Andreas A. Linninger

Pulsatile cerebrospinal fluid dynamics in the human brain

Disturbances of the cerebrospinal fluid (CSF) flow in the brain can lead to hydrocephalus, a condition affecting thousands of people annually in the US. Considerable controversy exists about fluid and pressure dynamics, and about how the brain responds to changes in flow patterns and compression in hydrocephalus. This paper presents a new model based on the first principles of fluid mechanics. This model of fluid-structure interactions predicts flows and pressures throughout the brains ventricular pathways consistent with both animal intracranial pressure (ICP) measurements and human CINE phase-contrast magnetic resonance imaging data. The computations provide approximations of the tissue deformations of the brain parenchyma. The model also quantifies the pulsatile CSF motion including flow reversal in the aqueduct as well as the changes in ICPs due to brain tissue compression. It does not require the existence of large transmural pressure differences as the force for ventricular expansion. Finally, the new model gives an explanation of communicating hydrocephalus and the phenomenon of asymmetric hydrocephalus.

Computational methods for predicting drug transport in anisotropic and heterogeneous brain tissue

Effective drug delivery for many neurodegenerative diseases or tumors of the central nervous system is challenging. Targeted invasive delivery of large macromolecules such as trophic factors to desired locations inside the brain is difficult due to anisotropy and heterogeneity of the brain tissue. Despite much experimental research, prediction of bio-transport phenomena inside the brain remains unreliable. This article proposes a rigorous computational approach for accurately predicting the fate of infused therapeutic agents inside the brain. Geometric and physiological properties of anisotropic and heterogeneous brain tissue affecting drug transport are accounted for by in-vivo diffusion tensor magnetic resonance imaging data. The three-dimensional brain anatomy is reconstructed accurately from subject-specific medical images. Tissue anisotropy and heterogeneity are quantified with the help of diffusion tensor imaging (DTI). Rigorous first principles physical transport phenomena are applied to predict the fate of a high molecular weight trophic factor infused into the midbrain. Computer prediction of drug distribution in humans accounting for heterogeneous and anisotropic brain tissue properties have not been adequately researched in open literature before.

A mathematical model of blood, cerebrospinal fluid and brain dynamics

Using first principles of fluid and solid mechanics a comprehensive model of human intracranial dynamics is proposed. Blood, cerebrospinal fluid (CSF) and brain parenchyma as well as the spinal canal are included. The compartmental model predicts intracranial pressure gradients, blood and CSF flows and displacements in normal and pathological conditions like communicating hydrocephalus. The system of differential equations of first principles conservation balances is discretized and solved numerically. Fluid–solid interactions of the brain parenchyma with cerebral blood and CSF are calculated. The model provides the transitions from normal dynamics to the diseased state during the onset of communicating hydrocephalus. Predicted results were compared with physiological data from Cine phase-contrast magnetic resonance imaging to verify the dynamic model. Bolus injections into the CSF are simulated in the model and found to agree with clinical measurements.

Dynamics of lateral ventricle and cerebrospinal fluid in normal and hydrocephalic brains.

To develop quantitative MRI techniques to measure, model, and visualize cerebrospinal fluid (CSF) hydrodynamics in normal subjects and hydrocephalic patients.

Normal and Hydrocephalic Brain Dynamics: The Role of Reduced Cerebrospinal Fluid Reabsorption in Ventricular Enlargement

CINE phase-contrast MRI (CINE-MRI) was used to measure cerebrospinal fluid (CSF) velocities and flow rates in the brain of six normal subjects and five patients with communicating hydrocephalus. Mathematical brain models were created using the MRI images of normal subjects and hydrocephalic patients. In our model, the effect of pulsatile vascular expansion is responsible for pulsatile CSF flow between the cranial and the spinal subarachnoidal spaces. Simulation results include intracranial pressure gradients, solid stresses and strains, and fluid velocities throughout the cranio-spinal system. Computed velocities agree closely with our in vivo CINE-MRI CSF flow measurements. In addition to normal intracranial dynamics, our model captures the transition to acute communicating hydrocephalus. By increasing the value for reabsorption resistance in the subarachnoid villi, our model predicts that the poroelastic parenchyma matrix will be drained and the ventricles enlarge despite small transmantle pressure gradients during the transitional phase. The poroelastic simulation thus provides a plausible explanation on how reabsorption changes could be responsible for enlargement of the ventricles without large transmantle pressure gradients.

