Magnetic resonance imaging of salivary gland tumours: Key findings for imaging characterisation

Predicting High-risk Capsular Features in Pleomorphic Adenoma of the Parotid Gland Through a Nomogram Model Based on ADC Imaging

RATIONALE AND OBJECTIVES

Based on Apparent Diffusion Coefficient (ADC) images, a nomogram model is established to accurately predict the high-risk capsular characteristics associated with pleomorphic adenoma of the parotid gland (PAP) recurrence.

MATERIALS AND METHODS

This retrospective study analyzed 190 patients with PAPs. Significant clinical radiological factors were identified through univariate difference analysis and multivariate regression analysis. The optimal threshold was determined by analyzing the average ADC value of the entire tumor, using the best Youden index and sensitivity analysis, and tumor subregions were delineated accordingly. Three radiomic models were constructed for the whole tumor and for high/low ADC areas, with the best model determined through statistical analysis. Ultimately, a nomogram model was constructed by combining the independent predictive factor of high-risk capsular features with the optimal radiomic predictive score. Model performance was comprehensively assessed by the area under the receiver operating characteristic curve (ROC AUC), accuracy, sensitivity, and specificity.

RESULTS

The best ADC division threshold as 1.25 × 10-3 mm2/s. Multivariate analysis identified High-ADC Zone Volume Percentage as an independent predictor for PAPs with high-risk capsular characteristics. The radiomic model based on the low ADC tumor subregion was optimal (AUC 0.899). The nomogram model, combining independent predictors and optimal imaging studies predictive score, demonstrated high performance (AUC 0.909). Decision curve analysis confirmed the nomogram's clinical applicability.

CONCLUSION

The nomogram model constructed from ADC quantitative imaging can predict PAPs patients with high-risk capsular features. These patients require intraoperative preventive measures to avoid tumor spillage and residuals, as well as extended postoperative follow-up.

Different MRI-based radiomics models for differentiating misdiagnosed or ambiguous pleomorphic adenoma and Warthin tumor of the parotid gland: a multicenter study

Purpose

To evaluate the effectiveness of MRI-based radiomics models in distinguishing between Warthin tumors (WT) and misdiagnosed or ambiguous pleomorphic adenoma (PA).

Methods

Data of patients with PA and WT from two centers were collected. MR images were used to extract radiomic features. The optimal radiomics model was found by running nine machine learning algorithms after feature reduction and selection. To create a clinical model, univariate logistic regression (LR) analysis and multivariate LR were used. The independent clinical predictors and radiomics were combined to create a nomogram. Two integrated models were constructed by the ensemble and stacking algorithms respectively based on the clinical model and the optimal radiomics model. The models' performance was evaluated using the area under the curve (AUC).

Results

There were 149 patients included in all. Gender, age, and smoking of patients were independent clinical predictors. With the greatest average AUC (0.896) and accuracy (0.839) in validation groups, the LR model was the optimal radiomics model. In the average validation group, the radiomics model based on LR did not have a higher AUC (0.795) than the clinical model (AUC = 0.909). The nomogram (AUC = 0.953) outperformed the radiomics model in terms of discrimination performance. The nomogram in the average validation group had a highest AUC than the stacking model (0.914) or ensemble model (0.798).

Conclusion

Misdiagnosed or ambiguous PA and WT can be non-invasively distinguished using MRI-based radiomics models. The nomogram exhibited excellent and stable diagnostic performance. In daily work, it is necessary to combine with clinical parameters for distinguishing between PA and WT.

ACR Appropriateness Criteria® Staging and Post-Therapy Assessment of Head and Neck Cancer

Imaging of head and neck cancer at initial staging and as part of post-treatment surveillance is a key component of patient care as it guides treatment strategy and aids determination of prognosis. Head and neck cancer includes a heterogenous group of malignancies encompassing several anatomic sites and histologies, with squamous cell carcinoma the most common. Together this comprises the seventh most common cancer worldwide. At initial staging comprehensive imaging delineating the anatomic extent of the primary site, while also assessing the nodal involvement of the neck is necessary. The treatment of head and neck cancer often includes a combination of surgery, radiation, and chemotherapy. Post-treatment imaging is tailored for the evaluation of treatment response and early detection of local, locoregional, and distant recurrent tumor. Cross-sectional imaging with CT or MRI is recommended for the detailed anatomic delineation of the primary site. PET/CT provides complementary metabolic information and can map systemic involvement. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

