Introduction

Diffusion kurtosis imaging (DKI), a non-invasive diffusion-weighted imaging (DWI) technique, can detect the non-Gaussian diffusion of water molecules in different tissues [1], and is helpful for the early detection, diagnosis, and treatment evaluation of patients with Nasopharyngeal carcinoma (NPC). Previous literature has shown that the choice of b-value combination, number of direction, and diffusion time can generate variability in DKI research, because they reflect the degree of diffusion weight [2,3]. Different b-value combinations will produce different estimates of DKI-derived parameters [4]. Choosing a suitable b-value combination is very crucial, which can further reduce time. Hence, this study will further explore the appropriate b-value combination for NPC.

Materials and Methods

This prospective study was approved by the Institutional Review Board and the requirement for formal informed consent was acquired from all patients. 38 patients were enrolled between March 2018 and December 2019. MRI examinations were performed on a 3.0T MRI scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) with 24-channel head and neck coil. A DKI with 5b-values was obtained using RESOLVE sequence, and the sequence parameters were as follows: 5b-values, including 200, 400, 800, 1500, 2000 s/mm2, TR = 3960 ms, TE1/TE2 = 68/98 ms, thickness/intersection gap = 4/0.4 mm, matrix size = 134 × 134; FOV = 258× 258 mm, readout segments = 5, Readout Partial Fourier (RPF) = 5/8, three orthogonal directions, scan time = 5min 13s. The different b-value combinations and corresponding simulated acquisition time used are shown in Table 1. All images with different b-value combinations were imported to a protype MR diffusion toolbox (Siemens Healthcare, Erlangen, Germany) for analysis, and the software fits the DKI model through equations (1)
$$ Sb/S0=exp(-b*D+1/6 b²*MD*MK (1)
Where, MD is the apparent diffusion coefficient, and MK is the apparent diffusion kurtosis. Differences in RESOLVE based DKI sequences between different b-value combinations with RPF were compared using the Kruskal-Wallis H test. P < 0.001 was considered significantly difference by Bonferroni correction.

Result

Through the comparison of the ICC and P values of 9 groups of different b-value combinations in RESOLVE-based DKI, group 2 (200, 800, 2000), group 6 (200, 400, 800, 2000) and group 7 (200, 800, 1500, 2000) simultaneously satisfy the conditions of no significant difference (P > 0.001) and excellent agreement (0.81-1.00) with group 9 (200, 400, 800, 1500, 2000) (Figure 1), as shown in Table 2. The ICC of MK and MD in the group 6 were the largest (0.9897 and 0.9804, respectively) compared to the group 6 and group 7. Combining b-value optimization and RPF technology, the group 6 (200, 400, 800, 2000) can save about 28% of the time (3min46s vs 5min13s).

Discussion

Some studies suggested that DKI should be added to routine clinical applications, which is helpful for cancer screening [5], and can also provide more accurate information about diffusion [6]. DKI may be helpful in predicting the radiotherapy response in NPC[8]. Therefore, the standardization of DKI imaging protocol is very essential, and the b-value optimization is one of the key factors. Both RPF and b-value combination can affect the scan time. In our study, when the RPF and the optimal b-value combination were used at the same time, that is, the group (200, 400, 800, 2000) with RPF can save up to 28% of time compared to the RESOLVE with RPF (200, 400, 800, 1500, 2000) and 56% without RPF (8min 31s)[7].

Conclusions

The combination of RPF and b-value optimization can ensure the stability of DKI parameters and reduce the scanning time. With the advantages of stable image quality and time saving, we recommended that the DKI imaging of (200, 400, 800, 2000) with 5/8 RPF can be applied to the clinical DKI research in NPC.

Acknowledgements

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Hubei Key Laboratory of Medical Information Analysis & Tumor Diagnosis and Treatment (Grant No. PJS140012005).

References

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