Automated in vivo analysis of tumor growth rate as a guide for therapeutic decisions to advance personalized cancer treatment

肿瘤生长速率的自动体内分析作为治疗决策的指南，以推进个性化癌症治疗

• 批准号: 9231706
• 负责人: Mizuki Nishino
• 金额: $ 60.66万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9231706
• 关键词: Address; Algorithms; BRAF gene; Back; Biometry; Cancer Center; Cancer Patient; Clinical; Clinical Trials; Collaborations; Computer software; Data; Decision Making; Development; Engineering; Ensure; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Evaluation; FDA approved; Feedback; Foundations; Goals; Growth; Guidelines; Image; Immune checkpoint inhibitor; Industrialization; Judgment; Kinetics; Left; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Measures; Medical; Methods; Modeling; Mutation; Non-Small-Cell Lung Carcinoma; Oncologist; Outcome; Patients; Physicians; Precision therapeutics; Productivity; Publishing; Radiology Specialty; Reader; Reference Values; Reporting; Reproducibility; Research; Research Personnel; Role; Scientist; System; Technical Expertise; Testing; Therapeutic; Time; Translating; Translations; Tumor Burden; Tumor Volume; Tyrosine Kinase Inhibitor; Woman; Work; X-Ray Computed Tomography; analytical tool; base; cancer therapy; clinical application; clinical investigation; clinical practice; clinically significant; cohort; image processing; improved; in vivo; industry partner; inhibitor/antagonist; logarithm; mutant; novel; oncology; personalized cancer therapy; personalized medicine; prognostic value; prospective; radiologist; research clinical testing; response; statistics; targeted agent; targeted therapy trials; targeted treatment; time use; tool; treatment duration; tumor; tumor growth; user-friendly

Project Summary The goal of this project is to develop a novel analytic software module for tumor growth rate assessment during therapy in advanced lung cancer patients. Tumor growth rate is a novel concept for evaluation of clinical benefit of cancer therapy and is proposed as objective guides for treatment decisions, however is not included in the current standards of tumor response evaluation. The concept of tumor growth rate is especially important in patients with specific mutations in their tumors, such as epidermal growth factor receptor (EGFR) mutations in lung cancer, treated with personalized therapy specifically targeting their mutations. EGFR-mutant patients show initial dramatic response to targeted therapy using EGFR inhibitors; however, their tumors grow back and eventually progress. Current clinical practice lacks objective guidelines about when EGFR inhibitor therapy can be safely continued while tumors are growing back, and the decision is left to treating physicians’ discretions. Similar clinical scenarios are observed during therapy using other targeting agents for various cancers, indicating an increasing clinical demand to fulfil this unmet need for objective guides for treatment decisions in the era of precision cancer therapy. Investigators of this academic-industrial partnership team have developed a method to objectively characterize of tumor growth rate over time using the serial clinical CT imaging data obtained in patients receiving cancer therapy. The method was applied to EGFR-mutant lung cancer patients as a well-studied paradigm, and provided a reproducible reference value that indicates fast versus slow growth. Given the demonstrated feasibility as a clinical investigation, the team proposes to deliver this novel analytic functionality to the clinical setting, by developing an automated analytic tool for tumor growth rate assessment and interpretation, which is essential to make the approach more widely adaptable within the clinical workflow. The academic-industrial team consists of accomplished investigators from Dana-Farber/Brigham and Women’s Cancer Center and industrial scientists from Toshiba Medical Systems Corporation, with expertise in oncology, radiology, biostatistics, and engineering, who have a track record of productive collaboration. The team has started to work together to address the following aims: Aim 1) Develop an analytic software module for tumor growth rate in lung cancer during therapy, which operates on an existing workstation; Aim 2) Optimize the module based on the reproducibility assessment and user feedback in a pilot cohort of 30 EGFR-mutant patients; and Aim 3) Apply the analytic software module for tumor growth rate in lung cancer patients treated in prospective trials. Delivery of the novel analytic module for tumor growth rate to the clinical setting will provide objective guides for treatment decision making during cancer therapy, and help to maximize the benefit of precision therapy for cancer. The demonstrated productivity of academic-industrial partnership with bidirectional research relationship further ensures successful completion of the project goal.

项目摘要 该项目的目标是开发一种新的分析软件模块，用于在肿瘤生长过程中评估肿瘤生长速率。 晚期肺癌患者的治疗。肿瘤生长率是一个新的概念，用于评价临床 癌症治疗的好处，并提出作为治疗决策的客观指南，但不包括在内 在目前的肿瘤反应评估标准中。肿瘤生长速度的概念尤为重要 在肿瘤中有特定突变的患者中，如表皮生长因子受体（EGFR）突变 在肺癌中，采用专门针对其突变的个性化治疗。EGFR突变患者 对使用EGFR抑制剂的靶向治疗显示出最初的显著反应;然而，他们的肿瘤会重新生长， 最终取得进展。目前的临床实践缺乏关于EGFR抑制剂治疗何时可以 在肿瘤重新生长期间，安全地继续使用，并由治疗医生自行决定。 在使用其他靶向剂治疗各种癌症期间观察到类似的临床情况， 这表明临床需求不断增加，以满足对治疗决策客观指南的未满足需求， 精准癌症治疗的时代这个学术-工业合作团队的研究人员开发了 一种使用系列临床CT成像数据客观表征肿瘤生长速率随时间变化的方法 在接受癌症治疗的患者中获得。该方法应用于EGFR突变型肺癌患者 作为一个良好的研究范例，并提供了一个可重复的参考值，表明快速与缓慢的增长。 考虑到作为临床研究的可行性，该团队建议提供这种新的分析方法。 通过开发用于肿瘤生长速率评估的自动化分析工具， 和解释，这是必不可少的，使该方法更广泛地适应临床工作流程。 学术-工业团队由来自Dana-Farber/Brigham和Women's的资深调查员组成。 癌症中心和东芝医疗系统公司的工业科学家，具有肿瘤学方面的专业知识， 放射学，生物统计学和工程学，他们有着富有成效的合作记录。该团队已经 开始合作，以解决以下目标：目标1）开发肿瘤分析软件模块 在现有工作站上运行的治疗期间肺癌的生长率;目标2）优化 基于30个EGFR突变体的试点队列中的再现性评估和用户反馈的模块 目的3）应用分析软件模块对接受治疗的肺癌患者的肿瘤生长率进行分析， 前瞻性试验。将新型肿瘤生长率分析模块交付到临床环境将提供 在癌症治疗过程中为治疗决策提供客观指导，并有助于最大限度地提高 精准治疗癌症学术界与工业界的伙伴关系所展示的生产力， 双向的研究关系进一步保证了项目目标的顺利完成。