Diagnosis Of Parotid Gland Tumors Research Articles

Parotid Gland Tumors in Northern Greece: A 7-year Retrospective Study of 207 Patients.

<b>Introduction:</b> Parotid gland neoplasms represent a heterogenous group of tumors, either benign or malignant. The diagnosis and management of parotid gland tumors is complicated by their relative infrequency and their diverse biologic behavior. <br><b>Aim:</b> The aim of this study is to investigate the epidemiological characteristics, the recurrence rates and the surgical approach employed for parotid gland tumors in Northern Greece. <br><b>Material and methods:</b> This is a single-center retrospective study. All patients admitted to the ENT department of "G. Papanikolaou" General Hospital of Thessaloniki from January 2012 to June 2019 with the diagnosis of parotid gland tumor were included in the study. Patients with incomplete charts and patients that underwent revision surgeries were excluded. Chi-squared tests were used to assess the associations between variables. <br><b>Results:</b> A total of 207 patients with a mean age of 54.97 (range 16-91) were included in the study. Benign neoplasms accounted for 87.9% of the cases. Warthin's tumor was the most common neoplasm encountered, with an incidence of 46.8%, followed by pleomorphic adenoma (31.9%). There was a higher incidence of parotid gland tumors in males and smokers (P = 0.025, P = 0.001 respectively). The majority of the patients were treated with an extracapsular resection (60.4%) or with a partial superficial parotidectomy (22.6%). In 12 cases (5.7%), there was a recurrence of the lesion. The most common complications encountered were facial nerve injury, Frey's syndrome and hematoma formation. <br><b>Conclusions:</b> Parotid gland tumors are typically benign, non-aggressive tumors, more frequently seen in men than women. There is a positive association between smoking and parotid gland tumor development. Comprehensive information regarding recurrence and complication rates is presented.

Deep-Learning for Diagnosis of Parotid Gland Tumor on MR Images

Deep-Learning for Diagnosis of Parotid Gland Tumor on MR Images

Ultrasonography techniques in the preoperative diagnosis of parotid gland tumors - an updated review of the literature.

Preoperative diagnosis of parotid tumors plays a crucial role in selecting and planning the surgical treatment. Ultrasound (US) with its modern techniques can contribute to the differential diagnosis of parotid tumors. This paper aims to achieve a comprehensive review of the ultrasound techniques used in the differential diagnosis of parotid tumors, based on the latest literature data. Considering that most parotid gland tumors are located in the superficial lobe, US is frequently the first imaging technique used for the diagnosis of parotid tumors. Sonoelastography can provide additional data on the elasticity of parotid tumors, but there is an overlap between malignant and benign parotid tumors parameters. Contrast-enhanced ultrasound adds value to conventional ultrasound and allows a more complete characterization of parotid tumors. Many authors have reported promising results using contrast-enhanced ultrasound in the differential diagnosis of parotid tumors. Multiparametric ultrasound with a careful and systematic approach usually allows an accurate differential diagnosis of parotid tumors.

RETRACTED ARTICLE: The diagnostic value of combined dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in characterization of parotid gland tumors

BackgroundMRI is considered to be the imaging modality of choice in preoperative diagnosis of parotid gland tumors and differentiating benign from malignant ones. Recently, functional MR imaging sequences including dynamic contrast-enhanced magnetic resonance imaging (DCE- MRI) and diffusion-weighted imaging (DWI) have significantly contributed to the diagnosis of head and neck masses. The purpose of this study was to evaluate the diagnostic value of combined DCE-MRI and DWI in characterization of parotid gland tumors.ResultsThere was significant difference between benign and malignant parotid gland tumors as regard the type of time intensity curve (TIC) (P < 0.001). There was significant difference between pleomorphic adenoma (PMA) and malignant parotid gland tumors (MT) as regard mean ADC value (P = 0.046) and TTP (P = 0.002). There was no significant difference between Warthin’s tumor (WT) and malignant parotid gland tumors as regard the ADC value and TTP (P > 0.5); on the other hand, WT usually have high WR when compared with MT (P = 0.004). Combined use of DCE-MRI and DWI had 100% sensitivity, 90.5% specificity, and 93.3% accuracy in differentiating benign from malignant parotid gland tumors.ConclusionCombined use of DCE-MRI and DWI could result in high sensitivity, specificity, and diagnostic accuracy in characterization of parotid gland tumors.

Classification of parotid gland tumors by using multimodal MRI and deep learning.

