Patient‐specific computational modeling of cortical spreading depression via diffusion tensor imaging. (11th April 2017)

• Record Type: Journal Article
• Authors: Kroos, Julia M.; Marinelli, Isabella; Diez, Ibai; Cortes, Jesus M.; Stramaglia, Sebastiano; Gerardo‐Giorda, Luca
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 33:Number 11(2017:Nov.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-04-11
• Subjects: cortical spreading depression -- diffusion tensor imaging -- finite element simulation -- patient‐specific cortical geometry -- reaction‐diffusion systems; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.2874
• Languages: English
• ISSNs: 2040-7939

Abstract

Abstract: Cortical spreading depression, a depolarization wave originating in the visual cortex and traveling towards the frontal lobe, is commonly accepted as a correlate of migraine visual aura. As of today, little is known about the mechanisms that can trigger or stop such phenomenon. However, the complex and highly individual characteristics of the brain cortex suggest that the geometry might have a significant impact in supporting or contrasting the propagation of cortical spreading depression. Accurate patient‐specific computational models are fundamental to cope with the high variability in cortical geometries among individuals, but also with the conduction anisotropy induced in a given cortex by the complex neuronal organisation in the grey matter. In this paper, we integrate a distributed model for extracellular potassium concentration with patient‐specific diffusivity tensors derived locally from diffusion tensor imaging data. Abstract : Cortical spreading depression, a depolarisation wave propagating from the visual cortex to the frontal lobe, is commonly accepted as a correlate of migraine aura. Although CSD is not fully understood yet, the highly individual geometry of the cortex is expected to have an impact on its propagation. We introduce a patient‐specific model that combines individual geometries, obtained from MRI imaging, with personalized coefficients, derived from diffusion tensor imaging to account for the anisotropy of the cortical tissue.