Diagnostic value of CT perfusion imaging for parotid neoplasms

Evaluation of Quantitative Dual-Energy Computed Tomography Parameters for Differentiation of Parotid Gland Tumors

RATIONALE AND OBJECTIVES

To assess the diagnostic performance of quantitative parameters from dual-energy CT (DECT) in differentiating parotid gland tumors (PGTs).

MATERIALS AND METHODS

101 patients with 108 pathologically proved PGTs were enrolled and classified into four groups: pleomorphic adenomas (PAs), warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). Conventional CT attenuation and DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), electron density (Rho), double energy index (DEI), and the slope of the spectral Hounsfield unit curve (λHU), were obtained and compared between benign tumors (BTs) and MTs, and further compared among the four subgroups. Logistic regression analysis was used to assess the independent parameters and the receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance.

RESULTS

Attenuation, Zeff, DEI, IC, NIC, and λHU in the arterial phase (AP) and venous phase (VP) were higher in MTs than in BTs (p < 0.001-0.047). λHU in VP and Zeff in AP were independent predictors with an area under the curve (AUC) of 0.84 after the combination. Furthermore, attenuation, Zeff, DEI, IC, NIC, and λHU in the AP and VP of MTs were higher than those of PAs (p < 0.001-0.047). Zeff and NIC in AP and λHU in VP were independent predictors with an AUC of 0.93 after the combination. Attenuation and Rho in the precontrast phase; attenuation, Rho, Zeff, DEI, IC, NIC, and λHU in AP; and the Rho in the VP of PAs were lower than those of WTs (p < 0.001-0.03). Rho in the precontrast phase and attenuation in AP were independent predictors with an AUC of 0.89 after the combination. MTs demonstrated higher Zeff, DEI, IC, NIC, and λHU in VP and lower Rho in the precontrast phase compared with WTs (p < 0.001-0.04); but no independent predictors were found.

CONCLUSION

DECT quantitative parameters can help to differentiate PGTs.

Deep-Learning-Based Automatic Segmentation of Parotid Gland on Computed Tomography Images

This study aims to develop an algorithm for the automatic segmentation of the parotid gland on CT images of the head and neck using U-Net architecture and to evaluate the model's performance. In this retrospective study, a total of 30 anonymized CT volumes of the head and neck were sliced into 931 axial images of the parotid glands. Ground truth labeling was performed with the CranioCatch Annotation Tool (CranioCatch, Eskisehir, Turkey) by two oral and maxillofacial radiologists. The images were resized to 512 × 512 and split into training (80%), validation (10%), and testing (10%) subgroups. A deep convolutional neural network model was developed using U-net architecture. The automatic segmentation performance was evaluated in terms of the F1-score, precision, sensitivity, and the Area Under Curve (AUC) statistics. The threshold for a successful segmentation was determined by the intersection of over 50% of the pixels with the ground truth. The F1-score, precision, and sensitivity of the AI model in segmenting the parotid glands in the axial CT slices were found to be 1. The AUC value was 0.96. This study has shown that it is possible to use AI models based on deep learning to automatically segment the parotid gland on axial CT images.

Advantages of contrast-enhanced CT combined with DCE-MRI in identifying malignant parotid tumor

OBJECTIVE

To study the value of single and combined application of contrast-enhanced computerized tomography (CT) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in diagnosing parotid tumors.

METHODS

In this retrospective study, 82 patients with parotid gland mass who received contrast-enhanced CT and DCE-MRI detection in The First People's Hospital of Huzhou from March 2018 to March 2022 were selected as study subjects. The nature of the parotid tumor was pathologically examined following the surgery. According to the pathological diagnosis results, these patients were divided into a benign group (n=59) and a malignant group (n=23). All patients underwent contrast-enhanced CT and DCE-MRI examinations. The diagnostic accuracy rates of contrast-enhanced CT, DCE-MRI and the joint application were compared. The CT or MRI images of benign and malignant parotid tumors were compared. The correlation of parotid cancer with the imaging features was analyzed. Diagnostic efficiency of contrast-enhanced CT, DCE-MRI and joint application for parotid cancer was assessed by receiver operating characteristic curve.

