Prostate cancer risk stratification via computational 3D pathology

通过计算 3D 病理学进行前列腺癌风险分层

• 批准号: 10459767
• 负责人: Jonathan T.C. Liu
• 金额: $ 62.44万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10459767
• 关键词: 3-Dimensional; Adjuvant Therapy; Archives; Biochemical; Biological Assay; Biopsy; Biopsy Specimen; Bread; Categories; Classification; Clinic; Clinical; Clinical Management; Complex; Computer software; Computing Methodologies; Data; Data Set; Development; Diagnostic; Disease; Excision; Gene Expression Profiling; Generations; Genitourinary system; Glass; Gleason Grade for Prostate Cancer; Goals; Guidelines; Hand; Histology; Histopathology; Image; Imaging Device; Indolent; Intuition; Light; Localized Disease; Magnetic Resonance Imaging; Malignant neoplasm of prostate; Methods; Microscope; Microscopic; Microscopy; Microtomy; Modeling; Molecular; Morphology; National Comprehensive Cancer Network; Neoplasm Metastasis; Nomograms; Nuclear; Oncologist; Oncology; Operative Surgical Procedures; Optics; Outcome; Pathologist; Pathology; Patients; Pennsylvania; Performance; Phenotype; Prognostic Marker; Prostate; Prostate Cancer therapy; Prostatectomy; Public Health; Radiation; Radical Prostatectomy; Recurrence; Resolution; Risk; Sampling; Serinus; Slide; Specimen; Structure; System; Technology; Three-dimensional analysis; Tissue Sample; Tissues; Training; Universities; Urologist; Validation; Visual; Washington; base; cancer imaging; cellular imaging; clinical risk; curative treatments; feature extraction; improved; innovation; instrumentation; men; novel; patient stratification; predictive marker; preservation; prognostic; prognostic assays; prognostic value; prognostication; prostate biopsy; prostate cancer risk; prototype; risk stratification; success; surgical risk; surveillance imaging; three dimensional structure; tool; validation studies; whole slide imaging

Summary. Prostate cancer (PCa) treatment management is currently heavily reliant upon slide-based histology of prostate biopsies and surgical specimens (prostatectomies). In particular, Gleason grading of histology sections provides a basis for stratifying patients for clinical management, and can result in dramatically different treatment paths. However, prognostication via Gleason grading suffers from several shortcomings, including subjective visual interpretation of complex 3D glandular morphologies based on 2D images, and analysis of a limited amount of tissue (~1% of the biopsy). These shortcomings contribute to poor inter-observer concordance amongst pathologists and poor stratification of patients with indolent vs. lethal disease. For the clinical management of PCa, two major challenges faced by urologists and oncologists, respectively, are: (1) correctly identifying men with low-risk PCa for active surveillance and (2) identifying men who are likely to have disease recurrence and metastasis after curative therapy (surgery or radiation), and hence would benefit from adjuvant therapy. With our open-top light-sheet (OTLS) microscope technologies, our team at the University of Washington (Liu group) has demonstrated the technical feasibility of achieving high-throughput slide-free 3D histology of biopsy and surgical specimens in a nondestructive and reversible manner that does not interfere with current histology methods. Potential benefits over traditional pathology include: (1) comprehensive imaging of specimens (biopsies and surgical bread loafs) rather than sparse sampling of thin sections on glass slides; (2) volumetric imaging of 3D structures that are prognostic; and (3) non-destructive imaging, which allows valuable biopsy specimens to be used for downstream assays. Our team at Case Western Reserve University (Madabhushi group) has also developed computational pathology classifiers, based on intuitive and interpretable “hand-crafted features,” for characterization of PCa aggressiveness based on 2D whole-slide imaging (WSI). In this R01 project, we seek to combine nondestructive 3D pathology with 3D computational pathology approaches to develop a novel prognostic assay, Prostate cancer Image Risk Score via 3D pathology (ProsIRiS3D), for discriminating between indolent and aggressive PCa. In Aim 1, we will develop the core technologies (hardware and software) for ProsIRiS3D. In particular, the goal of Aim 1a is to develop a “4th-generation” OTLS microscopy system capable of achieving sub-nuclear-resolution to explore the added prognostic benefit provided by such high-resolution features. In Aim 1b, computational imaging tools will be developed for extraction of novel 3D quantitative histomorphometric features for PCa prognostication. Our clinical validation studies will show that ProsIRiS3D is superior to analogous 2D approaches for urologists (Aim 2), to determine which newly biopsied patients should be placed on active surveillance vs. curative therapy, as well as for oncologists (Aim 3), to determine which prostatectomy patients have aggressive disease that may warrant adjuvant therapies.

总结。前列腺癌(PCA)的治疗管理目前严重依赖于幻灯片 前列腺活检和手术标本(前列腺切除术)的组织学。特别是，格里森评级 组织学切片为临床治疗的患者分层提供了基础，并可能导致显著的 不同的治疗路径。然而，通过格里森分级进行预测有几个缺点， 包括基于2D图像的复杂3D腺体形态的主观视觉解释，以及 对有限数量的组织进行分析(~1%的活检)。这些缺点导致观察员之间的互补性很差 病理学家之间的一致性和惰性与致命性疾病患者的不良分层。对于 PCa的临床管理分别是泌尿科医生和肿瘤科医生面临的两大挑战：(1) 正确识别患有低风险PCA的男性以进行主动监测，以及(2)识别可能患有 在根治治疗(手术或放射治疗)后疾病复发和转移，因此将受益于 辅助治疗。利用我们的开顶式光片(OTLS)显微镜技术，我们在加州大学的团队 华盛顿(刘集团)已经证明了实现高通量无幻灯片3D的技术可行性 活检和手术标本的组织学以不干扰的非破坏性和可逆的方式进行 用目前的组织学方法。与传统病理学相比，潜在的好处包括：(1)综合成像 对标本(活组织检查和外科面包)进行采样，而不是在玻片上进行稀疏的薄片采样； (2)可预测预后的3D结构的体积成像；以及(3)非破坏性成像，其允许 用于下游化验的有价值的活检标本。我们在凯斯西储大学的团队 (Madabhushi Group)还开发了基于直观和可解释的计算病理分类器 “手工制作的特征”，用于基于2D全幻灯片成像(WSI)表征PCA侵袭性。在……里面 在R01项目中，我们寻求将非破坏性3D病理学与3D计算病理学方法相结合 开发一种新的预后分析方法，前列腺癌三维病理图像风险评分(ProsIRiS3D)，用于 区分懒惰和咄咄逼人的PCA。在目标1中，我们将开发核心技术(硬件 和软件)用于ProsIRiS3D。具体地说，目标1a的目标是开发“第四代”OTLS显微镜 能够实现亚核分辨率的系统，以探索这种方法提供的额外预后益处 高分辨率功能。在目标1b中，将开发用于提取新的3D的计算成像工具 定量组织形态计量学特征用于PCa的预测。我们的临床验证研究将表明 对于泌尿科医生，ProsIRiS3D优于类似的2D方法(Aim 2)，以确定哪些新的活检 应对患者和根治疗法以及肿瘤学家(目标3)进行积极监测，以 确定哪些前列腺切除术患者有可能需要辅助治疗的侵袭性疾病。