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.

摘要前列腺癌（PCa）治疗管理目前严重依赖于基于载玻片的 前列腺活检和手术标本（前列腺切除术）的组织学。特别是，Gleason分级 组织学切片为临床管理的患者分层提供了基础， 不同的治疗路径。然而，通过格里森分级的分级存在几个缺点， 包括基于2D图像的复杂3D腺体形态的主观视觉解释，以及 分析有限数量的组织（约1%的活检）。这些缺点导致观察者之间的沟通不畅 病理学家之间的一致性以及惰性与致命疾病患者的分层较差。为 前列腺癌的临床管理，泌尿科医生和肿瘤科医生分别面临的两个主要挑战是：（1） 正确识别低风险PCa男性进行积极监测，（2）识别可能患有PCa的男性 治愈性治疗（手术或放疗）后疾病复发和转移，因此将受益于 辅助治疗凭借我们的开放式光片（OTLS）显微镜技术，我们在密歇根大学的团队 华盛顿（Liu group）已经证明了实现高通量无载玻片3D 以无损和可逆的方式对活检和手术标本进行组织学检查， 用目前的组织学方法。与传统病理学相比的潜在优势包括：（1）全面的成像 标本（活组织检查和手术面包），而不是在载玻片上薄切片的稀疏采样; (2)3D结构的体积成像是预后的;和（3）非破坏性成像，其允许 有价值的活检标本用于下游检测。凯斯西储大学Case Western Reserve University （Madabhushi小组）还开发了计算病理学分类器，基于直观和可解释的 “手工制作的特征”，用于基于2D全载玻片成像（WSI）表征PCa侵袭性。在 在R 01项目中，我们寻求将联合收割机非破坏性三维病理学与三维计算病理学方法相结合 开发一种新的预后分析，通过3D病理学的前列腺癌图像风险评分（ProsIRiS 3D）， 区分惰性和侵袭性前列腺癌。在目标1中，我们将开发核心技术（硬件 和软件）的ProsIRiS 3D。具体而言，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，以探索这种系统提供的额外预后益处。 高分辨率特征。在目标1b中，将开发计算成像工具，用于提取新的3D 定量组织形态计量学特征用于PCa鉴别。我们的临床验证研究将表明， 对于泌尿科医生来说，ProsIRiS 3D上级类似的2D方法（目的2），以确定哪些新活检 患者应接受积极的监测与治疗，以及肿瘤学家（目标3）， 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。