A retrospective study of nonneoplastic and neoplastic disorders of the salivary glands

The spectrum of major and minor salivary gland disorders varies widely. Epidemiological data on some injury categories are rare and often not up-to-date. This study aims to analyze epidemiological data using clinical, paraclinical, and histopathological parameters. Study was carried out for 5 years on the nonneoplastic and tumoral pathology of the salivary glands. Data were statistically analyzed using the appropriate parameters. Data analysis according to the biological behavior of the lesions revealed great heterogeneity. Statistically significant correlations were observed between the type of injury, age (P = .002) and gender (0.033). The environment of origin of the patients as well as the comorbidities reflected in most cases the nature of the process. Associations were also observed between the biological behavior of the lesions and the hemicranial topography (P = .019), the type of salivary gland (P = .024), and the surgical technique used (P < .001). Most cases were identified in the major salivary glands, often in the parotid. The most common diseases are represented by nonspecific chronic sialadenitis (nonneoplastic lesion), pleomorphic adenoma and Warthin tumor (benign tumors), mucoepidermoid carcinoma (malignant tumor), and squamous carcinoma (secondary tumor). They presented axial diameters between 2 to 95 mm. The most used curative technique was subtotal excision with facial nerve preservation. In conclusion, the study highlighted the main epidemiological aspects of salivary gland disorders. Some data agree with the specialty literature, and particular aspects are also observed. Therefore, this research is useful both in the medical and research fields.

Imaging of human papilloma virus (HPV) related oropharynx tumour: what we know to date

The tumours of head and neck district are around 3% of all malignancies and squamous cell carcinoma is the most frequent histotype, with rapid increase during the last two decades because of the increment of the infection due to human papilloma virus (HPV). Even if the gold standard for the diagnosis is histological examination, including the detection of viral DNA and transcription products, imaging plays a fundamental role in the detection and staging of HPV + tumours, in order to assess the primary tumour, to establish the extent of disease and for follow-up. The main diagnostic tools are Computed Tomography (CT), Positron Emission Tomography-Computed Tomography (PET-CT) and Magnetic Resonance Imaging (MRI), but also Ultrasound (US) and the use of innovative techniques such as Radiomics have an important role. Aim of our review is to illustrate the main imaging features of HPV + tumours of the oropharynx, in US, CT and MRI imaging. In particular, we will outline the main limitations and strengths of the various imaging techniques, the main uses in the diagnosis, staging and follow-up of disease and the fundamental differential diagnoses of this type of tumour. Finally, we will focus on the innovative technique of texture analysis, which is increasingly gaining importance as a diagnostic tool in aid of the radiologist.

Salivary gland neoplasms in small biopsies and fine needle aspirations

Salivary gland neoplasms are rare and represent a diverse group of head and neck tumors. Their diagnosis in limited cellularity specimens can be challenging as many of these have overlapping clinical, radiological presentation, and pathologic features. Fine needle aspiration and/or core biopsies are more of a norm than rarity to be performed preoperatively to provide invaluable information that can guide clinical management including surgery. Even though these limited specimens may not always provide a definitive diagnosis; they have high sensitivity in confirming primary neoplasia, assessing the tumor grade, and ruling out non-surgical disease. An algorithmic pattern based approach can help narrow the differential diagnosis; leading to a definitive diagnosis with the help of specific ancillary studies.

Newly Discovered Parotid Lesion: What Next?

When a parotid lesion is discovered incidentally, it can be challenging for the radiologist to provide specific recommendations for the next steps. This article describes how the radiologist can play an active role in managing incidentally discovered parotid lesions. First, we explore the significance of parotid lesions. Next, the pertinent anatomy of the parotid space is presented to develop an appropriate differential diagnosis. Lastly, we discuss critical clinical and imaging characteristics the radiologist can use to provide specific recommendations.

The Value of Multiparametric Magnetic Resonance Imaging in the Preoperative Differential Diagnosis of Parotid Gland Tumors

BACKGROUND

The aim of the present study was to determine the value of multiparametric MRI in the preoperative differential diagnosis of parotid tumors, which is essential for therapeutic strategy selection.

