Abstract
ObjectiveDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) histograms were used to investigate whether their parameters can distinguish between benign and malignant parotid gland tumors and further differentiate tumor subgroups.Materials and methodsA total of 117 patients (32 malignant and 85 benign) who had undergone DCE-MRI for pretreatment evaluation were retrospectively included. Histogram parameters including mean, median, entropy, skewness, kurtosis and 10th, 90th percentiles were calculated from time to peak (TTP) (s), wash in rate (WIR) (l/s), wash out rate (WOR) (l/s), and maximum relative enhancement (MRE) (%) mono-exponential models. The Mann–Whitney U test was used to compare the differences between the benign and malignant groups. The diagnostic value of each significant parameter was determined on Receiver operating characteristic (ROC) analysis. Multivariate stepwise logistic regression analysis was used to identify the independent predictors of the different tumor groups.ResultsFor both the benign and malignant groups and the comparisons among the subgroups, the parameters of TTP and MRE showed better performance among the various parameters. WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors. Warthin’s tumors showed significantly lower values on 10th MRE and significantly higher values on skewness TTP and 10th WOR, and the combination of 10th MRE, skewness TTP and 10th WOR showed optimal diagnostic performance (AUC, 0.971) and provided 93.12% sensitivity and 96.70% specificity. After Warthin’s tumors were removed from among the benign tumors, malignant parotid tumors showed significantly lower values on the 10th TTP (AUC, 0.847; sensitivity 90.62%; specificity 69.09%; P < 0.05) and higher values on skewness MRE (AUC, 0.777; sensitivity 71.87%; specificity 76.36%; P < 0.05).ConclusionDCE-MRI histogram parameters, especially TTP and MRE parameters, show promise as effective indicators for identifying and classifying parotid tumors. Entropy TTP and kurtosis MRE were found to be independent differentiating variables for malignant parotid gland tumors. The 10th WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors.
Highlights
Salivary gland neoplasms constitute approximately 3–5% of all head and neck tumors
Fine needle biopsy is the gold standard for preoperative diagnosis, it has some shortcomings [4, 5], such as the difficulty of obtaining a definite diagnosis from the biopsy and the accuracy not being ideal in the differential diagnosis of small and/or deep parotid tumors, since salivary gland tumors show various histopathological features [6, 7]
Interobserver agreement in the Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) analysis was perfect for all pharmacokinetic parameters (ICCs, range = 0.920– 0.976)
Summary
Salivary gland neoplasms constitute approximately 3–5% of all head and neck tumors. Approximately 70% of all salivary gland neoplasms occur in the parotid gland [1, 2].Xiang et al BMC Medical Imaging (2021) 21:194Accurate differentiation between malignant and benign lesions is important for the determination of therapeutic strategies and the prediction of the disease outcome [3]. Salivary gland neoplasms constitute approximately 3–5% of all head and neck tumors. Fine needle biopsy is the gold standard for preoperative diagnosis, it has some shortcomings [4, 5], such as the difficulty of obtaining a definite diagnosis from the biopsy and the accuracy not being ideal in the differential diagnosis of small and/or deep parotid tumors, since salivary gland tumors show various histopathological features [6, 7]. DCE-MRI has been already proven to provide satisfactory accuracy in differential diagnosis of benign and malignant tumors of the parotid gland [4, 12, 13]. It has been reported that DCE-MRI histogram analysis is effective in differentiating primary central nervous system lymphoma from atypical glioblastoma (GBM) and in detecting local tumor recurrence after treatment of head and neck squamous cell carcinoma [15, 16]
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