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Prostate Cancer Assessment Via Integrated 3D ARFI Elasticity Imaging and Multi-Parametric MRI

Prostate Cancer Assessment Via Integrated 3D ARFI Elasticity Imaging and Multi-Parametric MRI
通过集成 3D ARFI 弹性成像和多参数 MRI 进行前列腺癌评估
批准号:
8905274
负责人:
Matthew McCormick
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-04-01 至 2016-09-30

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英文摘要
 DESCRIPTION (provided by applicant): Prostate cancer (PCA) is the most common non-skin cancer and the second leading cause of cancer death in American men, with over 186,000 new cases diagnosed and over 28,000 PCA deaths annually in the United States. Ultrasound-guided biopsy is the standard of care for confirming cancer, typically following elevated PSA levels; however, it has been estimated that up to 20% of men require three or more biopsy sessions for diagnosis, and biopsies have a high risk of hemorrhage and infection. Furthermore, biopsies are not sufficient for tumor delineation or characterization because they sparsely sample the entire organ. Regretfully, the deficiencies of biopsy have lead to over-treatment of indolent disease with radical prostatectomies, a drastic treatment that has significant risks of infection, hemorrhage, urinary incontinence, and impotence. We are the inventors of Acoustic Radiation Force Impulse (ARFI) imaging and the inventors of Shear Wave Elasticity Imaging (SWEI) methods. We have now combined those methods into ARFI-SWEI imaging sequences that define a new and novel multi-parametric ultrasonic elasticity imaging system. This multi-parametric elasticity imaging approach provides an absolute, quantitative measure of tissue stiffness, at high resolution, in 3D, using ultrasound. We hypothesize that synergistic diagnostic information from B-mode, ARFI-SWEI and multi-parametric MRI (mpMRI, e.g., diffusion weighted imaging and MR spectroscopy imaging) enable (a) the sensitive and specific diagnosis of PCA and (b) the accurate delineation of PCA margins. We propose retrospective studies on existing 3D B-mode, ARFI-SWEI and mpMRI imaging datasets to test this hypothesis. 1
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A Computational Framework for Distributed Registration of Massive Neuroscience Images
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  • 项目类别:
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  • 项目类别:
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  • 项目类别:
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  • 依托单位:
海外基金