Tensor-valued diffusion MRI in under 3 minutes: an initial survey of microscopic anisotropy and tissue heterogeneity in intracranial tumors

被引:54
作者
Nilsson, Markus [1 ]
Szczepankiewicz, Filip [2 ]
Brabec, Jan [3 ]
Taylor, Marie [1 ]
Westin, Carl-Fredrik [2 ]
Golby, Alexandra [2 ]
van Westen, Danielle [1 ]
Sundgren, Pia C. [1 ,4 ]
机构
[1] Lund Univ, Dept Clin Sci Lund, Radiol, Lund, Sweden
[2] Harvard Med Sch, Brigham & Womens Hosp, Boston, MA 02115 USA
[3] Lund Univ, Dept Clin Sci Lund, Med Radiat Phys, Lund, Sweden
[4] Lund Univ, Bioimaging Ctr LBIC, Lund, Sweden
基金
瑞典研究理事会;
关键词
diffusion MRI; microscopic anisotropy; tumor heterogeneity; BRAIN; NMR; QUANTIFICATION; ECCENTRICITY; DENSITY; DESIGN;
D O I
10.1002/mrm.27959
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose To evaluate the feasibility of a 3-minutes protocol for assessment of the microscopic anisotropy and tissue heterogeneity based on tensor-valued diffusion MRI in a wide range of intracranial tumors. Methods B-tensor encoding was performed in 42 patients with intracranial tumors (gliomas, meningiomas, adenomas, and metastases). Microscopic anisotropy and tissue heterogeneity were evaluated by estimating the anisotropic kurtosis (MKA) and isotropic kurtosis (MKI), respectively. An extensive imaging protocol was compared with a 3-minutes protocol. Results The fast imaging protocol yielded parameters with characteristics in terms of bias and precision similar to the full protocol. Glioblastomas had lower microscopic anisotropy than meningiomas (MKA = 0.29 +/- 0.06 vs. 0.45 +/- 0.08, P = 0.003). Metastases had higher tissue heterogeneity (MKI = 0.57 +/- 0.07) than both the glioblastomas (0.44 +/- 0.06, P < 0.001) and meningiomas (0.46 +/- 0.06, P = 0.03). Conclusion Evaluation of the microscopic anisotropy and tissue heterogeneity in intracranial tumor patients is feasible in clinically relevant times frames.
引用
收藏
页码:608 / 620
页数:13
相关论文
共 67 条
[1]   Efficient measurement and calculation of MR diffusion Anisotropy images using the platonic variance method [J].
Akkerman, EM .
MAGNETIC RESONANCE IN MEDICINE, 2003, 49 (03) :599-604
[2]   A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features [J].
Alexander, Daniel C. .
MAGNETIC RESONANCE IN MEDICINE, 2008, 60 (02) :439-448
[3]   Brain water mobility decreases after astrocytic aquaporin-4 inhibition using RNA interference [J].
Badaut, Jerome ;
Ashwal, Stephen ;
Adami, Arash ;
Tone, Beatriz ;
Recker, Rebecca ;
Spagnoli, David ;
Ternon, Beatrice ;
Obenaus, Andre .
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 2011, 31 (03) :819-831
[4]  
Bigun J., 1987, Proceedings of the First International Conference on Computer Vision (Cat. No.87CH2465-3), P433
[5]  
BRABEC J, 2019, P 27 ANN M ISMRM MON, P1002
[6]  
BRYNOLFSSON P, 2019, P 27 ANN M ISMRM MON, P553
[7]   Examining brain microstructure using structure tensor analysis of histological sections [J].
Budde, Matthew D. ;
Frank, Joseph A. .
NEUROIMAGE, 2012, 63 (01) :1-10
[8]   The Correlation between Apparent Diffusion Coefficient and Tumor Cellularity in Patients: A Meta-Analysis [J].
Chen, Lihua ;
Liu, Min ;
Bao, Jing ;
Xia, Yunbao ;
Zhang, Jiuquan ;
Zhang, Lin ;
Huang, Xuequan ;
Wang, Jian .
PLOS ONE, 2013, 8 (11)
[9]   Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors [J].
Chenevert, TL ;
Stegman, LD ;
Taylor, JMG ;
Robertson, PL ;
Greenberg, HS ;
Rehemtulla, A ;
Ross, BD .
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2000, 92 (24) :2029-2036
[10]   Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection [J].
Chuhutin, Andrey ;
Hansen, Brian ;
Jespersen, Sune Norhoj .
NMR IN BIOMEDICINE, 2017, 30 (11)