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Independent Scientist: ARFI and RWI Ultrasound for Improved Atherosclerosis Imagi

Independent Scientist: ARFI and RWI Ultrasound for Improved Atherosclerosis Imagi
独立科学家:ARFI 和 RWI 超声可改善动脉粥样硬化 Imagi
批准号:
8310158
负责人:
Caterina M Gallippi
金额:
$10.18万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-15 至 2015-05-31

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DESCRIPTION (provided by applicant): While stroke remains the third leading cause of death behind heart disease and cancer and the primary cause of serious, long-term disability in the United States, decreasing incidence has been attributed to interventions including revascularization and statin therapy. However, administration of proper treatment is limited by inadequacies in modern diagnostic imaging technologies. These technologies are effective for detecting occlusive plaques associated with pronounced lumenal narrowing (occlusion) and/or blood flow obstruction, but their focus on lumenal features inhibits detection of nonocclusive plaques contained in arterial walls. Furthermore, their ability to predict plaque risk for causing cerebrovascular accident (CVA) is not established. There is a clear unmet need for a validated atherosclerosis imaging modality that can improve plaque detection and predict rupture risk. To address this need, our laboratory is developing novel acoustic radiation force-based images methods, which interrogate tissue composition and structure - features that indicate rupture risk. Our on-going R01 research involves developing one acoustic radiation force-based imaging methods, Acoustic Radiation Force Impulse (ARFI) ultrasound, for atherosclerosis diagnosis. We now propose to explore a new acoustic radiation force-based method, Relfected Wave Imaging (RWI), to improve ARFI's delineation of plaque composition and structure. We hypothesize that in vivo, transcutaneous ARFI and RWI ultrasound are capable of detecting occlusive and nonocclusive plaques in peripheral arteries and of assessing plaque composition and structure. The on-going R01 research pursues three specific aims: 1) Define the sensitivity and specificity of ARFI ultrasound for detecting plaques in familial hypercholesterolemic (FH) pigs, 2) Establish that ARFI imaging delineates plaque composition and structure in FH pigs, and 3) Establish that ARFI imaging delineates plaques and their composition and structure in humans. We now propose a new aim to develop RWI technology: 4) Exploit the reflections of acoustic radiation force-induced longitudinal and transverse waves to improve discrimination of plaque composition and structure in Reflected Wave Imaging (RWI). RWI alone and RWI as an adjunct to ARFI will be compared to ARFI alone for improvements in imaging sensitivity and specificity. The PI is trained in electrical engineering and ultrasound physics, but she proposes additional training in the physics of mechanical wave propagation in tissue to pursue aim #4 to her fullest capacity. In addition, the PI proposes training in clinical trials design, execution, and management as well as ethical conduct of research. PUBLIC HEALTH RELEVANCE: Stroke is the third leading cause of death and the primary cause of serious, long-term disability in the United States. Although timely and appropriate treatment is critical to saving lives, shortcomings in conventional diagnostic imaging technologies prevent advanced warning of the disease and delay therapy. The objectives of this research proposal are to demonstrate novel ultrasound imaging technologies - Acoustic Radiation Force Impulse (ARFI) and Reflected Wave Imaging (RWI) ultrasound - for improved diagnosis of atherosclerotic plaques and stroke risk.
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VisR Ultrasound for Noninvasively Interrogating Stromal Collagen Organization in Women as a Breast Cancer Biomarker
  • 批准号:
    10680931
  • 项目类别:
  • 资助金额:
    $59.35万
  • 财政年份:
    2023
  • 负责人:
    Caterina M Gallippi
  • 依托单位:
The Unified Medical Ultrasound Technology Development (UNMUTED) Predoctoral Training Program
VisR Ultrasound for Noninvasively Monitoring Renal Allograft Health
VisR Ultrasound for Noninvasively Monitoring Renal Allograft Health
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