Document Detail


Non-invasive cerebrospinal fluid pressure estimation using multi-layer perceptron neural networks.
MedLine Citation:
PMID:  23367120     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Cerebrospinal fluid pressure (CSFp) provides vital information in various neurological abnormalities including hydrocephalus, intracranial hypertension and brain tumors. Currently, CSFp is measured invasively through implanted catheters within the brain (ventricles and parenchyma) which is associated with a risk of infection and morbidity. In humans, the cerebrospinal fluid communicates indirectly with the ocular circulation across the lamina cribrosa via the optic nerve subarachnoid space. It has been shown that a relationship between retinal venous pulsation, intraocular pressure (IOP) and CSFp exists with the amplitude of retinal venous pulsation being associated with the trans-laminar pressure gradient (i.e. IOP-CSFp). In this study we use this characteristic to develop a non-invasive approach to estimate CSFp. 15 subjects were included in this study. Dynamic retinal venous diameter changes and IOP were measured and fitted into our model. Artificial neural networks (ANN) were applied to construct a relationship between retinal venous pulsation amplitude, IOP (input) and CSFp (output) and develop an algorithm to estimate CSFp based on these parameters. Results show a mean square error of 2.4 mmHg and 1.27 mmHg for train and test data respectively. There was no significant difference between experimental and ANN estimated CSFp values (p>0.01).This study suggests measurement of retinal venous pulsatility in conjunction with IOP may provide a novel approach to estimate CSFp non-invasively.
Authors:
S Mojtaba Golzan; Alberto Avolio; Stuart L Graham
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2012     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2012  
Date Detail:
Created Date:  2013-01-31     Completed Date:  2013-07-24     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  5278-81     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Cerebrospinal Fluid*
Neural Networks (Computer)*
Pressure

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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