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（由申请人提供）：使用水扩散测量，dMRI可以提供对组织微观结构和细胞取向的独特见解。在神经外科脑癌研究中，dMRI是唯一提供有关白色物质连接（纤维束）轨迹信息的现有方法。神经外科医生的目标是在手术切除肿瘤时保留关键的纤维束。dMRI还提供定量测量，可以帮助定义脑肿瘤的边界，或区分肿瘤浸润和水肿。在神经外科界，人们越来越意识到扩散模型必须超越当前的扩散张量临床标准，以获得更好的纤维束解剖准确性。但是，一些信息学挑战阻碍了dMRI的进展很容易达到临床癌症研究人员：1）dMRI的进展不受商业临床软件的支持，2）dMRI研究软件不是为临床癌症环境设计的，3）缺乏通用文件格式标准阻碍了dMRI软件包之间的互操作性。与其他流行的dMRI软件包不同，社区软件包3D Slicer 4.0（www.slicer.org）具有独特的定位，可以实现脑癌的新临床研究，因为它从一开始就为患者特定的癌症研究而设计。3D Slicer软件包是一个基于社区的开源软件平台，2013年全球共有68629次Slicer下载。虽然Slicer目前的dMRI功能与商业脑癌神经元导航软件中可用的技术相当，但3D Slicer中可用的基本扩散张量模型不再是研究的最新技术。 其缺点包括纤维束的解剖不准确性和DTI衍生测量的非特异性。我们建议开发开源软件基础设施和关键的临床相关工作流程，以便使用3D Slicer实现更先进的dMRI技术，用于开源癌症研究。此外，我们建议通过基于新提出的用于MR扩散纤维束成像存储的DICOM补充文件，为dMRI纤维束成像文件格式开发一个独立的符合标准的库，以提高文件格式的互操作性。我们将与当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合作者合作，他们都在研究中使用3D Slicer。我们的软件传播将利用基于社区的Slicer软件的基础设施。预期的成果是在开源软件3D Slicer和符合标准的纤维束成像文件格式库中提供最先进的dMRI工具套件。我们希望这种开源的dMRI技术能够实现脑癌的新临床研究。