Echocardiography

The book "Echocardiography - New Techniques" brings worldwide contributions from highly acclaimed clinical and imaging science investigators, and representatives from academic medical centers. Each chapter is designed and written to be accessible to those with a basic knowledge of echocardiography. Additionally, the chapters are meant to be stimulating and educational to the experts and investigators in the field of echocardiography. This book is aimed primarily at cardiology fellows on their basic echocardiography rotation, fellows in general internal medicine, radiology and emergency medicine, and experts in the arena of echocardiography. Over the last few decades, the rate of technological advancements has developed dramatically, resulting in new techniques and improved echocardiographic imaging. The authors of this book focused on presenting the most advanced techniques useful in today's research and in daily clinical practice. These advanced techniques are utilized in the detection of different cardiac pathologies in patients, in contributing to their clinical decision, as well as follow-up and outcome predictions. In addition to the advanced techniques covered, this book expounds upon several special pathologies with respect to the functions of echocardiography

Left Ventricular Border Tracking Using Cardiac Motion Models and Optical Flow

The use of automated methods is becoming increasingly important for assessing cardiac function quantitatively and objectively. In this study, we propose a method for tracking three-dimensional (3-D) left ventricular contours. The method consists of a local optical flow tracker and a global tracker, which uses a statistical model of cardiac motion in an optical-flow formulation. We propose a combination of local and global trackers using gradient-based weights. The algorithm was tested on 35 echocardiographic sequences, with good results (surface error: 1.35 ± 0.46 mm, absolute volume error: 5.4 ± 4.8 mL). This demonstrates the method’s potential in automated tracking in clinical quality echocardiograms, facilitating the quantitative and objective assessment of cardiac functio

Developing Ultrasound-Based Computer-Aided Diagnostic Systems Through Statistical Pattern Recognition

Computer-aided diagnosis (CAD) is the use of a computer software to help physicians having a better interpretation of medical images. CAD systems can be viewed as pattern recognition algorithms that identify suspicious signs on a medical image and complement physicians' judgments, by reducing inter-/intra-observer variability and subjectivity. The proposed CAD systems in this thesis have been designed based on the statistical approach to pattern recognition as the most successfully used technique in practice. The main focus of this thesis has been on designing (new) feature extraction and classification algorithms for ultrasound-based CAD purposes. Ultrasound imaging has a broad range of usage in medical applications because it is a safe device which does not use harmful ionizing radiations, it provides clinicians with real-time images, it is portable and relatively cheap. The thesis was concerned with developing new ultrasound-based systems for the diagnosis of prostate cancer (PCa) and myocardial infarction (MI) where these issues have been addressed in two separate parts. In the first part, 1) a new CAD system was designed for prostate cancer biopsy by focusing on handling uncertainties in labels of the ground truth data, 2) the appropriateness of the independent component analysis (ICA) method for learning features from radiofrequency (RF) signals, backscattered from prostate tissues, was examined and, 3) a new ensemble scheme for learning ICA dictionaries from RF signals, backscattered from a tissue mimicking phantom, was proposed. In the second part, 1) principal component analysis (PCA) was used for the statistical modeling of the temporal deformation patterns of the left ventricle (LV) to detect abnormalities in its regional function, 2) a spatio-temporal representation of LV function based on PCA parameters was proposed to detect MI and, 3) a local-to-global statistical shape model based on PCA was presented to detect MI

Shear wave echocardiography

In this thesis we demonstrate that the assessment of the diastolic function of the left ventricle withclassical echocardiography remain

Insights into cardiac remodelling by multi-modal magnetic resonance imaging and spectroscopy

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Dilated Cardiomyopathy. From Genetics to Clinical Management

The current definition of dilated cardiomyopathy (DCM) is relatively simple: it is a heart muscle disease characterized by left ventricular (LV) or biventricular dilation and systolic dysfunction in the absence of either pressure or volume overload or coronary artery disease sufficient enough to explain the dysfunction. In the last 30 years, prognosis of patients with DCM has dramatically been improved with few similarities in the history of cardiology and medicine. Typically, in the 1980s, the average survival rate was approximately 50% in a 5-year follow-up. Nowadays, at 10 years of follow-up, the survival/free from heart transplant rate is far beyond 85%, and the projection of this improvement is significantly better for those who have had DCM diagnosed in the late 2010s. This improvement in outcomes is fundamentally due to a better characterization of etiological factors, medical management for heart failure, and device treatment, like the implantable cardioverter defibrillator (ICD), for sudden cardiac death prevention. However, other milestones should be recognized for the improvement in the survival rate, namely, the early diagnosis due to familial and sport-related screening, which allow detection of DCM at a less severe stage, and the uninterrupted, active, and individualized long-term follow-up with continuous reevaluation of the disease and re-stratification of the risk

Novel insights in cardiac imaging to evaluate disease progression and mechanisms in cardiac amyloidosis

