Publications by authors named "Yuan Chun"

Motivation: In cine MRI, the measurements within each timeframe alone are too noisy for image reconstruction. Some information must be 'borrowed' from other time frames and the reconstruction algorithm is a slow iterative procedure.

Goals: We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction.

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Background: Carotid atherosclerosis is a major etiology of stroke. Although intraplaque hemorrhage (IPH) is known to increase stroke risk and plaque burden, its long-term effects on plaque dynamics remain unclear.

Objectives: This study aimed to evaluate the long-term impact of IPH on carotid plaque burden progression using deep learning-based segmentation on multi-contrast vessel wall imaging (VWI).

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Purpose: Embolic stroke of unidentified source (ESUS) represents 10-25% of all ischemic strokes. Our goal was to determine whether ESUS could be reclassified to cardioembolic (CE) or large-artery atherosclerosis (LAA) with machine learning (ML) using conventional clinical data.

Methods: We retrospectively collected conventional clinical features, including patient, imaging (MRI, CT/CTA), cardiac, and serum data from established cases of CE and LAA stroke, and factors with p < 0.

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PROPELLER MRI has been shown effective for rigid motion compensation, while the performance of existing PROPELLER reconstruction methods critically depend on selecting a proper reference blade. In this work, we proposed a robust implementation for PROPELLER reconstruction, which was incorporated with different reference selection methods, including single blade reference (SBR), combined blades reference (CBR), grouped blades reference (GBR) and Pipe et al.'s revised method, which requires no blade reference (NBR).

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An estimated 6.8 million people in the United States have an unruptured intracranial aneurysms, with approximately 30,000 people suffering from intracranial aneurysms rupture each year. Despite the development of population-based scores to evaluate the risk of rupture, retrospective analyses have suggested the limited usage of these scores in guiding clinical decision-making.

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Article Synopsis
  • * A new model was developed using a variational autoencoder framework, which incorporated a unique dissimilarity loss to enhance the model's ability to learn key MRI features and improve segmentation accuracy.
  • * The model outperformed nine existing methods in tests with 113 subjects, demonstrating significant improvements in various performance metrics for both segmentation and detection, suggesting it could greatly advance MRI analysis in clinical settings.
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The clinical significance of measuring vessel wall thickness is widely acknowledged. Recent advancements have enabled high-resolution 3D scans of arteries and precise segmentation of their lumens and outer walls; however, most existing methods for assessing vessel wall thickness are 2D. Despite being valuable, reproducibility and accuracy of 2D techniques depend on the extracted 2D slices.

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Purpose: Intraplaque haemorrhage (IPH) is a well-known risk factor for faster plaque progression (volume increase); however, its etiology is unclear. We aimed at determining what other local plaque- and systemic factors contribute to plaque progression and to the development and progression of IPH.

Methods: We examined 98 asymptomatic participants with carotid plaque using serial multi-contrast magnetic resonance imaging.

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Background And Purpose: The circle of Willis (COW) is a crucial mechanism for cerebral collateral circulation. This proof-of-concept study aims to develop and assess an analysis method to characterize the hemodynamics of the arterial segments in the COW by using arterial spin-labeling (ASL) based non-contrast-enhanced dynamic MR angiography (dMRA).

Materials And Methods: The developed analysis method uses a graph model, bootstrap strategy, and ensemble learning methodologies to determine the time curve shift from ASL dMRA to estimate the flow direction within the COW.

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Article Synopsis
  • Cardiovascular disease (CVD) is the top cause of illness and death worldwide, largely due to atherosclerosis, which affects about two-thirds of CVD patients.
  • Atherosclerosis develops over many years, offering a chance for preventive measures to avoid serious events like heart attacks and strokes, especially since early signs are seen in younger people.
  • There's a need for a shift in focus from treating advanced CVD to detecting it early; research should explore using precision medicine and biomarkers to identify atherosclerosis sooner and assess if this could lower healthcare costs globally.
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The development of layered metal sulfides with stable structure and accessible active sites is of great importance for sodium-ion batteries (SIBs). Herein, a simple liquid-mixing method is elaborately designed to immobilize WS nanoflakes on N-doped carbon (NC), then further coat carbon to produce WS/NC@C. In the formation process of this composite, the presence of NC not only avoids the overlap and improves the dispersion of WS nanoflakes, but also creates a connection network for charge transfer, where the wrapped carbon provides a stable chemical and electrochemical reaction interface.

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Background: Hypertension-induced impairment of the cerebral artery network contributes to cognitive impairment. Characterizing the structure and function of cerebral arteries may facilitate the understanding of hypertension-related pathological mechanisms and lead to the development of new indicators for cognitive impairment.

