A pseudo-Bayesian model-based approach for noninvasive intracranial pressure estimation

A noninvasive intracranial pressure (ICP) estimation method is proposed that incorporates model-based estimation within a probabilistic framework. A first-order subject-specific model of the cerebral vasculature relates arterial blood pressure with cerebral blood flow velocity. The model is solved for a range of physiologically plausible ICP values, and the resulting residual errors are transformed into likelihoods for each candidate ICP. The likelihoods are combined with a imulti-modal prior distribution of the ICP to yield an a posteriori distribution whose mode is taken as the final ICP estimate. An extension to this method is proposed to harness the temporal evolution of past ICP estimates for reducing dependence on the multi-modal prior distribution. This approach combines ICP estimates computed with a uniform prior belief with predictions from a single-state model of cerebral autoregulatory dynamics. This method was tested on data from thirteen patients from Boston Children's Hospital and yielded an ICP estimation bias (mean error or accuracy) of 0.3 nrmmHg and a root-mean-squared error (or precision) of 5.2 minHg. These performance characteristics are well within the acceptable range for clinical decision making. The method proposed here therefore constitutes a significant step towards robust, continuous, patient-specific noninvasive ICP determination.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Imaduddin, Syed M. (Syed Muhammad)

Advisor dc:contributor.advisor

• Thomas Heldt.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/117318

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/117318