Introduction: Systemic amyloidosis is characterised by the extracellular deposition of amyloid fibrils that misfold and aggregate causing disease when accumulation is sufficient to disrupt the structure and integrity of affected organs. Cardiac involvement causes a restrictive cardiomyopathy and determines prognosis. / Aims: My aims were 1) To assess the echocardiographic phenotype of patients with transthyretin (ATTR) cardiomyopathy and evaluate determinants of prognosis at baseline 2) To describe the echocardiographic progression in patients with ATTR cardiomyopathy over serial assessment 3) To assess the role of cardiac magnetic resonance (CMR)-derived extracellular volume (ECV) mapping to detect and estimate extra-cardiac amyloid load against Serum Amyloid P (SAP) scintigraphy 4) To assess the presence and mechanisms of myocardial ischaemia using stress perfusion CMR. / Results and Conclusions: Results demonstrate that 1) At baseline echocardiographic assessment in ATTR cardiomyopathy, stroke volume index, right atrial area index, longitudinal strain, E/e’ and severe aortic stenosis were independently associated with mortality. Compared to other genotypes, patients with V122I-associated ATTR cardiomyopathy had the most severe degree of dysfunction. 2) Worsening in the degree of mitral and tricuspid regurgitation at 12 and-24 months was associated with worse prognosis by echocardiography, and patients with V122-associated ATTR cardiomyopathy had more rapid progression when compared to other genotypes. 3) CMR derived ECV mapping shows high diagnostic performance to detect splenic and hepatic amyloid deposits with good correlation between ECV and amyloid load assessed by SAP scintigraphy. 4) Myocardial blood flow assessed by stress perfusion CMR is severely reduced in patients with cardiac amyloidosis and histological analysis of endomyocardial tissue shows evidence of hypoxia, vascular infiltration and capillary rarefaction. In conclusion, these results demonstrate that imaging in cardiac amyloidosis has an important role in optimising diagnosis, tracking individual changes over time and characterising amyloid organ involvement

Use of advanced echocardiography imaging techniques in the critically ill

Background: Critical care echocardiography has become standard of care in the ICU. New technologies have been developed and have shown potential clinical utility to elucidate myocardial dysfunction not seen with conventional imaging. We sought to determine the feasibility and potential clinical benefit of these techniques in common situations seen in the ICU. Hypothesis: Advanced echo techniques would be feasible in the majority of critically ill patients and have prognostic significance, clinical utility and diagnose cardiac abnormalities, potentially in a more sensitive manner than conventional techniques. Results: (a) Speckle tracking echocardiography (STE) Left ventricle and RV analysis with STE was feasibly in ~80% of patients. More dysfunction was found using STE vs conventional analysis. RV dysfunction assessed by STE held significant prognostic relevance in those with septic shock and highlighted subtle dysfunction induced by mechanical ventilation, both in animal and human studies. (b) 3D transthoracic echocardiography (3D TTE) Despite finding 3D TTE feasible in mechanically ventilated ICU patients (LV 72% and RV 55%), it lacked necessary low variability and high precision vs standard measures. (c) Myocardial contrast perfusion echocardiography (MCPE) Assessing acute coronary artery occlusion in the ICU patient is challenging. Troponin elevation, acute ECG changes, regional wall motion analysis on echo and overall clinical acumen often lack diagnostic capabilities. MCPE was found to be feasible in the critically ill and had better association predicting acute coronary artery occlusion vs clinical acumen alone. Conclusions: STE, 3D TTE and MCPE are feasible in the majority of ICU patients. STE may show dysfunction not recognised by conventional imaging. 3D TTE for volumetric analysis is likely not suitable for clinical use at this stage. MCPE may help guide interventions in acute coronary artery occlusion

Left atrial trajectory impairment in hypertrophic cardiomyopathy disclosed by geometric morphometrics and parallel transport

The analysis of full Left Atrium (LA) deformation and whole LA deformational trajectory in time has been poorly investigated and, to the best of our knowledge, seldom discussed in patients with Hypertrophic Cardiomyopathy. Therefore, we considered 22 patients with Hypertrophic Cardiomyopathy (HCM) and 46 healthy subjects, investigated them by three-dimensional Speckle Tracking Echocardiography, and studied the derived landmark clouds via Geometric Morphometrics with Parallel Transport. Trajectory shape and trajectory size were different in Controls versus HCM and their classification powers had high AUC (Area Under the Receiving Operator Characteristic Curve) and accuracy. The two trajectories were much different at the transition between LA conduit and booster pump functions. Full shape and deformation analyses with trajectory analysis enabled a straightforward perception of pathophysiological consequences of HCM condition on LA functioning. It might be worthwhile to apply these techniques to look for novel pathophysiological approaches that may better define atrio-ventricular interaction

Multidimensional embedded MEMS motion detectors for wearable mechanocardiography and 4D medical imaging