Various MRI sequences have shown their potential to discriminate parotid gland tumors, including but not limited to T 2‐weighted, postcontrast T 1‐weighted, and diffusion‐weighted images. In this study, we present a fully automatic system for the diagnosis of parotid gland tumors by using deep learning methods trained on multimodal MRI images. We used a two‐dimensional convolution neural network, U‐Net, to segment and classify parotid gland tumors. The U‐Net model was trained with transfer learning, and a specific design of the batch distribution optimized the model accuracy. We also selected five combinations of MRI contrasts as the input data of the neural network and compared the classification accuracy of parotid gland tumors. The results indicated that the deep learning model with diffusion‐related parameters performed better than those with structural MR images. The performance results (n = 85) of the diffusion‐based model were as follows: accuracy of 0.81, 0.76, and 0.71, sensitivity of 0.83, 0.63, and 0.33, and specificity of 0.80, 0.84, and 0.87 for Warthin tumors, pleomorphic adenomas, and malignant tumors, respectively. Combining diffusion‐weighted and contrast‐enhanced T 1‐weighted images did not improve the prediction accuracy. In summary, the proposed deep learning model could classify Warthin tumor and pleomorphic adenoma tumor but not malignant tumor.

Cross-sectional imaging and cytologic investigations in the preoperative diagnosis of parotid gland tumors - An updated literature review.

An accurate preoperative diagnosis of parotid tumors is essential for the selection and planning of surgical treatment. Various modern cross-sectional imaging and cytologic investigations can support the differential diagnosis of parotid tumors. The aim of this study was to achieve a comprehensive and updated review of modern imaging and cytologic investigations used in parotid tumor diagnosis, based on the latest literature data. This literature review could serve as a guide for clinicians in selecting different types of investigations for the preoperative differential diagnosis of parotid tumors. Magnetic resonance imaging (MRI) with its dynamic and advanced sequences is the first-line imaging investigation used in differentiating parotid tumors. Computed tomography (CT) and positron emission tomography (PET)-CT provide limited indications in differentiating parotid tumors. Fine needle aspiration biopsy and core needle biopsy can contribute with satisfactory results to the cytological diagnosis of parotid tumors. Dynamic MRI with its dynamic contrast-enhanced and diffusion-weighted sequences provides the best accuracy for the preoperative differential diagnosis of parotid tumors. CT allows the best evaluation of bone invasion, being useful when MRI cannot be performed, and PET-CT has value in the follow-up of cancer patients. The dual cytological and imaging approach is the safest method for an accurate differential diagnosis of parotid tumors.

Research on the Practical Classification and Privacy Protection of CT Images of Parotid Tumors based on ResNet50 Model

Parotid gland disease is one of the main causes of facial paralysis, and parotid gland tumor is a great threat to the life of patients. The main diagnostic way of parotid diseases is imaging examination, so it is of great significance for the rapid classification of parotid image. In conclusion, 51 CT images of parotid malignant tumors and 101 CT images of parotid pleomorphic adenomas are selected as the research data set, and an intelligent and efficient machine learning algorithm is proposed for the practical classification of parotid images. At the same time, this paper also explores the privacy protection of medical images. Based on the advantages of deep learning, such as no feature engineering, strong adaptability and easy conversion, ResNet50 model in deep learning is selected as the basic network framework to achieve the purpose of rapid classification of parotid CT images. This is the first time that ResNet50 classification algorithm is applied to the practical classification of parotid tumor CT images. The results show that the accuracy of the test set converges to 90% when the model is iterated 1000 times, which also proves that this study has certain practical significance and application value for the auxiliary diagnosis of parotid gland tumor and other head and neck tumors. Simultaneously, this paper also explores the application of desensitization strategy in CT images of parotid tumors, which improves the performance of the model and also greatly protects the privacy of patients, and has a good application prospect in medical big data.

Role of Fine Needle Aspiration Cytology in the Diagnosis of Parotid Gland Tumors: Analysis of 193 Cases.

