Automated Detection Framework of the Calcified Plaque with Acoustic Shadowing in IVUS Images

Intravascular Ultrasound (IVUS) is one ultrasonic imaging technology to acquire vascular cross-sectional images for the visualization of the inner vessel structure. This technique has been widely used for the diagnosis and treatment of coronary artery diseases. The detection of the calcified plaque with acoustic shadowing in IVUS images plays a vital role in the quantitative analysis of atheromatous plaques. The conventional method of the calcium detection is manual drawing by the doctors. However, it is very time-consuming, and with high inter-observer and intra-observer variability between different doctors. Therefore, the computer-aided detection of the calcified plaque is highly desired. In this paper, an automated method is proposed to detect the calcified plaque with acoustic shadowing in IVUS images by the Rayleigh mixture model, the Markov random field, the graph searching method and the prior knowledge about the calcified plaque. The performance of our method was evaluated over 996 in-vivo IVUS images acquired from eight patients, and the detected calcified plaques are compared with manually detected calcified plaques by one cardiology doctor. The experimental results are quantitatively analyzed separately by three evaluation methods, the test of the sensitivity and specificity, the linear regression and the Bland-Altman analysis. The first method is used to evaluate the ability to distinguish between IVUS images with and without the calcified plaque, and the latter two methods can respectively measure the correlation and the agreement between our results and manual drawing results for locating the calcified plaque in the IVUS image. High sensitivity (94.68%) and specificity (95.82%), good correlation and agreement (>96.82% results fall within the 95% confidence interval in the Student t-test) demonstrate the effectiveness of the proposed method in the detection of the calcified plaque with acoustic shadowing in IVUS images.     

血管内超声在冠状动脉疾病诊断和介入治疗中的应用

冠状动脉造影是目前公认的诊断冠状动脉病变和指导冠脉介入的金标准。然而,随着介入手术的发展,冠脉造影在评价冠脉病变方面存在的缺陷逐渐显露出来,已不能完全满足临床医生的需要。血管内超声以其优越的图像质量和空间分辨率在冠心病介入领域发挥独特的作用。作为冠脉造影的有效补充,血管内超声不仅能提供管腔和血管的直径信息,还能告知术者斑块负荷、斑块构成和血管重塑等,明确冠状动脉临界病变的性质、严重性和稳定性。此外,血管内超声还可以判断病变是否可以延迟血运重建,指导经皮冠状动脉介入的治疗策略和评估支架植入效果,有效地预防手术并发症。本文从血管内超声的概况,在冠状动脉疾病诊断和介入治疗等方面的应用进展进行了综述。     

超声造影在早期动脉粥样硬化疾病的研究进展

动脉粥样硬化一直是心血管医学面临的长期而严峻的挑战,随着代谢性危险因素的日益增多,动脉粥样硬化性疾病带来的危害日益突出;超声成像作为一种良好的无创、实时检查手段,一直作为动脉粥样硬化疾病诊断的首选诊断方法;近30年来超声影像学快速发展,从过去单纯对发生粥样硬化损伤的血管结构进行成像,经过各方面技术的发展,如今其对动脉粥样硬化组织内的结构以及病理过程的显像已成为可能。在本文中,将对近年来超声造影在早期AS疾病的诊治及疗效评价方面的进展作简要综述。     

Surface Roughness Detection of Arteries via Texture Analysis of Ultrasound Images for Early Diagnosis of Atherosclerosis

