Share:
Share this content in WeChat
X
Review
Research progress of neurite direction diffusion and density imaging for glioma classification
JU Chao  WANG Min  WANG Hong 

Cite this article as: Ju C, Wang M, Wang H. Research progress of neurite direction diffusion and density imaging for glioma classification[J]. Chin J Magn Reson Imaging, 2021, 12(4): 100-102, 110. DOI:10.12015/issn.1674-8034.2021.04.025.


[Abstract] Glioma is the most common intracranial malignant tumor, which is highly invasive and easy to relapse. At present, the grade of glioma mainly depends on postoperative pathology, but the early detection and preoperative grade of glioma are of great significance for the choice of surgical plan and postoperative prognosis of patients. In recent years, with the development of new magnetic resonance technology, diffusion magnetic resonance imaging (dMRI) plays an increasingly important role in the grading diagnosis of glioma. This article reviews the imaging principle and characteristics of neurite orientation dispersion and density imaging (NODDI) and its application in the grading diagnosis of glioma.
[Keywords] magnetic resonance imaging;diffusion-weighted imaging;neurite density;directional dispersion;glioma

JU Chao   WANG Min   WANG Hong*  

Department of Radiology, the Second Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, China

Wang H, E-mail: wangh_xj@163.com

Conflicts of interest   None.

This work was part of Natural Science Foundation of Xinjiang Uygur Autonomous Region (No. 2019D01C227, 2020D01C191).
Received  2020-12-21
Accepted  2021-01-28
DOI: 10.12015/issn.1674-8034.2021.04.025
Cite this article as: Ju C, Wang M, Wang H. Research progress of neurite direction diffusion and density imaging for glioma classification[J]. Chin J Magn Reson Imaging, 2021, 12(4): 100-102, 110. DOI:10.12015/issn.1674-8034.2021.04.025.

