Presentation on theme: "Blood flow monitoring in cerebral vessels A. P. Chupakhin Lavrentyev Institute of Hydrodynamics, Novosibirsk, Russia Novosibirsk State University In collaboration."— Presentation transcript:
Blood flow monitoring in cerebral vessels A. P. Chupakhin Lavrentyev Institute of Hydrodynamics, Novosibirsk, Russia Novosibirsk State University In collaboration with A. A. Cherevko, A. K. Khe (Lavrentyev Institute of Hydrodynamics, Novosibirsk State University) A. L. Krivoshapkin, K. Yu. Orlov (Meshalkin Novosibirsk Research Institute of Circulation Pathology) IV International Workshop on the Multiscale Methods and Modelling in Biology and Medicine October 29–31, 2014, Moscow, Russia
Cerebral hemodynamics Hemodynamics is a hydrodynamics of fluid with various inclusions in a complex net of vessels with walls of different properties. Blood rheology: leucocytes, erythrocytes, etc. Wall properties: elasticity, fluid–structure interaction. Vessel net: branching, junction. A human brain: is of mass ≈ 1.5% mass of the body, uses ≈ 20% blood and oxygen. Characteristic flow parameters: Pulsatile flow Velocity: 20–200 cm/s Pressure: 20–150 mm Hg Viscosity: 4 cP Vessel diameter: 0.5–5 mm Vessel length: 10 0 cm Re: ≤ 100
Mathematical modeling Models: Electric circuit, hydraulic analogy, balance relations, 1D gas dynamics, Navier—Stokes equations, flows in elastic tubes, etc. Local modeling: direct 3D computations. Hemodynamics on a graph. Problems: Obtaining reliable measurement data: there is no unique or “standard” circulation configuration, there is no possibility to take measurements precise enough in vivo. Mathematical modeling: construction of models consistent with the data obtained, definition of boundary conditions.
Arterial aneurysms (AA) An aneurysm is a localized, blood- filled balloon-like bulge in the wall of a blood vessel.
Arteriovenous malformation (AVM) is a direct connection between arteries and veins, without capillary system, which leads to inadequate blood supply, change of velocity and pressure profiles, tortuosity of vessels.
How it started Why can operations, that are visually similar, differ in results? What is the difference between them? How to measure this “difference”? Does the disease need to be treated? When and how? Does the operation really help the patient?
The aim Complex investigation of pathological cerebral vessels of human: clinical and physiological analysis, mathematical and computer modeling, in order to develop new methods for diagnostics, prognosis and treatment.
Description Arteriovenous malformation of mixed type (fistula component, intranidal aneurysms), located in left temporal lobe, Spetzler–Martin II grade Size: 33,5 х 22,5 х 25 mm. Afferents: M3, М4 segments. Drainage: dilated vein into left transverse sinus, sagittal sinus.
Angiography. Frontal projection Before operationAfter operation
Angiography. Lateral projection After operationBefore operation
Pressure and velocity in sinuses PressureVelocity
Novelty For the first time simultaneous pressure and velocity invasive measurements in feeding and draining vessels of AVM are taken. Qualitative changes in local hemodynamics during the embolization are shown. Experimental data are justified by AVM hydraulic model. The data obtained are used to propose principles of the most harmless endovascular treatment of cerebral AVMs.
Main hemodynamic parameters — Volumetric flow rate — Total pressure — Energy flow rate — Load — Specific load – is energy transferred into AVM – is energy transferred out of AVM
Hydraulic model of AVM l, d — length and diameter of tubes AVM
Dependence on the level of the AVM embolization mm Hg cJ cJ/cm 3 cm/s
Dependence on the level of the AVM embolization mm Hg cJ cJ/cm 3 cm/s Specific load
Group treatment statistics Research group Comparison group Number of patients3094 Number of embolization sessions34176 Hemorrhagic complication (hemodynamic, without manipulative)11 % of hemorrhagic complications per patients 3,3%11,7% Incapacitation as a result of perioperative hemorrhage04 (4,25%) Lethality01 (0,78%) Z = 2,039; p<0,05