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.

摘要