ArticleNeurosurgery practice2023
Time-Spatial Labeling Inversion Pulse (Time-SLIP) MRI for Evaluating Cerebrospinal Fluid Velocity and Visualizing Flow Dynamics in Patients With Chiari Type I Malformation.
Article in Neurosurgery practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Multimodality imaging of cerebrospinal fluid shunts: system evaluation and complications.Pediatric radiology · 2026Review
- A Novel MR Cine Sialography Technique for Evaluating Salivary Gland Function: Correlation with Unstimulated and Stimulated Saliva Volumes.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- The significance of cerebrospinal fluid dynamics in adolescent idiopathic scoliosis using time-SLIP MRI.Scientific reports · 2024Article
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9 authors.
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Abstract
BACKGROUND AND
objectivesPhase-contrast MRI is unstable and is not widely implemented in the imaging of Chiari malformation type I (CM-I) because of its low signal-to-noise ratio and the need for subsequent additional averaging. Time-spatial labeling inversion pulse MRI (T-SLIP MRI) is an emerging imaging modality with a high signal-to-noise ratio. This study is the first to examine cerebrospinal fluid (CSF) dynamics on the basis of velocity exclusively in patients with CM-I using T-SLIP MRI before and after posterior fossa decompression.
methodsEleven patients with CM-I underwent T-SLIP MRI before and/or after posterior fossa decompression. CSF dynamics were analyzed at 5 points around the craniovertebral junction. T-SLIP measurements included (1) targeted CSF labeling; (2) manual frame-by-frame annotation of the labeled CSF wave; (3) description of CSF flow in terms of wave functions calculated using computation software; and use of this function for (4) calculation of CSF velocity (rostral and caudal peak), total distance traveled by labeled CSF, and mean CSF velocity (
resultsRostral and caudal peaks significantly increased at 2 of the 5 points (40%), whereas
conclusionT-SLIP MRI data for patients with CM-I were successfully quantified on the basis of velocity. Tailor-made optimal decompression should be pursued based on both T-SLIP data with high accuracy and bibliographical craniometric data with surgical outcomes, which can now be easily and comprehensively analyzed using machine learning.
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