Comparison of compressed sensing diffusion spectrum imaging and diffusion tensor imaging in patients with intracranial masses Journal Article


Authors: Young, R. J.; Tan, E. T.; Peck, K. K.; Jenabi, M.; Karimi, S.; Brennan, N.; Rubel, J.; Lyo, J.; Shi, W.; Zhang, Z.; Prastawa, M.; Liu, X.; Sperl, J. I.; Fatovic, R.; Marinelli, L.; Holodny, A. I.
Article Title: Comparison of compressed sensing diffusion spectrum imaging and diffusion tensor imaging in patients with intracranial masses
Abstract: Purpose To compare compressed diffusion spectrum imaging (CS-DSI) with diffusion tensor imaging (DTI) in patients with intracranial masses. We hypothesized that CS-DSI would provide superior visualization of the motor and language tracts. Materials and methods We retrospectively analyzed 25 consecutive patients with intracranial masses who underwent DTI and CS-DSI for preoperative planning. Directionally-encoded anisotropy maps, and streamline hand corticospinal motor tracts and arcuate fasciculus language tracts were graded according to a 3-point scale. Tract counts, anisotropy, and lengths were also calculated. Comparisons were made using exact marginal homogeneity, McNemar's and Wilcoxon signed-rank tests. Results Readers preferred the CS-DSI over DTI anisotropy maps in 92% of the cases, and the CS-DSI over DTI tracts in 84%. The motor tracts were graded as excellent in 80% of cases for CS-DSI versus 52% for DTI; 58% of the motor tracts graded as acceptable in DTI were graded as excellent in CS-DSI (p = 0.02). The language tracts were graded as excellent in 68% for CS-DSI versus none for DTI; 78% of the language tracts graded as acceptable by DTI were graded as excellent by CS-DSI (p < 0.001). CS-DSI demonstrated smaller normalized mean differences than DTI for motor tract counts, anisotropy and language tract counts (p ≤ 0.01). Conclusion CS-DSI was preferred over DTI for the evaluation of motor and language white matter tracts in patients with intracranial masses. Results suggest that CS-DSI may be more useful than DTI for preoperative planning purposes. © 2016 Elsevier Inc.
Keywords: diffusion tensor; compressed-sensing; diffusion spectrum
Journal Title: Magnetic Resonance Imaging
Volume: 36
ISSN: 0730-725X
Publisher: Elsevier Science, Inc.  
Date Published: 2017-02-01
Start Page: 24
End Page: 31
Language: English
DOI: 10.1016/j.mri.2016.10.001
PROVIDER: scopus
PUBMED: 27742434
PMCID: PMC5222773
DOI/URL:
Notes: Article -- Export Date: 6 December 2016 -- Source: Scopus
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MSK Authors
  1. John Kyungjin Lyo
    30 Lyo
  2. Zhigang Zhang
    249 Zhang
  3. Weiji Shi
    117 Shi
  4. Robert J Young
    118 Young
  5. Nicole Brennan
    41 Brennan
  6. Sasan Karimi
    97 Karimi
  7. Kyung Peck
    80 Peck
  8. Andrei Holodny
    139 Holodny
  9. Mehrnaz Jenabi
    7 Jenabi
  10. Jennifer Brooke Rubel
    5 Rubel