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Diffusion kurtosis imaging for differentiating tumor KRAS mutation status in rectal cancer
Yanyan Xu1, Hongliang Sun1, Kaining Shi2, and Wu Wang1

1Radiology, China-Japan Friendship Hospital, Beijing, People's Republic of China, 2Philips Healthcare, China, Beijing, People's Republic of China

Synopsis

Diffusion kurtosis imaging (DKI), which is a non-Gaussian diffusion-weighted model proposed by Jensen et al 1, has the potential to characterize both normal and pathologic tissue 1-3, meanwhile, providing a new option for tumor garde 4 and assessment of treatment response 5-7. Previous studies 1-3, 8 found that DKI could better account for restricted water diffusion within the complex microstructure of most tissues. To our knowledge, however, no study has included evaluation of DKI characteristic in rectal cancer, especially in the aspect of KRAS mutant, which associated with clinical treatment and prognosis of colorectal cancers 9.

Purpose

To explore the potential clinical value of diffusion kurtosis imaging (DKI) in rectal cancers with different KRAS status

Methods

Fifty-three patients (mean age, 60.58 ± 13.04; range, 26-85 years), including 43 men and 10 women with pathologically proved rectal cancers from April 2015 to Mach 2016 were retrospectively analyzed. DKI with seven b values (0, 400, 800, 1000, 1200, 1500 and 2000s/mm2) were performed and relevant parameters (MD, mean diffusivity; MK, mean kurtosis; FA, fractional anisotropy) were calculated using dedicated software with DKI model. Patients were stratified into two groups -KRAS wild-type and mutant by amplification refractory mutation system (ARMS) method. The DKI derived parameters measured by two radiologists were tested first with Kolmogorov-Smirnov test for normality analysis and then with the Levene test for variance homogeneity analysis. The DKI derived parameters between KRAS wild-type group and KRAS mutant group were compared by using independent samples t test or Mann-Whitney U test according to the test results mentioned above. Intraobserver and interobserver agreements were evaluated using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. P＜0.05 was considered to indicate a statistically significant difference.

Results

There were 31 patients with KRAS wild-type and 22 with KRAS mutant (including 20 patients with exon 2 mutant, 2 with exon 4 mutant). Intra- and inter-observer reproducibility for MD, MK, FA were relatively good to excellent (ICCIntra=0.7832-0.8399, ICCinter=0.6349-0.8169; ICCIntra=0.6942-0.8387, ICCinter=0.6579-0.8740; ICCIntra=0.6619-0.9026, ICCinter=0.6799-0.8791), respectively. MD values were significantly higher in KRAS mutant group than in KRAS wild-type group([1.33±0.35]×10-3mm2/s VS [1.16±0.26]×10-3mm2/s; P = 0.048), whereas MK and FA values showed totally different trend with no significantly statistical differences( P = 0.531 for MK, P = 0.323 for FA).

Conclusion

The DKI derived parameter MD may provide additional information for different KRAS status differentiation, however, the results should be confirmed in further study.

Acknowledgements

No acknowledgement found.

References

1. Jensen JH, Helpern JA, Ramani A, et al. Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med. 2005;53(6):1432-1440.

2. Lu H, Jensen JH, Ramani A, et al. Three-dimensional characterization of non-Gaussian water diffusion in humans using diffusion kurtosis imaging. NMR Biomed. 2006;19(2):236-247.

3. Kun S, Xiaosong C, Weimin C, et al. Breast cancer: diffusion kurtosis MR imaging-diagnostic accuracy and correlation with clinical-pathologic factors. Radiology.2015;277(1):46-55.

4. Yan B, Yusong L, Jie T, et al. Grading of gliomas by using monoexponential, biexponential, and stretched exponential diffusion-weighted MR imaging and diffusion kurtosis MR imaging. Radiology. 2016; 278(2): 496-504.

5. Rosenkrantz AB, Sigmund EE, Winnick A, et al. Assessment of hepatocellular carcinoma using apparent diffusion coefficient and diffusion kurtosis indices: preliminary experience in fresh liverexplants. Magn Reson Imaging 2012;30:1534-1540.

6. Goshima S, Kanematsu M, Noda Y, et al. Diffusion kurtosis imaging to assess response to treatment in hypervascular hepatocellular carcinoma. AJR Am J Roentgenol. 2015; 204:W543-549.

7. Chen Y, Ren W, Zheng D, et al. Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients. J Magn Reson Imaging JMRI. 2015;42(5):1354-61. doi: 10.1002/jmri.24910.

8. Jensen JH, Helpern JA, Ramani A, et al. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med. 2005;53:1432-1440.

9. Shigenori K, Miho K, Shuhei T, et al. Prognostic value of KRAS and BRAF mutations in curatively resected colorectal cancer. World Journal of Gastroenterology. 2015;21(4):1275-1283.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)
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