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

Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use

Tissue tracking technology of routinely acquired cardiovascular magnetic resonance (CMR) cine acquisitions has increased the apparent ease and availability of non-invasive assessments of myocardial deformation in clinical research and practice. Its widespread availability thanks to the fact that this technology can in principle be applied on images that are part of every CMR or echocardiographic protocol. However, the two modalities are based on very different methods of image acquisition and reconstruction, each with their respective strengths and limitations. The image tracking methods applied are not necessarily directly comparable between the modalities, or with those based on dedicated CMR acquisitions for strain measurement such as tagging or displacement encoding. Here we describe the principles underlying the image tracking methods for CMR and echocardiography, and the translation of the resulting tracking estimates into parameters suited to describe myocardial mechanics. Technical limitations are presented with the objective of suggesting potential solutions that may allow informed and appropriate use in clinical applications

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Intravascular Ultrasound

Intravascular ultrasound (IVUS) is a cardiovascular imaging technology using a specially designed catheter with a miniaturized ultrasound probe for the assessment of vascular anatomy with detailed visualization of arterial layers. Over the past two decades, this technology has developed into an indispensable tool for research and clinical practice in cardiovascular medicine, offering the opportunity to gather diagnostic information about the process of atherosclerosis in vivo, and to directly observe the effects of various interventions on the plaque and arterial wall. This book aims to give a comprehensive overview of this rapidly evolving technique from basic principles and instrumentation to research and clinical applications with future perspectives

High-Frame-Rate Volumetric Porcine Renal Vasculature Imaging

Objective:The aim of this study was to assess the feasibility and imaging options of contrast-enhanced volumetric ultrasound kidney vasculature imaging in a porcine model using a prototype sparse spiral array. Methods: Transcutaneous freehand in vivo imaging of two healthy porcine kidneys was performed according to three protocols with different microbubble concentrations and transmission sequences. Combining high-frame-rate transmission sequences with our previously described spatial coherence beamformer, we determined the ability to produce detailed volumetric images of the vasculature. We also determined power, color and spectral Doppler, as well as super-resolved microvasculature in a volume. The results were compared against a clinical 2-D ultrasound machine. Results: Three-dimensional visualization of the kidney vasculature structure and blood flow was possible with our method. Good structural agreement was found between the visualized vasculature structure and the 2-D reference. Microvasculature patterns in the kidney cortex were visible with super-resolution processing. Blood flow velocity estimations were within a physiological range and pattern, also in agreement with the 2-D reference results. Conclusion:Volumetric imaging of the kidney vasculature was possible using a prototype sparse spiral array. Reliable structural and temporal information could be extracted from these imaging results.</p