1
Padhani AR, Koh DM, Collins DJ. Whole-body diffusion-weighted MR imag-ing in cancer:current status and research directions[J]. Radiology, 2011, 261(3): 700-718. DOI: 10.1148/radiol.11110474.
2
Maximov II, Tonoyan AS, Pronin IN. Differentiation of glioma malignancy grade using diffusion MRI[J]. Phys Med, 2017, 40: 24-32. DOI: 10.1016/j.ejmp.2017.07.002.
3
Donners R, Blackledge M, Tunariu N, et al. Quantitative whole-body diffusion-weighted MR imaging[J]. Magn Reson Imaging Clin N Am, 2018, 26(4): 479-494. DOI: 10.1016/j.mric.2018.06.002.
4
Caravan I, Ciortea CA, Contis A, et al. Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases[J]. Acta Radiol, 2018, 59(5): 599-605. DOI: 10.1177/0284185117727787.
5
Jiang L, Xiao CY, Xu Q, et al. Analysis of DTI-derived tensor metrics in differential diagnosis between low-grade and high-grade gliomas[J]. Front Aging Neurosci, 2017, 9: 271. DOI: 10.3389/fnagi.2017.00271.
6
Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. 1996[J]. J Magn Reson Imaging, 2011, 213(2): 560-570. DOI: 10.1016/j.jmr.2011.09.022.
7
Tan ZY, Yang J, Yan KX, et al. The value of diffusion kurtosis imaging in the differential diagnosis of high-grade glioma and solitary brain metastases[J]. Radiol Pract, 2017, 32(3): 218-222. DOI: 10.13609/j.cnki.1000-0313.2017.03.003.
8
Jensen JH, Helpern JA. MRI quantification of non-Gaussian water diffusion by kurtosis analysis[J]. NMR Biomed, 2010, 23(7): 698-710. DOI: 10.1002/nbm.1518.
9
Jensen JH, Helpern JA, Ramani A, et al. Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging[J]. Magn Reson Med, 2005, 53(6): 1432-1440. DOI: 10.1002/mrm.20508.
10
Glenn GR, Helpern JA, Tabesh A, et al. Quantitative assessment of diffusional kurtosis anisotropy[J]. NMR Biomed, 2015, 28(4): 448-459. DOI: 10.1002/nbm.3271.
11
Park M, Kim JW, Ahn SJ, et al. Evaluation of brain tumors using NO-DDI technique: A promising tool[J]. J Neuroradiol, 2020, 47(3): 185-186. DOI: 10.1016/j.neurad.2020.04.001.
12
Wen Q, Kelley DA, Banerjee S, et al. Clinically feasible NODDI character-ization of glioma using multiband EPI at 7 T[J]. Neuroimage Clin, 2015, 9: 291-299. DOI: 10.1016/j.nicl.2015.08.017.
13
Zhang H, Schneider T, Wheeler-Kingshott CA, et al. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain[J]. Neuroimage, 2012, 61(4): 1000-1016. DOI: 10.1016/j.neuroimage.2012.03.072.
14
Deligianni F, Carmichael DW, Zhang GH, et al. NODDI and tensor-based microstructural indices as predictors of functional connectivity[J]. PLoS One, 2016, 11(4): e0153404. DOI: 10.1371/journal.pone.0153404.
15
Merluzzi AP, Dean DC, Adluru N, et al. Age-dependent differences in brain tissue microstructure assessed with neurite orientation dispersion and density imaging[J]. Neurobiol Aging, 2016, 43: 79-88. DOI: 10.1016/j.neurobiolaging.
16
Fu XW, Ni HY. Neurite orientation dispersion and density imaging: the principle and progress in the central nervous system[J]. Int J Med Radiol, 2020, 43(1): 68-72. DOI: 10.19300/j.2020.Z17273.
17
Mastropietro A, Rizzo G, Fontana L, et al. Microstructural characterization of corticospinal tract in subacute and chronic stroke patients with distal lesions by means of advanced diffusion MRI[J]. Neuroradiology, 2019, 61(9): 1033-1045. DOI: 10.1007/s00234-019-02249-2.
18
Wang Z, Zhang S, Liu C, et al. A study of neurite orientation dispersion and density imaging in ischemic stroke[J]. Magn Reson Imaging, 2019, 57: 28-33. DOI: 10.1016/j.mri.2018.10.018.
19
Kamagata K, Hatano T, Okuzumi A, et al. Neurite orientation dispersion and density imaging in the substantia nigra in idiopathic Parkinson disease[J]. Eur Radiol, 2016, 26(8): 2567-2577. DOI: 10.1007/s00330-015-4066-8.
20
Liu WX, Lu P, Zhang XB, et al. Clinical application of magnetic resonanc-e NODDI in the diagnosis of putamen disease in patients with Parkinson's disease[J]. Chin J Magn Reson Imaging, 2020, 11(8): 610-614. DOI: 10.12015/issn.1674-8034.2020.08.003.
21
Mitchell T, Archer DB, Chu WT, et al. Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism[J]. Hum Brain Mapp, 2019, 40(17): 5094-5107. DOI: 10.1002/hbm.24760.
22
Timmers I, Zhang H, Bastiani M, et al. White matter microstructure pathology in classic galactosemia revealed by neurite orientation dispersion and density imaging[J]. J Inherit Metab Dis, 2015, 38(2): 295-304. DOI: 10.1007/s10545-014-9780-x.
23
Batalle D, Hughes EJ, Zhang H, et al. Early development of structural networks and the impact of prematurity on brain connectivity[J]. Neuroimage, 2017, 149: 379-392. DOI: 10.1016/j.neuroimage.2017.01.065.
24
Dean DC, Planalp EM, Wooten W, et al. Mapping white matter micro-structure in the one month human brain[J]. Sci Rep, 2017, 7(1): 9759. DOI: 10.1038/s41598-017-09915-6.
25
Winston GP, Micallef C, Symms MR, et al. Advanced diffusion imaging sequences could aid assessing patients with focal cortical dysplasia and epilepsy[J]. Epilepsy Res, 2014, 108(2): 336-339. DOI: 10.1016/j.eplepsyres.2013.11.004.
26
Li B, Zhu HB, Song GD, et al. The research on the precise treatment of molecular biomarkers and signaling pathways for glioma[J]. E J Transl Med, 2018, 5(7): 35-38. DOI: 10.12095/j.issn.2095-6894.2018.07.007.
27
Sun HJ. The application of precision medicine in tumor therapy[J]. Modern Business Trade Industry, 2019, 40(8): 93-94. DOI: 10.19311/j.cnki.1672-3198.2019.08.047.
28
Liu MY, Xie F, Zhang X, et al. Review of biomarkers for glioblastoma[J]. Current Biotechnol, 2019, 9(2): 129-138. DOI: 10.12015/issn.1674-8034.2020.08.003.
29
Lampinen B, Szczepankiewicz F, Martensson J, et al. Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI: a model comparison using spherical tensor encoding[J]. Neuroimage, 2017, 147: 517-531. DOI: 10.1016/j.neuroimage.2016.11.053.
30
Reynaud O, Winters KV, Hoang DM, et al. Pulsedand oscillating gradient MRI for assessment of cell size and extracellular space(POMACE) in mouse gliomas[J]. NMR Biomed, 2016, 29(10): 1350-1363. DOI: 10.1002/nbm.3577.
31
Vellmer S, Stirnberg R, Edelhoff D, et al. Comparative analysis of isotropic diffusion weighted imaging sequences[J]. J Magn Reson, 2017, 275: 137-147. DOI: 10.1016/j.jmr.2016.12.011.
32
Zhao J, Li JB, Wang JY, et al. Quantitative analysis of neurite orientation dispersion and density imaging in grading gliomas and detecting IDH-1 gene mutation status[J]. Neuroimage Clin, 2018, 19: 174-181. DOI: 10.1016/j.nicl.2018.04.011.
33
Wang JY, Chu JP, Zhao J, et al. Preliminary study on NODDI in cerebral glioma staging[J]. Radiol Pract, 2018, 33(7): 664-667. DOI: 10.13609/j.cnki.1000-0313.2018.07.002.
34
Shen MM, Wang SM, Hao Y, et al. Diagnosis of neurite orientation dispersion and density imaging for glioma classification[J]. Med Res Educat, 2020, 37(2): 37-43. DOI: 10.3969/j.issn.1674-490X.2020.02.006.
35
Xue B, Yu B, Huang MZ, et al. Progress in the application of neurite orientation dispersion and density imaging[J]. J Chin Clin Med Imaging, 2017, 28(12): 896-898. DOI: 10.3969/j.issn.1008-1062.2017.12.018.
36
Song YK, Chu JP. Advances in technical principles and clinical studies of dir-ectional dispersion and density imaging of nerve processes[J]. Diagnos Imaging Inter Radiol, 2017, 26(2): 157-161. DOI: 10.3969/j.issn.1005-8001.2017.02.014.

PREV Research progress on the effect of neuroimaging markers of cerebral small vessel disease on stroke
NEXT Research progress of neurite direction dispersion and density imaging in Alzheimer,s disease
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn