Quantitative DW-MRI for Early Breast Cancer Treatment Response Assessment

用于早期乳腺癌治疗反应评估的定量 DW-MRI

• 批准号: 8276595
• 负责人: THOMAS L CHENEVERT
• 金额: $ 53.74万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-09 至 2015-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8276595
• 关键词: Advanced Development; Algorithms; Automation; Biological Markers; Biological Preservation; Breast; Breast Cancer Treatment; Calibration; Cancer Patient; Characteristics; Clinical; Clinical Data; Clinical Trials; Clinical Trials Database; Clinical Trials Design; Collaborations; Computer software; Data; Data Set; Death Rate; Development; Diagnostic Neoplasm Staging; Diffusion; Diffusion Magnetic Resonance Imaging; Disease-Free Survival; Evaluation; Fatty acid glycerol esters; Freedom; Hour; Image; Lesion; Location; Magnetic Resonance Imaging; Mammary Neoplasms; Manufacturer Name; Maps; Measurement; Measures; Methods; Metric; Michigan; Morphologic artifacts; Multi-Institutional Clinical Trial; Multicenter Trials; Neoadjuvant Therapy; Oncologist; Outcome; Outcome Measure; Pathologic; Patient Care; Patients; Process; Protocols documentation; Quality Control; Quality of life; Recurrence; Reproducibility; Site; Solutions; System; Systemic Therapy; Temperature; Testing; Tissues; Treatment outcome; Tumor stage; Universities; Validation; Variant; Vendor; anticancer research; base; chemotherapy; clinical care; clinical decision-making; computerized; cost; design; effective therapy; image processing; image registration; improved; malignant breast neoplasm; novel; prospective; quality assurance; response; statistics; surgical research; tool; treatment response; tumor

DESCRIPTION (provided by applicant): Breast cancer treatment with neoadjuvant chemotherapy (NAC) can provide an opportunity for achieving a major decrease in recurrence and death rates by down-staging the tumor while improving breast preservation. However, the dilemma for patients is that NAC is only effective in about 70% of patients and the response is determined late or on completion of therapy with pathologic assessment of surgically excised tissue following NAC used to determine long-term disease-free survival. Ineffective therapy decreases quality of life, increases costs, and delays commencement of effective treatment. In this proposal, development of a noninvasive imaging biomarker which could provide for very early prediction of long-term outcome would revolutionize the clinical care of breast cancer patients. Furthermore, imaging would provide patient care to be individualized by providing an opportunity to adapt systemic treatment to a particular patient. This proposal will undertake a comprehensive approach to develop imaging protocols and methods for applying diffusion-weighted MRI for management of breast cancer patients through availability of high-quality clinical data, analytical algorithm development, advances in quality control and software implementation: 1) Use of clinical data obtained from two multi-center prospective clinical trials (Cancer Research sponsored UK trial entitled "Establishing the Efficacy of Advanced Semi-automated Functional MR Imaging in the Early Prediction of Response of Locally Advanced Breast Cancer to NAC" as well as the I-Spy 2 clinical trial entitled "An adaptive breast cancer trial design in the setting of NAC"; 2) Implementation of quality assurance methods using a novel temperature controlled phantom; 3) Development of analytical algorithms using deformable registration for novel, voxel-based as well as ROI-based analysis of DW-MRI data sets to enhance the sensitivity of the imaging response biomarker; 4) Development and validation of a software application for turn-key analysis of DW-MRI data. MRI-derived quantitative measurements of response will be evaluated as early response predictors of clinical outcome measures using novel analytical approaches, i.e. functional diffusion mapping (fDM) on registered data sets along with alternative ROI statistics. Quality assurance methods will be developed from multi-center use of our MR phantom. An industrial partnership/collaboration with a major image workstation manufacturer will assist with development of a platform with a complete software algorithmic solution for use as a clinical decision tool. Development of an early quantitative imaging biomarker based on DW-MRI data would provide for individualized patient care. PUBLIC HEALTH RELEVANCE: Narrative: Neoadjuvant chemotherapy of breast cancer patients allows a patient with the opportunity to forego upfront surgical research in an effort to first reduce the size of the lesion. This approach is ineffective in about 30% of patients, but response is normally determined late or on completion of therapy (4-6 months). Ineffective therapy decreases quality of life, increases costs, and delays commencement of effective treatment. Development of diffusion-MRI as an early imaging biomarker would allow for individualized patient treatment.

描述(申请人提供)：新辅助化疗(NAC)治疗乳腺癌可以提供一个机会，通过降低肿瘤的分期，在改善乳房保存的同时，大幅降低复发率和死亡率。然而，患者面临的两难境地是，NAC只对大约70%的患者有效，其反应是在治疗后期或完成时确定的，并用NAC后手术切除的组织的病理评估来确定长期无病生存。无效的治疗降低了生活质量，增加了成本，并推迟了有效治疗的开始。在这项提案中，开发一种能够非常早期地预测长期结果的非侵入性成像生物标记物将彻底改变乳腺癌患者的临床护理。此外，通过提供使系统治疗适应特定患者的机会，成像将提供个性化的患者护理。这项建议将采取全面的方法，通过高质量临床数据的可用性、分析算法的开发、质量控制的进步和软件的实施，开发应用扩散加权磁共振成像来管理乳腺癌患者的成像方案和方法：1)使用从两个多中心前瞻性临床试验(癌症研究赞助的英国试验，题为“建立先进的半自动功能磁共振成像在早期预测局部晚期乳腺癌对NAC的反应中的有效性”)以及I-Spy 2临床试验，题为“在NAC环境下的适应性乳腺癌试验设计”；2)使用新型温控体模实施质量保证方法；3)为基于体素和基于ROI的新型DW-MRI数据集分析开发可变形配准的分析算法，以提高成像响应生物标记物的灵敏度；4)开发和验证用于DW-MRI数据交钥匙分析的软件应用程序。MRI衍生的反应定量测量将被评估为临床结果测量的早期反应预测指标，使用新的分析方法，即注册数据集上的功能扩散图(FDM)以及可选的ROI统计。质量保证方法将从我们的MR体模的多中心使用中发展出来。与一家主要图像工作站制造商的行业伙伴关系/合作将帮助开发一个平台，该平台具有完整的软件算法解决方案，用作临床决策工具。基于DW-MRI数据的早期定量成像生物标记物的开发将为患者提供个性化护理。 公共卫生相关性：叙述：乳腺癌患者的新辅助化疗使患者有机会放弃前期的外科研究，以努力首先缩小病变的大小。这种方法对大约30%的患者无效，但反应通常是在治疗后期或完成治疗(4-6个月)时确定的。无效的治疗降低了生活质量，增加了成本，并推迟了有效治疗的开始。磁共振扩散成像作为早期影像生物标记物的发展将使患者个体化治疗成为可能。