TRADITIONAL POSTER - ismrm

Poster Sessions
criteria (e.g., right-handed males aged 25-50), and connectivity strengths for individuals belonging to different groups can be visually and quantitatively
compared (e.g., right-handed males vs. females).
1667. Diffusion MRI and Anatomical Tracer Tractography of Association Pathways in the Same Brain
Jennifer Campbell 1 , Ilana R. Leppert 1 , Stephen Frey 2 , Michael Petrides 2 , G. Bruce Pike 1
1 McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; 2 Cognitive
Neuroscience Unit, Montreal Neurological Institute, McGill University
Reliable in vivo diffusion MRI fibre tractography, particularly in association pathways, remains a difficult task due to a mismatch between the tract size and
the image resolution achievable in a reasonable scan time. The objective of this study was to perform both diffusion MRI tractography and traditional tracer
injection tract tracing in the association pathways of the same rhesus macaque monkey. Evaluation of diffusion MRI tract tracing in these association
pathways can give us insight into its feasibility for mapping subtle connectivity in the human brain.
Tractography Methods
Hall B Wednesday 13:30-15:30
1668. Estimation of the Uncertainty of Diffusion MRI Fiber Tracking Parameters with Residual Bootstrap
Christopher Tam Nguyen 1 , SungWon Chung 2 , Jeffrey I. Berman 1 , Roland G. Henry 1
1 Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States; 2 Radiology, Brigham
and Women's Hospital, Harvard University, Boston, MA, United States
Fiber tracking (FT) based on diffusion MR has important applications for structural connectivity analyses of brain diseases and pre-operative FT of the brain.
The residual bootstrap (RB) analysis on voxelwise DTI parameters is not appropriate to characterize the uncertainty in the large 3D regions defined by FT.
Therefore, we will illustrate the appropriate implementation of RB to obtain the uncertainty of fiber tracking parameters (FTPs) such as number of
streamlines (NOS). We validated our method with a Monte Carlo simulation showing that RB accurately estimated the SE of the NOS.
1669. Quantitative Improvement of Diffusion Spectrum Imaging Tractography Using Statistical Denoising
Li-Wei Kuo 1 , Justin P. Haldar 2 , Yu-Chun Lo 3 , Cheng-Liang Liu 1 , Zhi-Pei Liang 2 , Wen-Yih Isaac Tseng 1,4
1 Center for Optoelectronic Biomedicine, National Taiwan University College of Medicine, Taipei, Taiwan; 2 Department of Electrical
and Computer Engineering, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States; 3 Institute of
Biomedical Engineering, National Taiwan University, Taipei, Taiwan; 4 Department of Medical Imaging, National Taiwan University
Hospital, Taipei, Taiwan
Noise contamination is a significant problem in diffusion spectrum imaging (DSI) tractography, and previous work has proposed a statistical denoising
algorithm to mitigate the effects of low signal-to-noise ratio. In this work, improvements to fiber orientation accuracy due to denoising were quantified using
a systematic analysis of angular precision and dispersion metrics. Results show that the proposed denoising method significantly improves angular precision
and dispersion. Furthermore, the tractography results demonstrate better reconstruction of white-matter structures using the denoised data. Future work will
use the proposed denoising algorithm to improve spatial resolution and reduce scan time.
1670. Improved Probabilistic Streamlines Tractography by 2 nd Order Integration Over Fibre Orientation
Distributions
J-Donald Tournier 1,2 , Fernando Calamante 1,2 , Alan Connelly 1,2
1 Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia; 2 Department of Medicine,
University of Melbourne, Melbourne, Victoria, Australia
Probabilistic streamlines algorithms are amongst the most promising methods for fibre-tracking, but are potentially subject to a number of deficiencies.
These include a tendency to overshoot in highly curved regions, and to switch directions in crossing fibre regions. To address both of these issues, we
propose a higher-order probabilistic streamlines algorithm, based on 2 nd order integration over fibre orientation distributions (iFOD2), with a computational
complexity similar to current first order methods. We demonstrate the advantages of the proposed iFOD2 algorithm on simulated data, and apply the method
to in-vivo data.
1671. Tract-Based Parameterization of Local White Matter Geometry
Peter Savadjiev 1 , Marek Kubicki 1 , Sylvain Bouix 1 , Gordon L. Kindlmann 2 , Martha E. Shenton 1,3 , Carl-
Fredrik Westin 4
1 Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; 2 Computer Science, University of
Chicago, Chicago, IL, United States; 3 Psychiatry, VA Boston Healthcare System, , Brockton , MA, United States; 4 Radiology,
Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
Knowledge of fibre geometry and its variation along fibre tracts can be useful for the study of normal and pathological white matter. In this work we present
a tract-based analysis of two recently introduced measures of fibre geometry, which compute fibre dispersion and fibre curving, directly from a diffusion
tensor field and its gradient. These measures of fibre geometry are mapped and analysed along a parametric representation of fibre tracts. Such
representations of fibre tract geometry are an important tool for the understanding of white matter structure.