Computer-assisted Grading and Risk Stratification of Follicular Lymphoma

滤泡性淋巴瘤的计算机辅助分级和风险分层

• 批准号: 7812178
• 负责人: Metin Nafi Gurcan
• 金额: $ 31.59万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7812178
• 关键词: Accounting; Adopted; Adult; Aggressive Clinical Course; Agreement; Area; B-Cell Lymphomas; Biologic Characteristic; Biological; Cancer and Leukemia Group B; Cells; Centroblast; Classification; Clinic; Clinical; Clinical Trials; Collection; Communities; Computer Assisted; Computers; Data; Data Set; Databases; Detection; Development; Diagnosis; Diagnostic; Disease; Evaluation; Failure; Follicular Lymphoma; Genetic Markers; Goals; Histopathology; Image; Image Analysis; Indolent Clinical Course; Institution; Lymphoma; Morphology; Non-Hodgkin' s Lymphoma; Ohio; Outcome; Pathologist; Pathology; Patients; Performance; Private Practice; Process; Radiology Specialty; Reader; Research; Research Personnel; Resources; Risk; Scanning; Selection Bias; Site; Slide; Software Tools; Stratification; System; T-Lymphocyte; Techniques; Testing; Tissues; Toxic effect; United States; Universities; World Health Organization; base; chemotherapy; clinical practice; computer generated; computerized; design; digital; experience; high standard; improved; lymph nodes; macrophage; monocyte; outcome forecast; public health relevance; software development; tool; tumor

DESCRIPTION (provided by applicant): Follicular lymphoma (FL) is the second most common non-Hodgkin's lymphoma. Several treatment options exist today, but these are costly and include significant toxicities. No biological or genetic markers are available in clinical practice for reliable risk stratification of follicular lymphomas and the choice of appropriate treatment depends heavily on morphology-based histological grading. In a system adopted by the World Health Organization (WHO), follicular lymphomas are stratified into three grades depending on the average count of centroblasts in ten randomly selected, standard high-power fields (HPFs). Follicular lymphomas with low histological grades show an indolent clinical course with long average survival, but are considered incurable with currently available therapies. In contrast, high-grade follicular lymphomas have an aggressive clinical course and are rapidly fatal if not treated with aggressive chemotherapy. However, in contrast to low-grade follicular lymphoma, high-grade FL may be cured with aggressive chemotherapy. Currently, the inter-reader agreement between pathologists in grading FL is extremely low. In a multi-site study, the agreement among experts for the various grades of follicular lymphoma varied between 61% and 73%. Since only ten HPFs are used by the pathologist for practical reasons, this system may be prone to selection bias in cases that show significant differences in various areas of a section. The primary goal of this project is to develop an effective computer-aided system to assist pathologists in making diagnostic decisions about histological grading of follicular lymphoma. It is important to note that this project aims to provide supplementary information to the pathologist as he or she carries out the classification process; this is not an attempt to automate the classification process. To achieve this objective, ten board-certified hematopathologists (with experience in grading follicular lymphoma) from The Ohio State University, Cleveland Clinic, Vanderbilt University, and private practice will participate in the creation of the database that will contain digitized follicular lymphoma slide images, as well as the associated truth for the development and evaluation of the computer-aided follicular lymphoma grading system. After extensive evaluation of the system with the collected datasets and outcome data, as well as datasets from the Cancer and Leukemia Group B (CALGB) trials, the developed system will be installed at participating pathologists' institutions, and the developed software will be made available to the research community as a shareable resource. PUBLIC HEALTH RELEVANCE: Follicular lymphoma (FL) is the second most common non-Hodgkin's lymphoma. This project aims to provide supplementary information to the pathologist for the grading of the tumor using computerized image analysis techniques. The supplementary information will be useful for better diagnosis, prognosis and treatment of this disease.

描述（由申请人提供）：滤泡性淋巴瘤（FL）是第二常见的非霍奇金淋巴瘤。目前存在多种治疗方案，但这些方案成本高昂且具有显着的毒性。临床实践中没有可用的生物或遗传标记来对滤泡性淋巴瘤进行可靠的风险分层，并且适当治疗的选择在很大程度上取决于基于形态的组织学分级。在世界卫生组织 (WHO) 采用的系统中，滤泡性淋巴瘤根据十个随机选择的标准高倍视野 (HPF) 中中心母细胞的平均计数分为三个等级。组织学分级低的滤泡性淋巴瘤表现出惰性的临床病程，平均生存期长，但被认为用目前可用的疗法无法治愈。相比之下，高级别滤泡性淋巴瘤具有侵袭性临床病程，如果不采用侵袭性化疗治疗，会迅速致命。然而，与低度滤泡性淋巴瘤不同的是，高度滤泡性淋巴瘤可以通过积极的化疗治愈。目前，病理学家之间在 FL 分级方面的读者间一致性极低。在一项多中心研究中，专家对不同级别的滤泡性淋巴瘤的一致性在 61% 到 73% 之间。由于出于实际原因，病理学家仅使用 10 个 HPF，因此在切片的各个区域显示出显着差异的情况下，该系统可能容易出现选择偏差。该项目的主要目标是开发一种有效的计算机辅助系统，以协助病理学家做出有关滤泡性淋巴瘤组织学分级的诊断决策。值得注意的是，该项目旨在为病理学家进行分类过程提供补充信息；这并不是试图使分类过程自动化。为了实现这一目标，来自俄亥俄州立大学、克利夫兰诊所、范德比尔特大学和私人诊所的十名委员会认证的血液病理学家（具有滤泡性淋巴瘤分级经验）将参与创建包含数字化滤泡性淋巴瘤幻灯片图像的数据库，以及计算机辅助滤泡性淋巴瘤分级系统的开发和评估的相关事实。在使用收集的数据集和结果数据以及癌症和白血病 B 组 (CALGB) 试验的数据集对系统进行广泛评估后，开发的系统将安装在参与的病理学家机构，并且开发的软件将可供使用作为可共享资源向研究界提供。公共卫生相关性：滤泡性淋巴瘤 (FL) 是第二常见的非霍奇金淋巴瘤。该项目旨在为病理学家使用计算机图像分析技术对肿瘤进行分级提供补充信息。补充信息将有助于更好地诊断、预后和治疗该疾病。