Multiparametric transrectal ultrasound and photoacoustic imaging of human prostate

人前列腺多参数经直肠超声和光声成像

基本信息

批准号：
10651397
负责人：
Sri Rajasekhar Kothapalli
金额：
$ 38.69万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10651397
关键词：
Acoustics American Anatomy Animal Cancer Model Animal Model Artificial Intelligence Biological Markers Biopsy Biopsy Specimen Blood Blood Vessels Blood flow Cancer Patient Clinic Clinical Clinical Research Collaborations Devices Diagnosis Diagnostic Doppler Ultrasound Ensure FDA approved Functional Imaging Funding Goals Heterogeneity Human Hypoxia Image Image Guided Biopsy Imaging Techniques Imaging technology Indocyanine Green Indolent Intravenous Lesion Light Magnetic Resonance Imaging Malignant - descriptor Malignant Neoplasms Malignant neoplasm of prostate Maps Mechanics Microbubbles Modality Modeling Molecular Morphologic artifacts Multimodal Imaging Needle biopsy procedure Neoplasm Metastasis Operative Surgical Procedures PSA level Pathologic Patient-Focused Outcomes Patients Performance Phase I/II Clinical Trial Procedures Prostate Prostate Cancer therapy Prostatic Prostatic Neoplasms Radiation Research Role Sampling Screening for Prostate Cancer Sensitivity and Specificity Signal Transduction Specificity System Techniques Technology Test Result Time Tissues Translating Transrectal Ultrasound Ultrasonography Urology Visualization accurate diagnosis angiogenesis base cancer biomarkers cancer diagnosis cancer imaging clinically relevant clinically significant contrast enhanced cost denoising elastography experimental study human imaging human subject image guided imaging approach imaging biomarker imaging modality imaging platform imaging system improved in vivo in-vitro diagnostics liquid biopsy men molecular imaging mouse model multidisciplinary multiparametric imaging novel personalized medicine phantom model photoacoustic imaging portability pre-clinical prevent prostate biopsy prostate cancer model screening tissue mapping translational study tumor tumor progression ultrasound user-friendly

项目摘要

ABSTRACT Prostate cancer (PCa), with an annually increasing incident rate, has become the most commonly diagnosed cancer in American men. The accurate diagnosis of aggressive PCa is critical for the survival of patients. Transrectal ultrasound (TRUS) guided biopsy, the current standard procedure for evaluating the presence and aggressiveness of PCa, suffers from low core yield, leading to under-sampling and under-grading of clinically significant tumors. To fill the long-standing technical gap in PCa diagnosis, we propose to develop a novel multimodal imaging platform which integrates the emerging photoacoustic (PA) imaging technique with the established transrectal ultrasound (TRUS) for multiparametric PCa diagnosis and grading. With the unique capability to map structural/anatomical, mechanical, functional, and molecular information reflecting pathological conditions over the entire human prostate in vivo, non-invasively, the proposed TRUS and PA (i.e. TRUSPA) multiparametric imaging can sensitively detect spatially distributed prostate tumors and, more importantly, differentiate aggressive tumors from non-aggressive ones. Hence, multiparametric TRUSPA (mpTRUSPA), when performed in the same way as in current TRUS, could largely improve the guidance of biopsy sampling by ensuring highly effective core extraction within the most aggressive malignant regions of the prostate. The central hypothesis is that real-time mpTRUSPA imaging – displaying B-mode US based structural information, Power Doppler US based vascular flow, shear wave elastography (SWE) based tissue stiffness, and spectral PA images for mapping hypoxia and angiogenesis - can sensitively characterize cancer aggressiveness in vivo by mapping a group of structural, mechanical, and functional biomarkers of PCa, and can subsequently guide the biopsy sampling. This hypothesis will be objectively and rigorously examined via the proposed studies on clinically relevant PCa animal models and human subjects using the following specific aims: Aim 1: Develop and validate mpTRUSPA imaging system using studies on durable prostate mimicking phantoms and mouse models of aggressive and non-aggressive PCa. Aim 2: Develop and validate an artificial intelligence (AI) framework capable of signal denoising and localization, prostate segmentation, artifact correction, and spectral unmixing of deep tissue PAI signals in real-time. Aim 3: Validate a set of PCa imaging biomarkers that are accessible in vivo by the AI enhanced mpTRUSPA imaging system in a clinical setting. Once the performance of mpTRUSPA imaging of PCa is validated via the proposed studies on animal models and human subjects, this affordable and user-friendly technology will be ready for appropriate phase I/II clinical trials in the next funding cycle. TRUSPA, with the unique capability of detecting and differentiating clinically significant PCa non-invasively, in real time, can seamlessly fit into the current clinical procedure of image-guided biopsy, and holds great potential to shift the paradigm of PCa diagnosis.

抽象的前列腺癌（PCa）的发病率逐年增加，已成为最常见的诊断癌症准确诊断侵袭性前列腺癌对于患者的生存至关重要。经直肠超声 (TRUS) 引导活检是评估是否存在和存在的当前标准程序 PCa 的侵袭性，核心产量低，导致临床采样不足和分级不足为了填补 PCa 诊断中长期存在的技术空白，我们建议开发一种新型的方法。多模态成像平台，将新兴的光声（PA）成像技术与确立了经直肠超声（TRUS）对于PCa多参数诊断和分级的独特性。绘制反映病理的结构/解剖、机械、功能和分子信息的能力提议的 TRUS 和 PA（即 TRUSPA）以非侵入方式体内检测整个人类前列腺的状况多参数成像可以灵敏地检测空间分布的前列腺肿瘤，更重要的是，区分侵袭性肿瘤和非侵袭性肿瘤，因此，多参数 TRUSPA (mpTRUSPA)，当以与当前 TRUS 相同的方式进行时，可以通过以下方式很大程度上改善活检取样的指导：确保在前列腺最具侵袭性的恶性区域内进行高效的核心提取。中心假设是实时 mpTRUSPA 成像 – 显示基于 B 模式 US 的结构信息、基于能量多普勒超声的血管血流、基于剪切波弹性成像 (SWE) 的组织硬度、和光谱 PA 图像用于绘制缺氧和血管生成图 - 可以灵敏地表征癌症通过绘制一组 PCa 的结构、机械和功能生物标志物来确定体内攻击性，以及随后可以指导活检取样，该假设将通过客观和严格的检验。提出了针对临床相关 PCa 动物模型和人类受试者的研究，其具体目标如下：目标 1：利用耐用前列腺模拟体模的研究来开发和验证 mpTRUSPA 成像系统以及攻击性和非攻击性 PCa 的小鼠模型。目标 2：开发和验证人工智能。 (AI) 框架能够进行信号去噪和定位、前列腺分割、伪影校正以及实时对深层组织 PAI 信号进行光谱分离目标 3：验证一组 PCa 成像生物标志物。可以在临床环境中通过人工智能增强的 mpTRUSPA 成像系统在体内访问。一旦通过动物模型的拟议研究验证了前列腺癌 mpTRUSPA 成像的性能和人类受试者，这种负担得起且用户友好的技术将为适当的 I/II 期临床做好准备 TRUSPA 具有独特的临床检测和区分能力。显着的 PCa 非侵入性、实时性，可以无缝地融入当前图像引导的临床流程活检，并具有改变 PCa 诊断范式的巨大潜力。