Combined Use of Multiple Intravascular Imaging Techniques in Acute Coronary Syndrome

Kubo, Takashi; Terada, Kosei; Ino, Yasushi; Shiono, Yasutsugu; Tu, Shengxian; Tsao, Tien-Ping; Chen, Yundai; Park, Duk‐Woo

doi:10.3389/fcvm.2021.824128

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…Another study comparing 40 MHz IVUS and OCT in patients with ACS showed a 40 and 73% incidence of PR identified by IVUS and OCT, respectively [ 34 ]. Conventional IVUS cannot determine the presence or absence of small ruptures owing to its coarse resolution; hence why this technique poorly identifies PE [ 35 ]. However, in patients with ascertained PE, OCT can be visualized using HD-IVUS [ 5 ].…”

Section: Discussionmentioning

confidence: 99%

“…IVUS has been the cornerstone of intracoronary imaging for

20 years and can provide information on plaque burden and remodeling. In contrast, OCT has advantages in detecting fibrous cap thickness and thrombus formation [ 4 ]. However, OCT has several limitations, such as the need for complete blood removal and the use of contrast agents, even in patients with chronic kidney disease; this sometimes precludes the assessment of the underlying mechanisms.…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic Performance of 60 MHz High-Definition Intravascular Ultrasound versus Fourier Domain Optical Coherence Tomography for Identifying Plaque Rupture, Plaque Erosion, and Thrombosis in a Rabbit Model

Wang¹,

Qiao²,

Xing³

et al. 2023

Rev. Cardiovasc. Med.

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Background: Most acute coronary syndromes occur due to coronary thrombosis caused by plaque rupture (PR) and plaque erosion (PE). Precise in vivo differentiation between PR and PE is challenging for intravascular imaging. This study is the first to determine the diagnostic performance of the novel 60 MHz high-definition intravascular ultrasound (HD-IVUS) for differentiating atherosclerotic plaque morphology influenced by local hemodynamic flow in rabbits. This study evaluated the diagnostic performance of 60 MHz HD-IVUS in identifying thrombosis in rabbits. Methods: We established 60 rabbit models of atherosclerosis with left common carotid artery (LCCA) stenosis and 30 FeCl3-induced LCCA thrombosis. Intravascular imaging was assessed with 60 MHz HD-IVUS and fourierdomain optical coherence tomography (FD-OCT). The present study investigated the diagnostic accuracy of 60 MHz HD-IVUS for PR and PE, as well as thrombosis, using OCT-diagnosis as a standard reference. Results: 60 MHz HD-IVUS for identifying atherosclerotic plaque morphology using plaque cavity and minor intimal irregularities showed high sensitivity and specificity; 92.0 and 90.0% for identifying OCT-defined PR, and 80.0 and 70.0% for OCT-defined PE, respectively. In a rabbit thrombus model, 60 MHz HD-IVUS showed high sensitivity (88.0%) and specificity (80.0%) in identifying OCT-defined thrombosis. Conclusions: 60 MHz HD-IVUS can accurately identify PR and thrombosis. Further studies should confirm the clinical value of this novel technique in PE diagnosis.

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Section: Discussionmentioning

confidence: 99%

“…IVUS has been the cornerstone of intracoronary imaging for

Section: Introductionmentioning

confidence: 99%

Diagnostic Performance of 60 MHz High-Definition Intravascular Ultrasound versus Fourier Domain Optical Coherence Tomography for Identifying Plaque Rupture, Plaque Erosion, and Thrombosis in a Rabbit Model

Wang¹,

Qiao²,

Xing³

et al. 2023

Rev. Cardiovasc. Med.

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“…NIRS can detect lipid composition by analyzing the near-infrared absorption properties of atherosclerotic plaques. A thorough discussion of hybrid intravascular imaging modalities can be found in Bourantas et al (2017) and Kubo et al (2022) .…”

Section: Pipeline Of Image-based Computational Biomechanical Simulationsmentioning

confidence: 99%

Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases

Northrup

et al. 2022

Front. Bioeng. Biotechnol.

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Hemodynamic factors, induced by pulsatile blood flow, play a crucial role in vascular health and diseases, such as the initiation and progression of atherosclerosis. Computational fluid dynamics, finite element analysis, and fluid-structure interaction simulations have been widely used to quantify detailed hemodynamic forces based on vascular images commonly obtained from computed tomography angiography, magnetic resonance imaging, ultrasound, and optical coherence tomography. In this review, we focus on methods for obtaining accurate hemodynamic factors that regulate the structure and function of vascular endothelial and smooth muscle cells. We describe the multiple steps and recent advances in a typical patient-specific simulation pipeline, including medical imaging, image processing, spatial discretization to generate computational mesh, setting up boundary conditions and solver parameters, visualization and extraction of hemodynamic factors, and statistical analysis. These steps have not been standardized and thus have unavoidable uncertainties that should be thoroughly evaluated. We also discuss the recent development of combining patient-specific models with machine-learning methods to obtain hemodynamic factors faster and cheaper than conventional methods. These critical advances widen the use of biomechanical simulation tools in the research and potential personalized care of vascular diseases.

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“…A detector at the tip of the catheter collects ultrasound echoes or backscattered light signals. Finally, sequential cross-sectional images (short-axis view or B mode) that show cross sections of the vessels, including lumen, adventitia/media, intima, and plaque load [2] are formed. Longitudinal view (L-view) slices along the long axis of the vessel segment (i.e., time-axis view) are also obtained for volumetric analysis.…”

Section: Introductionmentioning

confidence: 99%

An Unsupervised Deep Learning Framework for Retrospective Gating of Catheter-Based Cardiac Imaging

Sun,

Yao,

Wang

2024

IET Signal Processing

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Motion artifacts are a major challenge in the in vivo application of catheter-based cardiac imaging modalities. Gating is a critical tool for suppressing motion artifacts. Electrocardiogram (ECG) gating requires a trigger device or synchronous ECG recordings for retrospective analysis. Existing retrospective software gating methods extract gating signals through separate steps based on changes in vessel morphology or image features, which require a high computational cost and are prone to error accumulation. In this paper, we report on an end-to-end unsupervised learning framework for retrospective image-based gating (IBG) of catheter-based intracoronary images, named IBG Network. It establishes a direct mapping from a continuously acquired image sequence to a gated subsequence. The network was trained on clinical data sets in an unsupervised manner, addressing the difficulty of obtaining the gold standard in deep learning-based motion suppression techniques. Experimental results of in vivo intravascular ultrasound and optical coherence tomography sequences show that the proposed method has better performance in terms of motion artifact suppression and processing efficiency compared with the state-of-the-art nonlearning signal-based and IBG methods.

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Combined Use of Multiple Intravascular Imaging Techniques in Acute Coronary Syndrome

Cited by 6 publications

References 24 publications

Diagnostic Performance of 60 MHz High-Definition Intravascular Ultrasound versus Fourier Domain Optical Coherence Tomography for Identifying Plaque Rupture, Plaque Erosion, and Thrombosis in a Rabbit Model

Diagnostic Performance of 60 MHz High-Definition Intravascular Ultrasound versus Fourier Domain Optical Coherence Tomography for Identifying Plaque Rupture, Plaque Erosion, and Thrombosis in a Rabbit Model

Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases

An Unsupervised Deep Learning Framework for Retrospective Gating of Catheter-Based Cardiac Imaging

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