Prostate-cancer Imaging by Combined Ultrasound and Magnetic-resonance Parameters

描述（由申请人提供）：滨江研究所、Beth Israel Deaconess医学中心、罗格斯大学和通用电气公司提议进行学术-工业合作研究，以显著改善前列腺癌（PCA）成像，从而改善前列腺活检指导以检测PCa;增强PCa的监测、监视和治疗;并实现局灶性PCa治疗的规划和执行。该项目意义重大，因为它解决了美国和其他发达国家的一个重大健康问题。该项目将克服现有临床成像方法无法通过以临床有效的方式结合先进的超声（US）和磁共振（MR）技术来可靠地对PCa进行成像的问题。所提出的方法将利用US对微观尺度上的组织的机械特性的敏感性以及MR对组织的化学成分的敏感性及其感测血液分布的能力。这些模态中的每一种都感测组织的不同和独立的性质，并且在单独使用时已经显示出改善PCa成像的令人鼓舞的潜力;组合从每一种模态导出的参数可以为PCa提供更优越的上级灵敏度和特异性。我们将使用高级分类器（如人工神经网络和支持向量机）将联合收割机US和MR参数结合起来。这些分类器已经为先进的US方法产生了0.91的ROC曲线面积，并且MR方法在许多研究中已经证明了等效的ROC曲线面积。我们将在原型成像系统的规格中体现综合功能，该原型成像系统可以实时生成前列腺组织分型图像（TTI），用于手术室或离线设置中的靶向活检或计划治疗。GE目前生产的最新Logiq E9仪器已经具备将先前获得的MR图像与US图像进行真实的融合的能力，这为结合US和MR参数并生成实时TTI提供了现有框架。基于联合US和MR参数成功生成可靠的前列腺TTI将通过显著改善PCa的诊断和治疗，代表PCa管理的巨大进步。 公共卫生相关性：滨江研究所、Beth Israel Deaconess医学中心、罗格斯大学和通用电气公司提议进行学术-工业合作研究，以显著改善前列腺癌（PCA）成像，从而改善前列腺活检指导;增强PCa的监测、监视和治疗;并实现局灶性PCa治疗的规划和执行。该项目将结合联合收割机先进的超声和磁共振技术的属性，并将其体现在一个原型成像系统中，该系统能够生成实时可靠描述PCa的新型组织类型图像。

DESCRIPTION (provided by applicant): Riverside Research Institute, Beth Israel Deaconess Medical Center, Rutgers University, and the General Electric Corporation propose to undertake an Academic-Industrial Partnership study to improve prostate- cancer (PCA) imaging markedly and thereby improve prostate-biopsy guidance to detect PCa; enhance monitoring, surveillance, and treatment of PCa; and enable planning and execution of focal PCa therapy. The project is highly significant because it addresses a major health problem in the United States and other developed countries. The project will overcome the current inability of established clinical-imaging method to image PCa reliably by combining the capabilities of advanced ultrasound (US) and magnetic-resonance (MR) techniques in a clinically effective manner. The proposed approach will exploit the sensitivity of US to mechanical properties of tissue on a microscopic scale with the sensitivity of MR to chemical constituents of tissue and its ability to sense blood distribution. Each of these modalities senses different and independent properties of tissue and has shown encouraging potential for improved imaging of PCa when used alone; combining parameters derived from each modality can provide far superior sensitivity and specificity for PCa. We will combine US and MR parameters using advanced classifiers such as artificial neural networks and support-vector machines. These classifiers already have produced ROC-curve areas of 0.91 for advanced US methods, and the MR methods have demonstrated equivalent ROC-curve areas in many studies. We will embody the combined capabilities in specifications for a prototype imaging system that can generate prostate tissue-typing images (TTIs) in real-time for targeting biopsies or planning treatment in the operating room or in an off-line setting. The latest Logiq E9 instrument currently being produced by GE already has a capability for fusing previously obtained MR images with US images in real time, which provides an existing framework for combining US and MR parameters and generating real-time TTIs. Successfully generating reliable prostate TTIs based on combined US and MR parameters will represent a quantum advance in PCa management by enabling significant improvements in the diagnosis and treatment of PCa. PUBLIC HEALTH RELEVANCE: Riverside Research Institute, Beth Israel Deaconess Medical Center, Rutgers University, and the General Electric Corporation propose to undertake an Academic-Industrial Partnership study to improve prostate- cancer (PCA) imaging markedly and thereby improve prostate-biopsy guidance; enhance monitoring, surveillance, and treatment of PCa; and enable planning and execution of focal PCa therapy. The project will combine attributes of advanced ultrasound and magnetic-resonance techniques and embody them in a prototype imaging system capable of generating novel tissue-type images that reliably depict PCa in real-time.