Introduction Parotid gland tumors include a wide variety of inflammatory and neoplastic diseases. The majority of these tumors are benign (80%), which usually require superficial parotidectomy, while the incidence of malignant tumors is lower (20%), requiring more radical surgery with or without neck dissection. The diagnosis cannot be established on the basis of clinical history and simple physical examination and requires complementary diagnostic methods. Fine needle aspiration cytology (FNAC) guided by ultrasound is a widely used diagnostic tool to evaluate parotid swellings. Objective To determine the sensitivity, specificity, positive and negative predictive values and diagnostic accuracy of FNAC in the diagnosis of parotid gland tumors. Methods A retrospective chart review of 193 patients who underwent preoperative FNAC and parotidectomy at the Aga Khan University Hospital, Karachi, Pakistan, from the period of January 2000 to December 2015 was performed. Results Out of 193 patients undergoing parotidectomy, 110 (57%) were males and 83 (43%) were females, the mean age being 48.21 and 43.76 years old, respectively. The mean duration of the symptoms was 41.33 months, and the most common symptom was preauricular swelling present in all patients, followed by pain, which was present in 29 patients (15%) and facial nerve weakness in 6 patients (3.1%). Fine needle aspiration cytology was performed preoperatively and the results were compared with the final histopathology, which showed sensitivity of 88.9%, specificity of 97.9%, positive predictive value of 93%, negative predictive value of 96.7% and diagnostic accuracy of 95.8%. Conclusion Our results suggest that FNAC is relatively an accurate method for preoperative diagnosis of parotid swelling and can prove to be a valuable tool for preoperative counseling of the nature of the disease and prognosis.

Multiparametric Magnetic Resonance Imaging for the Diagnosis and Differential Diagnosis of Parotid Gland Tumors.

The majority of salivary gland tumors occur in the parotid glands. Characterization (ie, benign or malignant, and histological type), location (deep or superficial), and invasion into the neighboring tissues of parotid tumors determine preoperative treatment planning. MRI gives more information than other imaging methods about the internal structure, localization, and relationship with other tissues of parotid tumors. Functional MRI methods (diffusion-weighted imaging, dynamic contrast-enhanced MRI, perfusion-weighted MRI, MR spectroscopy, etc.) have been increasingly used recently to increase the power of radiologists to characterize the tumors. Although they increase the workload of radiologists, the combined use of functional MRI methods improves accuracy in the differentiation of the tumors. There are a wide range of studies in the literature dealing with the combined use of different functional imaging methods in combination with conventional sequences. The aim of the present review is to evaluate conventional and functional/advanced MR methods, as well as multiparametric MRI applications combining them in the diagnosis of parotid gland tumors. Evidence Level: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;52:11-32.

The differential diagnosis of parotid gland tumors with high-resolution ultrasound in otolaryngological practice

The aim of the study is to define the utility of ultrasound (US) in differentiating benign from malignant parotid tumors as well as pleomorphic adenomas (PA) from monomorphic adenoma (MA). Seventy-two consecutive parotid gland tumors were analysed with high-resolution ultrasonography (12 MHz) with color Doppler imagining. The histopathological diagnosis was confirmed after parotidectomy for each lesion. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) for the US were established. Receiver operating characteristic curves were constructed to determine the predictive values of echogenicity, heterogeneity, and vascularity on color Doppler. Area under the curve (AUC) was calculated for each parameter considered. The analysed material included 27 MA, 26 PA, 1 basal cell adenoma, 8 inflammatory conditions, and 10 malignant neoplasms. The sensitivity, specificity, and accuracy of US in differentiation of malignant from benign lesions in the parotid gland were 60, 95.2, and 90.3%, respectively. The predictive values were: PPV 66.8% and NPV 93.6%. Differentiating diagnoses between PA and MA with US resulted in a sensitivity of 61.5%, specificity of 81.5%, and accuracy of 73.1%. The predictive values were: PPV 50% and NPV 68.8%, respectively. For distinguishing malignant from benign tumors, the highest AUC values noted were for heterogeneity and vascularization (0.8 and 0.743, respectively). The AUC values were the highest for hypoechogenicity and vascularization in separating PA from MA (0.718 and 0.685, respectively).

The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours.

The aim of this study was to determine the value of combining conventional MRI, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE)-MRI in diagnosing solid neoplasms in the parotid gland. A total of 148 subjects (101 subjects with benign and 47 subjects with malignant tumours) were evaluated with conventional MRI, DWI and DCE-MRI prior to surgery and pathologic verification. The items observed with conventional MRI included the shape, capsule and signal intensity of parotid masses. The apparent diffusion coefficient (ADC) was calculated from DWI that was obtained with a b-factor of 0 and 1000 s mm-2. A time-intensity curve (TIC) was obtained from DCE-MRI. There were significant differences (p < 0.01) in the shape, capsule, ADC and TIC between benign and malignant parotid tumours. Irregular neoplasms without a capsule, ADC <1.12 × 10-3 mm2 s-1 and a plateau enhancement pattern were valuable parameters for predicting malignant neoplasms. A combination of all of these parameters yielded sensitivity, specificity, accuracy, positive-predictive value and negative-predictive value of 85.1%, 94.1%, 91.2%, 87.0% and 93.1%, respectively. A combined analysis using conventional MRI, DWI and DCE-MRI is helpful in distinguishing benign from malignant tumours in the parotid gland.

