Developing informatics tools for optimized MRS for brain cancer research

开发信息学工具以优化脑癌研究的 MRS

• 批准号: 10413712
• 负责人: MALGORZATA MARJANSKA
• 金额: $ 38.07万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-07 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10413712
• 关键词: 19q; 3-Dimensional; Adoption; Adult; Anatomy; Automation; Back; Biological Markers; Body part; Brain Neoplasms; Calibration; Choline; Chromosomal Loss; Clinical; Clinical Research; Communities; Computer software; Custom; Cystathionine; Data; Data Analyses; Data Set; Exhibits; Glioma; Gold; Isocitrate Dehydrogenase; Judgment; Lesion; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant Neoplasms; Malignant neoplasm of brain; Measurement; Measures; Metabolic; Methods; Molecular; Monitor; Morphologic artifacts; Multi-Institutional Clinical Trial; Mutation; Normal tissue morphology; Pathologic; Patient Care; Patients; Performance; Phenotype; Phospholipid Metabolism; Physiologic pulse; Positioning Attribute; Procedures; Research; Research Personnel; Research Project Grants; Scanning; Source; Spectrum Analysis; System; Technical Expertise; Techniques; Time; Training; Vendor; Water; anticancer research; arm; automated analysis; base; body system; cancer therapy; clinical practice; clinical research site; data acquisition; deep neural network; heuristics; image guided; improved; informatics tool; interest; novel; open source; open source tool; prevent; skills; tool; translational barrier; treatment response; tumor; tumor progression

PROJECT SUMMARY/ABSTRACT This project proposes to develop methods for automated, real-time, single-voxel magnetic resonance spectroscopy (MRS) in brain tumors, integrate these methods with a clinical MRI system, evaluate their performance, and distribute them as open-source tools to the research community. MRS can provide metabolic information noninvasively for assessment of tumor phenotype and therapeutic response. Single-voxel MRS methods provide the best quality and most reliable data, but require the scanner operator to have a high skill level and expertise to produce good quality results. The need for this expert involvement in both acquisition and processing remains a critical barrier to the translation of MRS methods to clinical research sites without spectroscopy experts and to clinical practice. The first part of this project is to develop a method for 3D voxel placement using image guidance, integrate this method with a clinical MR system, and evaluate its performance. In the second part, we will automate our advanced MRS methods. In the third part, we will create real-time, automatic quantification tool specific to the obtained MRS data that will provide clinically interpretable results. We identified collaborators, the brain cancer researchers and clinicians, who will be early adopters and beta-testers of our tools. Successful completion of this project will improve data robustness and quality, eliminating the need for the expert interaction at the time of the scan and enabling adoption of MRS in multi- site clinical trials and clinical practice.

项目摘要/摘要 该项目建议开发自动，实时，单素磁共振的方法 脑肿瘤中的光谱法（MRS），将这些方法与临床MRI系统整合在一起，评估它们 性能，并将其作为开源工具分配给研究社区。太太可以提供代谢 无创的信息用于评估肿瘤表型和治疗反应。单腔MRS 方法提供了最佳质量和最可靠的数据，但要求扫描仪操作员具有高技能 水平和专业知识可产生高质量的结果。这两个收购都需要这项专家参与 并且处理仍然是将MRS方法转换为临床研究站点的关键障碍 光谱专家和临床实践。该项目的第一部分是为3D体素开发一种方法 使用图像指导放置，将此方法与临床MR系统整合在一起，并评估其 表现。在第二部分中，我们将自动化高级MRS方法。在第三部分，我们将创建 实时，自动量化工具特定于获得的MRS数据，该工具将提供临床解释 结果。我们确定了合作者，脑癌研究人员和临床医生，他们将成为早期采用者 我们工具的β测试器。成功完成该项目将改善数据鲁棒性和质量， 在扫描时消除了对专家互动的需求，并使MRS在多人中采用 现场临床试验和临床实践。