title: Intracranial pressure pulse waveform correlates with aqueductal cerebrospinal fluid stroke volume.
abstract: This study identifies a novel relationship between cerebrospinal fluid (CSF) stroke volume through the cerebral aqueduct and the characteristic peaks of the intracranial pulse (ICP) waveform. ICP waveform analysis has become much more advanced in recent years; however, clinical practice remains restricted to mean ICP, mainly due to the lack of physiological understanding of the ICP waveform. Therefore, the present study set out to shed some light on the physiological meaning of ICP morphological metrics derived by the morphological clustering and analysis of continuous intracranial pulse (MOCAIP) algorithm by investigating their relationships with a well defined physiological variable, i.e., the stroke volume of CSF through the cerebral aqueduct. Seven patients received both overnight ICP monitoring along with a phase-contrast MRI (PC-MRI) of the cerebral aqueduct to quantify aqueductal stroke volume (ASV). Waveform morphological analysis of the ICP signal was performed by the MOCAIP algorithm. Following extraction of morphological metrics from the ICP signal, nine temporal ICP metrics and two amplitude-based metrics were compared with the ASV via Spearman's rank correlation. Of the nine temporal metrics correlated with the ASV, only the width of the P2 region (ICP-Wi2) reached significance. Furthermore, both ICP pulse pressure amplitude and mean ICP did not reach significance. In this study, we showed the width of the second peak (ICP-Wi2) of an ICP pulse wave is positively related to the volume of CSF movement through the cerebral aqueduct. This finding is an initial step in bridging the gap between ICP waveform morphology research and clinical practice.
authors.affiliation: Neural Systems and Dynamics Laboratory, Department of Neurosurgery, the David Geffen School of Medicine, University of California-Los Angeles, 10833 Le Conte Ave., Los Angeles, CA 90095, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Hamilton
authors.forename: Kevin
authors.initials: K
authors.lastname: Baldwin
authors.forename: Jennifer
authors.initials: J
authors.lastname: Fuller
authors.forename: Paul
authors.initials: P
authors.lastname: Vespa
authors.forename: Xiao
authors.initials: X
authors.lastname: Hu
authors.forename: Marvin
authors.initials: M
authors.lastname: Bergsneider
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002535:Cerebral Aqueduct / Q000503:physiopathology*; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D006850:Hydrocephalus, Normal Pressure / Q000134:cerebrospinal fluid / Q000175:diagnosis / Q000503:physiopathology*; D007427:Intracranial Pressure; D008279:Magnetic Resonance Imaging; D008297:Male; D008991:Monitoring, Physiologic / Q000379:methods*; D011673:Pulsatile Flow; D063177:Pulse Wave Analysis; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors