Noninvasive intracranial compliance and pressure based on dynamic magnetic resonance imaging of blood flow and cerebrospinal fluid flow: review of principles, implementation, and other noninvasive approaches

Author:

Raksin Patricia B.,Alperin Noam,Sivaramakrishnan Anusha,Surapaneni Sushma,Lichtor Terry

Abstract

Current techniques for intracranial pressure (ICP) measurement are invasive. All require a surgical procedure for placement of a pressure probe in the central nervous system and, as such, are associated with risk and morbidity. These considerations have driven investigators to develop noninvasive techniques for pressure estimation. A recently developed magnetic resonance (MR) imaging–based method to measure intracranial compliance and pressure is described. In this method the small changes in intracranial volume and ICP that occur naturally with each cardiac cycle are considered. The pressure change during the cardiac cycle is derived from the cerebrospinal fluid (CSF) pressure gradient waveform calculated from the CSF velocities. The intracranial volume change is determined by the instantaneous differences between arterial blood inflow, venous blood outflow, and CSF volumetric flow rates into and out of the cranial vault. Elastance (the inverse of compliance) is derived from the ratio of the measured pressure and volume changes. A mean ICP value is then derived based on a linear relationship that exists between intracranial elastance and ICP. The method has been validated in baboons, flow phantoms, and computer simulations. To date studies in humans demonstrate good measurement reproducibility and reliability. Several other noninvasive approaches for ICP measurement, mostly nonimaging based, are also reviewed. Magnetic resonance imaging–based ICP measurement may prove valuable in the diagnosis and serial evaluation of patients with a variety of disorders associated with alterations in ICP.

Publisher

Journal of Neurosurgery Publishing Group (JNSPG)

Subject

Clinical Neurology,General Medicine,Surgery

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