S Linge

Simula Research Laboratory, Kristiania (historical), Oslo County, Norway

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Publications (15)13.66 Total impact

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    ABSTRACT: Chiari I patients have increased CSF velocities in the foramen magnum due hypothetically to increased pressure gradients or reduced flow resistance. We calculated flow resistance in the cervical spinal canal in a group of subjects with and without the Chiari malformation. Eight subjects including healthy volunteers and Chiari I patients were studied. From 3D high resolution MR images of the cervical spine mathematical models of the subarachnoid spaces were created by means of standard programs for segmentation and discretization. Oscillatory flow through the subarachnoid space was simulated. Cross-sectional area of the subarachnoid space was computed at each level from C1 through C4 and the length of this spinal canal segment was measured. Peak caudad CSF flow velocity at each level was plotted against cross-section area. CSF volumetric flux and resistance were calculated for each subject. The correlation between velocity and resistance was calculated. In all subjects, peak velocities increased progressively from C1 to C4 by 0.6 to 0.7 cm/s per level. Spinal canal areas diminished from C1 to C5 in each subject at a rate of -0.25 to -0.29 cm(2) per level. Resistance averaged 4.3 pascal/ml/s in the eight subjects; 3.8 pascal/ml/s in patients with tonsilar herniation and 6.0 pascal/ml/s in volunteers. Velocity correlated inversely with resistance (R(2) = 0.6). CSF velocities correlated inversely with the flow resistance in the upper cervical spinal canal. Resistance tends to be lower in Chiari I patients than in healthy volunteers.
    The neuroradiology journal. 03/2013; 26(1):106-10.
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    ABSTRACT: Flow simulations in patient-specific models of the subarachnoid space characterize CSF flow in more detail than MR flow imaging. We extended previous simulation studies by including cyclic CSF flow and patient-specific models in multiple patients with Chiari I. We compared simulation results with MR flow measurements. Volumetric high resolution image sets acquired in 7 patients with Chiari I, 3 patients who had previous craniovertebral decompression, and 3 controls were segmented and converted to mathematical models of the subarachnoid space. CSF flow velocities and pressures were calculated with high spatial and temporal resolution during simulated oscillatory flow in each model with the Navier-Stokes equations. Pressures, velocities, and bidirectional flow were compared in the groups (with Student t test). Peak velocities in the simulations were compared with peak velocities measured in vivo with PCMR. Flow visualization for patients and volunteers demonstrated nonuniform reversing patterns resembling those observed with PCMR. Velocities in the 13 subjects were greater between C2 and C5 than in the foramen magnum. Chiari patients had significantly greater peak systolic and diastolic velocities, synchronous bidirectional flow, and pressure gradients than controls. Peak velocities measured in PCMR correlated significantly (P = .003; regression analysis) despite differences between them. In simulations of CSF, patients with Chiari I had significantly greater peak systolic and diastolic velocities, synchronous bidirectional flow, and pressure gradients than controls.
    American Journal of Neuroradiology 04/2012; 33(9):1756-62. · 3.17 Impact Factor
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    ABSTRACT: CSF flow has been shown to exhibit complex patterns in MR images in both healthy subjects and in patients with Chiari I. Abnormal CSF flow oscillations, according to prevailing opinion, cause syringomyelia and other clinical manifestations that affect some patients with the Chiari I malformation. For this article, we reviewed the literature on PC MR of CSF flow, collected the published CFD studies relevant to CSF flow, and performed flow simulations. PC MR creates cine and still images of CSF flow and measurements of flow velocities. CFD, a technique used to compute flow and pressure in liquid systems, simulates the CSF flow patterns that occur in a specific geometry or anatomy of the SAS and a specific volume of flow. Published PC MR studies show greater peak CSF velocities and more complex flow patterns in patients with Chiari I than in healthy subjects, with synchronous bidirectional flow one of the characteristic markers of pathologic flow. In mathematic models of the SAS created from high-resolution MR images, CFD displays complex CSF flow patterns similar to those shown in PC MR in patients. CFD shows that the pressure and flow patterns vary from level to level in the upper spinal canal and differ between patients with Chiari and healthy volunteers. In models in which elasticity and motion are incorporated, CFD displays CSF pressure waves in the SAS. PC MR and CFD studies to date demonstrate significant alterations of CSF flow and pressure patterns in patients with Chiari I. CSF flow has nonlaminar complex spatial and temporal variations and associated pressure waves and pressure gradients. Additional simulations of CSF flow supplemented by PC MR will lead to better measures for distinguishing pathologic flow abnormalities that cause syringomyelia, headaches, and other clinical manifestations in Chiari I malformations.