Purpose: To investigate the associations between morphological features of the intracranial arteries distal to the circle of Willis on time-of-flight MRA (TOF-MRA) and cognitive performance in a hypertensive cohort.

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Constructing quantum dot-scale metal sulfides with defects and strongly coupled with carbon is significant for advanced sodium-ion batteries (SIBs). Herein, Se substituted VS quantum dots with anionic defects confined in nitrogen-doped carbon matrix (VSSe/NC) are fabricated. Introducing element Se into VS crystal expands the interlayer distance of VS, and triggers anionic defects, which can facilitate Na diffusions and act as active sites for Na storage.

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Background: Progression of intracranial atherosclerotic disease (ICAD) is associated with ischemic stroke events and can be quantified with three-dimensional (3D) intracranial vessel wall (IVW) MRI. However, longitudinal 3D IVW studies are limited and ICAD evolution remains relatively unknown.

Purpose: To evaluate ICAD changes longitudinally and to characterize the imaging patterns of atherosclerotic plaque evolution.

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Cardiac Magnetic Resonance Imaging (CMRI) is a quantitative technique that enables non-invasive assessment of heart structure and contractile function as well as the mechanisms underlying cardiovascular disease. Here we provide step-by-step instructions and imaging protocols for conducting cardiac MRI exam on the patients with cardiomyopathies. Our imaging protocols are specific to the 3 Tesla magnetic field strength.

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Introduction: Carotid atherosclerotic plaque is an important independent risk factor for stroke. Apolipoprotein E (APOE) influences cholesterol levels and certain isoforms are associated with increased carotid atherosclerosis, though the exact association between APOE and carotid plaque is uncertain. The study aimed to evaluate the association between APOE and carotid plaque.

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The ingenious architectural structural engineering is extensively identified as a cogent means for facilitating the electrochemical properties of conversion-type anode materials for sodium-ion storage. Herein, a delicate, scalable and controllable solvent-free strategy is proposed to synthesize ultrafine MnO quantum dots embedded into N-doped carbon to generate two-dimensional (2D) composites (MNC) with robust interfacial heterostructural interactions for high sodium ion storage and fast reaction kinetics, which averts the use of solvents and environmental pollution, greatly reduces time and production costs. The introduction of metallic Mn species simultaneously achieves the construction of ultrafine MnO quantum dots and strong interfacial heterostructural COMn bonds between metal species and 2D N-doped carbon matrix.

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Purpose: This study aimed to investigate the associations of atherosclerotic plaque characteristics in intracranial and extracranial carotid arteries with severity of white matter hyperintensities (WMHs) in symptomatic patients using magnetic resonance (MR) imaging.

Method: Patients with cerebrovascular symptoms and carotid plaque were recruited from the cross-sectional, multicenter study of CARE-II. Luminal stenosis of intracranial and extracranial carotid arteries, carotid plaque compositional features, and WMHs were evaluated by brain structural and vascular MR imaging.

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Purpose: Polycystic ovarian syndrome (PCOS) is an endocrine-metabolic condition affecting 5-10% of reproductive-aged women and characterized by hyperandrogenism, insulin resistance (IR), and hyperinsulinemia. CFTR is known to be regulated by steroid hormones, and our previous study has demonstrated an essential role of CFTR in β-cell function. This study aims to investigate the contribution of androgen and CFTR to hypersecretion of insulin in PCOS and the underlying mechanism.

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Background: Carotid artery atherosclerosis is highly prevalent in the general population and is a well-established risk factor for acute ischemic stroke. Although the morphological characteristics of vulnerable plaques are well recognized, there is a lack of consensus in reporting and interpreting carotid plaque features.

Objectives: The aim of this paper is to establish a consistent and comprehensive approach for imaging and reporting carotid plaque by introducing the Plaque-RADS (Reporting and Data System) score.

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Purpose: Atherosclerotic plaques of carotid artery (CA) and middle cerebral artery (MCA) are important causes of acute ischemic stroke (AIS). This study was designed to jointly assess the plaque distribution and features of CA and MCA in AIS patients with pial infarction (PI) and perforating artery infarction (PAI), and to investigate the associations between plaque characteristics and ischemic infarction patterns.

Methods: Imaging data of sixty-five patients from a cross-sectional study were reviewed.

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With the increase in the number of image data and the lack of corresponding labels, weakly supervised learning has drawn a lot of attention recently in computer vision tasks, especially in the fine-grained semantic segmentation problem. To alleviate human efforts from expensive pixel-by-pixel annotations, our method focuses on weakly supervised semantic segmentation (WSSS) with image-level labels, which are much easier to obtain. As a considerable gap exists between pixel-level segmentation and image-level labels, how to reflect the image-level semantic information on each pixel is an important question.

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