SpinDoctor: A MATLAB toolbox for diffusion MRI simulation

• Published in: NeuroImage (Orlando, Fla.) Vol. 202; p. 116120
• Main Authors: Li, Jing-Rebecca, Nguyen, Van-Dang, Tran, Try Nguyen, Valdman, Jan, Trang, Cong-Bang, Nguyen, Khieu Van, Vu, Duc Thach Son, Tran, Hoang An, Tran, Hoang Trong An, Nguyen, Thi Minh Phuong
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.11.2019; Elsevier Limited; Elsevier
• Subjects: Apparent diffusion coefficient; Applied and Computational Mathematics; Applied Medical Technology; Bioengineering; Bloch-Torrey equation; Boundary conditions; Computer applications; Computer Science; Datalogi; Diffusion coefficient; Diffusion magnetic resonance imaging; Finite elements; Imaging; Life Sciences; Magnetic resonance imaging; Modeling and Simulation; Myelin; NMR; Nuclear magnetic resonance; Ordinary differential equations; Partial differential equations; Simulation; Tillämpad matematik och beräkningsmatematik; Tillämpad medicinsk teknik; Water exchange; Bloch-torrey equation; Finite elements; Simulation; Diffusion magnetic resonance imaging; Apparent diffusion coefficient; Bloch-Torrey equation
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2019.116120

The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation. Under the assumption of negligible water exchange between compartments, the time-dependent apparent diffusion coefficient can be directly computed from the solution of a diffusion equation subject to a time-dependent Neumann boundary condition. This paper describes a publicly available MATLAB toolbox called SpinDoctor that can be used 1) to solve the Bloch-Torrey partial differential equation in order to simulate the diffusion magnetic resonance imaging signal; 2) to solve a diffusion partial differential equation to obtain directly the apparent diffusion coefficient; 3) to compare the simulated apparent diffusion coefficient with a short-time approximation formula. The partial differential equations are solved by P1 finite elements combined with built-in MATLAB routines for solving ordinary differential equations. The finite element mesh generation is performed using an external package called Tetgen. SpinDoctor provides built-in options of including 1) spherical cells with a nucleus; 2) cylindrical cells with a myelin layer; 3) an extra-cellular space enclosed either a) in a box or b) in a tight wrapping around the cells; 4) deformation of canonical cells by bending and twisting; 5) permeable membranes; Built-in diffusion-encoding pulse sequences include the Pulsed Gradient Spin Echo and the Oscillating Gradient Spin Echo. We describe in detail how to use the SpinDoctor toolbox. We validate SpinDoctor simulations using reference signals computed by the Matrix Formalism method. We compare the accuracy and computational time of SpinDoctor simulations with Monte-Carlo simulations and show significant speed-up of SpinDoctor over Monte-Carlo simulations in complex geometries. We also illustrate several extensions of SpinDoctor functionalities, including the incorporation of T2 relaxation, the simulation of non-standard diffusion-encoding sequences, as well as the use of externally generated geometrical meshes. •Simulates the diffusion MRI signal for general diffusion-encoding sequences.•Provides built-in options for creating geometries relevant to brain white matter.•Allows permeable membranes and can simulate the extra-cellular space.•Uses finite elements discretization of Bloch-Torrey equation with adaptive time stepping.