Systems, devices and methods for noninvasive or minimally-invasive estimation of intracranial pressure and cerebrovascular autoregulation

Abstract

The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.

1 - 30 . (canceled) 
     
     
         31 . A method for aligning physiological measurements, the method comprising:
 receiving, at a processor, a plurality of measurements related to arterial blood pressure and a plurality of measurements related to cerebral blood flow;   computing, at the processor, a plurality of estimates of a selected cerebrovascular property using a computational model comprising a plurality of model elements;   estimating a temporal offset between the plurality of measurements related to arterial blood pressure and the plurality of measurements related to cerebral blood flow by:
 determining a set of candidate temporal offsets; 
 selecting one of the candidate temporal offset based on the plurality of estimates; and 
   temporally aligning the plurality of measurements related to arterial blood pressure and the plurality of measurements related to cerebral blood flow based on the selected temporal offset.   
     
     
         32 . The method of  claim 31 , wherein the set of candidate temporal offsets is determined based on a first location corresponding to the plurality of measurements related to arterial blood pressure and a second location corresponding to the plurality of measurements related to cerebral blood flow. 
     
     
         33 . The method of  claim 31 , wherein the selected candidate temporal offset is selected to be the candidate temporal offset that optimizes a statistic of the plurality of estimates. 
     
     
         34 . The method of  claim 33 , wherein the selected candidate temporal offset minimizes a dispersion of the plurality of estimates. 
     
     
         35 . The method of  claim 31 , wherein:
 the model elements include a cerebrovascular resistance element, an intracranial pressure element, a cerebrovascular compliance element, an arterial blood pressure element, and a cerebrovascular flow element; and   the cerebrovascular property corresponds to at least one of the cerebrovascular resistance element, the intracranial pressure element, and the cerebrovascular compliance element.   
     
     
         36 . The method of  claim 35 , wherein the plurality of estimates is computed by optimizing an error criterion based on the received pluralities of measurements and model predictions of the arterial blood pressure element and the cerebrovascular flow element. 
     
     
         37 . The method of  claim 31 , further comprising using the plurality of estimates to estimate flow through a cerebrovascular resistance element of the computational model, wherein the selected cerebrovascular property corresponds to a cerebrovascular compliance element of the computational model. 
     
     
         38 . The method of  claim 31 , wherein computing the plurality of estimates comprises computing estimates of a cerebrovascular compliance element in a first stage of a two-stage algorithm. 
     
     
         39 . The method of  claim 31 , wherein computing the plurality of estimates comprises computing estimates of at least one of a cerebrovascular resistance element and a intracranial pressure element in a second stage of a two-stage algorithm. 
     
     
         40 . The method of  claim 31 , wherein the processor does not receive, prior to computing the plurality of estimates, patient-specific invasive intracranial pressure training data or population-specific invasive intracranial pressure training data. 
     
     
         41 . The method of  claim 31 , wherein the plurality of measurements related to arterial blood pressure corresponds to measurements of at least one characteristic feature of arterial blood pressure, and the plurality of measurements related to cerebral blood flow corresponds to measurements of at least one characteristic feature of cerebral blood flow. 
     
     
         42 . The method of  claim 31 , wherein the plurality of measurements related to cerebral blood flow are measurements of velocity of cerebral blood flow. 
     
     
         43 . A device for aligning physiological measurements, the device comprising:
 processing circuitry configured to:
 receive a plurality of measurements related to arterial blood pressure and a plurality of measurements related to cerebral blood flow; 
 compute a plurality of estimates of a selected cerebrovascular property using a computational model comprising a plurality of model elements; 
 estimate a temporal offset between the plurality of measurements related to arterial blood pressure and the plurality of measurements related to cerebral blood flow by:
 determining a set of candidate temporal offsets; 
 selecting one of the candidate temporal offset based on the plurality of estimates; and 
 
 temporally align the plurality of measurements related to arterial blood pressure and the plurality of cerebral blood flow measurements based on the selected temporal offset; and 
   a memory in communication with the processor, wherein the memory stores at least one of the received measurements, the computed estimates, and the set of candidate temporal offsets.   
     
     
         44 . The device of  claim 43 , wherein the set of candidate temporal offsets is determined based on a first location corresponding to the plurality of measurements related to arterial blood pressure and a second location corresponding to the plurality of measurements related to cerebral blood flow. 
     
     
         45 . The device of  claim 43 , wherein the selected candidate temporal offset is selected to be the candidate temporal offset that optimizes a statistic of the plurality of estimates. 
     
     
         46 . The device of  claim 45 , wherein the selected candidate temporal offset minimizes a dispersion of the plurality of estimates. 
     
     
         47 . The device of  claim 43 , wherein:
 the model elements include a cerebrovascular resistance element, an intracranial pressure element, a cerebrovascular compliance element, an arterial blood pressure element, and a cerebrovascular flow element; and   the cerebrovascular property corresponds to at least one of the cerebrovascular resistance element, the intracranial pressure element, and the cerebrovascular compliance element.   
     
     
         48 . The device of  claim 47 , wherein the plurality of estimates is computed by optimizing an error criterion based on the received pluralities of measurements and model predictions of the arterial blood pressure element and the cerebrovascular flow element. 
     
     
         49 . The device of  claim 43 , wherein the processing circuitry is further configured to use the plurality of estimates to estimate flow through a cerebrovascular resistance element of the computational model, and wherein the selected cerebrovascular property corresponds to a cerebrovascular compliance element of the computational model. 
     
     
         50 . The device of  claim 43 , wherein the processing circuitry computes the plurality of estimates by computing estimates of a cerebrovascular compliance element in a first stage of a two-stage algorithm. 
     
     
         51 . The device of  claim 43 , wherein the processing circuitry computes the plurality of estimates by computing estimates of at least one of a cerebrovascular resistance element and a intracranial pressure element in a second stage of a two-stage algorithm. 
     
     
         52 . The device of  claim 43 , wherein the processing circuitry does not receive, prior to computing the plurality of estimates, patient-specific invasive intracranial pressure training data or population-specific invasive intracranial pressure training data. 
     
     
         53 . The device of  claim 43 , wherein the plurality of measurements related to arterial blood pressure corresponds to measurements of at least one characteristic feature of arterial blood pressure, and the plurality of measurements related to cerebral blood flow corresponds to measurements of at least one characteristic feature of cerebral blood flow. 
     
     
         54 . The device of  claim 43 , wherein the plurality of measurements related to cerebral blood flow are measurements of velocity of cerebral blood flow.