Integrating Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging to Improve the Predictive Ca
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Annals of Biomedical Engineering (Ó 2020) https://doi.org/10.1007/s10439-020-02598-7
Original Article
Integrating Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging to Improve the Predictive Capabilities of CED Models MARCO VIDOTTO,1,4 MATTEO PEDERZANI,1,4 ANTONELLA CASTELLANO,2,3 VALENTINA PIERI,2,3 ANDREA FALINI,2,3 DANIELE DINI ,4 and ELENA DE MOMI1 1
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy; 2Vita-Salute San Raffaele University, Milan, Italy; 3Neuroradiology Unit and CERMAC, IRCCS San Raffaele Scientific Institute, Milan, Italy; and 4 Department of Mechanical Engineering, Imperial College, London, UK (Received 29 April 2020; accepted 17 August 2020) Associate Editor Arash Kheradvar oversaw the review of this article.
Abstract—This paper aims to develop a comprehensive and subject-specific model to predict the drug reach in Convection-Enhanced Delivery (CED) interventions. To this end, we make use of an advance diffusion imaging technique, namely the Neurite Orientation Dispersion and Density Imaging (NODDI), to incorporate a more precise description of the brain microstructure into predictive computational models. The NODDI dataset is used to obtain a voxel-based quantification of the extracellular space volume fraction that we relate to the white matter (WM) permeability. Since the WM can be considered as a transversally isotropic porous medium, two equations, respectively for permeability parallel and perpendicular to the axons, are derived from a numerical analysis on a simplified geometrical model that reproduces flow through fibre bundles. This is followed by the simulation of the injection of a drug in a WM area of the brain and direct comparison of the outcomes of our results with a stateof-the-art model, which uses conventional diffusion tensor imaging. We demonstrate the relevance of the work by showing the impact of our newly derived permeability tensor on the predicted drug distribution, which differs significantly from the alternative model in terms of distribution shape, concentration profile and infusion linear penetration length. Keywords—Computational model, Hydraulic permeability, Drug delivery, NODDI, DTI.
Address correspondence to Daniele Dini, Department of Mechanical Engineering, Imperial College, London, UK. Electronic mail: [email protected]
INTRODUCTION The blood-brain barrier (BBB) is a highly selective semipermeable vascular system composed by endothelial cells, astrocyte end-feet, and pericytes that serves as a diffusion barrier.3 Despite the BBB is essential for the normal function of the central nervous system, it is also a dramatically effective barrier that prevents most drugs from going from the blood stream to the brain tissue.3 For this reason, the BBB has been clearly identified as the main cause of the failure of chemotherapeutic treatments that aim at targeting the brain tissue.2,5,8,17 To overcome this obstacle, an innovative and promising technique, namely convection-enhanced delivery (CED),
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