Detecting Prostate Cancer using multi-protocol 3 Tesla in vivo MRI and MRS

描述(申请人提供)：Pi：Madabhushi，Anant早期发现前列腺癌(CAP)提供了治愈它的最大希望。目前，确定诊断CAP的唯一方法是对切除的组织进行组织学分析，这些组织是通过六分仪经直肠超声(TRUS)引导的盲法活检获得的。然而，对于升高的PSA水平，TRUS活检的准确率只有20%-25%。最近，高分辨率磁共振(MR)成像(MRI)在显示前列腺结构方面优于超声。计算机辅助诊断(CAD)是指使用计算机程序来帮助放射科医生从放射图像中检测异常。该项目的目的是开发一种从多协议3特斯拉体内MRI和磁共振波谱成像(MRSI)中检测前列腺癌的CAD系统。与MRI相关的最初较高的成本将被不必要的活检减少和通过活检发现的癌症数量的增加所抵消。这项工作的长期目标是促进高分辨率MRI/MRSI的CAD的使用：-1.在中高危患者中早期发现CAP，从而减少不必要的活检和根治性前列腺切除术的数量。2.通过用CAD辅助MRI引导的前列腺活检取代TRUS来提高癌症的发现率。3.用于改善前列腺治疗中的目标剂量一致性。4.用于评估对抗癌治疗的定量反应。拟开展的工作共包括3个具体目标和10项任务。将获得40个匿名患者数据集，其中包括前列腺切除前的多协议3Tesla(T)在体MRI/MRSI扫描和前列腺癌切除后伴随的整体组织切片的多协议3T体外MRI/MRSI扫描(目标1)。每个患者的研究将得到四种不同的磁共振成像方案--T1加权成像、T2加权成像、动态对比增强成像和扩散成像。组织学数据的纳入将允许通过H&E染色精确确定CAP区域。为了训练CAD系统在活体MRI上自动识别CAP，需要准确地确定活体肿瘤的空间位置。目的2通过将完整的组织切片与相应的体外MRI图像配准，确定活体内肿瘤地面真实性的空间范围。一旦CAP在体外MRI上的空间位置被确定后，这些图像就会与相应的在体MRI研究配准。目的3建立和评价在高分辨率在体MRI和MRSI研究中检测CAP的CAD系统。这个项目将是罗格斯大学和宾夕法尼亚大学(UPenn)的研究人员共同努力的成果。目标1(数据生成)将在宾夕法尼亚大学进行，而目标2(肿瘤地面真相生成)和目标3(CAD模型)将在罗格斯大学进行。1 PI：Madabhushi，即前列腺癌(CAP)是男性中第二常见的恶性肿瘤，2004年美国估计有23万新病例。在美国，目前诊断CAP的方案是让前列腺特异性抗原(PSA)水平升高的患者接受经直肠超声(TRUS)引导的活检。然而，几项研究已经报道：(1)单独使用PSA作为筛查试验会导致大量不必要的活检；(2)与TRUS相关的假阴性率很高。本工作的目标是将计算机辅助诊断(CAD)与多方案高分辨率活体磁共振成像(MRI)和磁共振波谱成像(MRSI)相结合，以提高前列腺癌检测的敏感性和特异性。这项拟议的工作通过指导治疗被CAD确定为肿瘤的特定区域，在结构(尿路和直肠壁)中具有翻译意义。

DESCRIPTION (provided by applicant): PI: Madabhushi, Anant Early detection of prostatic adenocarcinoma (CAP) offers the best hope of curing it. Currently, the only way to definitively diagnose CAP is through histological analysis of excised tissue, obtained via blind sextant trans-rectal ultrasound (TRUS)-directed biopsies. However, the accuracy of TRUS biopsies is only 20-25% for elevated PSA levels. Recently, high-resolution magnetic resonance (MR) imaging (MRI) has been shown to be superior to ultrasound in visualizing prostatic structures. Computer-aided diagnosis (CAD) refers to the use of computer programs in assisting radiologists detect abnormalities from radiological images. The aim of this project is to develop a CAD system to detect prostate cancer from multi-protocol 3 Tesla in vivo MRI and Magnetic Resonance Spectroscopic (MRS) Imaging (MRSI). The initial higher costs associated with MRI will be offset by a reduction in unnecessary biopsies and an increase in the number of cancers detected via biopsy. The long term goals of this work are to motivate use of CAD with high resolution MRI/MRSI:- 1. For early detection of CAP in moderate to high risk patients and thereby reduce the number of unnecessary biopsies and radical prostatectomies. 2. Improving cancer detection rates by replacing TRUS with CAD-assisted MRI guided prostate biopsies. 3. For improved target dose conformality in prostate therapy. 4. For assessing quantitative response to anti-cancer therapy. The proposed work comprises a total of 3 specific aims and 10 tasks. A total of 40 anonymised patient data sets comprising multi-protocol 3 Tesla (T) in vivo MRI/MRSI scans before and multi-protocol 3 T ex vivo MRI/MRSI scans with accompanying whole mount histological sections after prostatectomy will be obtained (Aim 1). Four different MR protocols will be obtained for each patient study -- T1-, T2-weighted, dynamic contrast-enhanced, and diffusion imaging. The inclusion of histological data will allow for precise determination of CAP regions via H&E staining. In order to train the CAD system to automatically identify CAP on in vivo MRI accurate determination of spatial location of cancer in vivo is required. Aim 2 involves determination of spatial extent of CAP (tumor ground truth) in vivo by first registering the whole mount histological sections with the corresponding ex vivo MRI images. Once the spatial location of CAP has been thus determined on ex vivo MRI, these images are then registered with the corresponding in vivo MRI studies. Aim 3 involves building and evaluating the CAD system for detecting CAP on the high resolution in vivo MRI and MRSI studies. This project will be a collaborative effort between investigators at Rutgers University and the University of Pennsylvania (UPENN). Aim 1 (Data Generation) will be carried out at UPENN while Aims 2 (Tumor ground truth generation) and 3 (CAD model) will be done at Rutgers. 1 PI: Madabhushi, Anant Prostatic adenocarcinoma (CAP) is the second most common malignancy among men with an estimated 230,000 new cases in the USA in 2004. The current protocol to diagnose CAP in the USA is to have patients with elevated prostate specific antigen (PSA) levels undergo a trans-rectal ultrasound (TRUS)-directed biopsy. However, several studies have reported (1) that using PSA alone as a screening test results in a large number of unnecessary biopsies and (2) there is a high false negative rate associated with TRUS. The goal of this work is to integrate computer-aided diagnosis (CAD) with multi-protocol high resolution in vivo Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopic Imaging (MRSI) in order to increase the sensitivity and specificity of prostate cancer detection. The proposed work has translational implications in, structures (urethra and rectal wall) by directing therapy towards specific areas determined as tumor by CAD.