http://stm.sciencemag.org/content/4/129/129ra44.abstract
Abstract
Intracranial pressure (ICP) is affected
in many neurological conditions. Clinical measurement of pressure on
the brain currently
requires placing a probe in the cerebrospinal
fluid compartment, the brain tissue, or other intracranial space. This
invasiveness
limits the measurement to critically ill
patients. Because ICP is also clinically important in conditions ranging
from brain
tumors and hydrocephalus to concussions,
noninvasive determination of ICP would be desirable. Our model-based
approach to
continuous estimation and tracking of ICP uses
routinely obtainable time-synchronized, noninvasive (or minimally
invasive)
measurements of peripheral arterial blood
pressure and blood flow velocity in the middle cerebral artery (MCA),
both at intra-heartbeat
resolution. A physiological model of
cerebrovascular dynamics provides mathematical constraints that relate
the measured waveforms
to ICP. Our algorithm produces patient-specific
ICP estimates with no calibration or training. Using 35 hours of data
from
37 patients with traumatic brain injury, we
generated ICP estimates on 2665 nonoverlapping 60-beat data windows.
Referenced
against concurrently recorded invasive
parenchymal ICP that varied over 100 millimeters of mercury (mmHg)
across all records,
our estimates achieved a mean error (bias) of
1.6 mmHg and SD of error (SDE) of 7.6 mmHg. For the 1673 data windows
over 22
hours in which blood flow velocity recordings
were available from both the left and the right MCA, averaging the
resulting
bilateral ICP estimates reduced the bias to 1.5
mmHg and SDE to 5.9 mmHg. This accuracy is already comparable to that of
some
invasive ICP measurement methods in current
clinical use.
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