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Cerebrospinal fluid (CSF) plays a critical role in brain metabolism and protection from external forces. Traditional MRI can provide some insights into CSF dynamics; however, more advanced and cost-effective methods are needed for precise and comprehensive visualization of flow patterns, velocities, and directions in clinical settings. In this paper, we demonstrate a new application of a few open-source computer vision software packages to capture CSF motion from time spatial inversion pulse (Time-SLIP) MRI clinical images (in DICOM format). To test the hypothesis that the CSF flow depends on head motions, a reliable and robust pipeline of processing Time-SLIP MRI images is developed to extract both anatomy and CSF motion dynamics. The paper presents a methodology for extracting unsteady flow information from Time-SLIP MRI images and the results of its application. The results show that the computer vision method can be applied to extract unsteady CSF flow information. We also discuss observations and identify future areas for improvement by integrating CFD simulations for validation as a vital component for studying CSF dynamics.

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MRI Image-Based Mapping of Human Head Motion and Brain Ventricular Cerebrospinal Fluid Flows Using Computer Vision

  • 会议论文

  • 发表日期：

    2025年

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  • Jin Xu,
  • William W. Liou,
  • Shinya Yamada,
  • Madoka Nakajima,
  • Masakazu Miyajima,
  • Ko Horikoshi

摘要

Cerebrospinal fluid (CSF) plays a critical role in brain metabolism and protection from external forces. Traditional MRI can provide some insights into CSF dynamics; however, more advanced and cost-effective methods are needed for precise and comprehensive visualization of flow patterns, velocities, and directions in clinical settings. In this paper, we demonstrate a new application of a few open-source computer vision software packages to capture CSF motion from time spatial inversion pulse (Time-SLIP) MRI clinical images (in DICOM format). To test the hypothesis that the CSF flow depends on head motions, a reliable and robust pipeline of processing Time-SLIP MRI images is developed to extract both anatomy and CSF motion dynamics. The paper presents a methodology for extracting unsteady flow information from Time-SLIP MRI images and the results of its application. The results show that the computer vision method can be applied to extract unsteady CSF flow information. We also discuss observations and identify future areas for improvement by integrating CFD simulations for validation as a vital component for studying CSF dynamics.