RESULTS

In terms of diagnostic accuracy, there was a significant difference between contrast-enhanced CT combined with DCE-MRI and contrast-enhanced CT alone (95.12% vs. 81.71%, P<0.001), and between the joint application and DCE-MRI alone (95.12% vs. 86.58%, P=0.004). Results of contrast-enhanced CT revealed statistical differences in tumor boundary, tumor size, calcification and cystic degeneration between benign and malignant tumors (P<0.05), but no obvious difference in lymph node enlargement between the two groups. MRI results showed that there were differences in the DCE-MRI time-signal intensity curve and ADC value between benign and malignant tumors (P<0.05). Correlation analysis results showed that the malignant tumor was negatively correlated with tumor boundary, calcification, cystic degeneration and ADC values, and it was positively correlated with DCE-MRI time-signal intensity curve and tumor size (P<0.05). Analysis of diagnostic efficacy showed that contrast-enhanced CT combined with DCE-MRI were significantly better than contrast-enhanced CT alone in terms of sensitivity and specificity (P<0.05). Moreover, the sensitivity of the joint application was also higher than that of MRI alone, while no obvious difference was found for specificity between joint application and MRI alone. The areas under the curve of contrast-enhanced CT combined with DCE-MRI in diagnosing malignant parotid tumor was remarkably greater than that of CT or MRI alone (P<0.05).

CONCLUSION

Contrast-enhanced CT combined with DCE-MRI can significantly improve the diagnostic accuracy, sensitivity and specificity for malignant parotid tumor, and the joint application was able to point out the direction of targeted surgical treatment plans.

Distinguishing Parotid Polymorphic Adenoma and Warthin Tumor Based on the CT Radiomics Nomogram: A Multicenter Study

RATIONALE AND OBJECTIVES

To develop, validate, and test a comprehensive radiomics prediction model to distinguish parotid polymorphic adenomas (PAs) and warthin tumors (WTs) using clinical data and enhanced computed tomography (CT) from a multicenter cohort.

MATERIALS AND METHODS

A total of 267 patients with PAs (n =172) or WTs (n = 95) from two hospitals were randomly divided into training (n =188) and validation (n =79) datasets. Radiomics features were extracted from the enhanced CT (arterial phase) followed by dimensionality reduction. Clinical and CT features were combined to establish a prediction model. A radiomics nomogram was constructed by combining RadScore and clinical factors. Moreover, an independent dataset of 31 patients from a third hospital was employed to test the model. Thus, the performance of the nomogram, radiomics signature, and clinical models was evaluated on the training, validation, and the independent testing datasets. Receiver operating characteristic (ROC) curves were used to compare the performance, and decision curve analysis (DCA) was used to evaluate the clinical effectiveness of the model.

RESULTS

A total of 15 radiomics features were selected from CT data as the imaging markers to generate RadScores, and demographics or clinical data like age, sex, and smoking factors combined with RadScores were used to distinguish PAs and WTs based on multivariate logistic regression analyses. The results showed that radiomics nomograms combining clinical factors and RadScores provided satisfactory predictive values for distinguishing PAs from WTs, with areas under ROC curves (AUC) of 0.979, 0.922, and 0.903 for the training, validation, and the independent testing datasets, respectively. Decision curve analysis revealed that the radiomics nomogram outperformed the clinical factor models in terms of accuracy and effectiveness.

CONCLUSION

CT-based radiomics nomograms combining RadScores and clinical factors can be used to identify PAs and WTs, which may help tumor management by clinicians.

Influence of post-label delay time on the performance of 3D pseudo-continuous arterial spin labeling magnetic resonance imaging in the characterization of parotid gland tumors

OBJECTIVE

To evaluate the influence of post-label delay times (PLDs) on the performance of 3D pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging for characterizing parotid gland tumors and to explore the optimal PLDs for the differential diagnosis.

MATERIALS AND METHOD

Fifty-eight consecutive patients with parotid gland tumors were enrolled, including 33 patients with pleomorphic adenomas (PAs), 16 patients with Warthin's tumors (WTs), and 9 patients with malignant tumors (MTs). 3D pCASL was scanned for each patient five times, with PLDs of 1025 ms, 1525 ms, 2025 ms, 2525 ms, and 3025 ms. Tumor blood flow (TBF) was calculated, and compared among different PLDs and tumor groups. Performance of TBF at different PLDs was evaluated using receiver operating characteristic analysis.

