PubMed Health⌕ Search

PubMed · 10838503

Pump-regulated cerebrospinal fluid drainage.

Abstract

The drainage of cerebrospinal fluid (CSF) from the lumbar subarachnoid space is an effective technique for the treatment of CSF fistula and control of intracranial pressure in children and adults. The use of the lumbar drain poses unique challenges, however, in the pediatric population. We present a safe and effective method of pump-controlled lumbar subarachnoid drainage. This technique allows accurate titration of CSF removal while providing a closed system which is not sensitive to position changes or patient activity. Four case histories are reviewed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J R Vender, P Houle, A M Flannery, K Fryburg, M R Lee. 2000. Pump-regulated cerebrospinal fluid drainage.. https://doi.org/10.1159/000028901

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A penalized likelihood approach to magnetic resonance image reconstruction.

Currently, images acquired via magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) technology are reconstructed using the discrete inverse Fourier transform. While computationally convenient, this approach is not able to filter out noise. This is a serious limitation because the amount of noise in MRI and fMRI can be substantial. In this paper, we propose an alternative approach to reconstruction, based on penalized likelihood methodology. In particular, we focus on non-linear shrinkage estimators and show that this approach achieves a great reduction in integrated mean squared error (IMSE) of the estimated image with respect to the currently used estimator. This approach is extremely fast and easy to implement computationally. In addition, it can be combined with various alternative approaches to MR image reconstruction and can be easily adapted to other, non-MRI contexts, in which the observed data and the quantities of interest are related via a linear transform.

Brain Diseases↗