Cardiac multiscale bioimaging is an emerging field that aims to provide a comprehensive understanding of the heart and its functions at various levels, from the molecular to the entire organ. It combines both physiologically and clinically relevant dimensions: from nano- and micrometer resolution imaging based on vibrational spectroscopy and high-resolution microscopy to assess molecular processes in cardiac cells and myocardial tissue, to mesoscale structural investigations to improve the understanding of cardiac (patho)physiology. Tailored super-resolution deep microscopy with advanced proteomic methods and hands-on experience are thus strategically combined to improve the quality of cardiovascular research and support future medical decision-making by gaining additional biomolecular information for translational and diagnostic applications.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.tibtech.2023.08.007 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
MFF-Net: A Lightweight Multi-Frequency Network for Measuring Heart Rhythm from Facial Videos.
Sensors (Basel)
December 2024
College of Electrical Engineering, Sichuan University, Chengdu 610065, China.
Remote photo-plethysmography (rPPG) is a useful camera-based health motioning method that can measure the heart rhythm from facial videos. Many well-established deep learning models can provide highly accurate and robust results in measuring heart rate (HR) and heart rate variability (HRV). However, these methods are unable to effectively eliminate illumination variation and motion artifact disturbances, and their substantial computational resource requirements significantly limit their applicability in real-world scenarios.
View Article and Find Full Text PDFDeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation.
Diagnostics (Basel)
December 2024
Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia.
Background: Cardiac magnetic resonance imaging (MRI) plays a crucial role in monitoring disease progression and evaluating the effectiveness of treatment interventions. Cardiac MRI allows medical practitioners to assess cardiac function accurately by providing comprehensive and quantitative information about the structure and function, hence making it an indispensable tool for monitoring the disease and treatment response. Deep learning-based segmentation enables the precise delineation of cardiac structures including the myocardium, right ventricle, and left ventricle.
View Article and Find Full Text PDFCellular EMT-status governs contact guidance in an electrospun TACS-mimicking model.
Mater Today Bio
February 2025
Pharmaceutical Technology and Biopharmaceutics, Department of Pharmacy, Ludwig-Maximilians-University München, Munich, Germany.
In this study, an advanced nanofiber breast cancer model was developed and systematically characterized including physico-chemical, cell-biological and biophysical parameters. Using electrospinning, the architecture of tumor-associated collagen signatures (TACS5 and TACS6) was mimicked. By employing a rotating cylinder or static plate collector set-up, aligned fibers (TACS5-like structures) and randomly orientated fibers (TACS6-like structures) fibers were produced, respectively.
View Article and Find Full Text PDF3D CT to 2D X-ray image registration for improved visualization of tibial vessels in endovascular procedures.
Int J Comput Assist Radiol Surg
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
Article Synopsis
- The study aims to improve visualization of arteries during endovascular procedures for peripheral artery disease by using an image registration technique that fuses X-ray and CT angiography images.
- The method involved aligning digital images based on the positions of the bones and achieved successful registration in most cases, with accurate alignment of less than 1 mm in distance.
- The results indicate that this technique is clinically viable for guiding interventions, as it allows for early detection of potential complications like guidewire perforations while maintaining a reasonable processing time.
Flow-Based Coronary Artery Bypass Graft Patency Metrics: Uncertainty Quantification Simulations to Guide Development.
Cardiovasc Eng Technol
January 2025
Transonic Systems Inc., 34 Dutch Mill Road, Ithaca, New York, 14850, USA.
Purpose: Over time, transit time flow measurement (TTFM) has proven itself as a simple and effective tool for intra-operative evaluation of coronary artery bypass grafts (CABGs). However, metrics used to screen for possible technical error show considerable spread, preventing the definition of sharp cut-off values to distinguish between patent, questionable, and failed grafts. The simulation study presented in this paper aims to quantify this uncertainty for commonly used patency metrics, and to identify the most important physiological parameters influencing it.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!