Breast Cancer Intravoxel-incoherent-motion MRI Multisite (BRIMM) Study - Resubmission - 1

乳腺癌体素内不相干运动 MRI 多部位 (BRIMM) 研究 - 重新提交 - 1

• 批准号: 10356032
• 负责人: Eric Edward Sigmund
• 金额: $ 37.53万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10356032
• 关键词: 3-Dimensional; Address; Adopted; Adoption; Affect; Algorithms; Apoptosis; Binding Sites; Biological Markers; Blood; Blood Vessels; Breast Cancer Patient; Cellularity; Clinical; Clinical Data; Communities; Complex; Computer software; Data; Diagnostic; Diffusion; Diffusion Magnetic Resonance Imaging; Early treatment; Environment; Equilibrium; Explosion; Future; Generations; Goals; Health; Heterogeneity; Image; International; Literature; Longitudinal Studies; Magnetic Resonance Imaging; Malignant Neoplasms; Measurement; Modeling; Motion; Necrosis; Neoadjuvant Therapy; Olea; Operative Surgical Procedures; Outcome Study; Pathologic; Patients; Performance; Phase; Prediction of Response to Therapy; Protocols documentation; Reproducibility; Research; Site; Statistical Data Interpretation; Techniques; Testing; Therapy trial; Time; Tissues; Toxic effect; Translating; Translations; Treatment outcome; Tumor Biology; Tumor Markers; Tumor Volume; Validation; Variant; Vascular Permeabilities; Vendor; aggressive breast cancer; angiogenesis; biophysical model; breast cancer survival; cancer care; cancer imaging; chemotherapy; clinical implementation; clinically relevant; cohort; design; diagnostic value; digital; digital repositories; imaging biomarker; imaging modality; imaging system; improved; individual patient; innovation; insight; malignant breast neoplasm; molecular subtypes; non-Gaussian model; non-invasive imaging; open source; potential biomarker; predicting response; prognostic; prognostic value; prospective; prototype; quantitative imaging; recruit; response; success; synergism; targeted treatment; tool; translational potential; treatment response; tumor; tumor heterogeneity; tumor microenvironment

PROJECT SUMMARY While the technological enterprise of magnetic resonance imaging (MRI) generates a host of biomarkers of the tumor environment, in particular for breast cancer, precious few (and typically only first-order markers) have been tested beyond single site studies with single workflow processing. To address both the need for advanced tissue characterization and multi-site translation, we propose a multi-site study of intravoxel incoherent motion (IVIM) MRI in breast cancer to determine its maximum translational prognostic benefit. The IVIM model, which includes separate markers of tissue cellularity, vascular volume, and micro-vascular flow, has been successfully applied in a range of cancers, including breast cancer by the project teams of this proposal. This project will determine inherent variability of the technique with hardware variation (3 vendors) and software platforms (6 packages), in a 5 site retrospective analysis of clinical breast cancer IVIM data. We will then conduct a prospective two-site IVIM longitudinal study of patients undergoing neoadjuvant chemotherapy to determine the best pre- or mid-treatment biomarkers to predict therapeutic response. At each stage, performance will be evaluated both within each site and in the combined cohort, with the goal of identifying biomarkers that are both useful and broadly translatable.

项目摘要 虽然磁共振成像的技术企业（MRI）产生了许多生物标志物 肿瘤环境，尤其是乳腺癌，很少有（通常只有一阶标记）具有 通过单个站点研究对单个工作流程处理进行了测试。解决对高级的需求 组织表征和多站点的翻译，我们提出了一项多站点内腔内不连贯运动的研究 （IVIM）乳腺癌中的MRI确定其最大的翻译预后益处。 IVIM模型，该模型 包括单独的组织细胞，血管体积和微血管流的单独标记已成功 在各种癌症中应用，包括该提案项目团队的乳腺癌。这个项目将 通过硬件变化（3个供应商）和软件平台确定技术的内在变异性（6 包装），在5个站点的回顾性分析IVIM数据的回顾性分析中。然后，我们将进行 对新辅助化学疗法的患者的前瞻性二次IVIM纵向研究，以确定 最好的预处理生物标志物预测治疗反应。在每个阶段，性能将是 在每个站点和联合队列中都进行了评估，目的是识别既有生物标志物 有用且可翻译。