Model-Based, Noninvasive Monitoring of Intracranial Pressure

Abstract

The project aims (i) to further develop and validate a novel model-based approach to noninvasive, calibration free determination of intracranial pressure (ICP) from quantities that are routinely measured in clinical settings, and (ii) to initiate the creation of a publicly available reference database of physiological signals collected from brain injury patients. Our noninvasive ICP (nICP) estimate requires simultaneous measurement of the waveforms of arterial blood pressure (ABP), obtained via radial artery catheter or finger cuff, and of cerebral blood flow velocity (CBFV) at a major cerebral artery, measured by transcranial Doppler (TCD). The target population for our initial database comprises subarachnoid hemorrhage patients in neuro-intensive care at our partner hospital, for whom ICP, ABP and CBFV are currently measured as the clinical standard of care. Our major accomplishments so far on this project include: assembling a component-based system to support data collection and processing in the intensive care setting; converting our earlier batch-mode nICP estimation algorithms to run continuously and in real time; developing the associated software and user interfaces; arranging for the data-collection modalities to satisfy an existing IRB that allows the collected data to be transferred to the publicly accessible MIMIC II database; and familiarizing the hospital staff with the equipment and procedures. We have also continued to work on developing signal-quality metrics, and have refinements and extensions of the underlying estimation algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2012
Accession Number
ADA568099

Entities

People

  • George Verghese

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Arteries
  • Biomedical Engineering
  • Biomedical Research
  • Blood
  • Blood Flow
  • Brain Injuries
  • Cardiovascular Physiological Phenomena
  • Databases
  • Digital Data
  • Health Services
  • Measurement
  • Monitoring
  • Standards

Fields of Study

  • Medicine

Readers

  • Cardiovascular Physiology
  • Clinical Trial Research.
  • Computational Modeling and Simulation