There is a strong research interest in identifying the surface roughness of the carotid arterial inner wall via texture analysis for early diagnosis of atherosclerosis. The purpose of this study is to assess the efficacy of texture analysis methods for identifying arterial roughness in the early stage of atherosclerosis. Ultrasound images of common carotid arteries of 15 normal mice fed a normal diet and 28 apoE^−/− mice fed a high-fat diet were recorded by a high-frequency ultrasound system (Vevo 2100, frequency: 40 MHz). Six different texture feature sets were extracted based on the following methods: first-order statistics, fractal dimension texture analysis, spatial gray level dependence matrix, gray level difference statistics, the neighborhood gray tone difference matrix, and the statistical feature matrix. Statistical analysis indicates that 11 of 19 texture features can be used to distinguish between normal and abnormal groups (p<0.05). When the 11 optimal features were used as inputs to a support vector machine classifier, we achieved over 89% accuracy, 87% sensitivity and 93% specificity. The accuracy, sensitivity and specificity for the k-nearest neighbor classifier were 73%, 75% and 70%, respectively. The results show that it is feasible to identify arterial surface roughness based on texture features extracted from ultrasound images of the carotid arterial wall. This method is shown to be useful for early detection and diagnosis of atherosclerosis.     

Recent Trends in Computer Assisted Diagnosis (CAD) System for Breast Cancer Diagnosis Using Histopathological Images

Breast cancer is one of the common type of cancer in females across the world. An early detection and diagnosis of breast cancer may reduce the mortality rate to a great extent. To diagnose breast cancer, different types of imaging modalities are used to collect samples like mammography, Computerized Tomography, Magnetic Resonance Imaging, Ultrasound and Biopsy. Histopathological images obtained from biopsy may influence how and at which stage the cancer is being diagnosed. The Computer Assisted Diagnosis (CAD) system helps the pathologists in early diagnosis of breast cancer. In this survey, the recently reported techniques for breast cancer diagnosis using histopathological images have been summarized. This study could be beneficial for: (i) Clinicians to receive second opinion from the CAD system for early diagnosis, and (ii) Researchers to analyze and enhance the existing state-of-art techniques used in CAD system, which may further reduce the gap of variability between intra and inter observer.     

Intravascular molecular-structural imaging with a miniaturized integrated near-infrared fluorescence and ultrasound catheter

Coronary artery disease (CAD) remains a leading cause of mortality and warrants new imaging approaches to better guide clinical care. We report on a miniaturized, hybrid intravascular catheter and imaging system for comprehensive coronary artery imaging in vivo. Our catheter exhibits a total diameter of 1.0 mm (3.0 French), equivalent to standalone clinical intravascular ultrasound (IVUS) catheters but enables simultaneous near-infrared fluorescence (NIRF) and IVUS molecular-structural imaging. We demonstrate NIRF-IVUS imaging in vitro in coronary stents using NIR fluorophores, and compare NIRF signal strengths for prism and ball lens sensor designs in both low and high scattering media. Next, in vivo intravascular imaging in pig coronary arteries demonstrates simultaneous, co-registered molecular-structural imaging of experimental CAD inflammation on IVUS and distance-corrected NIRF images. The obtained results suggest substantial potential for the NIRF-IVUS catheter to advance standalone IVUS, and enable comprehensive phenotyping of vascular disease to better assess and treat patients with CAD.     

Strain imaging with intravascular ultrasound array scanners: validation with phantom experiments.

Intravascular Ultrasound (IVUS) is routinely used in interventional cardiology for imaging coronary plaque morphology. However, the use of B-mode images for tissue characterization and detection of vulnerable coronary plaques is limited. Strain imaging with ultrasound is a new modality that provides additional information for tissue characterization by imaging differences in tissue stiffness. The aim is to differentiate between vulnerable (soft) plaques and less dangerous calcified (hard) plaques. In this work, the applicability of a time efficient strain imaging algorithm in conjunction with data from IVUS array transducers is evaluated. Unfocused radiofrequency (rf) data from the transducer array is acquired using custom made hardware. Rf line reconstruction is performed offline by synthetic aperture focusing techniques. Vessel mimicking phantoms of different geometries and material stiffness are made from agar and Polyvinyl Alcohol Cryogel (PVA). Experiments are conducted in a water tank and a water column is used for applying intraluminal pressure differences required for strain imaging. The results show that strain images can be calculated with A-lines reconstructed from unfocused rf raw data. Regions of different stiffness can be identified qualitatively by local strain variations. With the used algorithm strains of up to 2% can be imaged without significant decor-relation.     

