Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
National Centre for Healthy Ageing, Melbourne, Australia.
Int J Comput Assist Radiol Surg. 2023 Jan;18(1):171-179. doi: 10.1007/s11548-022-02736-7. Epub 2022 Sep 7.
The neuroimaging research community-which includes a broad range of scientific, medical, statistical, and engineering disciplines-has developed many tools to advance our knowledge of brain structure, function, development, aging, and disease. Past research efforts have clearly shaped clinical practice. However, translation of new methodologies into clinical practice is challenging. Anything that can reduce these barriers has the potential to improve the rate at which research outcomes can contribute to clinical practice. In this article, we introduce Karawun, a file format conversion tool, that has become a key part of our work in translating advances in diffusion imaging acquisition and analysis into neurosurgical practice at our institution.
Karawun links analysis workflows created using open-source neuroimaging software, to Brainlab (Brainlab AG, Munich, Germany), a commercially available surgical planning and navigation suite. Karawun achieves this using DICOM standards supporting representation of 3D structures, including tractography streamlines, and thus offers far more than traditional screenshot or color overlay approaches.
We show that neurosurgical planning data, created from multimodal imaging data using analysis methods implemented in open-source research software, can be imported into Brainlab. The datasets can be manipulated as if they were created by Brainlab, including 3D visualizations of white matter tracts and other objects.
Clinicians can explore and interact with the results of research neuroimaging pipelines using familiar tools within their standard clinical workflow, understand the impact of the new methods on their practice and provide feedback to methods developers. This capability has been important to the translation of advanced analysis techniques into practice at our institution.
神经影像学研究社区——包括广泛的科学、医学、统计和工程学科——已经开发了许多工具来推进我们对大脑结构、功能、发育、衰老和疾病的认识。过去的研究工作显然已经塑造了临床实践。然而,将新方法转化为临床实践具有挑战性。任何能够减少这些障碍的方法都有可能提高研究成果转化为临床实践的速度。在本文中,我们介绍了 Karawun,这是一种文件格式转换工具,它已成为我们将扩散成像采集和分析方面的进展转化为我们机构神经外科实践的关键部分。
Karawun 将使用开源神经影像学软件创建的分析工作流程与 Brainlab(德国慕尼黑的 Brainlab AG)连接起来,后者是一种商业上可用的手术计划和导航套件。Karawun 通过支持表示 3D 结构(包括轨迹流线)的 DICOM 标准来实现这一点,因此它提供的功能远远超过传统的屏幕截图或颜色叠加方法。
我们表明,使用开源研究软件中实现的分析方法从多模态成像数据创建的神经外科计划数据可以导入到 Brainlab 中。可以像创建 Brainlab 一样操作数据集,包括白质束和其他对象的 3D 可视化。
临床医生可以使用他们标准临床工作流程中的熟悉工具探索和交互研究神经影像学管道的结果,了解新方法对他们实践的影响,并向方法开发人员提供反馈。这种能力对于我们机构将高级分析技术转化为实践非常重要。