RESULTS

With an increasing PLD, TBF tended to gradually increase in PAs (p < 0.001), while TBF tended to slightly increase and then gradually decrease in WTs (p = 0.001), and PAs showed significantly lower TBF than WTs at all 5 PLDs (p < 0.05). PAs showed significantly lower TBF than MTs at 4 PLDs (p < 0.05), except at 3025 ms (p = 0.062). WTs showed higher TBF than MTs at all 5 PLDs; however, differences did not reach significance (p > 0.05). Setting a TBF of 64.350 mL/100g/min at a PLD of 1525 ms, or a TBF of 23.700 mL/100g/min at a PLD of 1025 ms as the cutoff values, optimal performance could be obtained for differentiating PAs from WTs (AUC = 0.905) or from MTs (AUC = 0.872).

CONCLUSIONS

Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice.

KEY POINTS

• With 5 different PLDs, 3D pCASL can reflect the variation of blood flow in parotid gland tumors. • 3D pCASL is useful for characterizing PAs from WTs or MTs. • Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice.

The Clinical Characteristics and CT Findings of Parotid and Submandibular Gland Tumours

Objective

To investigate the clinical characteristics and CT findings of parotid and submandibular gland tumours. Materials and methods. From May 2017 to April 2020, all patients with clinically proven parotid and submandibular gland enlargement and palpable masses underwent CT examinations. All patients were confirmed by pathology after surgery. The clinical characteristics and CT features were observed and evaluated. The mean density values before and after enhancement were measured and analyzed. The chi-square test, one-way ANOVA, and Student's t-test were used.

Results

Ninety-four patients with a total of 94 unilateral tumours in the parotid and submandibular glands were enrolled, including 38 pleomorphic adenomas (PAs), 27 Warthin's tumours (WTs), and 29 malignant tumours (MTs). The majority of the PAs (28/38) and MTs (23/29) were located in the parotid gland; the others were located in the submandibular gland. All the WTs were in the parotid gland. The most common benign tumours of the parotid gland were PAs (28/38, 73.7%) and WTs (27/27, 100%), and the most common MTs were mucoepidermoid carcinoma, acinic cell carcinoma, and squamous cell carcinoma (4/29, 13.8%). The most common benign and malignant tumours in the submandibular gland were PAs (10/38, 26.3%) and ductal adenocarcinomas (3/4, 75%). The majority of PA patients (28/38) were female, compared with WT (2/27) (P < 0.001) and malignant tumour patients (10/29) (P < 0.01). A significant difference was also found between WTs and MTs in female patients (P < 0.05). The mean age of PA patients was 43.4 ± 12.1 years, which was lower than that of WTs (62.1 ± 11.7) and MTs (58 ± 14.18) (P < 0.001, P < 0.001, and P=0.244, respectively). On CT imaging, the mean diameter of the PAs and WTs was significantly smaller than that of the MTs (P=0.001 and P < 0.001), and no difference was observed between the PAs and WTs (P=0.275). In the parotid gland, the superficial lobe was more frequently involved than the deep lobe (PAs, 22 : 6; WTs, 17 : 10; and MTs, 15 : 8). The majority of PAs and WTs demonstrated round shapes (25/38, 19/27) and were well defined (30/38, 24/27); by contrast, most MTs were lobulated, irregular shapes (24/29), and ill defined (25/29). On plain CT, the PAs were usually homogeneous, while MTs were frequently heterogeneous, with more necrosis, larger cystic areas, and more haemorrhage or calcification. The mean CT values of PAs, WTs, and MTs were 39.2 ± 3.9 HU, 39.1 ± 3.0 HU, and 37.6 ± 3.1 HU (P > 0.05), respectively. On contrast CT, the WTs were significantly enhanced compared with MTs and PAs, with mean CT values of 53.5 ± 4.0 HU, 84.4 ± 6.0 HU, and 65.2 ± 3.8 HU, respectively (all P < 0.001). The mean CT value changes for PAs, WTs, and MTs (∆) were 14.4 ± 3.0 HU, 45.3 ± 4.5 HU, and 27.7 ± 2.5 HU, respectively. Significant differences were observed between ∆_PAs and ∆_WTs, ∆_PAs and ∆_MTs, and ∆_WTs and ∆_MTs (all P < 0.001).

