Utility of histogram analysis of ADC maps for differentiating orbital tumors

Xiao-Quan Xu

We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors. METHODS Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2 , and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established. RESULTS Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%). CONCLUSION Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.

Kaynakça

Goh PS, Gi MT, Charlton A, et al. Review of or- bital imaging. Eur J Radiol 2008; 66:387-395. [CrossRef]

Xian J, Zhang Z, Wang Z, et al. Value of MR imaging in the differentiation of benign and malignant orbital tumors in adults. Eur Radiol 2010; 20:1692-1702. [CrossRef]

Ben Simon GJ, Annunziata CC, Fink J, et al. Re- thinking orbital imaging establishing guide- lines for interpreting orbital imaging studies and evaluating their predictive value in pa- tients with orbital tumors. Ophthalmology 2005; 112:2196-2207. [CrossRef]

Xu XQ, Cheng QG, Zu QQ, et al. Comparative study of the relative signal intensity on DWI, FLAIR, and T2 images in identifying the onset time of stroke in an embolic canine model. Neurol Sci 2014; 35:1059-1065. [CrossRef]

Sepahdari AR, Aakalu VK, Kapur R, et al. MRI of orbital cellulitis and orbital abscess: the role of diffusion-weighted imaging. AJR Am J Roent- genol 2009; 193:W244-250. [CrossRef]

Kapur R, Sepahdari AR, Mafee MF, et al. MR imaging of orbital inflammatory syndrome, or- bital cellulitis, and orbital lymphoid lesions: the role of diffusion-weighted imaging. AJNR Am J Neuroradiol 2009; 30:64-70. [CrossRef]

de Graaf P, Pouwels PJ, Rodjan F, et al. Sin- gle-shot turbo spin-echo diffusion-weighted imaging for retinoblastoma: initial experience. AJNR Am J Neuroradiol 2012; 33:110-118. [CrossRef]

Politi LS, Forghani R, Godi C, et al. ocular ad- nexal lymphoma: diffusion-weighted MR im- aging for differential diagnosis and therapeu- tic monitoring. Radiology 2010; 256:565-574. [CrossRef]

Sepahdari AR, Kapur R, Aakalu VK, et al. Diffu- sion-weighted imaging of malignant ocular masses: initial results and directions for further study. AJNR Am J Neuroradiol 2012; 33:314- 319. [CrossRef]

Sepahdari AR, Aakalu VK, Setabutr P, et al. Indeterminate orbital masses: restricted dif- fusion at MR imaging with echo-planar diffu- sion-weighted imaging predicts malignancy. Radiology 2010; 256:554-564. [CrossRef]

Lope LA, Hutcheson KA, Khademian ZP. Magnetic resonance imaging in the analysis of pediatric orbital tumors: utility of diffu- sion-weighted imaging. J AAPOS 2010; 14:257- 262. [CrossRef]

Razek AA, Elkhamary S, Mousa A. Differenti- ation between benign and malignant orbital tumors at 3-T diffusion MR imaging. Neurora- diology 2011; 53:517-522. [CrossRef]

Ahn SJ, Choi SH, Kim YJ, et al. Histogram anal- ysis of apparent diffusion coefficient map of standard and high B-value diffusion MR imag- ing in head and neck squamous cell carcino- ma: a correlation study with histological grade. Acad Radiol 2012; 19:1233-1240. [CrossRef]

Suo ST, Chen XX, Fan Y, et al. Histogram analy- sis of apparent diffusion coefŞcient at 3.0 T in urinary bladder lesions: correlation with patho- logic findings. Acad Radiol 2014; 21:1027- 1034. [CrossRef]

Ma X, Zhao X, Ouyang H, et al. Quantified ADC histogram analysis: a new method for differen- tiating mass-forming focal pancreatitis from pancreatic cancer. Acta Radiol 2014; 55:785- 792. [CrossRef]

Ryu YJ, Choi SH, Park SJ, et al. Glioma: appli- cation of whole-tumor texture analysis of diffusion-weighted imaging for the evalua- tion of tumor heterogeneity. PLoS One 2014; 9:e108335. [CrossRef]

Woo S, Cho JY, Kim SY, et al. Histogram anal- ysis of apparent diffusion coefficient map of diffusion-weighted MRI in endometrial cancer: a preliminary correlation study with histological grade. Acta Radiol 2014; 55:1270- 1277. [CrossRef]

Cho SH, Kim GC, Jang YJ, et al. Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response. Acta Radiol 2015; 56:1042- 1050. [CrossRef]

Zhang YD, Wang Q, Wu CJ, et al. The histogram analysis of diffusion-weighted intravoxel inco- herent motion (IVIM) imaging for differentiat- ing the gleason grade of prostate cancer. Eur Radiol 2015; 25:994-1004. [CrossRef]

Donati OF, Mazaheri Y, Afaq A, et al. Pros- tate cancer aggressiveness: assessment with whole-lesion histogram analysis of the ap- parent diffusion coefficient. Radiology 2014; 271:143-152. [CrossRef]

Heo SH, Shin SS, Kim JW, et al. Pre-treatment diffusion-weighted MR imaging for predicting tumor recurrence in uterine cervical cancer treated with concurrent chemoradiation: val- ue of histogram analysis of apparent diffusion coefficients. Korean J Radiol 2013; 14: 616-625. [CrossRef]

Kim EJ, Kim SH, Park GE, et al. Histogram anal- ysis of apparent diffusion coefficient at 3.0T: Correlation with prognostic factors and sub- types of invasive ductal carcinoma. J Magn Reson Imaging 2015; 42:1666-1678. [CrossRef]

Suh CH, Kim HS, Lee SS, et al. Atypical imaging features of primary central nervous system lymphoma that mimics glioblastoma: utility of intravoxel incoherent motion MR imaging. Ra- diology 2014; 272:504-513. [CrossRef]

Tailor TD, Gupta D, Dalley RW, et al. Orbit- al neoplasms in adults: clinical, radiologic, and pathologic review. Radiographics 2013; 33:1739-1758. [CrossRef]

Baek HJ, Kim HS, Kim N, et al. Percent change of perfusion skewness and kurtosis: a poten- tial imaging biomarker for early treatment response in patients with newly diagnosed glioblastomas. Radiology 2012; 264:834-843. [CrossRef]

Kang Y, Choi SH, Kim YJ, et al. Gliomas: histo- gram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffu- sion-weighted MR imaging--correlation with tumor grade. Radiology 2011; 261:882-890. [CrossRef]

Lu SS, Kim SJ, Kim N, et al. Histogram analy- sis of apparent diffusion coefficient maps for differentiating primary CNS lymphomas from tumefactive demyelinating lesions. AJR Am J Roentgenol 2015; 204:827-834. [CrossRef]

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