Computerized histologic image predictor of cancer outcome

癌症结果的计算机组织学图像预测器

• 批准号: 9305968
• 负责人: MICHAEL D FELDMAN
• 金额: $ 62.5万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9305968
• 关键词: Adjuvant; Adjuvant Chemotherapy; Adoption; Age; Agreement; Algorithms; Appearance; Architecture; Behavior; Biological Assay; Biological Markers; Biopsy; Breast; Breast Cancer Patient; Cancer Diagnostics; Cells; Clinical; Clinical Trials; Computer Assisted; Computer Vision Systems; Computer software; Computers; Country; Cues; Data; Development; Diagnosis; Diagnostic tests; Disease; Disease Outcome; Disease Progression; Distant; Early Diagnosis; Eastern Cooperative Oncology Group; Elements; Epigenetic Process; Estrogen receptor positive; Europe; Excision; Exhibits; Gene Expression; Gene Expression Profiling; Gene Proteins; Genetic Heterogeneity; Genomics; Goals; Guidelines; Head Cancer; Health; Hematoxylin and Eosin Staining Method; Histologic; Histopathology; Image; Image Analysis; Incidence; Income; Industrialization; Interobserver Variability; Joints; Malignant Neoplasms; Malignant neoplasm of cervix uteri; Malignant neoplasm of prostate; Measurement; Molecular; Morphology; Mutation; National Surgical Adjuvant Breast and Bowel Project; Neck Cancer; Nuclear; Operative Surgical Procedures; Outcome; Pathologic; Pathologist; Pathology; Patients; Performance; Phenotype; Positive Lymph Node; Production; Randomized Clinical Trials; Reading; Recurrence; Regulatory Pathway; Research; Resources; Reverse Transcriptase Polymerase Chain Reaction; Risk; Running; Shapes; Signal Transduction; Slide; Specimen; Staining method; Stains; Sum; System; Tamoxifen; Techniques; Technology; Telepathology; Texture; Time; Tissue imaging; Tissues; Treatment outcome; Tumor Biology; Visual; Woman; base; behavioral response; cancer cell; cancer imaging; chemotherapy; cohort; companion diagnostics; computerized; digital; disorder risk; histological image; histological specimens; hormone therapy; industry partner; malignant breast neoplasm; neoplastic cell; outcome prediction; prognostic assays; prototype; response; translation assay; treatment response; treatment strategy; tumor; tumor heterogeneity

SUMMARY: There is an increased need for predictive and prognostic assays to distinguish more and less aggressive phenotypes of cancer due to A) dramatic increase in cancer incidence and; B) improvements in early diagnosis. Predictive assays in particular will allow for patients with less aggressive disease to be spared more aggressive treatment. Most prognostic tests in the US and Europe are based on gene expression assays (e.g. Oncotype DX (ODx)). Recent studies have shown extensive genetic heterogeneity among cancer cells between tumors and even within the same tumor, suggesting that approaches for recommending therapy for a patient based on the “average” molecular signal of many cells are overly simplistic. Interestingly, for a number of cancers, tumor grade (morphologic appearance on tissue as assessed qualitatively or semi-quantitatively by a pathologist) has been found to be highly correlated with disease outcome. However pathologic grade tends to suffer from significant inter-observer variability. Digitzation of histological samples, or whole slide imaging, facilitates a quantitative approach towards evaluating disease progression and predicting outcome, while also facilitating the adoption of telepathology. Recently, research groups (including our own) have begun to show that computer extracted measurements of tumor morphology (e.g. capturing nuclear orientation, texture, shape, architecture) from routine H&E stained cancer tissue images can predict disease aggressiveness and treatment outcome. By computationally interrogating the entire tumor landscape and its most invasive elements from a standard H&E slide, these approaches can allow for more accurate capture of tumor heterogeneity, disease risk and hence the most appropriate treatment strategy. The goal of this academic-industrial partnership is to develop and validate a computerized histologic image-based predictor (CHIP) to identify which early-stage, estrogen receptor positive (ER+) breast cancer patients are candidates for hormonal therapy alone and which women are candidates for adjuvant chemotherapy based off analysis of the pathology slides derived from biopsy and surgical specimens. Inspirata Inc., a cancer diagnostics company which has recently licensed a number of histomorphometry based technologies from the Madabhushi group, will bring quality management systems and production software standards to help create a pre-commercial companion diagnostic test of the CHIP assay. Additionally Inspirata Inc. will build a complete regulatory pathway for successful translation of the assay in the US and abroad. Finally, the pre-commercial prototype of the CHIP assay will be independently validated using the same strategy and data cohorts as ODx. Our approach has several advantages over molecular assays such as ODx in that it (1) can interrogate the entire expanse of the pathology image enabling a more accurate capture of tumor heterogeneity and hence disease risk, (2) is non-disruptive of pathology workflow, (3) non-destructive of tissue and would be substantially (4) cheaper (critical in low to middle income countries) and (5) faster.

摘要：对预测性和预后评估的需求越来越多，以区分越来越小的 由于a）癌症事件的巨大增加而引起的癌症的侵略性表型； b）进步 早期诊断。特别是预测性测定将使侵略性较低的患者幸免 更具积极的治疗。美国和欧洲的大多数预后测试都是基于基因表达测定法 （例如Oncotype DX（ODX））。最近的研究表明，癌细胞之间广泛的遗传异质性 在肿瘤乃至同一肿瘤内之间，这表明建议治疗 基于许多细胞的“平均”分子信号的患者过于简单。 有趣的是，对于许多癌症，肿瘤等级（如评估的组织形态学外观 病理学家的定性或半量化）已发现与疾病高度相关 结果。但是，病理级倾向于患有明显的观察者间变异性。数字化 组织学样本或整个幻灯片成像，有助于评估疾病的定量方法 进步和预测结果，同时还支持采用心脏病学。最近，研究 组（包括我们自己的组）已经开始表明计算机提取了肿瘤形态的测量值 （例如，从常规的H＆E染色癌组织图像捕获核方向，质地，形状，体系结构） 可以预测疾病的侵略性和治疗结果。通过计算询问整个肿瘤 景观及其来自标准H＆E幻灯片的最具侵入性元素，这些方法可以允许更多 准确捕获肿瘤异质性，疾病风险，因此是最合适的治疗策略。 这种学术工业合作伙伴关系的目的是开发和验证计算机化的组织学 基于图像的预测因子（芯片），以确定哪个早期雌激素受体阳性（ER+）乳腺癌 患者是仅接受激素治疗的候选者，哪些女性是调整的候选者 化学疗法基于对活检和手术标本衍生的病理载玻片的分析。 Inspirata Inc.，一家癌症诊断公司，最近获得了许多基于组织形态的许可 Madabhushi集团的技术将带来质量管理系统和生产软件 有助于创建芯片分析的商业前伴侣诊断测试的标准。此外，Inspirata Inc.将建立完整的监管途径，以成功地翻译美国和国外的测定法。 最后，将使用相同 策略和数据队列作为ODX。我们的方法比ODX等分子测定具有多种优势 它（1）可以审问病理图像的整个扩张，从而更准确地捕获 肿瘤异质性，因此疾病风险，（2）对病理工作流程无破坏，（3） 组织，并且会更便宜（在低收入国家至少至关重要）和（5）更快。