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 这项指导的研究科学家发展（K01）奖将支持培训和职业发展 在近红外光谱和多模式X射线/弥散光学的近红外训练的初级研究员的 断层扫描，正在过渡到磁共振（MR）和弹性乳腺癌领域 成像。拟议的职业发展计划包括MR成像技术，癌症生物学的培训， 医学肿瘤学，临床研究和职业发展技能。拟议的研究重点是 新型乳腺癌成像技术的开发以及敏感，健壮和强大的多参数 成像标记以预测新辅助设置的早期病理结果，从而对 紧急临床需要为个体疾病量身定制治疗并改善乳腺癌的存活。功能 成像在监测新辅助化疗（NACT）方面是有利的，因为肿瘤生理的变化 明显早于实际肿瘤收缩。但是，乳腺肿瘤是复杂的，不断发展的系统 以其生物学性质和对 治疗。仅描绘肿瘤生理或生物物理学一个方面的个体功能生物标志物是 有限的，新兴的研究表明，它们的预测性能在不同的肿瘤中有所不同 亚型。一种将功能成像技术中信息与信息结合的多参数方法 需要对多方面的基础肿瘤生理的互补敏感性来监测NACT 不同乳腺癌类型的结果。为此，申请人提出了利用 多模式扩散光学层析成像，磁共振成像（MRI）和MR弹性成像 可以获取多功能光学，MRI和弹性图数据的主要假设的平台。 使用多模式乳房MR线圈有效地在健康的女性志愿者中有效； 2）开发的多参数 成像标记在预测病理学中的单个成像方式优于单个标记 乳腺癌患者的第一个治疗周期结束时，最早的反应 裸露； 3）多参数成像标记的预测性能不是显着的 乳腺癌亚型不同。这种方法将帮助我们对 与微环境，血管生成和 NACT导致代谢。一旦得到验证，从长远来看，它也有可能进步 反应引导的靶向治疗，这种方法在最近的Gepartrio试验中证明了这一方法，该试验可能导致 明显更高的无病和总生存率。研究项目和培训的成功是 确保由一组导师和合作者拥有互补的科学专业知识和实质性的 关于向年轻调查人员提供有关独立学术生涯的发展的经验。