Conclusion

Parotid and submandibular gland tumours have some typical clinical characteristics and CT findings, and plain and early contrast-phase CT combined with clinical parameters may be helpful for diagnosis.

The Role of Preoperative Computed Tomography Radiomics in Distinguishing Benign and Malignant Tumors of the Parotid Gland

Objective

This study aimed to develop and validate an integrated prediction model based on clinicoradiological data and computed tomography (CT)-radiomics for differentiating between benign and malignant parotid gland (PG) tumors via multicentre cohorts.

Materials and Methods

A cohort of 87 PG tumor patients from hospital #1 who were diagnosed between January 2017 and January 2020 were used for prediction model training. A total of 378 radiomic features were extracted from a single tumor region of interest (ROI) of each patient on each phase of CT images. Imaging features were extracted from plain CT and contrast-enhanced CT (CECT) images. After dimensionality reduction, a radiomics signature was constructed. A combination model was constructed by incorporating the rad-score and CT radiological features. An independent group of 38 patients from hospital #2 was used to validate the prediction models. The model performances were evaluated by receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) was used to evaluate the clinical effectiveness of the models. The radiomics signature model was constructed and the rad-score was calculated based on selected imaging features from plain CT and CECT images.

Results

Analysis of variance and multivariable logistic regression analysis showed that location, lymph node metastases, and rad-score were independent predictors of tumor malignant status. The ROC curves showed that the accuracy of the support vector machine (SVM)-based prediction model, radiomics signature, location and lymph node status in the training set was 0.854, 0.772, 0.679, and 0.632, respectively; specificity was 0.869, 0.878, 0.734, and 0.773; and sensitivity was 0.731, 0.808, 0.723, and 0.742. In the test set, the accuracy was 0.835, 0.771, 0.653, and 0.608, respectively; the specificity was 0.741, 0.889, 0.852, and 0.812; and the sensitivity was 0.818, 0.790, 0.731, and 0.716.

Conclusions

The combination model based on the radiomics signature and CT radiological features is capable of evaluating the malignancy of PG tumors and can help clinicians guide clinical tumor management.

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.

Intravoxel Incoherent Motion Magnetic Resonance Imaging for Assessing Parotid Gland Tumors: Correlation and Comparison with Arterial Spin Labeling Imaging

Objective

To compare and correlate the findings of intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging and arterial spin labeling (ASL) imaging in characterizing parotid gland tumors.

Materials and Methods

We retrospectively reviewed 56 patients with parotid gland tumors evaluated by MR imaging. The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and fraction of perfusion (f) values of IVIM imaging and tumor-to-parotid gland signal intensity ratio (SIR) on ASL imaging were calculated. Spearman rank correlation coefficient, chi-squared, Mann-Whitney U, and Kruskal-Wallis tests with the post-hoc Dunn-Bonferroni method and receiver operating characteristic curve assessments were used for statistical analysis.

Results

Malignant parotid gland tumors showed significantly lower D than benign tumors (p = 0.019). Within subgroup analyses, pleomorphic adenomas (PAs) showed significantly higher D than malignant tumors (MTs) and Warthin's tumors (WTs) (p < 0.001). The D* of WTs was significantly higher than that of PAs (p = 0.031). The f and SIR on ASL imaging of WTs were significantly higher than those of MTs and PAs (p < 0.05). Significantly positive correlation was found between SIR on ASL imaging and f (r = 0.446, p = 0.001). In comparison with f, SIR on ASL imaging showed a higher area under curve (0.853 vs. 0.891) in discriminating MTs from WTs, although the difference was not significant (p = 0.720).

Conclusion

IVIM and ASL imaging could help differentiate parotid gland tumors. SIR on ASL imaging showed a significantly positive correlation with f. ASL imaging might hold potential to improve the ability to discriminate MTs from WTs.