Systematic design of drug delivery therapies

This paper presents an engineering approach for optimal drug delivery to the human brain. The hierarchical design procedure addresses three major challenges: (i) physiologically consistent geometric models of the brain anatomy, (ii) discovery of unknown transport and metabolic reaction rates of therapeutic drugs by problem inversion, and (iii) a rigorous method for determining optimal parameters for delivering therapeutic agents to desired target anatomy in the brain. The proposed interdisciplinary approach integrates medical imaging and diagnosis with systems biology and engineering optimization in order to better quantify transport and reaction phenomena in the brain in vivo. It will enhance the knowledge gained from clinical data by combining advanced imaging techniques with large scale optimization of distributed systems. The new procedure will allow physicians and scientists to design and optimize invasive drug delivery techniques systematically based on in vivo drug distribution data and rigorous first principles models.

The frequency and magnitude of cerebrospinal fluid pulsations influence intrathecal drug distribution: key factors for interpatient variability.

BACKGROUND:Intrathecal drug delivery is an efficient method to administer therapeutic molecules to the central nervous system. However, even with identical drug dosage and administration mode, the extent of drug distribution in vivo is highly variable and difficult to control. Different cerebrospinal fluid (CSF) pulsatility from patient to patient may lead to different drug distribution. Medical image–based computational fluid dynamics (miCFD) is used to construct a patient-specific model to quantify drug transport as a function of a spectrum of physiological CSF pulsations. METHODS:Magnetic resonance imaging (MRI) and CINE MRI were performed to capture the patients central nervous system anatomy and CSF pulsatile flow velocities. An miCFD model was reconstructed from these MRIs and the patients CSF flow velocities were computed. The effect of CSF pulsatility (frequency and stroke volume) was investigated for a bolus injection of a model drug at the L2 vertebral level. Drug distribution profiles along the entire spine were computed for different heart rates: 43, 60, and 120 bpm, and varied CSF stroke volumes: 1, 2, and 3 mL. To assess toxicity risk for patients with different physiological variables, therapeutic and toxic concentration thresholds for a common anesthetic were derived from experimental studies. Toxicity risk analysis was performed for an injection of a spinal anesthetic for patients with different heart rates and CSF stroke volumes. RESULTS:Both heart rate and CSF stroke volume of the patient strongly influence drug distribution administered intrathecally. Doubling the heart rate (from 60 to 120 bpm) caused a 26.4% decrease in peak concentration in CSF after injection. Doubling the CSF stroke volume diminished the peak concentration after injection by 38.1%. Computations show that potentially toxic peak concentrations due to injection can be avoided by changing the infusion rate. Using slower infusion rates could avoid high peak concentrations in CSF while maintaining drug concentrations above the therapeutic threshold. CONCLUSIONS:Our computations identify key variables for patient to patient variability in drug distribution in the spine observed clinically. The speed of drug transport is strongly affected by the frequency and magnitude of CSF pulsations. Toxicity risks associated with an injection can be reduced for a particular patient by adjusting the infusion variables with our rigorous miCFD model.

Three-dimensional computational prediction of cerebrospinal fluid flow in the human brain

A three-dimensional model of the human cerebrospinal fluid (CSF) spaces is presented. Patient-specific brain geometries were reconstructed from magnetic resonance images. The model was validated by comparing the predicted flow rates with Cine phase-contrast MRI measurements. The model predicts the complex CSF flow patterns and pressures in the ventricular system and subarachnoid space of a normal subject. The predicted maximum rostral to caudal CSF flow in the pontine cistern precedes the maximum rostral to caudal flow in the ventricles by about 10% of the cardiac cycle. This prediction is in excellent agreement with the subject-specific flow data. The computational results quantify normal intracranial dynamics and provide a basis for analyzing diseased intracranial dynamics.

Hematocrit Distribution and Tissue Oxygenation in Large Microcirculatory Networks

Oxygen tension in the brain is controlled by the microcirculatory supply of RBC, but the effect of non‐Newtonian blood flow rheology on tissue oxygenation is not well characterized. This study assesses different biphasic blood flow models for predicting tissue oxygen tension as a function of microcirculatory hemodynamics.

Rigorous Mathematical Modeling Techniques for Optimal Delivery of Macromolecules to the Brain

Several treatment modalities for neurodegenerative diseases or tumors of the central nervous system involve invasive delivery of large molecular weight drugs to the brain. Despite the ample record of experimental studies, accurate drug targeting for the human brain remains a challenge. This paper proposes a systematic design method of administering drugs to specific locations in the human brain based on first principles transport in porous media. The proposed mathematical framework predicts achievable treatment volumes in target regions as a function of brain anatomy and infusion catheter position. A systematic procedure to determine the optimal infusion and catheter design parameters that maximize the penetration depth and volumes of distribution will be discussed. The computer simulations are validated with agarose gel phantom experiments and rat data. The rigorous computational approach will allow physicians and scientists to better plan the administration of therapeutic drugs to the central nervous system.