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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要该指导研究科学家发展（K01）奖将支持培训和职业发展一名接受过近红外光谱和多模态 X 射线/漫射光学培训的初级研究员断层扫描，正在转向磁共振 (MR) 和乳腺癌弹性成像领域成像。拟议的职业发展计划包括 MR 成像技术、癌症生物学、肿瘤医学、临床研究和职业发展技能。拟议的研究重点是开发新型乳腺癌成像技术和灵敏、稳健且强大的多参数成像标记物可在新辅助治疗早期预测病理结果，从而对临床迫切需要针对个体疾病制定治疗方案并提高乳腺癌的生存率。功能性由于肿瘤生理学的变化，成像有利于监测新辅助化疗（NACT）比实际的肿瘤缩小更早出现。然而，乳腺肿瘤是复杂的、不断发展的系统其生物学性质和响应具有深刻的空间和时间异质性治疗。仅描述肿瘤生理学或生物物理学一方面的个体功能生物标志物是有限的和新兴的研究表明，它们的预测性能在不同肿瘤中存在差异亚型。一种多参数方法，将功能成像技术的信息与监测 NACT 需要对多方面的潜在肿瘤生理学具有互补的敏感性不同乳腺癌类型的结果。为此，申请人建议利用多模态扩散光学断层扫描、磁共振成像 (MRI) 和 MR 弹性成像测试主要假设的平台：1）可以获取多功能光学、MRI 和弹性成像数据使用多模式乳腺 MR 线圈对健康女性志愿者进行有效治疗； 2) 多参数开发在预测病理学方面，成像标记物优于单个成像方式的单个标记物乳腺癌患者的第一个治疗周期结束时即可完全缓解正在进行 NACT； 3）多参数成像标志物的预测性能不显着乳腺癌亚型之间存在差异。这种方法将帮助我们全面了解肿瘤中与微环境、血管生成和相关的多种同时发生的生理变化 NACT 的代谢结果。一旦得到验证，从长远来看，它还有潜力推进反应引导的靶向治疗，该方法在最近的 GeparTrio 试验中证明可以导致显着提高无病生存率和总生存率。研究项目和培训的成功由具有互补科学专业知识和实质性的导师和合作者团队确保在为年轻研究人员发展独立学术生涯提供建议方面拥有丰富的经验。