Quantitative histopathology for cancer prognosis using quantitative phase imaging on stained tissues

使用染色组织的定量相位成像进行癌症预后的定量组织病理学

• 批准号: 9977150
• 负责人: Kevin William Eliceiri
• 金额: $ 49.7万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-12 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9977150
• 关键词: Algorithms; Architecture; Attention; Basement membrane; Biological Assay; Biological Markers; Biopsy; Blood; Breast; Calibration; Cancer Prognosis; Classification; Clinic; Collagen Fiber; Collection; Color; Desmoplastic; Development; Diagnostic; Disease Marker; Early Diagnosis; Epidermal Growth Factor Receptor; Epithelial; Epithelium; Estrogen Receptors; Goals; Gold; Health; Histopathology; Human; Image; Imaging Device; Imaging technology; Institutes; Interference Microscopy; Interobserver Variability; Investigation; Light; Malignant Neoplasms; Mammary Neoplasms; Maps; Measures; Mediating; Methodology; Microscope; Microscopic; Microscopy; Molecular; Morphologic artifacts; Morphology; Mosaicism; Non-Malignant; Operative Surgical Procedures; Optics; Outcome; Pathologist; Pathology; Patient Care; Patient risk; Patients; Performance; Phase; Physicians; Preparation; Procedures; Progesterone Receptors; Prognostic Marker; Prostate; Quantitative Microscopy; Research; Risk stratification; Role; Scanning; Signal Transduction; Site; Slice; Slide; Specimen; Stains; TP53 gene; Techniques; Technology; Testing; Thick; Time; Tissue Stains; Tissues; Training; Translating; Treatment Protocols; Treatment outcome; Tumor Cell Invasion; Tumor-Derived; Wisconsin; Woman; Work; automated segmentation; base; biomarker evaluation; cancer cell; clinically relevant; diagnostic accuracy; image processing; imaging biomarker; immunohistochemical markers; improved; instrument; malignant breast neoplasm; microscopic imaging; nanoscale; new technology; novel; outcome forecast; outcome prediction; pathology imaging; personalized medicine; prognostic; prognostic tool; prototype; response; tool; tumor initiation; tumor microenvironment; whole slide imaging

Project Summary About 1 in 8 U.S. women will develop invasive breast cancer over the course of her lifetime. Early diagnosis and prognosis are key to improving health outcomes. Prognostic markers in tissue biopsies help clinicians make treatment decisions and refine the patient risk stratification. New research expands the current prognostic markers to better deliver personalized treatment regimens. However, the variability of preanalytical factors (biopsy collection, processing and storage) can have a significant impact on biomarkers evaluation which can result in potentially serious consequences in terms of patient care. There is an identified need for developing clinically relevant biomarkers that are invariant to biospecimen preparation. This project proposes a technical solution to extracting intrinsic tissue morphology information, unaffected by variability in tissue staining, slice thickness, or sectioning errors. Spatial Light Interference Microscopy (SLIM) was shown to provide prognostic markers derived from tumor microenvironment using nanoscale organization of the non-malignant tissue adjacent to cancer cells, i.e., the stromal response to cancer. Preliminary results indicate that SLIM can distinguish between pairs of “matched” patients (good vs. bad outcome) and has the capability to eliminate false positives and help the clinician assign the appropriate treatment. For this project, we will validate color SLIM (cSLIM) capabilities as a prognostic tool for existing, stained histopathology slides. cSLIM will render simultaneously bright field and quantitative phase images, in a single scan. cSLIM will be implemented in a whole slide imaging (WSI) instrument with the color bright field image familiar to pathologists, while maintaining a stain-independent signal, which has intact prognosis value. The WSI instrument’s high sensitivity to stroma and collagen fibers will be used to develop robust markers for breast prognosis, which are independent of tissue slice thickness, color variability within the same stain type (say, H & E), and across stains (H & E, various immunochemical stains, etc). With this new instrument, we will test the staining-invariance performance on 196 TMA cases and validate with 300 biopsies. The work is the results of combining expertise in imaging, pathology, and image processing across four sites: UIUC Beckman Institute, the Mills Breast Cancer Institute in Urbana, UIC Pathology, and U. Wisconsin.

项目摘要 在她一生中，大约有8个女性将患上侵入性乳腺癌。早期诊断 预后是改善健康结果的关键。组织活检中的预后标记有助于临床医生 做出治疗决策并完善患者的风险分层。新研究扩大了当前 预后标记以更好地提供个性化的治疗方案。但是，精髓的变异性 因素（活检，加工和存储）可能对生物标志物评估产生重大影响 这可能会导致患者护理的潜在严重后果。有确定的需求 开发临床上相关的生物标志物，这些生物标志物是生物循环制剂不变的。 该项目提出了一种技术解决方案，用于提取固有的组织形态信息，不受 组织染色，切片厚度或切片误差的变异性。空间光干扰显微镜 （纤细）显示使用使用肿瘤微环境衍生的预后标记 与癌细胞相邻的非恶性组织的纳米级组织，即基质反应 癌症。初步结果表明，Slim可以区分成对的“匹配”患者（良好VS。 不良结果）并具有消除误报的能力并帮助临床分配适当的 治疗。 对于此项目，我们将验证颜色纤细（CSLIM）功能，作为现有的预后工具 染色的组织病理学幻灯片。 CSLIM将简单地呈现明亮的场和定量阶段 图像，一次扫描。 CSLIM将以颜色的整体幻灯片成像（WSI）仪器实施 病理学家熟悉的明亮现场图像，同时保持独立的信号，该信号完好无损 预后价值。 WSI仪器对基质和胶原蛋白纤维的高敏感性将用于开发 乳房预后的鲁棒标记，与组织切片厚度无关，颜色可变性 相同的污渍类型（例如H＆E），以及跨污渍（H＆E，各种免疫化学污渍等）。有了这个新的 仪器，我们将测试196个TMA病例的染色不变性能，并用300验证 活检。这项工作是结合跨成像，病理和图像处理方面的专业知识的结果 四个地点：UIUC Beckman Institute，Urbana，UIC病理学和U. 威斯康星州。