超声弹性成像技术在乳腺肿块诊断中的研究进展及应用

超声弹性成像技术(UE)是一种新的超声成像技术,能够根据组织硬度进行成像,估计出组织内部的弹性信息,从而反映它的结构特点,该技术较传统触诊检查更加客观,在乳腺肿块的鉴别诊断中有较高的价值,其临床应用广泛并且得到了快速的发展。现就国内外文献对UE技术的原理、图像分析方法、技术研究进展及其在乳腺肿块鉴别诊断中的应用进行综述。     

眼部常见疾病的超声诊断分析

目的：总结眼部常见疾病的超声表现,探讨超声对其的诊断价值。方法：对2009年6月～2010年6月来我院超声科行眼部超声检查（占位性病变经手术或病理学结果证实）的63例患者的资料进行回顾性分析,归纳总结了眼部常见疾病的二维超声（2D）、彩色多普勒（CDFI）及超声造影（CEUS）表现。结果：眼部疾病的超声图像在位置、形状、边界、声学特点及对周围组织的影响等方面具有特征性表现;超声造影能有效地显示出病灶内的血管及血流灌注情况。结论：超声对眼部常见病的诊断是一种简便、无创、经济且诊断符合率高的辅助影像学方法,具有较高的实际应用价值。     

Intravascular ultrasound imaging of myocardial-infarction-related arteries after percutaneous transluminal coronary angioplasty reveals significant plaque burden and compensatory enlargement

We studied patients with acute myocardial infarction (MI) by intravascular ultrasound (IVUS) to elucidate the controversy as to the amount and severity of the atherosclerotic disease at the culprit lesion site in acute MI, as discrepancies exist between angiographic and pathological reports. Twenty-five consecutive patients (age 56 3 10.5 years), with acute MI, underwent IVUS study of the MI-related artery immediately following successful PTCA to the culprit lesion. The IVUS images were analyzed quantitatively and qualitatively and were compared with the angiography of the same arteries. At the PTCA site, 64% of the lesions had an area stenosis of 50-70% and the plaque cross-sectional area (CSA) averaged 0.5 3 0.18 of the arterial CSA. IVUS-defined atherosclerosis was found also in 72% of the segments proximal and distal to the culprit lesion with a plaque/artery CSA ratio of 0.25 3 0.2. The angiogram revealed only 30% of these segments to be abnormal (P 3 0.001). Sixty-nine per cent of all the plaques were defined as 'soft' (low echo-genecity) versus 31% 'hard' (high echo-genecity). The hard plaques were larger than the soft plaques (0.5 3 1.6 versus 0.37 3 0.19 CSA index, respectively, P 3 0.01). With the increase in plaque area there was a significant increase in arterial cross-sectional area. This was demonstrated for all the diseased segments with a correlation coefficient of 0.49 (P 3 0.0001) and for the diseased reference sites a similar correlation coefficient of 0.49 (P 3 0.003) was found. Contrary to coronary angiographic-based reports, this IVUS study revealed a significant atheromatous plaque burden at the culprit lesion of MI-related arteries as well as diffuse atherosclerosis in the reference segments proximal and distal to the lesion. The detection of compensatory enlargement may explain the discrepancies between the histopathological and the angiographic studies.     

Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained. Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for this study. Manual OCT segmentation was performed by experts using virtual histology IVUS as guidance, and used as gold standard in the automatic segmentations. The overall classification accuracy based on CNN method achieved 95.8%, and the accuracy based on SVM was 71.9%. The CNN-based segmentation method can better characterize plaque compositions on OCT images and greatly reduce the time spent by doctors in segmenting and identifying plaques.     

Technology and research developments in carotid image registration

Brain stroke is the leading cause of death worldwide. Mortality, morbidity and economic effects of stroke are alarming. Carotid atherosclerosis is the most common cause of stroke. Early identification, monitoring and quantification of carotid plaque with the help of imaging modalities can help manage the stroke and evaluate the effectiveness of medical therapy. Carotid image registration has the potential to improve the monitoring, quantification and characterization of the disease. It helps to accurately correlate the findings of various imaging modalities for the diagnostic and therapeutic purposes. This paper aims to present the current state-of-the-art in carotid image registration techniques. For the monomodality registration, ultrasound and magnetic resonance imaging are the primary concerns. Multimodality registration will cover the combination of different modalities. The registration process and validation methods for carotid image registration are also discussed.     

