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Preliminary research of DKI parameters in predicting the prognosis of brain acute stroke lesions
CHEN Fang  YANG Yong-gui  GUO Gang 

DOI:10.12015/issn.1674-8034.2018.02.010.


[Abstract] Objective: This paper aims to research the greater advantage of diffusion kurtosis imaging (DKI) in predicting the prognosis of the brain acute stroke than diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI).Materials and Methods: We chose a female patient who has 9 acute stroke lesions in brain. We measured the DWI, DKI parameters and volume of 9 lesions. We found that the prognosis of 9 lesions was diverse in the re-examination after 12 days. Four lesions which volume decreased were divided into group 1, and five lesions which volume increased were divided into group 2. The difference of DWI and DKI parameters between two groups was assessed by independent-samples t test. The correlation between DWI, DKI parameters and volume change before and after treatment was assessed by Pearson correlation coefficients.Results: It shows that mean kurtosis (MK), axial kurtosis (Ka), radical kurtosis (Kr), △MK and △Ka have strong correlation with the volume change before and after treatment, the correlation coefficients are 0.791, 0.805, 0.732, 0.802 and 0.855. △MK is significant difference (P<0.05) between two groups of lesions. △ADC and other DKI parameters are not significant difference (P>0.05) between two groups.Conclusions: The result indicates that the larger of the DKI parameters (MK, Ka, Kr) may predict the worse prognosis. DKI may provide guidance to clinical treatment and assessment in brain acute stroke.
[Keywords] Diffusion Kurtosis imaging；Stroke；Diffusion weighted imaging；Diffusion tensor imaging；Magnetic resonance imaging；Prognosis

CHEN Fang Department of Radiology, Xiamen No.2 Hospital, Xiamen 361021, China

YANG Yong-gui Department of Radiology, Xiamen No.2 Hospital, Xiamen 361021, China

GUO Gang* Department of Radiology, Xiamen No.2 Hospital, Xiamen 361021, China

*Correspondence to: Guo G, E-mail: guogangxm@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of Xiamen Science and Technology Plan Project No. 3502Z20144050 Xiamen Program of Joint Effort for Tackling Major Diseases No. 3502Z20149032
Received  2017-08-18
Accepted  2017-11-27
DOI: 10.12015/issn.1674-8034.2018.02.010
DOI:10.12015/issn.1674-8034.2018.02.010.

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