A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

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.Lili Niu, Ming Qian, Wei Yang, Long Meng, Yang Xiao, Kelvin K. L. Wong, Derek Abbott, Xin Liu, Hairong Zhen

Wireless Ultrasound Video Transmission for Stroke Risk Assessment: Quality Metrics and System Design

In this paper we discuss the use of clinical quality criteria in the assessment and design of ultrasound video compression systems. Our goal is to design efficient systems that can be used to transmit quality ultrasound videos at the lowest possible bitrates. This led us to the development of a spatially- varying encoding scheme, where quantization levels are spatially varying as a function of the diagnostic significance of the video. Diagnostic Regions of Interest (ROIs) for carotid ultrasound medical video are defined, which are then used as input for Flexible Macroblock Ordering (FMO) slice encoding. Diagnostically relevant FMO slice encoding is attained by enabling variable quality slice encoding, tightly coupled by each region's diagnostic importance. Redundant Slices (RS) utilization increases compressed video's resilience over error prone transmission mediums. We present preliminary findings on three carotid ultrasound videos at CIF resolution, for packet loss rates up to 30%. Subjective quality evaluation incorporates a clinical rating system that provides for independent evaluations of the different parts of the video. Experimental results show that encoded videos attain enhanced diagnostic performance under noisy environments, while at the same time achieving significant bandwidth requirements reductions

Ultrasound Asymptomatic Carotid Plaque Image Analysis for the Prediction of the Risk of Stroke

High-resolution vascular B-mode and Doppler ultrasound provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques [1]. Carotid stenosis alone has limitations in predicting risk and does not show plaque vulnerability and instability, thus other ultrasonographic plaque morphologic characteristics have been studied for better prediction of the risk stroke. Plaque echogenicity as assessed by B-mode ultrasound has been found to reliably predict the content of soft tissue and the amount of calcification in carotid plaques. Additionally, it has been reported that subjects with echolucent atherosclerotic plaques have increased risk of ischemic cerebrovascular events [2]. More recent studies by Nicolaides et al. [3] Topakian et al. [4] and Kyriacou et al. [5], showed that plaque echolucency and plaque morphology can be used to predict stroke. Other studies have reported that plaques that are more echolucent and heterogeneous are often associated with higher cerebrovascular risk and the development of ipsilateral neurological symptoms [3, 6, 7, 8, 9, 10]. In contrast, homogeneous hypoechoic and hyperechoic plaques without evidence of ulceration usually remain asymptomatic