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

结合超声和磁共振参数的前列腺癌成像

基本信息

批准号：
8677765
负责人：
Ernest Joseph Feleppa
金额：
$ 55.35万
依托单位：
RIVERSIDE RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-08-09 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8677765
关键词：
Ablation Achievement Acoustics Address Adverse effects Area Atlas of Cancer Mortality in the United States Biological Neural Networks Biopsy Biopsy Specimen Bladder Blood Blood Vessels Chemicals Classification Clinical Cryosurgery Data Data Analyses Databases Developed Countries Development Diagnosis Diffusion Diffusion Magnetic Resonance Imaging Disease Disease Progression Disease regression Drug Formulations Engineering Frequencies Generations Gland Goals Health Histocompatibility Testing Histology Image Israel Lead Machine Learning Magnetic Resonance Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of prostate Mechanics Medical center Metabolic Methods Microscopic Modality Monitor Morphologic artifacts NIH Program Announcements Neoplasm Metastasis Nerve Operating Rooms Operative Surgical Procedures Patients Performance Perfusion Process Property Prostate Prostate Cancer therapy Prostate-Specific Antigen Prostatectomy Quantitative Evaluations ROC Curve Radio Radiosurgery Rectum Research Research Institute Resolution Risk Sensitivity and Specificity Serum Signal Transduction Specimen Spectrum Analysis Staging Structure of base of prostate Surface System Technical Expertise Techniques Technology Time Tissues Ultrasonography United States Universities Urethra Ursidae Family base blind cancer diagnosis cancer imaging cancer therapy computer aided detection computerized cost experience high risk image registration imaging modality improved instrument instrumentation interest lymph nodes novel outcome forecast prototype quantitative ultrasound quantum response standard care tool treatment planning tumor

项目摘要

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.

描述（由申请人提供）：河滨研究所、贝斯以色列女执事医疗中心、罗格斯大学和通用电气公司提议进行一项学术-工业合作研究，以显着改善前列腺癌（PCA）成像，从而改善前列腺活检前列腺癌检测指南；加强前列腺癌的监测、监测和治疗；并能够规划和执行局灶性 PCa 治疗。该项目非常重要，因为它解决了美国和其他发达国家的一个主要健康问题。该项目将以临床有效的方式结合先进的超声 (US) 和磁共振 (MR) 技术的功能，克服目前现有临床成像方法无法可靠地对 PCa 进行成像的问题。所提出的方法将利用 US 对微观尺度上组织机械特性的敏感性以及 MR 对组织化学成分的敏感性及其感知血液分布的能力。这些模式中的每一种都可以感知组织的不同且独立的特性，并且在单独使用时显示出改善 PCa 成像的令人鼓舞的潜力；结合从每种模态获得的参数可以为 PCa 提供远超优越的灵敏度和特异性。我们将使用先进的分类器（例如人工神经网络和支持向量机）结合 US 和 MR 参数。这些分类器已经为先进的 US 方法生成了 0.91 的 ROC 曲线面积，并且 MR 方法在许多研究中证明了等效的 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，该系统可以实时生成前列腺组织分型图像（TTI），用于在手术室或离线环境中进行靶向活检或规划治疗。 GE 目前生产的最新 Logiq E9 仪器已经能够将先前获得的 MR 图像与 US 图像实时融合，这为组合 US 和 MR 参数并生成实时 TTI 提供了现有框架。基于超声和磁共振参数的结合，成功生成可靠的前列腺 TTI，将显着改善 PCa 的诊断和治疗，从而代表 PCa 管理的巨大进步。