A novel flow waveform partitioning method based on the HeartCon and its clinical application. [PDF]
Wang H, Lin G, Han Z, Liu X.
europepmc +1 more source
Abstact figure legend A panoramic 3D optical mapping system was developed, enabling imaging of action potential waves across the entire strongly deforming ventricular surface of beating isolated hearts. The system comprises 12 high‐speed cameras and a soccerball‐shaped imaging chamber with 48 light‐emitting diodes (LEDs).
Shrey Chowdhary +5 more
wiley +1 more source
An 11-Year-Old Athlete With Dynamic Stenosis of Coronary Artery Anomaly With Normal FFR-Dobutamine But Abnormal iFR-Dobutamine. [PDF]
Stark AW +7 more
europepmc +1 more source
Phase-targeting rapid cryofixation of the beating heart and histological analysis unveil contractile state-dependent sarcomere dynamics. [PDF]
Tamura S +8 more
europepmc +1 more source
Modelling Motion‐Induced Signal Corruption in Steady‐State Diffusion MRI
ABSTRACT Purpose Diffusion‐weighted steady‐state free precession (DW‐SSFP) is a diffusion imaging sequence achieving high SNR efficiency. A key challenge for in vivo DW‐SSFP is the sequence's severe motion sensitivity, currently limiting investigations to low or no motion regimes.
Benjamin C. Tendler +3 more
wiley +1 more source
Echocardiographic Evaluation of the Right Ventricular Thickness, Myocardial Visualization, and Fractional Area Change: The Impact of Contrast Agent and Transducer Selection. [PDF]
Park Y +5 more
europepmc +1 more source
ABSTRACT Purpose To demonstrate that a recently reported bright ferritin magnetic resonance imaging (MRI) platform can track transplanted human pluripotent stem cell (hPSC)‐derived cardiomyocytes (hPSC‐CMs) longitudinally and on‐demand in the rat heart.
Keyu Zhuang +12 more
wiley +1 more source
Cardiac phase modulates behavior and response related lateralization in visual spatial conflicts during change detection. [PDF]
von Haugwitz L, Wascher E, Larra MF.
europepmc +1 more source
ABSTRACT Purpose The aim of this study is to evaluate a deep variational network, FlowVN, for the reconstruction of heavily undersampled 4D Flow MRI across multiple sites. Methods FlowVN was trained on fully sampled 4D Flow MRI datasets of healthy volunteers from one site. The model was tested on retrospective undersampled data (R = 6–22) of six normal
Sohaib Ayaz Qazi +6 more
wiley +1 more source

