Open source diffusion MRI technology for brain cancer research

用于脑癌研究的开源扩散 MRI 技术

• 批准号: 9324191
• 负责人: Lauren Jean O'Donnell
• 金额: $ 36.83万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-22 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9324191
• 关键词: Address; Algorithms; Anatomy; Atlases; Awareness; Boston; Brain; Brain Neoplasms; Brain imaging; Clinical; Clinical Research; Communities; Computer software; Data; Development; Diffusion; Diffusion Magnetic Resonance Imaging; Documentation; Edema; Event; Feedback; Fiber; Funding; Germany; Goals; Image; Imagery; Infiltration; Informatics; International; Internet; Intervention Studies; Language; Libraries; Licensing; Malignant Neoplasms; Malignant neoplasm of brain; Malignant neoplasm of prostate; Measurement; Measures; Medical; Methods; Modeling; Modernization; Monitor; Neuroanatomy; Neurons; Neurosurgeon; Operative Surgical Procedures; Outcome; Patients; Performance; Positioning Attribute; Research; Research Infrastructure; Research Personnel; Resource Sharing; Running; Technology; Testing; Time; Tissues; Translating; United States National Institutes of Health; anticancer research; base; cellular imaging; clinical translation; clinically relevant; data modeling; design; file format; improved; insight; interoperability; model development; neurosurgery; novel; open source; prevent; public health relevance; response; technology development; tool; tractography; tumor; usability; water diffusion; white matter

 DESCRIPTION (provided by applicant): Using measurements of water diffusion, dMRI can give unique insights into the microstructure and cellular orientation of tissues. In neurosurgical brain cancer research, dMRI is the only existing method that provides information about the trajectories of the white matter connections (fiber tracts). Neurosurgeons aim to preserve key fiber tracts when surgically removing tumors. dMRI also provides quantitative measurements that may aid in defining the borders of brain tumors, or in distinguishing tumor infiltration from edema. There is a growing awareness in the neurosurgery community that diffusion models must move beyond the current clinical standard of the diffusion tensor for better anatomical accuracy of fiber tracts. But several informatics challenges prevent advances in dMRI from easily reaching clinical cancer researchers: 1) advances in dMRI are not supported by commercial clinical software, 2) dMRI research software is not designed for clinical cancer settings, and 3) a lack of common file format standards prevents interoperability between dMRI software packages. Unlike other popular dMRI packages, the community software package 3D Slicer 4.0 (www.slicer.org) is uniquely positioned to enable novel clinical research in brain cancer because it was designed from the start for patient-specific cancer research. The 3D Slicer software package is an open-source community-based software platform, with 68629 total Slicer downloads around the world in 2013. While the current dMRI capabilities of Slicer are comparable to the technology available in commercial brain cancer neuron navigation software, the basic diffusion tensor model available in 3D Slicer is no longer state of the art for research. Its drawbacks include anatomical inaccuracies in fiber tracts and non-specificity of DTI-derived measurements. We propose to develop the open-source software infrastructure and key clinically-relevant workflows necessary to move toward more advanced dMRI technologies for open-source cancer research using 3D Slicer. In addition, we propose to improve file format interoperability by developing a standalone standards- compliant library for dMRI tractography file formats, based on the newly proposed DICOM supplement for MR diffusion tractography storage. We will collaborate with local and international neurosurgical brain cancer researchers as well as our prostate cancer research collaborators, all of whom use 3D Slicer in their research. Our software dissemination will leverage the infrastructure in place for the community-based Slicer software. The expected outcome is a state-of-the-art suite of dMRI tools in the open-source software 3D Slicer and a standards-compliant tractography file format library. We expect that this open source dMRI technology will enable novel clinical research in brain cancer.

 描述（由适用提供）：使用水扩散的测量，DMRI可以为组织的微观结构和细胞方向提供独特的见解。在神经外科脑癌研究中，DMRI是唯一提供有关白质连接轨迹（纤维区）信息的现有方法。神经外科医生旨在在手术切除肿瘤时保持关键的纤维区域。 DMRI还提供了定量测量，可以有助于定义脑肿瘤的边界或区分肿瘤浸润与水肿。在神经外科社区中，人们越来越意识到，扩散模型必须超越扩散张量的当前临床标准，以提高纤维区域的解剖精度。但是，一些信息性挑战阻止了DMRI的进步轻松到达临床癌症研究人员：1）商业临床软件不支持DMRI的进步，2）DMRI研究软件不是为临床癌症设置而设计的，而3）缺乏常见的文件格式标准标准会导致DMRI软件包装之间的可介入性。与其他受欢迎的DMRI软件包不同，社区软件包3D Slicer 4.0（www.slicer.org）具有独特的位置，可以实现脑癌的新型临床研究，因为它是从一开始就针对患者特异性癌症研究而设计的。 3D SliCer软件包是一个开源社区的软件平台，2013年全球68629个Slicer下载量为68629。SLICER的当前DMRI功能与商业脑癌神经元导航软件中可用的技术相媲美，但基本的扩散tensor Tensor模型在3D SliCer中不再可用于研究。 它的缺点包括纤维区域的解剖不准确性以及DTI衍生测量的非特异性。我们建议开发开源软件基础架构和关键的临床与临床相关的工作流程，以迈向使用3D切片机进行开源癌症研究的更先进的DMRI技术。此外，我们建议通过开发符合DMRI Tractography文件格式的独立标准库来改善文件格式的互操作性，这是基于新提出的DICOM补充，用于MR扩散拖拉机存储。我们将与本地和国际神经外科脑癌研究人员以及我们的前列腺癌研究人员合作，他们在研究中都使用3D切片机。我们的软件传播将利用基于社区的切片机软件的基础架构。预期的结果是开源软件3D切片机中的DMRI工具的最先进套件和符合标准的拖拉图文件格式库。我们预计，这种开源DMRI技术将在脑癌方面进行新的临床研究。