Novel and facile criterion to assess the accuracy of WSS estimation by 4D flow MRI

Cardiovascular hardware simulator and artificial aorta-generated central blood pressure waveform database according to various vascular ages for cardiovascular health monitoring applications

This study presents a database of central blood pressure waveforms according to cardiovascular health conditions, to supplement the lack of clinical data in cardiovascular health research, constructed by a cardiovascular simulator. Blood pressure (BP) is the most frequently measured biomarker, and in addition to systolic and diastolic pressure, its waveform represents the various conditions of cardiovascular health. A BP waveform is formed by overlapping the forward and reflected waves, which are affected by the pulse wave velocity (PWV). The increase in vascular stiffness with aging increases PWV, and the PWV-age distribution curve is called vascular age. For cardiovascular health research, extensive data of central BP waveform is essential, but the clinical data published so far are insufficient and imbalanced in quantity and quality. This study reproduces the central BP waveform using a cardiovascular hardware simulator and artificial aortas, which mimic the physiological structure and properties of the human. The simulator can adjust cardiovascular health conditions to the same level as humans, such as heart rate of 40-100 BPM, stroke volume of 40-100 mL, and peripheral resistance of 12 steps. Also, 6 artificial aortas with vascular ages in the 20-70 were fabricated to reproduce the increase in vascular stiffness due to aging. Vascular age calculated from measured stiffness of artificial aorta and central BP waveform showed an error of less than 3 years from the clinical value. Through this, a total of 636 waveforms were created to construct a central BP waveform database according to controlled various cardiovascular health conditions.

STANet: Spatio-Temporal Adaptive Network and Clinical Prior Embedding Learning for 3D+T CMR Segmentation

The segmentation of cardiac structure in magnetic resonance images (CMR) is paramount in diagnosing and managing cardiovascular illnesses, given its 3D+Time (3D+T) sequence. The existing deep learning methods are constrained in their ability to 3D+T CMR segmentation, due to: (1) Limited motion perception. The complexity of heart beating renders the motion perception in 3D+T CMR, including the long-range and cross-slice motions. The existing methods' local perception and slice-fixed perception directly limit the performance of 3D+T CMR perception. (2) Lack of labels. Due to the expensive labeling cost of the 3D+T CMR sequence, the labels of 3D+T CMR only contain the end-diastolic and end-systolic frames. The incomplete labeling scheme causes inefficient supervision. Hence, we propose a novel spatio-temporal adaptation network with clinical prior embedding learning (STANet) to ensure efficient spatio-temporal perception and optimization on 3D+T CMR segmentation. (1) A spatio-temporal adaptive convolution (STAC) treats the 3D+T CMR sequence as a whole for perception. The long-distance motion correlation is embedded into the structural perception by learnable weight regularization to balance long-range motion perception. The structural similarity is measured by cross-attention to adaptively correlate the cross-slice motion. (2) A clinical prior embedding learning strategy (CPE) is proposed to optimize the partially labeled 3D+T CMR segmentation dynamically by embedding clinical priors into optimization. STANet achieves outstanding performance with Dice of 0.917 and 0.94 on two public datasets (ACDC and STACOM), which indicates STANet has the potential to be incorporated into computer-aided diagnosis tools for clinical application.

Clinical application of four-dimensional flow cardiovascular magnetic resonance in Marfan syndrome: A systematic review and meta-analysis

This study aims to fill this gap by assessing the application of 4D flow CMR in MFS through a systematic review and meta-analysis. We conducted a comprehensive search of databases from their inception to May 1, 2023. Eligibility criteria were established based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS), with studies scoring above five deemed high quality. Meta-analyses were performed using Stata 15.1 software. Nine studies were analyzed. Findings indicate MFS patients had increased vortex flow in the descending aorta (DAo), larger aortic root diameter (ARD) and Z-scores, lower inner wall shear stress (WSS) in the proximal descending aorta (pDAo), reduced in-plane rotational flow (IRF) in the aortic arch and proximal descending aorta (pDAo), and increased pulse wave velocity (PWV) in the ascending aorta (AAo) and DAo compared to healthy subjects. No significant difference in systolic flow reversal ratio was observed. Sensitivity analysis showed no heterogeneity and Egger's test revealed no publication bias. This meta-analysis underscores the effectiveness of 4D flow CMR in detecting MFS, particularly through indicators such as vortex flow, WSS, IRF, ARD, and PWV. The findings provide insights into diagnosing cardiovascular diseases and predicting cardiovascular events in MFS patients. Further case-control studies are needed to establish measurement standards and explore potential indicators for improved diagnosis and treatment of MFS.

Correct Closure of the Left Atrial Appendage Reduces Stagnant Blood Flow and the Risk of Thrombus Formation: A Proof-of-Concept Experimental Study Using 4D Flow Magnetic Resonance Imaging

OBJECTIVE

The study was conducted to investigate the effect of correct occlusion of the left atrial appendage (LAA) on intracardiac blood flow and thrombus formation in patients with atrial fibrillation (AF) using four-dimensional (4D) flow magnetic resonance imaging (MRI) and three-dimensional (3D)-printed phantoms.

MATERIALS AND METHODS

Three life-sized 3D-printed left atrium (LA) phantoms, including a pre-occlusion (i.e., before the occlusion procedure) model and correctly and incorrectly occluded post-procedural models, were constructed based on cardiac computed tomography images from an 86-year-old male with long-standing persistent AF. A custom-made closed-loop flow circuit was set up, and pulsatile simulated pulmonary venous flow was delivered by a pump. 4D flow MRI was performed using a 3T scanner, and the images were analyzed using MATLAB-based software (R2020b; Mathworks). Flow metrics associated with blood stasis and thrombogenicity, such as the volume of stasis defined by the velocity threshold (|V̅| < 3 cm/s), surface-and-time-averaged wall shear stress (WSS), and endothelial cell activation potential (ECAP), were analyzed and compared among the three LA phantom models.

RESULTS

Different spatial distributions, orientations, and magnitudes of LA flow were directly visualized within the three LA phantoms using 4D flow MRI. The time-averaged volume and its ratio to the corresponding entire volume of LA flow stasis were consistently reduced in the correctly occluded model (70.82 mL and 39.0%, respectively), followed by the incorrectly occluded (73.17 mL and 39.0%, respectively) and pre-occlusion (79.11 mL and 39.7%, respectively) models. The surface-and-time-averaged WSS and ECAP were also lowest in the correctly occluded model (0.048 Pa and 4.004 Pa^-1 , respectively), followed by the incorrectly occluded (0.059 Pa and 4.792 Pa^-1 , respectively) and pre-occlusion (0.072 Pa and 5.861 Pa^-1 , respectively) models.

CONCLUSION

These findings suggest that a correctly occluded LAA leads to the greatest reduction in LA flow stasis and thrombogenicity, presenting a tentative procedural goal to maximize clinical benefits in patients with AF.