Improving the diagnosis of common parotid tumors via the combination of CT image biomarkers and clinical parameters

Background

Our study aims to develop and validate diagnostic models of the common parotid tumors based on whole-volume CT textural image biomarkers (IBMs) in combination with clinical parameters at a single institution.

Methods

The study cohort was composed of 51 pleomorphic adenoma (PA) patients and 42 Warthin tumor (WT) patients. Clinical parameters and conventional image features were scored retrospectively and textural IBMs were extracted from CT images of arterial phase. Independent-samples t test or Chi-square test was used for evaluating the significance of the difference among clinical parameters, conventional CT image features, and textural IBMs. The diagnostic performance of univariate model and multivariate model was evaluated via receiver operating characteristic (ROC) curve and area under ROC curve (AUC).

Results

Significant differences were found in clinical parameters (age, gender, disease duration, smoking), conventional image features (site, maximum diameter, time-density curve, peripheral vessels sign) and textural IBMs (mean, uniformity, energy, entropy) between PA group and WT group (P<0.05). ROC analysis showed that clinical parameter (age) and quantitative textural IBMs (mean, energy, entropy) were able to categorize the patients into PA group and WT group, with the AUC of 0.784, 0.902, 0.910, 0.805, respectively. When IBMs were added in clinical model, the multivariate models including age-mean and age-energy performed significantly better than the univariate models with the improved AUC of 0.940, 0.944, respectively (P<0.001).

Conclusions

Both clinical parameter and CT textural IBMs can be used for the preoperative, noninvasive diagnosis of parotid PA and WT. The diagnostic performance of textural IBM model was obviously better than that of clinical model and conventional image model in this study. While the multivariate model consisted of clinical parameter and textural IBM had the optimal diagnostic performance, which would contribute to the better selection of individualized surgery program.

Perfusion Computed Tomography Scan Imaging in Differentiation of Benign from Malignant Parotid Lesions

Introduction  The most common site of salivary gland tumors is the parotid gland. Computed tomography (CT), magnetic resonance imaging (MRI), and sonography are imaging modalities to differentiate benign from malignant parotid tumors.

Objective  The aim of this study is the evaluation of the diagnostic value of perfusion CT for differentiating histological categorization of benign and malignant parotid tumors.

Methods  A total of 29 patients with parotid neoplasms were enrolled in this study. Mean age and all CT perfusion variables (gradient and permeability, blood flow [BF], blood volume [BV], mean transit time [MTT], permeability surface [PS], maximum intensity projection [MIP], time-density curve [TDC], and time to peak [TTP]) were compared among three groups (malignant tumors [MTs], Warthin's tumor [WT] and pleomorphic adenomas [PA]).

Results  The mean age of the patients was 55.9 ± 14.1 (26–77), and 15 of them were male (51.7%). Eleven lesions were PAs [37.9%], 8 lesions were WTs (27.6%0 and 10 lesions (34.5%) were MTs (6 acinic cell carcinomas [ACCs], 3 adenocystic carcinomas [AdCCs], and 1 mucoepidermoid carcinoma [MEC]). The mean age of the patients with WTs was 62 ± 7.5 years; 52 ± 14.2 for patients with Pas, and 55.2 ± 17.2 for those with MTs ( p  = 0.32). The mean MIP was 122.7 ± 12.2 in WT, while it was 80.5 ± 19.5 in PA, and 76.2 ± 27.1 in MTs ( p  < 0.001); The mean MIP for WT was higher than for PAs and MTs; the values of MTs and PAs were not statistically different. The average of BF, BV, and curve peak were higher in WTs in comparison with the other two groups, and curve time 2 and TTP were higher in PAs in comparison with MTs.

Conclusion  Based on this study, perfusion CT of the parotid gland and its parameters can distinguish between benign and malignant parotid masses.

Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging for Differentiation Between Parotid Neoplasms

PURPOSE

This study was designed to evaluate the role of multiparametric magnetic resonance imaging (MRI) for differentiation of parotid gland neoplasms.