    American Journal of Neuroradiology 03/2010; 31(6):997-1002. · 3.17 Impact Factor
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  • 11/2009;
  • 10/2009;
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    ABSTRACT: Knowledge of cardiac electrophysiology is efficiently formulated in terms of mathematical models. However, most of these models are very complex and thus defeat direct mathematical reasoning founded on classical and analytical considerations. This is particularly so for the celebrated bidomain model that was developed almost 40 years ago for the concurrent analysis of extra- and intracellular electrical activity. Numerical simulations based on this model represent an indispensable tool for studying electrophysiology. However, complex mathematical models, steep gradients in the solutions and complicated geometries lead to extremely challenging computational problems. The greatest achievement in scientific computing over the past 50 years has been to enable the solving of linear systems of algebraic equations that arise from discretizations of partial differential equations in an optimal manner, i.e. such that the central processing unit (CPU) effort increases linearly with the number of computational nodes. Over the past decade, such optimal methods have been introduced in the simulation of electrophysiology. This development, together with the development of affordable parallel computers, has enabled the solution of the bidomain model combined with accurate cellular models, on geometries resembling a human heart. However, in spite of recent progress, the full potential of modern computational methods has yet to be exploited for the solution of the bidomain model. This paper reviews the development of numerical methods for solving the bidomain model. However, the field is huge and we thus restrict our focus to developments that have been made since the year 2000.
    Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences 06/2009; 367(1895):1931-50. · 2.89 Impact Factor
  • 01/2009;
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    ABSTRACT: To compute the effects of parameter perturbations for single ischemic cardiac cells, and to determine how perturbations influenced the tendency for the cells to undergo spontaneous depolarization (automaticity) during 20 min of acute ischemia. A modified Luo-Rudy 1 cell model was used. Since the range of biological variation and measurement errors is largely unknown, we conducted our study of the consequences of perturbations under the assumption that cell model parameters have a normal distribution with a 10% standard deviation. A total of 10000 random cell realizations were tested while varying important Luo-Rudy cell model parameters. Ischemia was modelled by deterministic functions chosen for the expected values of crucial ion concentrations and gating parameters as they developed with time, while realizing the respective parameter values from static normal distributions with a 10% standard deviation. It was found that the tendency towards automaticity did increase as the stochastic parameters were varied. In particular, cells with standard Luo-Rudy parameter values did not become automatic during ischemia, whereas a significant portion of the cells with randomized parameter values did. The relative importance of model parameter variations was also determined and a sodium m-gate activation parameter was identified as the most critical parameter. The frequency of arrhythmic events during acute ischemia is known to be bell-shaped, with a peak at around 7-8 min after the onset of ischemia. Our simulations display a similar peak in the frequency of automaticity.
    Computers in biology and medicine 01/2008; 38(11-12):1218-27. · 1.27 Impact Factor
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    American Journal of Neuroradiology 31:185–192. · 3.17 Impact Factor
  • American Journal of Neuroradiology.
  • Proceedings from the 21st Nordic Seminar on Computational Mechanics (NSCM-21);
  • Proceedings of the ASNR 47th Annual Meeting, Vancouver, Canada;
  • ASNR 49th Annual Meeting and the Foundation of the ASNR Symposium;