Differential Diagnosis of Parotid Gland Tumors: Role of Shear Wave Elastography.

Aim To create a predictive score for the discrimination between benign and malignant parotid tumors using elastographic parameters and to compare its sensitivity and specificity with standard ultrasound. Methods A total of 124 patients with parotid gland lesions for whom surgery was planned were examined using conventional ultrasound, Doppler examination, and shear wave elastography. Results of the examinations were compared with those ones of histology. Results There were 96 benign and 28 malignant lesions in our cohort. Blurred tumor margin alone proved to be an excellent predictor of malignancy with the sensitivity of 79% and specificity of 97%. Enlarged cervical lymph nodes, tumor vascularisation, microcalcifications presence, homogeneous echogenicity, and bilateral occurrence also discriminated between benign and malignant tumors. However, their inclusion in a predictive model did not improve its performance. Elastographic parameters (the stiffness maxima and minima ratio being the best) also exhibited significant differences between benign and malignant tumors, but again, their inclusion did not significantly improve the predictive power of the blurred margin classifier. Conclusion Even though elastography satisfactorily distinguishes benign from malignant lesions on its own, it hardly provides any additional value in evaluation of biological character of parotid gland tumors when used as an adjunct to regular ultrasound examination.

The Role of Fine Needle Aspiration in the Diagnosis of Parotid Gland Tumors: Correlation With Preoperative Computerized Tomography Tumor Size.

The role of fine needle aspiration cytology (FNAC) in the diagnosis of parotid gland masses is still controversial, regarding its sensitivity and specificity that vary between 41% and 100% and between 86% and 100% respectively.The aim of this study was to identify the specificity and sensitivity of FNAC of parotid gland tumors in relation to the tumor size as characterized preoperatively by computer tomography. The medical files of 79 patients whom were referred to the MaxilloFacila Surgery Department, Rambam medical center, over a 10.5-year period (2000-2010) were analyzed retrospectively.The extensity of the operation was determined by the location of the tumor as presented in computed tomography (CT) radiography, and preoperative FNAC examination.The majority of the masses were located in the superficial lobe (88.52%), and only 11.48% of the patients were located in the deep lobe (8:1 ratio). FNAC results were nondiagnostic in 7 patients (8.86%), 62 patients were diagnosed as inflammatory and benign lesion in (78.48%), malignant tumors were diagnosed in 10 patients (12.65%).The sensitivity in our study was 90%, the specificity was 98%, positive predictive value was 90%, negative predictive value was 98%, and diagnostic accuracy was 88%. The positive predictive value was 90%, the negative predictive value was 98%.Analyzing the effect of the preoperative CT size upon the accuracy of the FNAC diagnosis, we found that lesion with preoperative CT size greater than 24 mm has a more accurate FNAC result (P = 0.034).

Preoperative Diagnostic Strategy for Parotid Gland Tumors Using Diffusion-Weighted MRI and Technetium-99m Pertechnetate Scintigraphy: A Prospective Study.

ObjectiveFine needle aspiration cytology (FNAC) for diagnosis of a parotid gland tumor is widely used but its sensitivity is low and non-diagnostic rate is relatively high. In contrast, core needle biopsy (CNB) has a higher sensitivity and lower rate of sampling errors but has a higher risk of injury to adjacent organs such as facial nerve than FNAC. Screening of patients with parotid gland tumors to identify cases of pleomorphic adenoma (PA) and Warthin tumor (WT) may allow CNB to be confined to patients without PA and WT. We established an algorithm for preoperative diagnosis and management of parotid gland tumor using diffusion-weighted MRI and 99mTc pertechnetate scintigraphy. This algorithm was developed with the goal of maximal reduction of the number of patients in whom CNB is required. The purpose of the study is to validate our algorithm prospectively.MethodsA prospective study was conducted in 71 cases who were newly diagnosed with parotid gland tumor and 53 cases were enrolled in the study. In the algorithm, PA (high apparent diffusion coefficient (ADC) mean≥1.5×10−3 mm2/s) and non-PA (low ADCmean<1.5×10−3 mm2/s) cases are first distinguished based on the ADCmean on diffusion-weighed MRI. Second, among suspected non-PA cases, WT and non-WT are distinguished using technetium-99m pertechnetate scintigraphy. CNB is then performed only in probable non-PA and non-WT cases.ResultsAlthough CNB was only required in 40% (21/53) of all cases, we made a preoperative histopathological diagnosis with an accuracy of 87% (46/53) and we correctly diagnosed whether a tumor was benign or malignant with an accuracy of 96% (51/53). Preoperative surgical planning had to be changed during surgery in only one case (2%)ConclusionsOur algorithm is valuable in terms of clinical practice with highly potential for preoperative diagnosis and with less risk of CNB procedure.