METHODS

A three-year prospective study was conducted with 65 patients. Each patient was investigated preoperatively with multiparametric MRI and surgical excision of the tumor was performed. The preoperative imaging diagnosis was compared with the histopathological report. Several MRI parameters were analyzed, including T1 and T2 weighted image (WI), apparent diffusion coefficient (ADC), time to peak (TTP), and the time intensity curve (TIC).

RESULTS

In the differential diagnosis of benign from malignant tumors, T2WI and ADC showed statistically significant differences. Multiparametric MRI had a sensitivity, specificity, and accuracy of 81.8%, 88.6% and 92.3%, respectively. All of the studied parameters (T1, T2, TIC, TTP, ADC) were significantly different in the comparison between pleomorphic adenomas and Warthin tumors. With reference to the scope of this study, the conjunction of multiparametric and conventional MRI demonstrated a sensitivity, specificity, and accuracy of 94.1%, 100%, and 97.8%, respectively.

CONCLUSIONS

Morphological analysis using conventional MRI combined with diffusion-weighted imaging (DW) and dynamic contrast-enhanced (DCE) multiparametric MRI improved the preoperative differential diagnosis of parotid gland tumors.

Polar Vessel: A New Ultrasound Sign for Complementary Diagnosis of Major Salivary Gland Adenoid Cystic Carcinoma

OBJECTIVES

To investigate the characteristic ultrasonographic findings of adenoid cystic carcinoma (ACC) in major salivary glands and identify the value of polar vessel in color Doppler flow imaging (CDFI) for the diagnosis of ACC.

METHODS

From January 2017 to December 2021, 76 patients with parotid and submandibular gland tumors, including 14 patients with ACC, as confirmed by surgery and histopathology, were enrolled. Their clinicopathologic information and ultrasound (US) features were recorded and analyzed. The performance of polar vessel in CDFI for differentiating ACC from non-ACC (benign tumors and mucoepidermoid carcinoma [MEC]) was analyzed.

RESULTS

ACC in the major salivary gland was more likely to be associated with pain symptoms (P = .027) and unclear borders and rough edges in grayscale US (P = .002, .015, respectively) than benign tumors. Compared to MEC, ACC tended to feature a homogeneous internal echo (P = .008). ACC of the major salivary gland had a significantly higher incidence of polar vessel sign than that of non-ACC (benign tumors and MEC) (P < .0001, .0001, respectively). The polar vessel sign showed good performance in distinguishing between ACC and non-ACC, with an area under the receiver operating characteristic curve of 0.857, a sensitivity of 71.4%, a specificity of 100%, and an accuracy of 94.7%. Positive predictive value and negative predictive value were calculated at 100% and 93.9%, respectively.

CONCLUSIONS

The US sign of polar vessel has high diagnostic efficiency, and it may have important potential for use as a new complementary sign for the diagnosis of ACC in major salivary glands.

A Deep Learning Model for Classification of Parotid Neoplasms Based on Multimodal Magnetic Resonance Image Sequences

OBJECTIVE

To design a deep learning model based on multimodal magnetic resonance image (MRI) sequences for automatic parotid neoplasm classification, and to improve the diagnostic decision-making in clinical settings.

METHODS

First, multimodal MRI sequences were collected from 266 patients with parotid neoplasms, and an artificial intelligence (AI)-based deep learning model was designed from scratch, combining the image classification network of Resnet and the Transformer network of Natural language processing. Second, the effectiveness of the deep learning model was improved through the multi-modality fusion of MRI sequences, and the fusion strategy of various MRI sequences was optimized. In addition, we compared the effectiveness of the model in the parotid neoplasm classification with experienced radiologists.

RESULTS

The deep learning model delivered reliable outcomes in differentiating benign and malignant parotid neoplasms. The model, which was trained by the fusion of T2-weighted, postcontrast T1-weighted, and diffusion-weighted imaging (b = 1000 s/mm² ), produced the best result, with an accuracy score of 0.85, an area under the receiver operator characteristic (ROC) curve of 0.96, a sensitivity score of 0.90, and a specificity score of 0.84. In addition, the multi-modal paradigm exhibited reliable outcomes in diagnosing the pleomorphic adenoma and the Warthin tumor, but not in the identification of the basal cell adenoma.

CONCLUSION

An accurate and efficient AI based classification model was produced to classify parotid neoplasms, resulting from the fusion of multimodal MRI sequences. The effectiveness certainly outperformed the model with single MRI images or single MRI sequences as input, and potentially, experienced radiologists.

