Diffusion kurtosis imaging for preliminary analysis of micro-structural changes of brain tissue affected by acute ischemic stroke
Liuhong Zhu1, Zhongping Zhang2, Qihua Cheng1, Phillip Zhe Sun3, and Gang Guo1

1Radiology, Xiamen Second Hospital, Xiamen, China, People's Republic of, 2MR Research China, GE Healthcare, Beijing, China, People's Republic of, 3Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States

Synopsis

One hundred and thirteen patients with acute ischemic stroke underwent DKI sequence scanning. 131 lesions were outlined and divided into six groups. The changed percentages of DKI indices (FA%, MD%, Da%, Dr%, MK%, Ka%, Kr%) relative to normal contra-lateral ROI were computed. The statistical analysis results illustrated that there was a trend that when the acute ischemic stroke affected tissue mostly contained white matter, the complexity of micro-structure changes of the tissue was much higher than other affected locations. Also, the kurtosis-derived parameters presented to have greater potential in distinguishing each group.

Background and Purpose

Diffusion kurtosis imaging (DKI) has been developed to probe non-Gaussian properties of water diffusion in brain tissues recently[1-4]. The aim of this study was to explore the value of DKI technology in the analysis of micro-structural change complexity of brain tissue affected by acute ischemic stroke.

Material and Methods

One hundred and thirteen patients ((66.62±14.88) Y, 42 women, 71 men) with acute ischemic stroke underwent routine MR scanning with additional DKI sequence scanning (b=0, 1000, 2000s/mm2, 15 directions) from February 2014 to August 2015. 131 lesions in common affected locations (Periventricular white matter area (PWM): 35 lesions; corpuscallosum area (CC): 6 lesions; cerebellum area (CB): 17 lesions; basal ganglia area (BG): 11 lesions; brain stem area (BS): 17 lesions; lobes mixed with grey and white matter (LGW): 45 lesions) were outlined. Normal contra-lateral region of interest (ROI), which was the mirror region of each lesion, was also outlined. The values of DKI-derived indices, such as fraction anisotropy (FA), mean diffusion (MD), axial diffusion (Da), radial diffusion (Dr), mean kurtosis (MK), axial kurtosis (Ka) and radial kurtosis (Kr), were calculated. The changed percentages of all index (FA%, MD%, Da%, Dr%, MK%, Ka%, Kr%) relative to normal contra-lateral ROI were also computed. Statistical analysis about multiple comparisons using Kolmogorov-Smirnov test among groups were performed.

Results

Diffusivity-derived indices (FA, MD, Da and Dr) decreased and kurtosis-derived parameters (MK, Ka and Kr) increased in all lesion groups (Table1). The upper 3 lines in figure1 performed larger fluctuation than the lower 4 lines among groups. Table2 showed the Kolmogorov-Smirnov test of DKI metrics between every two groups. It showed that there was significant difference (p<0.05) of MK% between almost all of the two groups (except BG vs. BS; BG vs. LGW; BS vs. LGW) (p<0.05), and Ka% performs nearly the same as MK%. While there was no significant difference of MD% and Da% between almost all of the two groups (except PWM vs. CB; PWM vs. BG; PWM vs. BS) (p>0.05). Dr% illustrated no statistical significance among all groups (p>0.05). FA% was significantly lower in PWM group and CC group than BG group (p=0.002 and 0.009 respectively). The change percentage of kurtosis-derived parameters in descending order was as following: CC > PWM > BS > LGW > BG > CB.

Discussions

Tissues locating at CC area and PWM area mainly contained bunches of white matter, while contained grey matter nucleus at BG area. The results illustrated that there was a trend that when the acute ischemic stroke affected tissue mostly contained white matter, the complexity of micro-structure changes of the tissue was much higher than other affected locations. Also, the kurtosis-derived parameters performed larger fluctuation among groups, which meant that they had greater potential in distinguishing each group.

Conclusion

DKI technology could reveal the different complexity of micro-structure changes among various locations affected by acute ischemic stroke, and kurtosis-derived parameters perform better than diffusivity-derived parameters among groups.

Acknowledgements

We are grateful for the support from Na Xu, Yehua Song and Ruiqiang Peng from the department of internal neurology of Xiamen Second Hospital during patient recruitment and data acquisition. This work was supported by Joint project for Xiamen key diseases (Grant No. 3502Z20149032) and Planned Project Grant (Grant No. 3502Z20154065) from Xiamen Science and Technology Bureau.

References

[1] Winston GP. The potential role of novel diffusion imaging techniques in the understanding and treatment of epilepsy. Quant Imaging Med Surg. 2015 ; 5(2):279-87.

[2] Hui ES, Cheung MM, Qi L, et al.. Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis. Neuroimage 2008; 42:122–134.

[3] Jensen JH, Helpern JA, Ramani A. MRI Quantification of Non-Gaussian Water Diffusion by Kurtosis Analysis. NMR Biomed 2010; 23(7): 698–710.

[4] Zhu J, Zhuo C, Qin W, et al.. Performances of diffusion kurtosis imaging and diffusion tensor imaging in detecting white matter abnormality in schizophrenia. Neuroimage Clin. 2014 ; 7:170-6.

Figures

Table 1. Mean value of change percentages of DKI metrics in each group

Figure. 1 The comparison of DKI matrices among groups

Table 2. Kolmogorov-Smirnov test of DKI metrics among groups



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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