Label-free blood serum detection by using surface-enhanced Raman spectroscopy and support vector machine for the preoperative diagnosis of parotid gland tumors.

BackgroundIt is difficult for the parotid gland neoplasms to make an accurate preoperative diagnosis due to the restriction of biopsy in the parotid gland neoplasms. The aim of this study is to apply the surface-enhanced Raman spectroscopy (SERS) method for the blood serum biochemical detection and use the support vector machine for the analysis in order to develop a simple but accurate blood serum detection for preoperative diagnosis of the parotid gland neoplasms.MethodsThe blood serums were collected from four groups: the patients with pleomorphic adenoma, the patients with Warthin’s tumor, the patients with mucoepidermoid carcinoma and the volunteers without parotid gland neoplasms. Au nanoparticles (Au NPs) were mixed with the blood serum as the SERS active nanosensor to enhance the Raman scattering signals produced by the various biochemical materials and high quality SERS spectrum were obtained by using the Raman microscope system. Then the support vector machine was utilized to analyze the differences of the SERS spectrum from the blood serum of different groups and established a diagnostic model to discriminate the different groups.ResultsIt was demonstrated that there were different intensities of SERS peaks assigned to various biochemical changes in the blood serum between the parotid gland tumor groups and normal control group. Compared with the SERS spectra of the normal serums, the intensities of peaks assigned to nucleic acids and proteins increased in the SERS spectra of the parotid gland tumor serums, which manifested the differences of the biochemical metabolites in the serum from the patients with parotid gland tumors. When the leave-one-sample-out method was used, support vector machine (SVM) played an outstanding performance in the classification of the SERS spectra with the high accuracy (84.1 % ~ 88.3 %), sensitivity (82.2 % ~ 97.4 %) and specificity (73.7 % ~ 86.7 %). Though the accuracy, sensitivity and specificity decreased in the leave-one-patient-out cross validation, the mucoepidermoid carcinoma was still easier to diagnose than other tumors.DiscussionThe specific molecular differences of parotid gland tumors and normal serums were significantly demonstrated through the comparison between the various SERS spectra.But compared with the serum SERS spectra reported in the other studies, some differences exist between the spectra in this study and the ones reported in the lietratures. These differences may result from the various nano-particles, the different preparation of serum and equipment parameters, and we could need a further research to find an exact explanation.Based on the SERS spectra of the serum samples, SVM have shown a giant potential to diagnose the parotid gland tumors in our preliminary study. However, different cross validaiton methods could effect the accuracy and a further study involing a great number of samples should be needed.ConclusionsThis exploratory research demonstrated the great potential of SERS combined with SVM into a non-invasive clinical diagnostic method for preoperative diagnosis of parotid gland tumors. And the internal relation between the spectra and patients should be established in the further study.

Comparison of cross-sectional radiological with fine needle aspiration biopsy and histopathological examination in differential diagnosis of parotid gland tumors

Comparison of cross-sectional radiological with fine needle aspiration biopsy and histopathological examination in differential diagnosis of parotid gland tumors

An intraoperative diagnosis of parotid gland tumors using Raman spectroscopy and support vector machine

The preoperative and intraoperative diagnosis of parotid gland tumors is difficult, but is important for their surgical management. In order to explore an intraoperative diagnostic method, Raman spectroscopy is applied to detect the normal parotid gland and tumors, including pleomorphic adenoma, Warthin’s tumor and mucoepidermoid carcinoma. In the 600–1800 cm−1 region of the Raman shift, there are numerous spectral differences between the parotid gland and tumors. Compared with Raman spectra of the normal parotid gland, the Raman spectra of parotid tumors show an increase of the peaks assigned to nucleic acids and proteins, but a decrease of the peaks related to lipids. Spectral differences also exist between the spectra of parotid tumors. Based on these differences, a remarkable classification and diagnosis of the parotid gland and tumors are carried out by support vector machine (SVM), with high accuracy (96.7~100%), sensitivity (93.3~100%) and specificity (96.7~100%). Raman spectroscopy combined with SVM has a great potential to aid the intraoperative diagnosis of parotid tumors and could provide an accurate and rapid diagnostic approach.

