TY - JOUR
T1 - Automated vs. conventional tractography in multiple sclerosis
T2 - Variability and correlation with disability
AU - Reich, Daniel S.
AU - Ozturk, Arzu
AU - Calabresi, Peter A.
AU - Mori, Susumu
N1 - Funding Information:
Funding sources: NIH grants K99NS064098 , P41RR015241 , R01AG020012 , and K01EB009120 ; and National Multiple Sclerosis Society grant TR3760A3 . This research was also supported by the intramural research program of the NIH, NINDS. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.
PY - 2010/2/15
Y1 - 2010/2/15
N2 - Diffusion-tensor-imaging fiber tractography enables interrogation of brain white matter tracts that subserve different functions. However, tract reconstruction can be labor and time intensive and can yield variable results that may reduce the power to link imaging abnormalities with disability. Automated segmentation of these tracts would help make tract-specific imaging clinically useful, but implementation of such segmentation is problematic in the presence of diseases that alter brain structure. In this work, we investigated an automated tract-probability-mapping scheme and applied it to multiple sclerosis, comparing the results to those derived from conventional tractography. We found that the automated method has consistently lower scan-rescan variability (typically 0.7-1.5% vs. up to 3% for conventional tractography) and avoids problems related to tractography failures within and around lesions. In the corpus callosum, optic radiation, and corticospinal tract, tract-specific MRI indices calculated by the two methods were moderately to strongly correlated, though systematic, tract-specific differences were present. In these tracts, the two methods also yielded similar correlation coefficients relating tract-specific MRI indices to clinical disability scores. In the optic tract, the automated method failed. With judicious application, therefore, the automated method may be useful for studies that investigate the relationship between imaging findings and clinical outcomes in disease.
AB - Diffusion-tensor-imaging fiber tractography enables interrogation of brain white matter tracts that subserve different functions. However, tract reconstruction can be labor and time intensive and can yield variable results that may reduce the power to link imaging abnormalities with disability. Automated segmentation of these tracts would help make tract-specific imaging clinically useful, but implementation of such segmentation is problematic in the presence of diseases that alter brain structure. In this work, we investigated an automated tract-probability-mapping scheme and applied it to multiple sclerosis, comparing the results to those derived from conventional tractography. We found that the automated method has consistently lower scan-rescan variability (typically 0.7-1.5% vs. up to 3% for conventional tractography) and avoids problems related to tractography failures within and around lesions. In the corpus callosum, optic radiation, and corticospinal tract, tract-specific MRI indices calculated by the two methods were moderately to strongly correlated, though systematic, tract-specific differences were present. In these tracts, the two methods also yielded similar correlation coefficients relating tract-specific MRI indices to clinical disability scores. In the optic tract, the automated method failed. With judicious application, therefore, the automated method may be useful for studies that investigate the relationship between imaging findings and clinical outcomes in disease.
KW - Corpus callosum
KW - Corticospinal tract
KW - Diffusion tensor imaging
KW - Magnetization transfer imaging
KW - Multiple sclerosis
KW - Tractography
KW - Visual system
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U2 - 10.1016/j.neuroimage.2009.11.043
DO - 10.1016/j.neuroimage.2009.11.043
M3 - Article
C2 - 19944769
AN - SCOPUS:73749086028
SN - 1053-8119
VL - 49
SP - 3047
EP - 3056
JO - NeuroImage
JF - NeuroImage
IS - 4
ER -