Oeltzschner Georg, Zöllner Helge J, Hui Steve C N, Mikkelsen Mark, Saleh Muhammad G, Tapper Sofie, Edden Richard A E
Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
J Neurosci Methods. 2020 Sep 1;343:108827. doi: 10.1016/j.jneumeth.2020.108827. Epub 2020 Jun 27.
Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization.
Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects.
Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques.
COMPARISON WITH EXISTING METHOD(S): Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey's open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis.
Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.
磁共振波谱(MRS)数据的处理和定量分析远未标准化,需要与第三方软件对接。在此,我们介绍Osprey,这是一个用于MRS数据的完全集成的开源数据分析管道,它将预处理、线性组合建模、定量分析和数据可视化无缝集成。
Osprey可加载多种常见的MRS数据格式,执行相控阵线圈组合、单个瞬态的频率和相位校正、信号平均以及傅里叶变换。使用模拟基集和样条基线对处理后的频谱进行线性组合建模。将MRS体素与解剖图像进行配准,对解剖图像进行分割以进行组织校正,并根据建模参数和组织分割进行定量分析。每个分析步骤的结果都在Osprey图形用户界面中可视化。在健康受试者获取的12个点分辨表面线圈谱(PRESS)、11个多量子激发点分辨表面线圈谱(MEGA-PRESS)和8个高分辨率多量子激发表面线圈谱(HERMES)数据集中展示了该分析管道。
Osprey成功加载、处理、建模并定量分析了通过各种传统和频谱编辑技术获取的MRS数据。
Osprey是首个将统一预处理、线性组合建模、组织校正和定量分析整合到一个连贯生态系统中的MRS软件。与现有的通常为闭源的编译建模软件相比,Osprey的开源代码理念使研究人员能够集成最新的数据处理和建模程序,并有可能朝着分析标准化方向发展。
Osprey将强大的经过同行评审的数据处理方法整合到一个模块化工作流程中,社区开发者可轻松对其进行扩展,从而能够快速实施新方法。