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

 描述(申请人提供)：前列腺癌(PCA)是美国男性最常见的非皮肤癌，也是导致癌症死亡的第二大原因，在美国每年有超过18.6万例新诊断病例和超过2.8万例前列腺癌死亡。超声引导的活检是确认癌症的标准护理，通常是在PSA水平升高后；然而，据估计，多达20%的男性需要三次或更多活检才能诊断，而且活检有很高的出血和感染风险。此外，活组织检查不足以描绘或描述肿瘤，因为它们稀少地对整个器官进行采样。遗憾的是，活检的不足导致了根治性前列腺切除术对惰性疾病的过度治疗，这种激进的治疗方法具有感染、出血、尿失禁和阳萎的显著风险。我们是声辐射力脉冲(ARFI)成像的发明者，也是剪切波弹性成像(SWII)方法的发明者。我们现在已经将这些方法结合到Arfi-Swei成像序列中，定义了一种新的、新的多参数超声弹性成像系统。这种多参数弹性成像方法使用超声波，以高分辨率、3D形式提供组织硬度的绝对、定量测量。我们假设协同诊断 来自B型、ARFI-Swei和多参数磁共振成像(mpMRI，例如扩散加权成像和磁共振波谱成像)的信息使(A)对PCa的敏感和特异的诊断和(B)准确地描绘PCa的边缘。我们建议对现有的3DB型、ARFI-Swei和mpMRI成像数据集进行回顾性研究，以验证这一假设。1

 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