基于血管内高频超声的血管壁组织应变成像及弹性重构

利用血管内高频超声（Intravascular Ultrasound,IVUS)成像技术,对IVUS图像灰度值进行换能器偏心校正后,提出了基于遗传算法的管壁组织运动分阶叠加光流估计方法获得血管内施压条件下组织微元位移与应变分布,采用弹性重构方法获得了实际血管壁真正意义上的横断面弹性显微图像,由离体猪血管实验结果证实。将血管力学实验研究推进到二维亚毫米微结构层次,有希望为经皮腔内冠状动脉血管形术（Percutaneous Transluminal Coronary Angioplasty,PTCA)过程监控与治疗评价提供新的技术手段。     

Multispectral fluorescence lifetime imaging system for intravascular diagnostics with ultrasound guidance: in vivo validation in swine arteries

Fluorescence lifetime technique has demonstrated potential for analysis of atherosclerotic lesions and for complementing existing intravascular imaging modalities such as intravascular ultrasound (IVUS) in identifying lesions at high risk of rupture. This study presents a multimodal catheter system integrating a 40 MHz commercial IVUS and fluorescence lifetime imaging (FLIm) using fast helical motion scanning (400 rpm, 0.75 mm/s), able to acquire in vivo in pulsatile blood flow the autofluorescence emission of arterial vessels with high precision (5.08 ± 0.26 ns mean average lifetime over 13 scans). Co‐registered FLIm and IVUS data allowed 3D visualization of both biochemical and morphological vessel properties. Current study supports the development of clinically compatible intravascular diagnostic system integrating FLIm and demonstrates, to our knowledge, the first in vivo intravascular application of a fluorescence lifetime imaging technique. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Using 2D In Vivo IVUS-Based Models for Human Coronary Plaque Progression Analysis and Comparison with 3D Fluid-Structure Interaction Models: A Multi-Patient Study

Computational modeling has been used extensively in cardiovascular and biological research, providing valuable information. However, 3D vulnerable plaque model construction with complex geometrical features and multicomponents is often very time consuming and not practical for clinical implementation. This paper investigated if 2D atherosclerotic plaque models could be used to replace 3D models to perform correlation analysis and achieve similar results. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from a patient follow-up study to construct 2D structure-only and 3D FSI models to obtain plaque wall stress (PWS) and strain (PWSn) data. One hundred and twenty-seven (127) matched IVUS slices at baseline and follow up were obtained from 3 patients. Our results showed that 2D models overestimated stress and strain by 30% and 33%, respectively, compared to results from 3D FSI models. 2D/3D correlation comparison indicated that 116 out of 127 slices had a consistent correlation between plaque progression (WTI) and wall thickness; 103 out of 127 slices had a consistent correlation between WTI and PWS; and 99 out of 127 slices had a consistent correlation between WTI and PWSn. This leads to the potential that 2D models could be used in actual clinical implementation where quick analysis delivery time is essential.     

A pragmatic approach to understand peripheral artery lumen surface stiffness due to plaque heterogeneity

The goal of this study was to develop a pragmatic approach to build patient-specific models of the peripheral artery that are aware of plaque inhomogeneity. Patient-specific models using element-specific material definition (to understand the role of plaque composition) and homogeneous material definition (to understand the role of artery diameter and thickness) were automatically built from intravascular ultrasound images of three artery segments classified with low, average, and high calcification. The element-specific material models had average surface stiffness values of 0.0735, 0.0826, and 0.0973?MPa/mm, whereas the homogeneous material models had average surface stiffness values of 0.1392, 0.1276, and 0.1922?MPa/mm for low, average, and high calcification, respectively. Localization of peak lumen stiffness and differences in patient-specific average surface stiffness for homogeneous and element-specific models suggest the role of plaque composition on surface stiffness in addition to local arterial diameter and thickness.     

