title: Inferring cerebrovascular changes from latencies of systemic and intracranial pulses: a model-based latency subtraction algorithm.
abstract: Changes in cerebral blood flow velocity (CBFV) pulse latency reflect pathophysiological changes of the cerebral vasculature based on the theory of pulse wave propagation. Timing CBFV pulse onset relative to electrocardiogram QRS is practical. However, it introduces confounding factors of extracranial origins for characterizing the cerebral vasculature. This study introduces an approach to reducing confounding influences on CBFV latency. This correction approach is based on modeling the relationship between CBFV latency and systemic arterial blood pressure (ABP) pulse latency. It is tested using an existing data set of CBFV and ABP from 14 normal subjects undergoing pressure cuff tests under both normoxic and acute hypoxic states. The results show that the proposed CBFV latency correction approach produces a more accurate measure of cerebral vascular changes, with an improved positive correlation between beat-to-beat CBFV and the CBFV latency time series, for example, correlation coefficient increased from 0.643 to 0.836 for group-averaged cuff deflation traces at normoxia. In conclusion, this study suggests that subtraction of systemic ABP latency improves CBFV latency measurements, which in turn improve the characterization of cerebral vascular changes.
authors.affiliation: Neural Systems and Dynamics Laboratory, Department of Neurosurgery, The David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA. xhu@mednet.ucla.edu
authors.forename: Xiao
authors.initials: X
authors.lastname: Hu
authors.forename: Andrew W
authors.initials: AW
authors.lastname: Subudhi
authors.forename: Peng
authors.initials: P
authors.lastname: Xu
authors.forename: Shadnaz
authors.initials: S
authors.lastname: Asgari
authors.forename: Robert C
authors.initials: RC
authors.lastname: Roach
authors.forename: Marvin
authors.initials: M
authors.lastname: Bergsneider
mesh_terms: D000328:Adult; D000465:Algorithms; D001783:Blood Flow Velocity; D002560:Cerebrovascular Circulation; D005260:Female; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D011674:Pulse; D055815:Young Adult