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: 10647788
• 负责人: Jonathan T.C. Liu
• 金额: $ 60.92万
• 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/10647788
• 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; 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; Recurrent disease; Resolution; Risk; Risk Assessment; Sampling; Serinus; Slide; Specimen; Structure; System; Technology; Three-dimensional analysis; Tissue Sample; Tissues; Training; Universities; Urologist; Validation; Visual; Washington; 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; prostate surgery; 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.

概括。前列腺癌（PCA）治疗管理目前非常依赖基于幻灯片的 前列腺活检和手术标本（前列腺切除术）的组织学。特别是格里森等级 组织学部分为对临床管理进行分层的基础提供了基础，并可能导致急剧 不同的治疗路径。但是，通过格里森（Gleason）等级提示有几个缺点， 包括基于2D图像的复杂3D腺形态的主观视觉解释，以及 分析有限量的组织（约1％的活检）。这些缺点导致了不良观察者 病理学家的一致性与致命疾病的患者分层不良。为了 PCA的临床管理，分别是泌尿科医生和肿瘤学家面临的两个主要挑战，是：（1） 正确识别患有低风险PCA的男性进行主动监视，（2）确定可能有 治疗治疗后的疾病复发和转移（手术或放射线），因此将受益于 辅助治疗。借助我们的开放式灯罩（OTLS）显微镜技术，我们的团队在大学 华盛顿（刘集团）证明了实现高通量幻灯片3D的技术可行性 活检和手术标本的组织学以不破坏和可逆的方式不干扰 使用当前的组织学方法。对传统病理学的潜在好处包括：（1）全面成像 标本（活检和手术面包面包），而不是对载玻片上的薄部分的稀疏采样； （2）预后的3D结构的体积成像； （3）非破坏性成像，这允许 可用于下游测定的有价值的活检标本。我们的凯斯西部储备大学的团队 （Madabhushi Group）还基于直观且可解释的开发了计算病理分类器 “手工制作的功能”，用于基于2D全扫描成像（WSI）的PCA侵略性表征。在 这个R01项目，我们试图将非破坏性3D病理与3D计算病理学方法相结合 为了开发一种新颖的预后测定，前列腺癌图像风险评分通过3D病理（Prosiris3d），用于 区分懒惰和侵略性PCA。在AIM 1中，我们将开发核心技术（硬件 和软件）prosiris3d。特别是，目标1a的目的是开发“第四代” OTLS显微镜 能够实现亚核分辨率的系统，以探索此类提供的额外预后益处 高分辨率功能。在AIM 1B中，将开发计算成像工具来提取新颖的3D PCA预后的定量组织形态计量学特征。我们的临床验证研究将表明 prosiris3d优于泌尿科医生的类似2D方法（AIM 2），以确定哪些新生活检 应将患者进行主动监测与治疗疗法以及肿瘤学家（AIM 3） 确定哪些前列腺切除术患者患有侵袭性疾病，可能需要调整疗法。