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: 8024533
• 负责人: Metin Nafi Gurcan
• 金额: $ 27.24万
• 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/8024533
• 关键词: Accounting; Adopted; Adult; Aggressive Clinical Course; Agreement; Area; B-Cell Lymphomas; Biologic Characteristic; Biological Markers; 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; Health; 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）：卵泡淋巴瘤（FL）是第二常见的非霍奇金淋巴瘤。今天存在几种治疗选择，但是这些选择很昂贵，包括重大毒性。在临床实践中，没有生物学或遗传标记可用于可靠的卵泡淋巴瘤风险分层，并且选择适当的治疗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，根据十个随机选择的标准高功率领域（HPFS）中的centroblasts平均计数，将卵泡淋巴瘤分为三个年级。组织学等级低的卵泡淋巴瘤显示出顽强的临床病程，平均生存率很长，但当前可用的疗法被认为是无法治愈的。相反，高级卵泡淋巴瘤具有侵略性的临床病程，如果不接受侵略性化学疗法治疗，则迅速致命。但是，与低度卵泡淋巴瘤相比，高级FL可以通过侵略性化疗来治愈。当前，病理学家在分级FL中的读取者一致性极低。在一项多站点的研究中，专家之间对于各种卵泡淋巴瘤的一致性在61％至73％之间变化。由于病理学家出于实际原因仅使用十个HPF，因此该系统可能很容易出现选择偏差的情况，这些案例显示了一节的各个区域的显着差异。该项目的主要目标是开发有效的计算机辅助系统，以帮助病理学家做出有关卵泡淋巴瘤组织学分级的诊断决策。重要的是要注意，该项目旨在在病理学家进行分类过程时向病理学家提供补充信息；这不是试图自动化分类过程的尝试。 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.在通过收集的数据集和结果数据进行了广泛评估，以及来自癌症和白血病B组（CALGB）试验的数据集后，将在参与的病理学家的机构中安装开发的系统，并将开发的软件可作为可共享的研究社区提供给研究社区。公共卫生相关性：卵泡淋巴瘤（FL）是第二常见的非霍奇金淋巴瘤。该项目旨在使用计算机图像分析技术向病理学家提供补充信息，以进行肿瘤的分级。补充信息将有助于更好地诊断，预后和对该疾病的治疗。