Quantification of new structural features of coronary plaques by computational post-hoc analysis of virtual histology-intravascular ultrasound images

Cardiovascular disease and complications are often mediated by the development and rupture of atherosclerotic plaques. Plaque composition is a major factor that determines plaque vulnerability. Intravascular ultrasound (IVUS) and spectral analysis of the radio frequency signal provide an in vivo tissue characterisation of atherosclerotic plaques, known as virtual histology (VH–IVUS). In VH–IVUS analysis, four histological tissue components are classified: fibrous, fibro/fatty, necrotic core and calcium. Existing technology determines only the area of each component within the plaque. Quantitative, objective characterisation of other plaque components' patterns within the plaque is lacking. The aim of this study was to determine new compositional and structural indices which indicate spatial distribution, heterogeneity and dispersity of each VH–IVUS-derived component within the plaque area and also with respect to the plaque–lumen border. We developed an automated computational system in Java for the analysis of both single cross-sectional segments and the whole length of the examined plaque (volumetric analysis). The following parameters were computed: the number of different solid segments and the area of the largest solid segment of each component within the plaque, the per cent of the lumen border that is surrounded by each component, the number of different solid segments and the largest area of a solid segment of each component that adjoins the lumen border. Especially components' localisation in relation to the lumen border may significantly influence plaque vulnerability and plaque–stent interaction, which should be investigated in future clinical studies.     

冠状动脉易损斑块影像学最新研究进展

冠心病(CAD)是世界上致死率最高的疾病之一,其中,以急性冠状动脉综合征(ACS)病情最为凶险,而近70%的急性冠脉事件并不是由显著地冠状动脉狭窄引起,而是由冠状动脉易损斑块(vulnerable plaque)破裂造成的急性狭窄,以及其后血栓形成所致,因此冠状动脉易损斑块是导致急性冠状动脉综合征的主要元凶,因此需要早期发现易损斑块并积极进行干预。近两年来,CT、MRI、血管内超声(IVUS)和光学相干断层成像(OCT)广泛应用于易损斑块的评估并取得显著进展,而分子影像学能从分子层面揭示易损斑块形成机制以及更加早期识别斑块进行。本文简要总结近两年影像学方法对易损斑块的最新研究进展及热点。     

Thrombotic complication during intracoronary imaging

Intracoronary imaging with intracoronary ultrasound and coherence tomography is often used in the follow-up of coronary stent implantation. The present case shows an infrequent complication of these procedures, suggesting our continued attention to the selective use of these invasive procedures.     

Fluid-structure interaction models based on patient-specific IVUS at baseline and follow-up for prediction of coronary plaque progression by morphological and biomechanical factors: A preliminary study

Plaque morphology and biomechanics are believed to be closely associated with plaque progression. In this paper, we test the hypothesis that integrating morphological and biomechanical risk factors would result in better predictive power for plaque progression prediction. A sample size of 374 intravascular ultrasound (IVUS) slices was obtained from 9 patients with IVUS follow-up data. 3D fluid-structure interaction models were constructed to obtain both structural stress/strain and fluid biomechanical conditions. Data for eight morphological and biomechanical risk factors were extracted for each slice. Plaque area increase (PAI) and wall thickness increase (WTI) were chosen as two measures for plaque progression. Progression measure and risk factors were fed to generalized linear mixed models and linear mixed-effect models to perform prediction and correlation analysis, respectively. All combinations of eight risk factors were exhausted to identify the optimal predictor(s) with highest prediction accuracy defined as sum of sensitivity and specificity. When using a single risk factor, plaque wall stress (PWS) at baseline was the best predictor for plaque progression (PAI and WTI). The optimal predictor among all possible combinations for PAI was PWS + PWSn + Lipid percent + Min cap thickness + Plaque Area (PA) + Plaque Burden (PB) (prediction accuracy = 1.5928) while Wall Thickness (WT) + Plaque Wall Strain (PWSn) + Plaque Area (PA) was the best for WTI (1.2589). This indicated that PAI was a more predictable measure than WTI. The combination including both morphological and biomechanical parameters had improved prediction accuracy, compared to predictions using only morphological features.