Systems, devices and methods for noninvasive or minimally-invasive estimation of intracranial pressure and cerebrovascular autoregulation
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. A method for assessing autoregulation, comprising:
receiving, at a processor, a plurality of arterial blood pressure measurements and a plurality of cerebrovascular flow measurements;
computing, at the processor, a plurality of estimates of a selected cerebrovascular property using a computational model comprising a plurality of model elements, 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;
the cerebrovascular property corresponds to at least one of the cerebrovascular resistance element, the intracranial pressure element, and the cerebrovascular compliance element; and
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; and
providing an assessment of cerebrovascular autoregulation based on the plurality of estimates.
2. The method of claim 1 , further comprising estimating flow through the cerebrovascular resistance element using the plurality of estimates, wherein the selected cerebrovascular property corresponds to the cerebrovascular compliance element.
3. The method of claim 1 , wherein at least one of the model elements is computed at least once per cardiac cycle.
4. The method of claim 1 , wherein at least one of the model elements is estimated using a data window of a pre-specified size.
5. The method of claim 1 , wherein computing the plurality of estimates comprises using a two-stage algorithm.
6. The method of claim 5 , wherein computing the plurality of estimates comprises computing estimates of the cerebrovascular compliance element in a first stage of the two-stage algorithm.
7. The method of claim 5 , wherein computing the plurality of estimates comprises computing estimates of at least one of the cerebrovascular resistance element and the intracranial pressure element in a second stage of a two-stage algorithm.
8. The method of claim 1 , wherein the error criterion is least-squared error.
9. The method of claim 1 , 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.
10. The method of claim 1 , wherein the plurality of estimates is a plurality of relative estimates.
11. A device for assessing autoregulation the device including:
a processor, the processor configured to:
receive a plurality of arterial blood pressure measurements and a plurality of cerebrovascular flow measurements;
compute and display a plurality of estimates of a selected cerebrovascular property using a computational model comprising a plurality of model elements, wherein:
the model elements include a cerebrovascular compliance element, a cerebrovascular resistance element, an intracranial pressure element, an arterial blood pressure element, and a cerebrovascular flow element;
the cerebrovascular property corresponds to at least one of the cerebrovascular resistance element, the intracranial pressure element, and the cerebrovascular compliance element; and
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; and
provide an assessment of cerebrovascular autoregulation based on the plurality of estimates
a memory in communication with the processor for storing at least one of the received measurements and the computed estimates.
12. The device of claim 11 , further comprising:
a sensing device in communication with the processor for sensing the arterial blood pressure measurements.
13. The device of claim 12 , wherein the sensing device includes at least one of an arterial catheter, a tonometry sensor, a sphygmomanometer sensor, and a photoplethysmography sensor.
14. The device of claim 11 , further comprising:
a sensing device in communication with the processor for sensing the cerebrovascular flow measurements.
15. The device of claim 14 , wherein the sensing device includes an ultrasound sensor.
16. The device of claim 11 , further comprising a signal quality processor in communication with the processor configured to assess the quality of the received measurements.
17. The device of claim 16 , wherein the signal quality processor is configured to remove unwanted portions of the received measurements.
18. The device of claim 17 , wherein the unwanted portions include noise and artifact.
19. The device of claim 11 , further comprising a smoothing processor configured to filter the computed estimates.
20. The device of claim 19 , wherein the smoothing processor is configured to filter the computed estimates using a median filter.
21. The device of claim 11 , further comprising an extraction processor for extracting intra-beat features of the received measurements.
22. The device of claim 11 , wherein at least one of the estimates is computed at least once per cardiac cycle.
23. The device of claim 11 , wherein the processor computes the estimates using a data window of a pre-specified size.
24. The device of claim 11 , wherein the processor computes the estimates using a two-stage algorithm.
25. The device of claim 24 , wherein the processor computes an estimate of a cerebrovascular compliance in a first stage of the two-stage algorithm.
26. The device of claim 24 , wherein the processor computes an estimate of at least one of a cerebrovascular resistance and an intracranial pressure in a second stage of the two-stage algorithm.
27. The device of claim 11 , wherein the processor does not receive, prior to computing at least one estimate in the plurality of estimates, patient-specific invasive intracranial pressure training data or population specific invasive intracranial pressure training data.
28. The device of claim 11 , wherein the estimate is a relative estimate.