A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP) Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration

Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP) algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US) and magnetic resonance (MR). Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP) algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS) transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.     

A Feasibility Study of an Intravascular Imaging Antenna to Image Atherosclerotic Plaques in Swine Using 3.0 T MRI

Purpose

To investigate the feasibility of an intravascular imaging antenna to image abdominal aorta atherosclerotic plaque in swine using 3.0T magnetic resonance imaging (MRI).

Methods

Atherosclerotic model was established in 6 swine. After 8 months, swine underwent an MR examination, which was performed using an intravascular imaging guide-wire, and images of the common iliac artery and the abdominal aorta were acquired. Intravascular ultrasound (IVUS) was performed in the right femoral artery; images at the same position as for the MR examination were obtained. The luminal border and external elastic membrane of the targeted arteries were individually drawn in the MR and IVUS images. After co-registering these images, the vessel, lumen, and vessel wall areas and the plaque burden in the same lesions imaged using different modalities were calculated and compared. The diagnostic accuracy of intravascular MR examination in delineating the vessel wall and detecting plaques were analyzed and compared using IVUS.

Results

Compared with IVUS, good agreement was found between MRI and IVUS for delineating vessel, lumen, and vessel wall areas and plaque burden (r value: 0.98, 0.95, 0.96 and 0.91, respectively; P<0.001).

Conclusion

Compared with IVUS, using an intravascular imaging guide-wire to image deep seated arteries allowed determination of the vessel, lumen and vessel wall areas and plaque size and burden. This may provide an alternative method for detecting atherosclerotic plaques in the future.     

Strain measurement in coronary arteries using intravascular ultrasound and deformable images

Atherosclerotic plaque rupture is responsible for the majority of myocardial infarctions and acute coronary syndromes. Rupture is initiated by mechanical failure of the plaque cap, and thus study of the deformation of the plaque in the artery can elucidate the events that lead to myocardial infarction. Intravascular ultrasound (IVUS) provides high resolution in vitro and in vivo cross-sectional images of blood vessels. To extract the deformation field from sequences of IVUS images, a registration process must be performed to correlate material points between image pairs. The objective of this study was to determine the efficacy of an image registration technique termed Warping to determine strains in plaques and coronary arteries from paired IVUS images representing two different states of deformation. The Warping technique uses pointwise differences in pixel intensities between image pairs to generate a distributed body force that acts to deform a finite element model. The strain distribution estimated by image-based Warping showed excellent agreement with a known forward finite element solution, representing the gold standard, from which the displaced image was created. The Warping technique had a low sensitivity to changes in material parameters or material model and had a low dependency on the noise present in the images. The Warping analysis was also able to produce accurate strain distributions when the constitutive model used for the Warping analysis and the forward analysis was different. The results of this study demonstrate that Warping in conjunction with in vivo IVUS imaging will determine the change in the strain distribution resulting from physiological loading and may be useful as a diagnostic tool for predicting the likelihood of plaque rupture through the determination of the relative stiffness of the plaque constituents.     

A genomewide linkage study of 1,933 families affected by premature coronary artery disease: The British Heart Foundation (BHF) Family Heart Study

