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）每年增加入射率，已成为最常见的诊断美国男性的癌症。侵略性PCA的准确诊断对于患者的存活至关重要。经直肠超声（TRUS）引导活检，这是评估存在和的当前标准程序 PCA的侵略性，核心产量低，导致临床上的采样和上层重要的肿瘤。为了填补PCA诊断中的长期技术空白，我们建议开发一种小说多模式成像平台将新兴的光声（PA）成像技术与用于多参数PCA诊断和分级的转直直肠超声（TRU）。与独特绘制结构/解剖学，机械，功能和分子信息的能力，反映了病理整个人类前列腺的条件在体内，非侵入性，拟议的trus和pa（即truspa）多参数成像可以灵敏地检测空间分布的前列腺肿瘤，更重要的是将侵袭性肿瘤与非侵入性肿瘤区分开。因此，多参数truspa（mptruspa），当以与当前TRU中相同的方式执行时，可以在很大程度上通过确保前列腺最具侵略性的恶性区域内的高效核心提取。中心假设是实时MPTRUSPA成像 - 显示基于B模式的结构信息，基于US的动力多普勒血管流，基于剪切波弹性图（SWE）的组织刚度，用于映射缺氧和血管生成的光谱PA图像 - 可以灵敏地表征癌症通过映射PCA的一组结构，机械和功能生物标志物，并在体内进行侵略性随后可以指导活检采样。该假设将通过提出了针对临床相关的PCA动物模型和人类受试者的拟议研究：使用以下特定目的： AIM 1：使用模仿PROSTATE的研究来开发和验证MPTRUSPA成像系统以及侵略性和非攻击性PCA的鼠标模型。目标2：开发和验证人工智能（AI）能够信号定位和定位，前列腺分割，伪影校正和实时对深组织PAI信号的光谱拆解。目标3：验证一组PCA成像生物标志物在临床环境中，AI增强的MPTRUSPA成像系统可以在体内访问。一旦通过对动物模型的拟议研究验证了PCA的MPTRUSPA成像和人类受试者，这项负担得起且用户友好的技术将准备好进行适当的I/II期临床在下一个资金周期中进行的试验。 TRUSPA，具有检测和临床区分的独特能力实时非侵入性的PCA可以无缝地适合当前图像引导的临床程序活检，并具有改变PCA诊断范式的巨大潜力。