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
    39 Lyo
  2. Zhigang Zhang
    428 Zhang
  3. Weiji Shi
    121 Shi
  4. Robert J Young
    228 Young
  5. Nicole Brennan
    44 Brennan
  6. Sasan Karimi
    115 Karimi
  7. Kyung Peck
    117 Peck
  8. Andrei Holodny
    207 Holodny
  9. Mehrnaz Jenabi
    26 Jenabi
  10. Jennifer Brooke Rubel
    5 Rubel