NDLI: Non-invasive cerebrospinal fluid pressure estimation using multi-layer perceptron neural networks

Content Provider	IEEE Xplore Digital Library
Author	Golzan, S.M. Avolio, A. Graham, S.L.
Copyright Year	2012
Description	Author affiliation: Australian Sch. of Adv. Med., Macquarie Univ., Sydney, NSW, Australia (Golzan, S.M.; Avolio, A.; Graham, S.L.)
Abstract	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.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	5278
Ending Page	5281
File Size	760729
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347185
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Retina Artificial neural networks Estimation Fluids Veins Neurons Educational institutions
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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