New diagnostic markers in salivary gland tumors

Parotid gland tumors are a rare and heterogeneous entity. Molecular markers are sparse. The aim of the study was to identify new diagnostic markers in benign and malignant salivary tumors. A tissue microarray was constructed with 158 tumor samples. Expression of 21 tumor antigens involved in tumor cell survival and known for prognostic potential was assessed immunohistochemically in all parotid gland samples. CEA, Cox-1, Cox-2, Sigma, beta-Catenin, WISP-1 and PDGF-beta were differently regulated in benign and malignant parotid tumors. Subsequently, these seven proteins entered the step-wise logistic regression analysis. As a second step, we defined a score for differentiating benign versus malignant parotid lesions: 4*CEA+15*Cox-1+4*Cox-2+4*Sigma+3*PDGF-beta+10*beta-Catenin+14*Wisp1. Sensitivity and specificity of 94 and 83% were reached. Besides routine hematoxylin and eosin staining, definition of new diagnostic markers and subsequently a new diagnostic score are an attempt to create an additional tool for the diagnosis of parotid gland tumors.

Diagnostic Accuracy of Fine Needle Aspiration Cytology in Parotid Lesions

Objective. Histopathology of parotid gland tumors is extremely varied and complex due to heterogeneous cellular composition. Preoperative diagnostic tools include fine needle aspiration cytology, the role of which remains controversial. The aim of this paper is to evaluate the usefulness and accuracy of fine needle aspiration cytology (FNAC) in the diagnosis of parotid gland tumors. Methods. We retrospectively reviewed charts of 129 patients who underwent parotidectomy for parotid lesions at Aga Khan University Hospital from 2002 to 2010. We compared the results of preoperative FNAC with final histopathological diagnosis. Results. Concordance with histological results was observed in 86%, specificity was 98%, sensitivity was 84%, and diagnostic accuracy was 94%. Conclusion. Our results demonstrate that preoperative cytology in parotid lesions is fairly accurate and useful in diagnosing benign from malignant and in planning appropriate approach for treatment.

Interest of diffusion-weighted and gadolinium-enhanced dynamic MR sequences for the diagnosis of parotid gland tumors

This study aimed to evaluate the value of diffusion-weighted imaging (DWI) and gadolinium-enhanced dynamic magnetic resonance imaging (MRI) for differentiating benign and malignant parotid gland tumors, and for characterizing the various histological types (pleomorphic adenoma, and Warthin's and malignant tumors). This retrospective study involved 60patients with suspected parotid gland tumors (mean age: 59.4years), and was carried out from April2005 to February2008. All had undergone pathological examination. All MRI examinations were performed using the Siemens Magnetom Avanto 1.5T MRI system. Non-enhanced T1-weighted (T1W), gadolinium-enhanced fat-suppressed T1W and T2-weighted (T2W) images were obtained for all 60patients, with diffusion-weighted echoplanar imaging (DW-EPI) and apparent diffusion coefficient (ADC) evaluation in 59patients, and gadolinium-enhanced dynamic MRI sequences in 51patients. Interpretation was carried out by two experienced radiologists (the first evaluation used T1W, gadolinium-enhanced fat-suppressed T1W and T2W images; the second evaluation used T1W, T2W, DWI and dynamic MRI) and, for each case, the benign/malignant nature of the tumor and its histological type were determined. After the second reading, increases were noted in sensitivity, specificity, malignant positive predictive value (PPV) and negative predictive value (NPV), as well as in accuracy (90-100% for the first observer, and 90-97% for the second observer). Interobserver reliability also showed a significant increase from the first to the second reading (kappa=0.63 to 0.87, respectively). Gadolinium-enhanced dynamic MRI and DW-EPI with ADC evaluation improved the performance of MRI in distinguishing between benign and malignant parotid gland tumors, and characterizing the different histological types of benign tumors (pleomorphic adenoma and Warthin's), thus leading to greater consensus in interpretation of the images.