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REAL TIME ULTRASOUND ENTROPY-BASED QUANTIFICATION OF FIBROFATTY LIVER DISEASE

纤维脂肪肝病的实时超声基于熵的定量

基本信息

批准号：
9093796
负责人：
John E. McCarthy
金额：
$ 19.06万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-07-01 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9093796
关键词：
Address Adult Affect Age Algorithms Animal Model Biopsy Blood Transfusion Caring Cessation of life Child Cholesterol Classification Clinic Clinical Complex Data Databases Detection Development Devices Diagnosis Diagnostic Diffuse Discrimination Disease Elderly Elements Ensure Entropy Environment Epidemic Evaluation Fatty Liver Fatty acid glycerol esters Fibrosis Financial compensation Frequencies Goals Health Histologic Individual Inflammation Injury Investigation Label Liver Liver diseases Longitudinal Studies Maps Measures Methodology Methods Microanatomy Modeling Myopathy Needle biopsy procedure Organ Oryctolagus cuniculus Pathology Patient Monitoring Patients Pattern Personal Satisfaction Physiological Prevalence Procedures Process Property Rattus Risk Scheme Sensitivity and Specificity Severities Signal Transduction Stream Structure Techniques Technology Testing Time Tissues Training Transducers Translating Translations Ultrasonic Diagnosis Ultrasonics Ultrasonography Work attenuation base bile duct clinical application cohort cost detector feeding imaging system liver biopsy malignant muscle neoplasm non-alcoholic fatty liver novel point of care radio frequency radiofrequency response signal processing tissue processing

项目摘要

DESCRIPTION (provided by applicant): The major problem addressed in this proposal is the development and evaluation of a noninvasive ultrasonic diagnostic approach for mapping a set of unique and quantitative ultrasonic metrics for liver disease. These are anticipated to differentiate physiological from pathological liver microanatomy in patients with diverse liver diseases with the use of conventional ultrasound scanners and a novel signal processing methodology. The method is based on radiofrequency signal (RF) processing schemes referred to as information theoretic detectors (ITD's) that have been shown to detect pathological changes in muscle diseases and cancer by measuring selected signal entropies. In this analysis of ultrasound data, we seek to describe the fundamental information content and the exact organization of scattering structures depicted within the backscattered ultrasound data. All of our present results have been obtained without the need for attenuation correction, and by real-time capable algorithms. These unique attributes of entropy analysis suggest that the automated processing we propose would be particularly robust for discrimination of deep tissues in a clinical environment. Most importantly, these techniques work on individual radio frequency A-Lines available from single element transducers and thus may be translated to the clinic without the need for relatively expensive imaging systems. As prevalence of liver disease increases with age (e.g. non alcoholic fatty liver disease: 9.7% among children, 26% among people 40-59 years old) the availability of a rapid, low-cost, point-of-care device for longitudina diagnosis of liver pathologies would find widespread clinical application supporting the health and well-being of older adults.

描述(由申请人提供)：本提案中解决的主要问题是开发和评估一种非侵入性超声诊断方法，用于绘制一套独特的、定量的肝脏疾病超声指标。通过使用常规超声扫描仪和一种新的信号处理方法，这些有望区分不同肝病患者的生理性和病理性肝脏显微解剖。该方法基于被称为信息理论检测器(ITD)的射频信号(RF)处理方案，已被证明通过测量选定的信号熵来检测肌肉疾病和癌症的病理变化。在超声数据的这种分析中，我们试图描述背向散射超声数据中描述的基本信息内容和散射结构的准确组织。我们目前的所有结果都是在不需要衰减校正的情况下，通过具有实时能力的算法获得的。熵分析的这些独特属性表明，我们提出的自动化处理将特别适用于临床环境中深层组织的区分。最重要的是，这些技术适用于从单元件换能器获得的单个射频A线，因此可以在不需要相对昂贵的成像系统的情况下转移到临床上。随着肝病患病率随着年龄的增长而增加(例如，非酒精性脂肪性肝病在儿童中占9.7%，在40-59岁人群中占26%)，提供一种快速、低成本、可用于肝脏病理纵向诊断的点式设备将在临床上得到广泛应用，以支持老年人的健康和福祉。