Clinical Application of Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples (A-Glyph LIC)

Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping

In diffusion MRI, the advent of high angular resolution diffusion imaging (HARDI) and HARDI with compressed sensing (HARDI+CS) has led to clinically practical signal acquisition techniques which allow for the assessment of white matter architecture in routine patient studies. However, the reconstruction and visualization of fiber pathways by tractography has not yet been established as a standard methodology which can easily be applied. This is due to various algorithmic problems, such as a lack of robustness, error propagation and the necessity of fine-tuning parameters depending on the clinical question. In the framework of a clinical study of glioma patients, we compare two different whole-brain tracking methods to a local connectivity mapping approach which has recently shown promising results in an adaptation to diffusion MRI. The ability of the three methods to correctly depict fiber affection is analyzed by comparing visualization results to representations of local diffusion profiles provided by orientation distribution functions (ODFs). Our results suggest that methods beyond fiber tractography, which visualize local connectedness rather than global connectivity, should be evaluated further for pre-surgical assessment of fiber affection.

Improvement in White Matter Tract Reconstruction with Constrained Spherical Deconvolution and Track Density Mapping in Low Angular Resolution Data: A Pediatric Study and Literature Review

INTRODUCTION

Diffusion-weighted magnetic resonance imaging (DW-MRI) allows noninvasive investigation of brain structure in vivo. Diffusion tensor imaging (DTI) is a frequently used application of DW-MRI that assumes a single main diffusion direction per voxel, and is therefore not well suited for reconstructing crossing fiber tracts. Among the solutions developed to overcome this problem, constrained spherical deconvolution with probabilistic tractography (CSD-PT) has provided superior quality results in clinical settings on adult subjects; however, it requires particular acquisition parameters and long sequences, which may limit clinical usage in the pediatric age group. The aim of this work was to compare the results of DTI with those of track density imaging (TDI) maps and CSD-PT on data from neonates and children, acquired with low angular resolution and low b-value diffusion sequences commonly used in pediatric clinical MRI examinations.

MATERIALS AND METHODS

We analyzed DW-MRI studies of 50 children (eight neonates aged 3-28 days, 20 infants aged 1-8 months, and 22 children aged 2-17 years) acquired on a 1.5 T Philips scanner using 34 gradient directions and a b-value of 1,000 s/mm². Other sequence parameters included 60 axial slices; acquisition matrix, 128 × 128; average scan time, 5:34 min; voxel size, 1.75 mm × 1.75 mm × 2 mm; one b = 0 image. For each subject, we computed principal eigenvector (EV) maps and directionally encoded color TDI maps (DEC-TDI maps) from whole-brain tractograms obtained with CSD-PT; the cerebellar-thalamic, corticopontocerebellar, and corticospinal tracts were reconstructed using both CSD-PT and DTI. Results were compared by two neuroradiologists using a 5-point qualitative score.

RESULTS

The DEC-TDI maps obtained presented higher anatomical detail than EV maps, as assessed by visual inspection. In all subjects, white matter (WM) tracts were successfully reconstructed using both tractography methodologies. The mean qualitative scores of all tracts obtained with CSD-PT were significantly higher than those obtained with DTI (p-value < 0.05 for all comparisons).

CONCLUSION

CSD-PT can be successfully applied to DW-MRI studies acquired at 1.5 T with acquisition parameters adapted for pediatric subjects, thus providing TDI maps with greater anatomical detail. This methodology yields satisfactory results for clinical purposes in the pediatric age group.