Methods and systems for optimizing perivascular neuromodulation therapy using computational fluid dynamics
Methods and systems for optimizing perivascular neuromodulation therapy using computational fluid dynamics. Digital data regarding three-dimensional imaging of a target blood vessel and corresponding hemodynamic data are inputs to generating a computational fluid dynamics (CFD) model. The CFD model enables identification of one or more regions of the vessel suitable for neuromodulation therapy and/or identifying one or more regions of the vessel to avoid during such therapy. A system of the present technology can include a neuromodulation catheter, a computing device that can generate and analyze the CFD model, and a user interface for displaying the vessel with indicia for target regions and/or avoidance regions.
1 . A system comprising:
a processor configured to:
receive digital data including information about at least one feature of a blood vessel of a patient;
receive hemodynamic data from at least one sensor;
generate a model of the blood vessel based at least in part on the digital data and the hemodynamic data;
determine at least one of a target region of the blood vessel for delivery of neuromodulation therapy or an avoidance region of the blood vessel for avoiding delivery of neuromodulation therapy based on the model; and
generate an output indicative of at least one of the target region or the avoidance region.
2 . The system of claim 1 , wherein the at least one feature of the blood vessel includes at least one of a cross-sectional area of the blood vessel, a cross-sectional diameter of the blood vessel, a volume of a portion of the blood vessel, or a length of the portion of the blood vessel.
3 . The system of claim 1 , wherein the at least one feature of the blood vessel includes at least one of a vessel wall, a portion of the vessel wall, a lumen, a branch, a bifurcation, a carina, an ostium, a taper region, an aneurysm, fibromuscular dysplasia, an occlusion, an impingement, a calcification, or an intimal deposit.
4 . The system of claim 1 , wherein the digital data comprises three-dimensional imaging data.
5 . The system of claim 1 , wherein the digital data includes data acquired using at least one of x-ray imaging, computed tomography, magnetic resonance imaging, fluoroscopy, ultrasound, optical coherence tomography (OCT), or intracardiac echocardiography (ICE).
6 . The system of claim 1 , wherein the digital data includes data acquired using angiography.
7 . The system of claim 1 , wherein the hemodynamic data comprises a measurement of at least one of blood pressure, blood flow, blood impedance, or viscosity of blood of the patient.
8 . The system of claim 1 , further comprising a neuromodulation catheter including a sensor of the at least one sensor.
9 . The system of claim 1 , further comprising an external device including a sensor of the at least one sensor.
10 . The system of claim 1 , wherein the model comprises a computational fluid dynamics (CFD) model of the blood vessel.
11 . The system of claim 1 , wherein the processor is configured to determine the target region based on the model.
12 . The system of claim 11 , wherein the processor is configured to determine the target region by at least comparing a hemodynamic parameter at a given location within the blood vessel to a threshold value.
13 . The system of claim 1 , wherein the processor is configured to determine the avoidance region based on the model.
14 . The system of claim 13 , wherein the processor is configured to determine the avoidance region by at least comparing a hemodynamic parameter at a given location within the blood vessel to a threshold value.
15 . The system of claim 13 , wherein the processor is configured to determine the avoidance region by at least identifying portions of the blood vessel having low wall shear stress (WSS), high WSS, high WSS gradients, an ostium, a carina, a taper region, a calcification, a fibromuscular dysplasia, an aneurysm, a bifurcation, a region of blood flow separation, an eddy, a region of impinged blood flow, a region of turbulent blood flow, a region of secondary blood flow, or a combination thereof.
16 . The system of claim 1 , wherein generating the output comprises displaying a representation of the blood vessel including visual markers indicating at least one of the target region or the avoidance region.
17 . The system of claim 1 , wherein the processor is configured to:
receive data from a neuromodulation catheter regarding a position of the neuromodulation catheter in the blood vessel; and
output a recommendation of whether to proceed with neuromodulation therapy at the position based on the at least one of the avoidance region or the target region.
18 . A method comprising:
receiving, by a processor, digital data including information about at least one feature of a blood vessel of a patient;
receiving, by the processor, hemodynamic data from a sensor;
generating, by the processor, a model of the blood vessel based at least in part on the digital data and the hemodynamic data;
determining, by the processor, at least one of a target region of the blood vessel for delivery of neuromodulation therapy or an avoidance region of the blood vessel for avoiding delivery of neuromodulation therapy based on the model; and
generating, by the processor, an output indicative of at least one of the target region or the avoidance region.
19 . The method of claim 18 , wherein determining the at least one of the target region or the avoidance region comprises determining the avoidance region by at least identifying, based on the model of the blood vessel, portions of the blood vessel having low wall shear stress (WSS), high WSS, high WSS gradients, an ostium, a carina, a taper region, a calcification, a fibromuscular dysplasia, an aneurysm, a bifurcation, a region of blood flow separation, an eddy, a region of impinged blood flow, a region of turbulent blood flow, a region of secondary blood flow, or a combination thereof.