Background: Cardiovascular diseases are the number one cause of death. Of these deaths, almost 80% are due to coronary artery disease (CAD) and cerebrovascular disease. Multidimensional microelectromechanical systems (MEMS) sensors allow measuring the mechanical movement of the heart muscle offering an entirely new and innovative solution to evaluate cardiac rhythm and function. Recent advances in miniaturized motion sensors present an exciting opportunity to study novel device-driven and functional motion detection systems in the areas of both cardiac monitoring and biomedical imaging, for example, in computed tomography (CT) and positron emission tomography (PET). Methods: This Ph.D. work describes a new cardiac motion detection paradigm and measurement technology based on multimodal measuring tools — by tracking the heart’s kinetic activity using micro-sized MEMS sensors — and novel computational approaches — by deploying signal processing and machine learning techniques—for detecting cardiac pathological disorders. In particular, this study focuses on the capability of joint gyrocardiography (GCG) and seismocardiography (SCG) techniques that constitute the mechanocardiography (MCG) concept representing the mechanical characteristics of the cardiac precordial surface vibrations. Results: Experimental analyses showed that integrating multisource sensory data resulted in precise estimation of heart rate with an accuracy of 99% (healthy, n=29), detection of heart arrhythmia (n=435) with an accuracy of 95-97%, ischemic disease indication with approximately 75% accuracy (n=22), as well as significantly improved quality of four-dimensional (4D) cardiac PET images by eliminating motion related inaccuracies using MEMS dual gating approach. Tissue Doppler imaging (TDI) analysis of GCG (healthy, n=9) showed promising results for measuring the cardiac timing intervals and myocardial deformation changes. Conclusion: The findings of this study demonstrate clinical potential of MEMS motion sensors in cardiology that may facilitate in time diagnosis of cardiac abnormalities. Multidimensional MCG can effectively contribute to detecting atrial fibrillation (AFib), myocardial infarction (MI), and CAD. Additionally, MEMS motion sensing improves the reliability and quality of cardiac PET imaging.Moniulotteisten sulautettujen MEMS-liiketunnistimien käyttö sydänkardiografiassa sekä lääketieteellisessä 4D-kuvantamisessa Tausta: Sydän- ja verisuonitaudit ovat yleisin kuolinsyy. Näistä kuolemantapauksista lähes 80% johtuu sepelvaltimotaudista (CAD) ja aivoverenkierron häiriöistä. Moniulotteiset mikroelektromekaaniset järjestelmät (MEMS) mahdollistavat sydänlihaksen mekaanisen liikkeen mittaamisen, mikä puolestaan tarjoaa täysin uudenlaisen ja innovatiivisen ratkaisun sydämen rytmin ja toiminnan arvioimiseksi. Viimeaikaiset teknologiset edistysaskeleet mahdollistavat uusien pienikokoisten liiketunnistusjärjestelmien käyttämisen sydämen toiminnan tutkimuksessa sekä lääketieteellisen kuvantamisen, kuten esimerkiksi tietokonetomografian (CT) ja positroniemissiotomografian (PET), tarkkuuden parantamisessa. Menetelmät: Tämä väitöskirjatyö esittelee uuden sydämen kineettisen toiminnan mittaustekniikan, joka pohjautuu MEMS-anturien käyttöön. Uudet laskennalliset lähestymistavat, jotka perustuvat signaalinkäsittelyyn ja koneoppimiseen, mahdollistavat sydämen patologisten häiriöiden havaitsemisen MEMS-antureista saatavista signaaleista. Tässä tutkimuksessa keskitytään erityisesti mekanokardiografiaan (MCG), joihin kuuluvat gyrokardiografia (GCG) ja seismokardiografia (SCG). Näiden tekniikoiden avulla voidaan mitata kardiorespiratorisen järjestelmän mekaanisia ominaisuuksia. Tulokset: Kokeelliset analyysit osoittivat, että integroimalla usean sensorin dataa voidaan mitata syketiheyttä 99% (terveillä n=29) tarkkuudella, havaita sydämen rytmihäiriöt (n=435) 95-97%, tarkkuudella, sekä havaita iskeeminen sairaus noin 75% tarkkuudella (n=22). Lisäksi MEMS-kaksoistahdistuksen avulla voidaan parantaa sydämen 4D PET-kuvan laatua, kun liikeepätarkkuudet voidaan eliminoida paremmin. Doppler-kuvantamisessa (TDI, Tissue Doppler Imaging) GCG-analyysi (terveillä, n=9) osoitti lupaavia tuloksia sydänsykkeen ajoituksen ja intervallien sekä sydänlihasmuutosten mittaamisessa. Päätelmä: Tämän tutkimuksen tulokset osoittavat, että kardiologisilla MEMS-liikeantureilla on kliinistä potentiaalia sydämen toiminnallisten poikkeavuuksien diagnostisoinnissa. Moniuloitteinen MCG voi edistää eteisvärinän (AFib), sydäninfarktin (MI) ja CAD:n havaitsemista. Lisäksi MEMS-liiketunnistus parantaa sydämen PET-kuvantamisen luotettavuutta ja laatua