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    Reply: | American Journal of Neuroradiology  
    


















    


























    
  
  




    
    

  

      


    

      

  
  
  

    

  

    

  

                
    

      

  

    

  
      
  
  

    


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ReplyLETTER

  
      

  
      
Reply:

  
    	
N. Tu, L. Bu and G. Wu

  
    	
American Journal of Neuroradiology September 2019,  40 (9) E46-E47; DOI: https://doi.org/10.3174/ajnr.A6204 

  
  
  



  


  
  



  
      
  
  

    
We appreciate the comments by Dr Giannelli and colleagues regarding our recent article “Treatment Response Prediction of Nasopharyngeal Carcinoma Based on Histogram Analysis of Diffusional Kurtosis Imaging,” which raised an interesting issue on the influence factors of diffusional kurtosis imaging (DKI) estimation bias.
As they mentioned, DWI with 3 diffusion-weighted directions is currently the de facto standard in the application of DKI in body tumor. There are objective reasons for using 3 perpendicular directions in body application of non-Gaussian diffusional kurtosis imaging rather than >15 directions as in brain white matter evaluations.1 First, the different anisotropic features between body and head lead to a basic need for >15 directions in white matter applications, while 3 directions may be sufficient in body applications.2 Second, the increase of directions will result in a large increase in acquisition time, more likely leading to bulk and respiration motion, which should be avoided in body imaging acquisitions. Third, trace weighted images (TWIs) could increase the low signal-to-noise ratio in body tissue and make images robust to motion.3,4
Giannelli et al have reported that the percentage error in K and D estimation using TWIs in head and neck cancer can be non-negligible for single lesions. They recommended the use of at least 15 diffusion-weighting directions and 2 non-null b-values in quantitative DKI analysis based on a simulation study5 and a prospective study.6 They drew this conclusion on the basis of a small sample study with a group of 18 patients with significantly different types of head and neck tumors, for example, tongue squamous cell carcinoma and lymphoma, using 3 main diffusion directions (x, y, z) with an acquisition time of 8 minutes 21 seconds (the time of our study is 3 minutes 26 seconds).
As we all know, different types of tumors have remarkably different biologic microstructures, resulting in differing diffusivity. For example, nasopharyngeal carcinoma (NPC) is a special type of head and neck tumor that has remarkably different biologic characteristics than other head and neck tumors. It is relatively isotropic, though the microstructure complexity differs according to treatment response.7 Moreover, the acquisition of NPC MR images is relatively more sensitive to bulk and respiratory artifacts; therefore, an appropriate short acquisition time is important. Therefore, the reproductivity and reliability of the recommendation for more directions not only in patients with NPC but also in those with other head and neck tumors remains controversial and needs further validation in unique types of tumors with certain sample sizes. Moreover, it appears that the DKI parameters may differ among different MR imaging systems and different institutions.8,-,10 Further study should be a multicenter large-sample-size prospective validation of this recommendation. The more complex the algorithm, the more error will occur during each step of calculation. Hence, a simplified geometric model may be more feasible in clinical application.11
In conclusion, the use of only 3 perpendicular directions in general DKI body applications may lead to non-negligible bias during calculation. However, in body solid tumors with fewer anisotropic characteristics, 3 directions may be sufficient in clinical application. These comments remind us to pay more attention to the influencing factors of DKI acquisitions. On the other hand, because the imaging biomarkers differ in numerous studies,7,8,10,12,-,14 these comments give us an idea of how to explain the variation among these studies, to modify the parameter calculations, and to increase the possibility of exploring unique, proper, and impactful metrics as image biomarkers for further clinical application.
