Multiparametric multimodal imaging for breast cancer neoadjuvant chemotherapy monitoring

项目总结/摘要 该指导研究科学家发展（K 01）奖将支持培训和职业发展 一名初级研究员，曾接受过近红外光谱和多模式X射线/漫射光学 断层扫描，谁是过渡到磁共振（MR）和弹性成像乳腺癌领域 显像拟议的职业发展计划包括磁共振成像技术，癌症生物学， 医学肿瘤学、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、强大的多参数 成像标记物，以预测新辅助治疗早期的病理结果， 迫切的临床需要量身定制治疗个别疾病和提高乳腺癌生存率。功能 成像在监测新辅助化疗（NACT）中是有利的， 比实际的肿瘤缩小要早然而，乳腺肿瘤是一个复杂的、不断发展的系统， 其特点是在其生物学性质和对环境的反应方面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的一个方面的个体功能性生物标志物是 有限的和新兴的研究表明，它们的预测性能在不同肿瘤之间存在差异， 亚型一种多参数方法，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补充敏感性来监测NACT 不同类型乳腺癌的预后。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）可以采集多功能光学、MRI和弹性成像数据 有效地在健康女性志愿者使用多模态乳腺MR线圈; 2）开发的多参数 在预测病理学方面，成像标记物优于来自个体成像模式的个体标记物 在乳腺癌患者中，早在第一个治疗周期结束时即达到完全缓解 接受NACT; 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。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 由于NACT的代谢。一旦得到验证，从长远来看，它也有可能推进 反应引导的靶向治疗，在最近的GeparTrio试验中证明的方法可以导致 无病生存率和总生存率显著提高。研究项目和培训的成功是 由具有互补的科学专业知识和实质性知识的导师和合作者团队确保 在指导年轻研究人员发展独立的学术生涯方面的经验。

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.