Sage Journals: Discover world-class research

Abstract

Background

Diffusion kurtosis imaging (DKI) is a technique based on the theory that the diffusion of water follows non-Gaussian distribution; until now, few studies have explored the usefulness of DKI in differentiating parotid gland tumors.

Purpose

To evaluate the potential of DKI in the characterization of parotid gland tumors.

Material and Methods

DKI was performed in 40 patients with parotid gland tumors (33 benign, 7 malignant). DKI parameters including apparent diffusion coefficient (D_app) and apparent kurtosis coefficient (K_app) were obtained using the DK model and compared. Intraclass correlation coefficient (ICC) was used to evaluate inter-observer agreement of DKI derived parameters.

Results

Excellent inter-observer agreements (D_app, ICC = 0.988; K_app, ICC = 0.985) were achieved during quantitative measurements. There were no significant differences in D_app (P = 0.055) and K_app (P = 0.915) between the benign and malignant groups. In the subgroup analyses, pleomorphic adenomas showed higher D_app (P < 0.001) and lower K_app (P = 0.037) than malignant tumors. Combination of D_app and K_app showed optimal discriminative value (area under curve [AUC] = 0.913; sensitivity = 88.89%; specificity = 85.71%). Pleomorphic adenomas also showed higher D_app (P < 0.001) and lower K_app (P < 0.001) than Warthin’s tumors. A combination of D_app and K_app showed optimal discriminative value (AUC = 1.000; sensitivity = 100%; specificity = 100%). Warthin’s tumors demonstrated higher K_app than malignant tumors (P < 0.001), while no significant difference was found on D_app (P = 0.448). The AUC, sensitivity, and specificity of K_app for discriminating Warthin’s tumors from malignant tumors at an optimal threshold of 0.735 were 0.905, 88.89%, and 85.71%, respectively.

Conclusion

DKI may be a promising imaging technique for characterizing parotid gland tumors.

Keywords

Parotid gland pleomorphic adenoma Warthin’s tumor magnetic resonance imaging diffusion kurtosis imaging

Get full access to this article

View all access options for this article.

References

Bradley

PJ.

Classification of salivary gland neoplasms. Adv Otorhinolaryngol 2016; 78:1–8.

Takumi

Fukukura

Hakamada

et al . Value of diffusion tensor imaging in differentiating malignant from benign parotid gland tumors. Eur J Radiol 2017; 95:249–256.

Yabuuchi

Matsuo

Kamitani

et al . Parotid gland tumors: can addition of diffusion-weighted MR imaging to dynamic contrast-enhanced MR imaging improve diagnostic accuracy in characterization? Radiology 2008; 249:909–916.

Christe

Waldherr

Hallett

et al . MR imaging of parotid tumors: typical lesion characteristics in MR imaging improve discrimination between benign and malignant disease. Am J Neuroradiol 2011; 32:1202–1207.

Yabuuchi

Fukuya

Tajima

et al . Salivary gland tumors: diagnostic value of gadolinium-enhanced dynamic MR imaging with histopathologic correlation. Radiology 2003; 226:345–354.

Kanda

Fukusato

Matsuda

et al . Gadolinium-based contrast agent accumulates in the brain even in subjects without severe renal dysfunction: evaluation of autopsy brain specimens with inductively coupled plasma mass spectroscopy. Radiology. 2015; 276:228–232.

Xu XQ, Choi YJ, Sung YS, et al. Intravoxel incoherent motion MR imaging in the head and neck: correlation with dynamic contrast-enhanced MR imaging and diffusion-weighted imaging. Korean J Radiol 2016;17:641–649.

Tao

Yang

Wang

et al . The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours. Dentomaxillofac Radiol 2017; 46:20160434.

Fruehwald-Pallamar

Czerny

Holzer-Fruehwald

et al . Texture-based and diffusion-weighted discrimination of parotid gland lesions on MR images at 3.0 Tesla. NMR Biomed 2013; 26:1372–1379.

10.

Yuan

Tang

Tao

Parotid gland lesions: separate and combined diagnostic value of conventional MRI, diffusion-weighted imaging and dynamic contrast-enhanced MRI.

Br J Radiol 2016; 89:20150912.

11.

Habermann

Arndt

Graessner

et al . Diffusion-weighted echo-planar MR imaging of primary parotid gland tumors: is a prediction of different histologic subtypes possible? Am J Neuroradiol 2009; 30:591–596.

12.

Chen

et al . Quantitative evaluation of diffusion-kurtosis imaging for grading endometrial carcinoma: a comparative study with diffusion-weighted imaging. Clin Radiol 2017; 72:995.e11–995.e20.

13.

Chu

Zhang

Zhou

et al . Diffusional kurtosis imaging of parotid glands in Sjögren’s syndrome: Initial findings. J Magn Reson Imaging 2017; 46:1409–1417.

14.

Xu XQ, Ma G, Wang YJ, et al. Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage. Oncotarget 2017;8:47230–47238.

15.

Zhang

Bao

et al.

Diffusion kurtosis imaging in the differential diagnosis of parotid gland disease and parotid adenolymphoma: preliminary results. Dentomaxillofacial Radiol 2018; 47:20170388.

16.

Zhang

et al . Diffusion kurtosis imaging for differentiating parotid tumors. Int J Clin Exp Med 2017; 10:8025–8030.

17.

Stejskal

Tanner

Spin diffusion measurements: spin echoes in the presence of a time dependent field gradient.

J Chem Phys 1965; 42:288–292.

18.

DeLong

Clarke-Pearson

DL.

Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

Biometrics 1988; 44:837–845.

19.

Xu XQ, Su GY, Hu H, et al. Effects of regions of interest methods on apparent coefficient measurement of the parotid gland in early Sjögren’s syndrome at 3T MRI. Acta Radiol 2017;58:27-33.

20.

Wang YJ, Xu XQ, Hu H, et al. Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region. Acta Radiol 2018;59:672–680.

21.

Xiao

Tang

Qiang

et al . Differentiation of olfactory neuroblastomas from nasal squamous cell carcinomas using MR diffusion kurtosis imaging and dynamic contrast-enhanced MRI. J Magn Reson Imaging 2018; 47:354–361.

22.

Sun

Chen

Chai

et al . Breast Cancer: diffusion kurtosis MR imaging-diagnostic accuracy and correlation with clinical-pathologic factors. Radiology 2015; 277:46–55.

23.

Sumi

Van Cauteren

Sumi

et al . Salivary gland tumors: use of intravoxel incoherent motion MR imaging for assessment of diffusion and perfusion for the differentiation of benign from malignant tumors. Radiology 2012; 263:770–777.

24.

Eida

Sumi

Sakihama

et al.

Apparent diffusion coefficient mapping of salivary gland tumors: prediction of the benignancy and malignancy. Am J Neuroradiol 2007; 28:116–121.

25.

Jiang

Tang

Zhong

et al . Diffusion kurtosis imaging for differentiating between the benign and malignant sinonasal lesions. J Magn Reson Imaging 2017; 45:1446–1454.

26.

Kato

Fujimoto

Matsuo

et al . Usefulness of diffusion-weighted MR imaging for differentiating between Warthin's tumor and oncocytoma of the parotid gland. Jpn J Radiol 2017; 35:78–85.

27.

Yuan

Yeung

Mok

GS.

Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma.

PLoS One 2014; 9:e87024.

Preliminary study of using diffusion kurtosis imaging for characterizing parotid gland tumors

Abstract

Background

Purpose

Material and Methods

Results

Conclusion

Keywords

Get full access to this article

References