METHODS

Prospective study was conducted upon 52 consecutive patients (30 men, 22 women; aged 24-78 years; mean, 51 years) with parotid tumours that underwent multiparametric MRI using combined static MRI, dynamic contrast enhanced (DCE) MRI, and diffusion-weighted imaging (DWI). The static MRI parameter, time signal intensity curves (TIC) derived from DCE-MRI, and apparent diffusion coefficient (ADC) values of parotid tumours were correlated with histopathological findings.

RESULTS

Static MRI revealed a significant difference between both benign and malignant lesions in regards to margin definition (P < .001) and T2 hypointensity (P < .013), with a diagnostic accuracy 95% and 78.33% respectively. Study of the TIC type on DCE-MRI revealed statistically significant difference between benign and malignant lesions (P < .001) and diagnostic accuracy 96.55%. There was no statistically significant difference (P = .181) between the ADC values of benign and malignant lesions. ROC curve analysis revealed that by using ADC cut-off value of 1 × 10^-3 mm²/s had accuracy of 84.62% respectively for differentiating Warthin from malignant tumours that could be modified to higher value (94.28%) by excluding lymphoma from malignant lesions. By using cutoff value of 1.3 × 10^-3 mm²/s to differentiate pleomorphic adenoma from malignancy, ROC curve analysis had high accuracy of 97.06%.

CONCLUSION

Multiparametric MRI can be used for differentiation of malignant from benign parotid tumours and characterization of some benign parotid tumours.

Diagnostic value of single-source dual-energy spectral computed tomography in differentiating parotid gland tumors: initial results

Background

An accurate preoperative diagnosis that helps distinguish between benign and malignant parotid gland tumors is very important because the results strongly affect surgical procedures. We aimed to evaluate the value of single-source dual-energy computed tomography (ssDECT) in differentiating malignant from benign parotid gland tumors.

Methods

Fifty patients underwent enhanced neck ssDECT scanning before surgery. The images were analyzed using the gemstone spectral imaging (GSI) viewer software.

Results

Fifty-two tumors (43 patients) were confirmed histopathologically, comprising of 12 pleomorphic adenomas (PAs), 24 Warthin tumors (WTs) (15 patients), and 16 malignant tumors (MTs). The iodine concentration (IC), normalized iodine concentration to common carotid artery (NIC_A) and slope value of the spectral curve (λ_HU) of the WTs were significantly higher than those of MTs and PAs (all P<0.05). The optimal IC, NIC_A and λ_HU thresholds for differentiating PAs from MTs were 0.91 mg/mL, 0.15 and 1.09, respectively, achieving sensitivities of 91.7%, 91.7% and 91.7%, specificities of 95.0%, 85.0% and 95.0%, and accuracies of 94.2%, 86.5% and 94.2%, respectively for distinguishing PAs from MTs. The optimal IC, NIC_A and λ_HU thresholds for distinguishing WTs from MTs were 1.46 mg/mL, 0.20 and 1.72, achieving sensitivities of 91.7%, 95.8% and 91.7%, and specificities of 89.3%, 85.7% and 89.3%, respectively. The accuracy was 90.4%, 90.4% and 90.4%, respectively.

Conclusions

The parameters of ssDECT in enhanced CT scans are useful in the differential diagnosis of parotid tumors.

Characterization of salivary gland tumours with diffusion tensor imaging

OBJECTIVES

To characterize salivary glands tumours with diffusion tensor imaging.

METHODS

This study was conducted upon 53 patients (aged 18-81 years: mean 37 years) with salivary gland tumours that underwent diffusion tensor imaging was obtained using a single-shot echoplanar imaging sequence with parallel imaging at 1.5 T scanner. 48 slices were obtained, with a thickness of 2.5 mm, with no gap and the total scan duration was 7-8 min. The fractional anisotropy (FA) and the mean diffusivity (MD) value of the salivary gland tumours was calculated and correlated with pathological findings. Image analysis was performed by one radiologist. The receiver operating characteristic curve was drawn to detect the cut-off point of FA and MD used to characterize salivary gland tumours.

RESULTS

The mean FA and MD of malignant salivary gland tumours (n = 17) (0.41 ± 0.07 and 0.89 ± 0.15 × 10-3 mm2 s-1) was significantly different (p = 0.001) than that of benign tumours (n = 36) (0.19 ± 0.07 and 1.28 ± 0.42 × 10-3 mm2 s-1), respectively. Combined FA and MD used to differentiate malignant from benign tumours has an area under the curve (AUC) of 0.974, and an accuracy of 86%. There was a significant difference in FA between Warthin tumours and malignant tumours (p = 0.001). Selection FA of 0.35 to differentiate malignant tumours from Warthin tumours revealed AUC of 0.878 and an accuracy of 80%. There was a significant difference in FA and MD of malignant tumours and pleomorphic adenomas (p = 0.001). Combined FA and MD used to differentiate malignant tumours from pleomorphic adenomas revealed AUC of 0.993, and an accuracy of 93%. There was a significant difference in FA and MD of Warthin tumours and pleomorphic adenomas (p = 0.001). Combined FA and MD used to differentiate Warthin tumours from pleomorphic adenomas revealed AUC of 0.978, and an accuracy of 86%.

CONCLUSIONS

Diffusion-weighed imaging is a promising non-invasive method and it may be useful for the characterization and differentiation of benign and malignant salivary gland tumours.

Cross-sectional Imaging of Parotid Gland Nodules: A Brief Practical Guide

Clinical evaluation and ultrasound examination are the first steps in the evaluation of a patient with a swelling of the parotid region. After the detection of a nodular lesion, cytological or histological confirmation is usually performed to achieve the diagnosis, while the choice of cross-sectional imaging (computed tomography scan and magnetic resonance imaging) may significantly vary from one physician to another, on the basis of the degree of confidence that both radiologist and surgeon have with this kind of imaging. This work focuses on some essential “reporting points” in cross-sectional imaging evaluation of parotid nodules, chiefly helpful to the radiologist when the ultrasonography assessment is considered incomplete and requires a further evaluation.

Lymphoepithelial carcinoma of the salivary glands

RATIONALE

Lymphoepithelial carcinoma (LEC) is a rare malignancy with the histopathological feature of undifferentiated carcinoma and an intermixed reactive lymphoplasmacytic infiltration. Although clinically significant because of its malignant nature, it is difficult to make a differential diagnosis by preoperative imaging. Here, we report 3 cases of primary LEC arising in the major salivary glands, which showed unusual imaging features unlike other malignant tumors.

PATIENT CONCERNS

Our first case is a 44-year-old man with LEC in the right parotid gland, the second case is a 71-year-old woman with LEC in the right submandibular gland, and the third case is a 35-year-old woman with LEC in the right parotid gland. All of the patients presented with a palpable mass of variable duration.

DIAGNOSES

Computed tomography (CT) scans revealed a relatively well-defined, slightly hyperattenuated exophytic solid mass that had homogeneous well-enhanced regions. Ultrasonography (US) in the first 2 cases showed well-defined, hypoechoic solid masses with posterior enhancement. The CT findings seem to be benign tumors, but US features are compatible with highly cellular and hypervascular tumors.

INTERVENTIONS

The resection of the involved salivary gland with postoperative radiation therapy was performed.

OUTCOMES

There was no evidence of recurrence or metastasis after 5 years in all 3 patients.

LESSONS

Understanding these unusual imaging findings may be helpful in detecting LEC, and may also help clinicians provide adequate management to patients, such as surgery with adjuvant radiotherapy, because of its malignant entity.

Can lymphovascular invasion be predicted by preoperative multiphasic dynamic CT in patients with advanced gastric cancer?

OBJECTIVES

To determine whether multiphasic dynamic CT can preoperatively predict lymphovascular invasion (LVI) in advanced gastric cancer (AGC).

METHODS

278 patients with AGC who underwent preoperative multiphasic dynamic CT were retrospectively recruited. Tumour CT attenuation difference between non-contrast and arterial (Δ_AP), portal (Δ_PP) and delayed phase (Δ_DP), tumour-spleen attenuation difference in the portal phase (Δ_T-S), tumour contrast enhancement ratios (CERs), tumour-to-spleen ratio (TSR) and tumour volumes were obtained. All CT-derived parameters and clinicopathological variables associated with LVI were analysed by univariate analysis, followed by multivariate and receiver operator characteristics (ROC) analysis. Associations between CT predictors for LVI and histopathological characteristics were evaluated by the chi-square test.

RESULTS

Δ_PP (OR, 1.056; 95% CI: 1.032-1.080) and Δ_T-S (OR, 1.043; 95% CI: 1.020-1.066) are independent predictors for LVI in AGC. Δ_PP, Δ_T-S and their combination correctly predicted LVI in 74.8% (AUC, 0.775; sensitivity, 88.6%; specificity, 54.1%), 68.7% (AUC, 0.747; sensitivity, 68.3%; specificity, 69.4%) and 71.7% (AUC, 0.800; sensitivity, 67.6%; specificity, 77.8%), respectively. There were significant associations between CT predictors for LVI with tumour histological differentiation and Lauren classification.

CONCLUSION

Multiphasic dynamic CT provides a non-invasive method to predict LVI in AGC through quantitative enhancement measurement.

KEY POINTS

• Lymphovascular invasion rarely can be evaluated preoperatively in advanced gastric cancer (AGC). • Δ _PP and Δ _T-S were independent predictors for LVI in patients with AGC. • Δ _PP and Δ _T-S showed acceptable predictive performance for LVI. • Combination of Δ _PP and Δ _T-S improved predictive performance for LVI. • Multiphasic dynamic CT may be a useful adjunct for detecting LVI preoperatively.

Dynamic Contrast-Enhanced CT in Patients with Pancreatic Cancer

The aim of this systematic review is to provide an overview of the use of Dynamic Contrast-enhanced Computed Tomography (DCE-CT) in patients with pancreatic cancer. This study was composed according to the PRISMA guidelines 2009. The literature search was conducted in PubMed, Cochrane Library, EMBASE, and Web of Science databases to identify all relevant publications. The QUADAS-2 tool was implemented to assess the risk of bias and applicability concerns of each included study. The initial literature search yielded 483 publications. Thirteen articles were included. Articles were categorized into three groups: nine articles concerning primary diagnosis or staging, one article about tumor response to treatment, and three articles regarding scan techniques. In exocrine pancreatic tumors, measurements of blood flow in eight studies and blood volume in seven studies were significantly lower in tumor tissue, compared with measurements in pancreatic tissue outside of tumor, or normal pancreatic tissue in control groups of healthy volunteers. The studies were heterogeneous in the number of patients enrolled and scan protocols. Perfusion parameters measured and analyzed by DCE-CT might be useful in the investigation of characteristic vascular patterns of exocrine pancreatic tumors. Further clinical studies are desired for investigating the potential of DCE-CT in pancreatic tumors.

Differential diagnostic value of computed tomography perfusion combined with vascular endothelial growth factor expression in head and neck lesions

There are numerous types of head and neck lesions (HNLs), and conventional computed tomography (CT) has low specificity and sensitivity in the definitive and differential diagnosis of HNLs. The aim of the present study was to evaluate the value of perfusion CT (CTP) combined with vascular endothelial growth factor (VEGF) expression in the differentiation between malignant and benign HNLs. In total, 41 HNLs, which were pathologically confirmed, underwent CTP and VEGF expression analysis. All lesions were divided into three groups: Group A, benign hypovascular lesions; Group B, benign hypervascular lesions; and Group C, malignant lesions. Time density curve (TDC) and CTP parameters [maximum intensity projection (MIP), blood volume (BV), blood flow (BF), mean transit time and capillary permeability] were analyzed. The association between perfusion measurements and VEGF was assessed using Pearson's correlation. TDCs were classified into three types, and type I was more frequently identified in benign tumors (Groups A and B) compared with malignant tumors (Group C) (P=0.003). Malignant tumors primarily had a TDC of type II and III. MIP, BF and BV were all significantly higher in Groups B and C compared to Group A (P<0.01). VEGF expression of malignant tumors was significantly higher than benign tumors (P=0.007). No correlation was identified between VEGF and any CTP parameter. The present findings suggest that CTP combined with VEGF may differentiate between malignant and benign HNLs, and between benign hypovascular and hypervascular lesions.