A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms

TY - JOUR

T1 - A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms

AU - Close, Thomas G.

AU - Tournier, Jacques-Donald

AU - Tournier, Jacques-Donald

AU - Calamante, Fernando

AU - Johnston, Leigh A.

AU - Mareels, Iven

AU - Connelly, Alan

PY - 2009/10/1

Y1 - 2009/10/1

N2 - The assessment of Diffusion-Weighted MRI (DW-MRI) fibre-tracking algorithms has been limited by the lack of an appropriate 'gold standard'. Practical limitations of alternative methods and physical models have meant that numerical simulations have become the method of choice in practice. However, previous numerical phantoms have consisted of separate fibres embedded in homogeneous backgrounds, which do not capture the true nature of white matter. In this paper we describe a method that is able to randomly generate numerical structures consisting of densely packed bundles of fibres, which are much more representative of human white matter, and simulate the DW-MR images that would arise from them under many imaging conditions. User-defined parameters may be adjusted to produce structures with a range of complexities that spans the levels we would expect to find in vivo. These structures are shown to contain many different features that occur in human white matter and which could confound fibre-tracking algorithms, such as tract kissing and crossing. Furthermore, combinations of such features can be sampled by the random generation of many different structures with consistent levels of complexity. The proposed software provides means for quantitative assessment via direct comparison between tracking results and the exact location of the generated fibres. This should greatly improve our understanding of algorithm performance and therefore prove an important tool for fibre tracking development. (C) 2009 Elsevier Inc. All rights reserved.

AB - The assessment of Diffusion-Weighted MRI (DW-MRI) fibre-tracking algorithms has been limited by the lack of an appropriate 'gold standard'. Practical limitations of alternative methods and physical models have meant that numerical simulations have become the method of choice in practice. However, previous numerical phantoms have consisted of separate fibres embedded in homogeneous backgrounds, which do not capture the true nature of white matter. In this paper we describe a method that is able to randomly generate numerical structures consisting of densely packed bundles of fibres, which are much more representative of human white matter, and simulate the DW-MR images that would arise from them under many imaging conditions. User-defined parameters may be adjusted to produce structures with a range of complexities that spans the levels we would expect to find in vivo. These structures are shown to contain many different features that occur in human white matter and which could confound fibre-tracking algorithms, such as tract kissing and crossing. Furthermore, combinations of such features can be sampled by the random generation of many different structures with consistent levels of complexity. The proposed software provides means for quantitative assessment via direct comparison between tracking results and the exact location of the generated fibres. This should greatly improve our understanding of algorithm performance and therefore prove an important tool for fibre tracking development. (C) 2009 Elsevier Inc. All rights reserved.

KW - DIFFUSION TENSOR

KW - HUMAN BRAIN

KW - SPHERICAL DECONVOLUTION

KW - MRI DATA

KW - POLARIZED-LIGHT

KW - OPTIC TRACTS

KW - TRACTOGRAPHY

KW - ORIENTATION

KW - VALIDATION

KW - PHANTOM

U2 - 10.1016/j.neuroimage.2009.03.077

DO - 10.1016/j.neuroimage.2009.03.077

M3 - Article

SN - 1053-8119

VL - 47

SP - 1288

EP - 1300

JO - NeuroImage

JF - NeuroImage

IS - 4

ER -