Coronary artery disease (CAD) and its most important complication, myocardial infarction (MI), are the leading cause of premature death in the Western world. CAD has a substantial genetic basis, especially when it occurs early. We investigated the genetic determinants of premature CAD by performing a genomewide linkage analysis of 4,175 affected subjects from 1,933 families recruited throughout the United Kingdom. Each family had at least two available siblings with CAD, with validated onset before age 66 years. Linkage analysis was performed using 416 microsatellite markers. We observed suggestive linkage, for both CAD and MI, to a region on chromosome 2. For CAD, a LOD score of 1.86 was observed at marker D2S2271, which, in an ordered subset analysis, increased to 2.70 in families (n=1,698) with a minimum age at diagnosis of 56 years or younger. For MI, an overlapping peak with a LOD score of 1.15 was observed at marker D2S2216, which increased to 2.1 in families (n=801) with a minimum age at diagnosis of 59 years or younger. Exclusion mapping showed that 100% of the autosomal genome could be excluded for locus-specific sibling relative risks of 1.5 and 1.6 for CAD and MI, respectively. The region identified on chromosome 2 overlaps linked regions observed in two other smaller genome scans for CAD. Together, these findings strongly suggest that there is a locus on chromosome 2 that influences coronary atherosclerosis risk. The exclusion of a common locus that increases risk of CAD to siblings by >50% has important implications for strategies for further defining the genetic basis of CAD.     

First-in-human imaging using a MR-compatible e4D ultrasound probe for motion management of radiotherapy

PurposeRespiration-induced tumor or organ positional changes can impact the accuracy of external beam radiotherapy. Motion management strategies are used to account for these changes during treatment. The authors report on the development, testing, and first-in-human evaluation of an electronic 4D (e4D) MR-compatible ultrasound probe that was designed for hands-free operation in a MR and linear accelerator (LINAC) environment.MethodsUltrasound components were evaluated for MR compatibility. Electromagnetic interference (EMI) shielding was used to enclose the entire probe and a factory-fabricated cable shielded with copper braids was integrated into the probe. A series of simultaneous ultrasound and MR scans were acquired and analyzed in five healthy volunteers.ResultsThe ultrasound probe led to minor susceptibility artifacts in the MR images immediately proximal to the ultrasound probe at a depth of <10 mm. Ultrasound and MR-based motion traces that were derived by tracking the salient motion of endogenous target structures in the superior-inferior (SI) direction demonstrated good concordance (Pearson correlation coefficients of 0.95–0.98) between the ultrasound and MRI datasets.ConclusionWe have demonstrated that our hands-free, e4D probe can acquire ultrasound images during a MR acquisition at frame rates of approximately 4 frames per second (fps) without impacting either the MR or ultrasound image quality. This use of this technology for interventional procedures (e.g. biopsies and drug delivery) and motion compensation during imaging are also being explored.     

基于启发式A^＊算法的超声图像颈动脉内膜提取

从超声图像准确提取颈动脉内膜,为基于颈动脉超声图像判断动脉粥样硬化服务。方法提出一种基于启发式A*算法从超声图像中提取颈动脉内膜边缘的方法。先使用图像分割法区分血管腔和血管壁,再采用结合图像灰度值特点的A*算法准确地提取颈动脉内膜边缘。结果通过对临床采集的32幅颈动脉超声图像的分析研究,表明本方法自动提取的结果与医生手工描绘的结果基本吻合。结论本方法有望应用于超声图像颈动脉内膜的自动提取。     

Measurement of the transverse strain tensor in the coronary arterial wall from clinical intravascular ultrasound images

Atherosclerotic plaque rupture is the major cause of acute coronary syndromes. Currently, there is no reliable diagnostic tool to predict plaque rupture. Knowledge of plaque mechanical properties based on local artery wall strain measurements would be useful for characterizing its composition and predicting its vulnerability. Due to cardiac motion, strain estimation in clinical intravascular ultrasound (IVUS) images is extremely challenging. A method is presented to estimate cross-sectional coronary artery wall strain in response to cardiac pulsatile pressure using clinically acquired IVUS images, which are acquired in continuous pullback mode. First, cardiac phase information is retrieved retrospectively from an IVUS image sequence using an image-based gating method, and image sub-sequences at systole and diastole are extracted. Then, images at branch sites are used as landmarks to align the two image sub-sequences. Finally, the paired images at each site are registered to measure the 2D strain tensor of the coronary artery cross-section. This method has been successfully applied to IVUS images of a left anterior descending (LAD) coronary artery acquired clinically during a standard procedure. Such complete strain information should be useful for identifying vulnerable plaque.