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: 10064076
• 负责人: Mizuki Nishino
• 金额: $ 56.78万
• 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 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10064076
• 关键词: Address; BRAF gene; Back; Biometry; Cancer Center; Cancer Patient; Clinical; Clinical Trials; Collaborations; Computer software; Data; Decision Making; Development; Digital Imaging and Communications in Medicine; 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; Oncology; 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; personalized cancer therapy; personalized medicine; prognostic value; prospective; radiologist; research clinical testing; response; segmentation algorithm; 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.

项目概要 该项目的目标是开发一种新颖的分析软件模块，用于评估肿瘤生长率 晚期肺癌患者的治疗。肿瘤生长速率是评估临床疗效的一个新概念 癌症治疗的益处，被提议作为治疗决策的客观指南，但不包括在内 在现行的肿瘤反应评价标准中。肿瘤生长速度的概念尤为重要 肿瘤中存在特定突变的患者，例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疗法进行治疗。 EGFR 突变患者 对使用 EGFR 抑制剂的靶向治疗显示出最初的显着反应；然而，他们的肿瘤会重新生长并 最终取得进展。目前的临床实践缺乏关于何时可以进行 EGFR 抑制剂治疗的客观指南 当肿瘤重新生长时，可以安全地继续治疗，并由治疗医生自行决定。 在使用其他靶向药物治疗各种癌症期间观察到类似的临床情况， 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 癌症精准治疗时代。这个学术-工业合作团队的研究人员已经开发出 一种使用连续临床 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突变肺癌患者 作为一个经过充分研究的范例，并提供了可重复的参考值，表明快速增长与缓慢增长。 鉴于临床研究的可行性已得到证实，该团队建议提供这种新颖的分析 通过开发用于肿瘤生长率评估的自动化分析工具，将功能应用于临床环境 和解释，这对于使该方法在临床工作流程中具有更广泛的适应性至关重要。 学术-工业团队由来自丹娜—法伯/布莱根和妇女医院的卓有成就的研究人员组成 癌症中心和东芝医疗系统公司的工业科学家拥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。团队有 开始共同努力实现以下目标： 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 模块基于 30 个 EGFR 突变体试点队列的可重复性评估和用户反馈 患者;目标 3) 应用分析软件模块分析接受治疗的肺癌患者的肿瘤生长率 前瞻性试验。将新型肿瘤生长率分析模块交付给临床环境将提供 客观指导癌症治疗过程中的治疗决策，并有助于最大限度地提高癌症治疗的效益 癌症的精准治疗。学术与工业合作伙伴关系所展现的生产力 双向研究关系进一步确保了项目目标的成功完成。

项目成果

Tumor Response Dynamics of Advanced Non-small Cell Lung Cancer Patients Treated with PD-1 Inhibitors: Imaging Markers for Treatment Outcome.

• DOI: 10.1158/1078-0432.ccr-17-1434
• 发表时间: 2017-10-01
• 期刊: Clinical cancer research : an official journal of the American Association for Cancer Research
• 作者: Nishino M;Dahlberg SE;Adeni AE;Lydon CA;Hatabu H;Jänne PA;Hodi FS;Awad MM
• 通讯作者: Awad MM

Lung Cancer in Lung Transplant Recipients: Clinical, Radiologic, and Pathologic Characteristics and Treatment Outcome.

肺移植受者的肺癌：临床、放射学和病理学特征和治疗结果。

• DOI: 10.1097/rct.0000000000001466
• 发表时间: 2023
• 期刊: Journal of computer assisted tomography
• 影响因子: 1.3
• 作者: Tseng,Shu-Chi;Gagne,StaciM;Hatabu,Hiroto;Lin,Gigin;Sholl,LynetteM;Nishino,Mizuki
• 通讯作者: Nishino,Mizuki

The associations of interstitial lung abnormalities with cancer diagnoses and mortality.

• DOI: 10.1183/13993003.02154-2019
• 发表时间: 2020-12
• 期刊: The European respiratory journal
• 作者: Axelsson GT;Putman RK;Aspelund T;Gudmundsson EF;Hida T;Araki T;Nishino M;Hatabu H;Gudnason V;Hunninghake GM;Gudmundsson G
• 通讯作者: Gudmundsson G

Imaging of Histiocytosis in the Era of Genomic Medicine.

基因组医学时代的组织细胞增多症的成像。

• DOI: 10.1148/rg.2019180054
• 发表时间: 2019
• 期刊: Radiographics : a review publication of the Radiological Society of North America, Inc
• 作者: Park,Hyesun;Nishino,Mizuki;Hornick,JasonL;Jacobsen,EricD
• 通讯作者: Jacobsen,EricD

M1b Disease in the 8th Edition of TNM Staging of Lung Cancer: Pattern of Single Extrathoracic Metastasis and Clinical Outcome.

第 8 版肺癌 TNM 分期中的 M1b 疾病：单胸外转移模式和临床结果。

• DOI: 10.1634/theoncologist.2018-0596
• 发表时间: 2019
• 期刊: The oncologist
• 作者: Park,Hyesun;Dahlberg,SuzanneE;Lydon,ChristineA;Araki,Tetsuro;Hatabu,Hiroto;Rabin,MichaelS;Johnson,BruceE;Nishino,Mizuki
• 通讯作者: Nishino,Mizuki