants were interviewed after a week regarding discomfort, respiratory symptoms and fever sensation. Participants with COPD were followed with telephone interviews every three months for one year regarding exacerbations. Microbial samples and negative controls went through laboratory processing including DNA extraction, PCR and sequencing of the 16S rRNA gene. Extensive bioinformatic processing of sequencing data and microbiota analyses were performed using QIIME2 and R. Pre-processing included bioinformatic identification and removal of contaminant sequences. We them compared bacterial taxonomy and alpha and beta diversity in individuals with and without COPD exacerbations in the follow-up. Results: Bronchoscopy is generally a safe procedure with low mortality and few severe complications, but the literature shows a wide range of specific complication rates, and it was not possible to conclude on discomfort or predictors. In MicroCOPD, 239 participants underwent bronchoscopy once, 61 underwent more than one bronchoscopy. Complications occurred in 25.9% of first bronchoscopies. The rate of potentially severe complications was 1.3%. Participants with COPD experienced more dyspnoea than participants without lung disease. Sedation and lower age were associated with less complications. 47.7% reported fever. Discomfort was associated with fever, dread of bronchoscopy, high COPD Assessment Test score, and never-smoking. Complications and fever in a first bronchoscopy were often predictive for complications and fever in a second bronchoscopy. We found no difference in alpha and beta diversity between participants with and without COPD exacerbations, and no ASV or genus was found to be consistently differentially abundant or distributed between the groups. Conclusions: Bronchoscopy is a generally safe procedure, even in research into COPD, but is not free of risk. Bronchoscopy was associated with frequent need for unplanned interventions, discomfort and fever sensation in MicroCOPD. We found no association between the lung microbiota at stable state and exacerbations of COPD.Doktorgradsavhandlin

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems