Effects of region of interest sizes on apparent diffusion coefficient measurements of pleomorphic adenoma, Warthin tumor, and normal parotid parenchyma

Histogram analysis of ultrasonographic images in the differentiation of benign and malignant parotid gland tumors

OBJECTIVE

We evaluated the diagnostic value of histogram analysis (HA) using ultrasonographic (US) images for differentiation among pleomorphic adenoma (PA), adenolymphoma (AL), and malignant tumors (MT) of the parotid gland.

STUDY DESIGN

Preoperative US images of 48 patients with PA, 39 patients with AL, and 17 patients with MT were retrospectively analyzed for gray-scale histograms. Nine first-order texture features derived from histograms of the tumors were compared. Area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic performance of texture features. The Youden index maximum exponent was used to calculate sensitivity and specificity.

RESULTS

Statistically significant differences were discovered in Mean and Skewness HA values between PA and AL (P<0.001), and in Mean values between AL and MT (P<0.001). However, comparison of PA and MT showed no statistically significant differences (P>0.01). Excellent discrimination was detected between PA and AL (AUC=0.802), and between AL and MT (AUC=0.822). The combination of Mean plus Skewness improved discrimination between PA and AL (AUC=0.823) with sensitivity values reaching 1.00. However, Mean plus Skewness applied to differentiate PA from AL and Mean values applied to distinguish AL and MT resulted in low specificity, indicating many false positive interpretations.

CONCLUSIONS

Histogram analysis is useful for differentiating PA from AL and AL from MT but not PA from MT.

Enhanced CT-based texture analysis and radiomics score for differentiation of pleomorphic adenoma, basal cell adenoma, and Warthin tumor of the parotid gland

OBJECTIVE

To evaluate the diagnostic performance of computed tomography (CT) radiomics analysis for differentiating pleomorphic adenoma (PA), Warthin tumor (WT), and basal cell adenoma (BCA).

METHODS

A total of 189 patients with PA (n = 112), WT (n = 53) and BCA (n = 24) were divided into a training set (n = 133) and a test set (n = 56). The radiomics features were extracted from plain CT and contrast-enhanced CT images. After dimensionality reduction, plain CT, multiphase-enhanced CT, integrated radiomics signature models and radiomics score (Rad-score) were established and calculated. The receiver operating characteristic (ROC) curve analysis was taken for the assessment of the model performance, and then comparison was conducted among these models. Decision curve analysis (DCA) was adopted to assess the clinical benefits of the models. Diagnostic performances including sensitivity, specificity, and accuracy of the radiologists were evaluated.

RESULTS

Seven, nine, fourteen, and fourteen optimal features were used to constructed plain scan, arterial phase, venous phase, and integrated radiomics signature models, respectively. ROC analysis showed these four models were able to differentiate PA from BCA and WT, with the area under the ROC curve (AUC) values of 0.79, 0.90, 0.87, and 0.94 in the training set, and 0.79, 0.89, 0.86, and 0.94 in the test set, respectively. The integrated model had better diagnostic performance than single-phase radiomics model, but it had similar diagnostic performance to that of the radiomics model based on the arterial phase (p > 0.05). The sensitivity, specificity, and accuracy in the diagnosis of PA were 0.86, 0.46, and 0.70 for the non-subspecialized radiologist and 0.88, 0.77, and 0.84 for the subspecialized radiologist, respectively. Six venous phase parameters were finally selected in differentiating WT from BCA. The predictive effect of the model was favorable, with AUC value of 0.95, sensitivity of 0.96, specificity of 0.83, and accuracy of 0.92. The sensitivity, specificity, and accuracy in the diagnosis between WT and BCA were 0.26, 0.87, and 0.45 for the non-subspecialized radiologist and 0.85, 0.58, and 0.77 for the subspecialized radiologist, respectively.

CONCLUSION

The CT-based radiomics analysis showed favorable predictive performance for differentiating PA, WT, and BCA, thus may be helpful in the clinical decision-making.

Apparent diffusion coefficient measurement of the parotid gland parenchyma

The measurements of apparent diffusion coefficient (ADC) with diffusion weighted magnetic resonance imaging (DW-MRI) is becoming a popular diagnostic and research tool for examination of parotid glands. However, there is little agreement between the reported ADC values of the parotid gland in published literature. In this review 43 studies on ADC measurement of the parotid glands were included. The analyses indicated several possible culprits of the observed ADC discrepancies. For example, DW-MRI examinations under gustatory stimulation gives higher ADC values compared to the unstimulated parotid gland (P=0.003). The diffusion weighting factors (b-values) can either increase (b-value <200 s/mm²) or decrease ADC values (b-values >1,000 s/mm²). The timing of follow-up DW-MRI after radiotherapy (RT) indicates correlation to the found ADC values (R² =0.39). Interestingly, the choice of regions of interest (ROI) appears not to affect the measurements of ADC (P=0.75). It can be concluded that there is a critical need for standardization of ADC measurement of the parotid glands to allow valid inter-study comparisons and eventually to reach consensus on the use of ADC as biomarker.

Carcinoma ex pleomorphic adenoma of major salivary glands: CT and MR imaging findings

OBJECTIVES

To describe the CT and MR imaging characteristics of primary carcinoma ex pleomorphic adenoma (Ca-ex-PA) in major salivary glands and present more information for recognizing this malignancy.

METHODS

212 patients with primary Ca-ex-PA in major salivary glands (169 in the parotid gland, 36 in the submandibular gland, 7 in the sublingual gland) underwent CT and MR imaging (plain and contrast-enhanced scans) prior to surgical management and histopathological examination. The CT and MR imaging findings of this condition were retrospectively reviewed and correlated with their pathological types: non-invasive carcinoma (Type I, 37 cases), minimally invasive carcinoma (Type II, 18 cases), and widely invasive carcinoma (TypeIII, 157 cases). The binary logistic regression analysis was used to analyze the independent influencing factors of morphology and boundary for differentiating between Type I/II and Type III of Ca-ex-PA, and the sensitivity, specificity and positive predictive value were calculated. Differences in apparent diffusion coefficient (ADC) values between Type I/II and Type III of Ca-ex-PA were calculated by independent sample t-tests.

RESULTS

On CT and MR imaging, there were 190/212 cases (89.6%) identified as lobular, 203/212 cases (95.8%) with enhancement, and 173/212 cases (81.6%) with inhomogeneous after contrast administration.Calcification within the mass was shown in 76 of 192 cases (39.6%) on plain CT examination. Of 55 neoplasms with Type I and II, 38 (69.1%) were presented as round or oval and 42 (76.4%) as well-defined margins. Of 157 neoplasms with Type III, 103 (65.6%) were presented as irregular form and 110 (70.1%) as uneven margins or with partial uneven margins.The sensitivity, specificity and positive predictive value for distinguishing Type I/II and Type III tumors according to the morphology and boundary were 78.34%, 63.64% and 86.01%, respectively. The mean ADC value of Ca-ex-PA (22 cases) in major salivary glands was about 0.93 × 10^-3 mm² s^-1, and there was no significant difference in mean ADC value between Type I/II and Type III of this neoplasm. Cervical lymph node metastasis and distance metastasis were found in 67 patients (31.6%, Type III) and 32 patients (15.1%, Type I in 1; Type II in 1; and Type III in 30), respectively.

CONCLUSIONS

Most Ca-ex-PA is characterized by an irregular, lobular, and inhomogeneous enhanced neoplasm with uneven margin or partial uneven margin on CT and MR imaging, which is frequently corresponding with Type III. And a round or oval mass with well-defined margin usually correlates with Type I and II. Morphology and boundary are important basis for distinguishing Type I/II and Type III tumors. Calcification within the neoplasm shown on CT may be regarded as a specific sign for indicating this malignancy. Low ADC value is an important manifestation of this neoplasm.Ca-ex-PA with Type III is more likely to have cervical lymph node metastasis and distant metastasis.

Feasibility evaluation of amide proton transfer-weighted imaging in the parotid glands: a strategy to recognize artifacts and measure APT value

Background

The feasibility and image quality of three-dimensional (3D) amide proton transfer (APT)-weighted (APTw) in parotid tumor lesions have not been well established in previous studies. This study aimed to evaluate the utility of APT imaging in parotid lesions and glands.

Methods

Patients with parotid lesions received 3D turbo spin echo (TSE) APTw on a 3.0T scanner. Two radiologists, who were blinded to the clinical data, independently evaluated the APTw image quality using 4-point Likert scales (1= poor, 4= excellent) in terms of integrity and hyperintensity artifacts. An image quality selection protocol was built based on the two scores. Evaluable images (integrity score >1) and trustable images (integrity score >3 and hyperintensity artifacts score >2) were then enrolled for APTw value comparison between parotid lesions and glands.

Results

Forty consecutive patients were included in this study. Four patients were excluded due to severe motion (n=3) or dental (n=1) artifacts, and 36 patients received the APT sequence. Among these, more parotid tumor lesions (34/36, 94.4%) than normal parotid glands (23/31, 74.2%) revealed excellent integrity scores (score =4) (P=0.034). Most parotid tumor lesions (24/34, 70.6%) and glands (16/28, 57.1%) revealed no or little hyperintensity artifacts for diagnosis (scores 3 and 4). APT values of parotid lesions and glands in the evaluable groups were 2.11%±1.15% and 1.60%±1.56%, respectively, and the difference was not significant (P=0.197). APT values of parotid lesions and glands in the trustable groups were 1.99%±1.18% and 1.03%±1.09%, respectively, and the difference was statistically significant (P=0.018).

Conclusions

3D APTw could be used to differentiate parotid tumors and normal parotid glands; however, the technology still needs to be improved to remove artifacts. In our study, most APTw images of tumor lesions in parotid glands had acceptable image quality, and these APTw images are feasible for diagnostic use.

