Multi-parametric Perfusion MRI for Therapy Response Assessment in Brain Cancer

多参数灌注 MRI 用于脑癌治疗反应评估

• 批准号: 10190871
• 负责人: Ashley M Stokes
• 金额: $ 34.77万
• 依托单位: ST. JOSEPH'S HOSPITAL AND MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10190871
• 关键词: 3-Dimensional; Adopted; Adoption; Affect; Aftercare; Agreement; Algorithmic Analysis; Algorithms; Architecture; Biological Markers; Biometry; Biopsy; Blood Vessels; Brain Neoplasms; Cellularity; Characteristics; Clinical; Clinical Management; Clinical Trials; Community Clinical Oncology Program; Computer software; Contrast Media; Data; Diagnosis; Dose; Ensure; Evaluation; Excision; Functional Magnetic Resonance Imaging; Functional disorder; Future; Gadolinium; Glioma; Goals; Guidelines; Healthcare; Image; Image Analysis; Industry Standard; Injections; Institution; Lead; Libraries; Magnetic Resonance Imaging; Malignant neoplasm of brain; Measurement; Measures; Medical Care Costs; Meta-Analysis; Methodology; Methods; Morbidity - disease rate; Multi-Institutional Clinical Trial; Multicenter Trials; Operative Surgical Procedures; Outcome; Oxygen; Patient Care; Patients; Performance; Perfusion; Permeability; Phase; Physiologic pulse; Physiological; Predisposition; Prospective cohort; Protocols documentation; Publishing; Pythons; Radiation therapy; Recurrence; Reporting; Reproducibility; Reproducibility of Results; Research; Resources; Scanning; Scheme; Site; Standardization; Structure; Testing; The Cancer Imaging Archive; Time; Vendor; automated algorithm; base; bevacizumab; cerebral blood volume; clinical practice; clinical translation; commercialization; contrast enhanced; conventional therapy; drug discovery; early detection biomarkers; healthy volunteer; imaging modality; improved; mortality; neuro-oncology; novel; open source; personalized care; predictive tools; programs; prospective; quality assurance; quantitative imaging; radiation effect; response; targeted treatment; tool; treatment planning; treatment response; tumor; tumor progression; user-friendly

The long-term goal of this program is to improve patient care by optimizing and validating quantitative magnetic resonance imaging methods for the early prediction of brain cancer response to therapy. Currently, contrast-enhanced MRI (CE-MRI) represents the standard for guiding almost all aspects of brain tumor clinical management, including surgical biopsy/resection, radiation treatment planning, and post-treatment surveillance for response assessment. Unfortunately, CE-MRI’s accuracy remains limited, which creates significant clinical challenges. Thus, clinical decisions often require surgical biopsy for definitive diagnosis, which increases medical costs, patient morbidity/mortality, and resource utilization. To overcome the limitations of CE-MRI, dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are increasingly used to evaluate tumor perfusion and permeability. Studies have shown that DSC/DCE parameters correlate with tumor grade, can predict the likelihood of tumor progression after therapy, and differentiate treatment related effects versus tumor progression. However, the widespread clinical adoption and incorporation of DSC-MRI into multi-site clinical trials has been hindered due to variable acquisition methods, contrast agent dosing schemes and analysis protocols, which to date, have yet to be standardized and automated for clinical use. These issues are known to affect the repeatability and interpretation of DSC-MRI metrics. Spin and gradient echo (SAGE) DSC-MRI sequences enable the use of lower doses of Gd-based contrast agents, require less scan time, are less sensitive to acquisition parameters, are methodologically more reproducible, yield more accurate perfusion parameters, provide simultaneous measures of DCE-MRI, vessel size and vessel architectural imaging data, oxygen delivery and novel metrics highly sensitive to tumor cellular characteristics. Accordingly, SAGE methods enable the interrogation of unique and complementary readouts on tumor microstructure and function that correlate with clinical outcomes and can identify patients responding to therapy. Before clinical trials can benefit from SAGE based DSC-MRI the acquisition and analysis protocols need to be optimized, automated and standardized. Thus, we propose to: 1) implement multi-vendor, SAGE- DSC-MRI protocols, 2) establish automated and open source algorithms for quality assurance and analysis, 3) partner with Imaging Biometrics to develop a commercially integrated, vendor neutral image analysis platform for analyzing SAGE DSC-MRI data and 4) validate SAGE DSC-MRI tools for predicting glioma response to bevacizumab therapy. Impact on Healthcare: We will provide the neuro-oncology community with validated, quantitative image acquisition and analysis methods for identifying early therapeutic response that are appropriate for multi-site clinical trials of conventional and targeted brain tumor therapies, thereby enabling more rapid drug discovery and improved individualized care for patients.

该计划的长期目标是通过优化和定量验证来改善患者护理 目前，用于早期预测脑癌治疗反应的磁共振成像方法。 对比增强 MRI (CE-MRI) 代表了指导脑肿瘤临床几乎所有方面的标准 管理，包括手术活检/切除、放射治疗计划和治疗后监测 不幸的是，CE-MRI 的准确性仍然有限，这产生了重要的临床意义。 因此，临床决策通常需要手术活检来明确诊断，这增加了挑战。 医疗费用、患者发病率/死亡率和资源利用 为了克服 CE-MRI 的局限性， 动态磁化率对比 (DSC) MRI 和动态对比增强 (DCE) MRI 的使用越来越多 研究表明 DSC/DCE 参数与肿瘤灌注和渗透性相关。 肿瘤分级，可以预测治疗后肿瘤进展的可能性，并区分治疗相关的 然而，DSC-MRI 的广泛临床应用和结合。 由于采集方法、造影剂剂量的变化，进入多中心临床试验受到阻碍 迄今为止，方案和分析方案尚未标准化和自动化以供临床使用。 已知这些问题会影响 DSC-MRI 指标的可重复性和解释。 echo (SAGE) DSC-MRI 序列能够使用较低剂量的基于 Gd 的造影剂，需要更少的 扫描时间，对采集参数不太敏感，方法上更具可重复性，产量更高 精确的灌注参数，同时提供 DCE-MRI、血管大小和血管的测量 建筑成像数据、氧气输送和对肿瘤细胞特征高度敏感的新指标。 因此，SAGE 方法能够询问肿瘤的独特且互补的读数 与临床结果相关的微观结构和功能，可以识别患者的反应 在临床试验之前，可以从基于 SAGE 的 DSC-MRI 采集和分析协议中受益。 需要优化、自动化和标准化，因此，我们建议：1）实施多供应商、SAGE-。 DSC-MRI 协议，2) 建立用于质量保证和分析的自动化和开源算法，3) 与 Imaging Biometrics 合作开发商业集成、供应商中立的图像分析平台 用于分析 SAGE DSC-MRI 数据，以及 4) 验证 SAGE DSC-MRI 工具用于预测神经胶质瘤的反应 贝伐珠单抗疗法对医疗保健的影响：我们将为神经肿瘤学界提供经过验证的、 用于识别早期治疗反应的定量图像采集和分析方法 适用于常规和靶向脑肿瘤治疗的多中心临床试验，从而使 更快速的药物发现和改善的患者个体化护理。