References
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    1. Giannelli  M, 
    2. Marzi  C, 
    3. Mascalchi  M, et al
    . Toward a standardized approach to estimate kurtosis in body applications of a non-Gaussian diffusion kurtosis imaging model of water diffusion. Radiology 2017;285:329–31 doi:10.1148/radiol.2017170995 pmid:28926313
  2. 2.
    1. Iima  M, 
    2. Le Bihan  D.
     Clinical intravoxel incoherent motion and diffusion MR imaging: past, present, and future. Radiology 2016;278:13–32 doi:10.1148/radiol.2015150244 pmid:26690990
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    1. Filli  L, 
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    1. Iima  M, 
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    . Quantitative non-Gaussian diffusion and intravoxel incoherent motion magnetic resonance imaging: differentiation of malignant and benign breast lesions. Invest Radiology 2015;50:205–11 doi:10.1097/RLI.0000000000000094 pmid:25260092
  5. 5.
    1. Giannelli  M, 
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     On the use of trace-weighted images in body diffusional kurtosis imaging. Magn Reson Imaging 2016;34:502–07 doi:10.1016/j.mri.2015.12.013 pmid:26706136
  6. 6.
    1. Marzi  S, 
    2. Minosse  S, 
    3. Vidiri  A, et al
    . Diffusional kurtosis imaging in head and neck cancer: On the use of trace-weighted images to estimate indices of non-Gaussian water diffusion. Med Phys 2018;45:5411–19 doi:10.1002/mp.13238 pmid:30317646
  7. 7.
    1. Tu  N, 
    2. Zhong  Y, 
    3. Wang  X, et al
    . Treatment response prediction of nasopharyngeal carcinoma based on histogram analysis of diffusional kurtosis imaging. AJNR Am J Neuroradiol 2019;40:326–33 doi:10.3174/ajnr.A5925 pmid:30630832
  8. 8.
    1. Law  BK, 
    2. King  AD, 
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    . Diffusion-weighted imaging of nasopharyngeal carcinoma: can pretreatment DWI predict local failure based on long-term outcome? AJNR Am J Neuroradiol 2016;37:1706–12 doi:10.3174/ajnr.A4792 pmid:27151750
  9. 9.
    1. Zhang  Y, 
    2. Liu  X, 
    3. Zhang  Y, et al
    . Prognostic value of the primary lesion apparent diffusion coefficient (ADC) in nasopharyngeal carcinoma: a retrospective study of 541 cases. Sci Rep 2015;5:12242 doi:10.1038/srep12242 pmid:26184509
  10. 10.
    1. Zheng  D, 
    2. Lai  G, 
    3. Chen  Y, et al
    . Integrating dynamic contrast-enhanced magnetic resonance imaging and diffusion kurtosis imaging for neoadjuvant chemotherapy assessment of nasopharyngeal carcinoma. J Magn Reson Imaging 2018;48:1208–16 doi:10.1002/jmri.26164 pmid:29693765
  11. 11.
    1. Jensen  JH, 
    2. Helpern  JA.
     MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 2010;23:698–710 doi:10.1002/nbm.1518 pmid:20632416
  12. 12.
    1. Liyan  L, 
    2. Si  W, 
    3. Qian  W, et al
    . Diffusion kurtosis as an in vivo imaging marker of early radiation-induced changes in radiation-induced temporal lobe necrosis in nasopharyngeal carcinoma patients. Clin Neuroradiol 2018;28:413–20 doi:10.1007/s00062-017-0585-9 pmid:28447147
  13. 13.
    1. Zhong  J, 
    2. Shi  P, 
    3. Chen  Y, et al
    . Diffusion kurtosis imaging of a human nasopharyngeal carcinoma xenograft model: Initial experience with pathological correlation. Magn Reson Imaging 2018;47:111–17 doi:10.1016/j.mri.2017.12.012 pmid:29221965
  14. 14.
    1. Fujima  N, 
    2. Yoshida  D, 
    3. Sakashita  T, et al
    . Prediction of the treatment outcome using intravoxel incoherent motion and diffusional kurtosis imaging in nasal or sinonasal squamous cell carcinoma patients. Eur Radiology 2017;27:956–65 doi:10.1007/s00330-016-4440-1 pmid:27255401
  


  
  



  



    

  



  

                
    

      

  

    

  
      
  
  

    


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