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.

Multiparametric magnetic resonance imaging of parotid tumors: A systematic review

PURPOSE

The purpose of this systematic review was to provide an overview of the contribution of multiparametric magnetic resonance imaging (MRI) in the diagnosis of parotid tumors (PT) and recommendations based on current evidences.

MATERIAL AND METHODS

We performed a retrospective systematic search of PubMed, EMBASE, and Cochrane Library databases from inception to January 2020, using the keywords "magnetic resonance imaging" and "salivary gland neoplasms".

RESULTS

The initial search returned 2345 references and 90 were deemed relevant for this study. A total of 54 studies (60%) reported the use of diffusion-weighted imaging (DWI) and 28 studies (31%) the use of dynamic contrast-enhanced (DCE) imaging. Specific morphologic signs of frequent benign PT and suggestive signs of malignancy on conventional sequences were reported in 37 studies (41%). DWI showed significant differences in apparent diffusion coefficient (ADC) values between benign and malignant PT, and especially between pleomorphic adenomas and malignant PT, with cut-off ADC values between 1.267×10^-3mm²/s and 1.60×10^-3mm²/s. Perfusion curves obtained with DCE imaging allowed differentiating among pleomorphic adenomas, Warthin's tumors, malignant PT and cystic lesions. The combination of morphological MRI sequences, DCE imaging and DWI helped increase the diagnostic accuracy of MRI.

CONCLUSION

Multiparametric MRI, including morphological MRI sequences, DWI and DCE imaging, is the imaging modality of choice for the characterization of focal PT and provides features that are highly suggestive of a specific diagnosis.

Intravoxel incoherent motion diffusion-weighted imaging for discrimination of benign and malignant retropharyngeal nodes

PURPOSE

Anatomical imaging criteria for the diagnosis of malignant head and neck nodes may not always be reliable. This study aimed to evaluate the diagnostic value of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) DWI in discriminating benign and malignant metastatic retropharyngeal nodes (RPNs).

METHODS

IVIM DWI using 14 b-values was performed on RPNs of 30 patients with newly diagnosed metastatic nasopharyngeal carcinoma (NPC) and 30 patients with elevated plasma Epstein-Barr virus (EBV)-DNA without NPC who were part of an EBV-based NPC screening program. Histogram measurements of the two groups were compared for pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion volume fraction (f) and apparent diffusion coefficient (ADC) using the Mann-Whitney U test. Area under the curves (AUCs) of significant measurements were calculated from receiver-operating characteristics analysis and compared using the DeLong test.

RESULTS

Compared with metastatic RPNs, benign RPNs had lower ADC_mean (0.73 vs 0.82 × 10^-3 mm²/s) and D_mean (0.60 vs 0.71 × 10^-3 mm²/s) and a higher D*_mean (35.21 vs 28.66 × 10^-3 mm²/s) (all p < 0.05). There was no difference in the f measurements between the two groups (p = 0.204 to 0.301). D_mean achieved the highest AUC of 0.800, but this was not statistically better than the AUCs of the other parameters (p = 0.148 to 0.991).

CONCLUSION

Benign RPNs in patients with EBV-DNA showed greater restriction of diffusion compared with malignant metastatic RPNs from NPC. IVIM did not show a significant advantage over conventional DWI in discriminating benign and malignant nodes.

Diffusion-weighted MRI: impact of the size of the ROI in detecting metastases in subcentimeter lymph nodes in head and neck squamous cell carcinoma

PURPOSE

Our aim is to determine the impact of the size of ROI in detecting subcentimeter metastatic lymph nodes in patients with head and neck squamous cell carcinoma (HNSCC). Secondary aim is to determine the impact of the histopathologic grade of the primary cancer on the ADC value of the metastatic nodes.

METHODS

The prospective study included 51 patients with histopathologically proven HNSCC at the primary site. Primary site includes oral cavity, oropharynx, larynx, and hypopharynx. ADC values of the lymph nodes were measured on ADC maps by placing two ROIs in the lymph nodes (0.2 cm² in the center of the node and the whole node). Lymph nodes were dissected by levels, marked by the surgeon, and sent to the pathologist.

RESULTS

By applying a smaller ROI, ADC values have greater sensitivity, specificity, NPV, PPV, and AUC in detecting metastasis compared to the ADC value of the entire node (88.0%, 80.73%, 90.7%, 75.9%, 0.912% versus 80.0%, 77.98%, 85% ,71.4%, and 0.819%, respectively) p < 0.001. Statistically significant negative correlation was established between the tumor grade and the ADC of lymph node at ROI 0.2 cm²and ROI of the whole lymph node (rho = - 0.425; p = 0.002, and rho = - 0.298; p = 0.038, respectively).

CONCLUSION

ROI size affects the ADC value of the nodes. The higher histopathological grade of the primary tumor is inversely correlated with the ADC value of the lymph nodes.