Improving Image-Guided Radiation Therapy of Gliomas with High-Resolution MR Spectroscopic Imaging

利用高分辨率磁共振波谱成像改善神经胶质瘤的图像引导放射治疗

• 批准号: 10501516
• 负责人: Chao Ma
• 金额: $ 51.42万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501516
• 关键词: Address; Adjuvant Chemotherapy; Adjuvant Radiotherapy; Adoption; Area; Biological; Biological Markers; Biopsy; Blood - brain barrier anatomy; Brain; Clinical; Data; Development; Dose; Evaluation; Excision; Extravasation; Glioblastoma; Glioma; Goals; Guidelines; Head; Heterogeneity; Histology; Hypoxia; Image; Image Enhancement; Imaging technology; Infiltration; Inflammation; Investigation; Knowledge; Label; Location; Machine Learning; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant - descriptor; Malignant Glioma; Malignant neoplasm of brain; Maps; Measurement; Metabolic; Methods; Microscopic; Motion; Necrosis; Newly Diagnosed; Noise; Operative Surgical Procedures; Outcome; Patients; Performance; Phase I Clinical Trials; Phase III Clinical Trials; Positron-Emission Tomography; Postoperative Period; Predisposition; Protons; Radiation therapy; Recurrence; Reproducibility; Research; Resolution; Sampling; Scanning; Sensitivity and Specificity; Signal Transduction; Specificity; Specimen; Speed; Structure; Techniques; Time; Tissues; Tumor Volume; Uncertainty; United States; Validation; Water; base; brain tissue; brain tumor imaging; chemotherapy; clinical application; computerized data processing; contrast enhanced; data acquisition; density; experimental study; follow-up; image guided radiation therapy; imaging modality; improved; in vivo; innovation; ischemic injury; metabolic imaging; molecular imaging; neoplastic; neoplastic cell; novel; quantum; research clinical testing; simulation; spectroscopic imaging; standard care; tool; treatment planning; tumor

ABSTRACT Glioma make up 80% of all primary malignant brain tumors. The current standard treatment for newly diagnosed gliomas includes maximal surgical resection, radiation therapy (RT), and chemotherapy. A key technical challenge in RT treatment planning is accurate target volume delineation of gliomas. The current clinical guidelines for target volume delineation rely primarily on structural Magnetic Resonance Imaging (MRI) images. Gross Tumor Volume (GTV) is defined based on contrast-enhanced T1-weighted MRI and T2-weighted MRI. However, structural MRI alone lacks specificity for delineation of true tumor boundaries. Accordingly, Clinical Target Volume (CTV) is often defined as the GTV plus a large margin (e.g., 20-25 mm) to account for possible microscopic infiltration. The lack of specificity of structural MRI is a critical factor limiting the investigation and clinical application of new RT techniques for better clinical outcome. MR spectroscopic imaging (MRSI) has long been recognized as a potentially powerful tool for label-free molecular imaging of brain tumor. In a recent Phase I clinical trial, MRSI is used to guide dose escalation in RT for Glioblastoma multiforme patients, showing very promising preliminary results. Although general clinical applications of MRSI have been impeded by its limited spatial resolution and long scan time, significant progresses have been made in addressing these technical challenges over the past decade using advanced data acquisition and processing methods. Our group have successfully developed a powerful MRSI technology, known as SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation). SPICE effectively integrates rapid scanning, sparse sampling, quantum simulation of molecule resonance structures, and machine learning to enable rapid high-resolution MRSI. Preliminary results by our and other groups have shown an exciting potential of SPICE to achieve an unprecedented combination of resolution, speed, and SNR for metabolic imaging. We have also demonstrated, for the first time, the feasibility of mapping T1, T2 and proton-density parameters of brain tissues using the unsuppressed water signals from the SPICE scans. The primary goal of this project is to leverage this significant advance in MRSI technology and investigate the use of high-resolution metabolic and structural information to achieve more accurate target volume delineation for RT treatment planning of gliomas. We will: 1) further develop and optimize SPICE for MRI/MRSI-guided RT of gliomas in clinical settings, 2) perform systematic performance evaluation of the proposed method on phantoms, healthy subjects, and glioma patients, and 3) investigate the use of metabolic and structural biomarkers for delineation of biological target volume to improve image-guided RT of gliomas. The proposed research is innovative in developing a novel molecular imaging technology and a timely effort on improving RT treatment planning of gliomas with quantitative metabolic and structural biomarkers. Successful completion of the project will have a significant impact on image-guided RT for gliomas, opening up new opportunities for better control of recurrence in glioma patients using dose escalated RT.

抽象的 胶质瘤占所有原发性恶性脑肿瘤的80％。新诊断的当前标准治疗 神经胶质瘤包括最大手术切除，放射治疗（RT）和化学疗法。关键技术 RT治疗计划中的挑战是胶质瘤的准确目标量描述。当前的临床 目标体积描述指南主要依赖于结构磁共振成像（MRI）图像。 根据对比增强的T1加权MRI和T2加权MRI定义了总肿瘤体积（GTV）。 但是，仅结构MRI缺乏描述真正肿瘤边界的特异性。因此，临床 目标体积（CTV）通常定义为GTV加上较大的边距（例如20-25毫米），以解决可能 显微镜浸润。缺乏结构MRI的特异性是限制研究和 新的RT技术的临床应用，以获得更好的临床结果。 MR光谱成像（MRSI）的长期 被公认为是脑肿瘤无标记的分子成像的潜在强大工具。在最近的阶段 I临床试验，MRSI用于指导RT的胶质母细胞瘤多形患者的剂量升级，显示出非常非常 有希望的初步结果。尽管MRSI的一般临床应用已受到其有限的影响 空间分辨率和长时间的扫描时间，在解决这些技术方面取得了重大进展 在过去的十年中，使用高级数据采集和处理方法提出了挑战。我们的小组有 成功地开发了一种强大的MRSI技术，称为香料（通过利用光谱成像 时尚相关性）。香料有效地整合了快速扫描，稀疏采样，量子模拟 分子共振结构和机器学习以实现快速高分辨率MRSI。初步的 我们和其他群体的结果表现出令人兴奋的香料潜力，以实现前所未有的 分辨率，速度和SNR的组合，用于代谢成像。我们也首次证明了 使用未抑制的水映射脑组织的T1，T2和质子密度参数的可行性 香料扫描的信号。该项目的主要目标是利用MRSI的重大进步 技术并调查使用高分辨率代谢和结构信息以实现更多的使用 精确的目标体积描述用于神经胶质瘤的RT治疗计划。我们将：1）进一步开发和优化 临床环境中神经胶质瘤的MRI/MRSI引导RT的香料，2）进行系统的性能评估 提出的关于幻像，健康受试者和神经胶质瘤患者的方法，以及3）研究代谢的使用 和结构性生物标志物，用于划定生物靶标体积，以改善神经胶质瘤的图像引导的RT。这 拟议的研究具有创新的创新性，以开发一种新颖的分子成像技术和及时的努力 通过定量代谢和结构生物标志物改善神经胶质瘤的RT治疗计划。成功的 该项目的完成将对神经胶质瘤的图像引导的RT产生重大影响，并开放新的 使用剂量升级的RT更好地控制神经胶质瘤患者复发的机会。