Multiparametric multimodal imaging for breast cancer neoadjuvant chemotherapy monitoring

用于乳腺癌新辅助化疗监测的多参数多模态成像

• 批准号: 10237213
• 负责人: Bin Deng
• 金额: $ 14.08万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-21 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10237213
• 关键词: Algorithms; Angiogenesis Inhibitors; Area; Biological; Biological Markers; Biomechanics; Biophysics; Blood Volume; Breast; Breast Cancer Patient; Breast Cancer Treatment; Cancer Biology; Cellularity; Chemoresistance; Clinical; Clinical Research; Complex; Coupling; Cytotoxin; Data; Data Set; Development; Development Plans; Diagnosis; Diffusion Magnetic Resonance Imaging; Disease; ERBB2 gene; Emission-Computed Tomography; Enrollment; Ensure; Epidermal Growth Factor Receptor; Female; Functional Imaging; Functional disorder; Goals; Heterogeneity; Human; Hypoxia; Image; Imaging Techniques; Imaging technology; In complete remission; Individual; Lead; Magnetic Resonance; Magnetic Resonance Elastography; Magnetic Resonance Imaging; Malignant Neoplasms; Mammary Neoplasms; Medical Oncology; Mentored Research Scientist Development Award; Mentors; Metabolism; Methods; Monitor; Morphology; Multimodal Imaging; Nature; Near-Infrared Spectroscopy; Neoadjuvant Therapy; Operative Surgical Procedures; Optics; Outcome; Pathologic; Pathology Report; Patients; Performance; Physiological; Physiology; Positron-Emission Tomography; Postoperative Period; Prognosis; Protocols documentation; ROC Curve; Regression Analysis; Research; Research Personnel; Research Project Grants; Research Training; Roentgen Rays; Role; Scanning; Scientist; Solid Neoplasm; Survival Rate; System; Systemic Therapy; Techniques; Testing; Tissues; Training; Training Support; Translations; Treatment Protocols; Vascular Permeabilities; X-Ray Computed Tomography; advanced breast cancer; angiogenesis; base; breast cancer diagnosis; breast cancer survival; breast imaging; cancer imaging; cancer subtypes; cancer type; career; career development; chemotherapy; cohort; contrast enhanced; data fusion; density; design; diffuse optical tomography; drug discovery; early detection biomarkers; elastography; experience; hemodynamics; hormone receptor-positive; image guided; image reconstruction; imaging biomarker; imaging modality; imaging platform; improved; individualized medicine; innovation; insight; instrumentation; magnetic field; malignant breast neoplasm; multimodality; novel; novel therapeutics; optical imaging; prototype; research and development; response; skill acquisition; success; targeted treatment; tissue oxygenation; treatment response; tumor; tumor hypoxia; viscoelasticity; volunteer

Project Summary/Abstract This Mentored Research Scientist Development (K01) Award will support the training and career development of a junior investigator with prior training in near-infrared spectroscopy and multimodal x-ray/diffuse optical tomography, who is transitioning into the field of magnetic resonance (MR) and elastographic breast cancer imaging. The proposed career development plan includes training in MR imaging techniques, cancer biology, medical oncology, clinical research, and career development skills. The proposed research focuses on the development of novel breast cancer imaging techniques and sensitive, robust, and powerful multiparametric imaging markers to predict pathological outcomes early in neoadjuvant settings, thereby responding to an urgent clinical need to tailor treatment to individual diseases and improve breast cancer survival. Functional imaging is advantageous in monitoring neoadjuvant chemotherapy (NACT) since changes in tumor physiology manifest earlier than actual tumor shrinkage. However, breast tumors are complex, evolving systems characterized by profound spatial and temporal heterogeneity in their biological nature and response to treatment. Individual functional biomarkers that depict only one aspect of tumor physiology or biophysics are limited, and emerging studies have shown that their predictive performance varies among tumors with different subtypes. A multiparametric approach that combines information from functional imaging technologies with complementary sensitivities to the multifaceted underlying tumor physiology is needed to monitor NACT outcomes across different breast cancer types. To this end, the applicant has proposed to leverage a multimodal diffuse optical tomography, magnetic resonance imaging (MRI), and MR elastography imaging platform to test the main hypotheses that 1) multifunctional optical, MRI and elastography data can be acquired efficiently in healthy female volunteers using a multimodal breast MR coil; 2) the developed multiparametric imaging markers outperform individual markers from individual imaging modalities in predicting pathologic complete response as early as at the conclusion of the first cycle of treatment in breast cancer patients undergoing NACT; and 3) the predictive performance of multiparametric imaging markers is not significantly different among breast cancer subtypes. This approach will help us gain a comprehensive understanding of the multitude of simultaneous physiological changes in tumors related to microenvironment, angiogenesis, and metabolism as a result of NACT. Once validated, in the longer term, it also has the potential to advance response-guided targeted therapy, the approach demonstrated in the recent GeparTrio trial that can lead to significantly higher disease-free and overall survival rates. The success of the research project and training is ensured by a team of mentors and collaborators with complementary scientific expertise and substantial experience in advising young investigators on the development of an independent academic career.

项目摘要/摘要 该指导研究科学家发展奖(K01)将支持培训和职业发展 受过近红外光谱学和多模X射线/漫反射光学培训的初级调查员 断层扫描，谁正在过渡到磁共振(MR)和弹性成像乳腺癌领域 成像。拟议的职业发展计划包括磁共振成像技术、癌症生物学、 内科肿瘤学、临床研究和职业发展技能。拟议的研究重点放在 乳腺癌新成像技术的发展和灵敏、稳健、强大的多参数 在新辅助治疗环境中早期预测病理结果的成像标记物，从而对 临床迫切需要针对个别疾病进行量身定制的治疗，并提高乳腺癌的存活率。功能性 由于肿瘤生理学的改变，成像在监测新辅助化疗(NACT)方面具有优势。 比实际肿瘤缩小更早表现出来。然而，乳腺肿瘤是复杂的、不断进化的系统。 具有其生物学性质和反应的严重的时空异质性 治疗。仅描述肿瘤生理或生物物理的一个方面的个体功能生物标记物是 有限的，新兴的研究表明，它们的预测性能在不同的肿瘤中不同 子类型。多参数方法将来自功能成像技术的信息与 需要对多方面的潜在肿瘤生理学的互补敏感性来监测NACT 不同类型乳腺癌的结果。为此，申请人提议利用 多模式漫反射光学层析成像、磁共振成像(MRI)和磁共振弹性成像成像 用于验证以下主要假设的平台：1)可以获取多功能光学、MRI和弹性成像数据 在健康女性志愿者中使用多模式乳腺磁共振线圈的效率；2)开发的多参数 在预测病理方面，成像标记物优于个体成像方法中的个体标记物 乳腺癌患者在第一周期治疗结束时最早完全缓解 3)多参数成像标记物的预测性能不显著 不同的乳腺癌亚型不同。这种方法将有助于我们全面了解 肿瘤中与微环境、血管生成和肿瘤相关的多种同步生理变化 新陈代谢是新陈代谢的结果。一旦得到验证，从长远来看，它也有推进的潜力 反应引导的靶向治疗，在最近的GeparTrio试验中展示的方法可以导致 显著提高无病存活率和总体存活率。研究项目和培训的成功之处在于 由一组导师和合作者确保，他们具有互补的科学专业知识和大量的 就独立学术生涯的发展为年轻研究人员提供建议的经验。