LEVEL OF EVIDENCE

3 Laryngoscope, 133:327-335, 2023.

Discriminating between benign and malignant salivary gland tumors using diffusion-weighted imaging and intravoxel incoherent motion at 3 Tesla

PURPOSE

The purpose of this study was to retrospectively evaluate the diagnostic performances of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for discriminating between benign and malignant salivary gland tumors (SGTs).

MATERIALS AND METHODS

Sixty-seven patients with 71 SGTs who underwent MRI examination at 3 Tesla were included. There were 34 men and 37 women with a mean age of 57 ± 17 (SD) years (age range: 20-90 years). SGTs included 21 malignant tumors (MTs) and 50 benign SGTs (33 pleomorphic adenomas [PAs] and 17 Warthin's tumors [WTs]). For each SGT, DWI and IVIM parameters, mean, skewness, and kurtosis of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion volume fraction (f) were calculated and further compared between SGTs using univariable analysis. Areas under the curves (AUC) of receiver operating characteristic of significant parameters were compared using the Delong test.

RESULTS

Significant differences in ADC_mean, D_mean and D*_mean were found between SGTs (P < 0.001). The highest AUC values were obtained for ADC_mean (0.949) for identifying PAs and D*_mean (0.985) for identifying WTs and skewness and kurtosis did not outperform mean. To discriminate benign from malignant SGTs with thresholds set to maximize Youden index, IVIM and DWI produced accuracies of 85.9% (61/71; 95% CI: 75.6-93.0) and 77.5% (55/71; 95% CI: 66.0-86.5) but misdiagnosed MTs as benign in 28.6% (6/21) and 61.9% (13/21) of SGTs, respectively. After maximizing specificity to 100% for benign SGTs, the accuracies of IVIM and DWI decreased to 76.1% (54/71; 95% CI: 64.5-85.4) and 64.8% (46/71; 95% CI: 52.5-75.8) but no MTs were misdiagnosed as benign. IVIM and DWI correctly diagnosed 66.0% (33/50) and 50.0% (25/50) of benign SGTs and 46.5% (33/71) and 35.2% (25/71) of all SGTs, respectively.

CONCLUSION

IVIM is more accurate than DWI for discriminating between benign and malignant SGTs because of its advantage in detecting WTs. Thresholds set by maximizing specificity for benign SGTs may be advantageous in a clinical setting.

Frequency and imaging features of the adjacent osseous changes of salivary gland carcinomas in the head and neck region

PURPOSE

The association between salivary gland carcinomas and adjacent osseous changes in the head and neck region is not clear. We evaluated the frequency and imaging features of such changes and investigated the specific characteristics of salivary gland carcinomas associated with them.

METHODS

A total of 118 patients with histologically proven salivary gland carcinomas were retrospectively reviewed. The imaging characteristics of osseous changes were sorted into three categories based on computed tomography images: sclerotic change, erosive change, and lytic change. The frequency of all these osseous changes and any one of them was compared between different pathologies using Fisher's exact test. Odds ratios were calculated to evaluate the association between these changes and perineural spread.

RESULTS

Osseous changes were found in 21 (18%) of 118 cases. Among these, seven (6%) cases were with sclerotic, nine (8%) with erosive, and nine (8%) with lytic changes (four with mixed change). Adenoid cystic carcinoma showed a significantly higher frequency of sclerotic and erosive changes, and either osseous change, than the other salivary gland carcinomas (p < 0.001 for each). Sclerotic changes were only present in the adenoid cystic carcinomas. Perineural spread was a significant factor in showing higher osseous change frequencies (odds ratio = 3.98, p = 0.006).

CONCLUSION

Among salivary gland carcinomas in the head and neck region, adenoid cystic carcinomas had a significantly higher frequency of adjacent osseous changes, especially sclerotic changes, than other salivary gland carcinomas.

A practical overview of CT and MRI features of developmental, inflammatory, and neoplastic lesions of the sphenoid body and clivus

The sphenoid bone is an unpaired bone that contributes to the formation of the skull base. Despite the enormous progress in transnasal endoscopic visualisation, imaging techniques remain the cornerstones to characterise any pathological condition arising in this area. In the present review, we offer a bird's-eye view of the developmental, inflammatory, and neoplastic alterations affecting the sphenoid body and clivus, with the aim to propose a practical diagnostic aid for radiologists based on clinico-epidemiological, computed tomography, and magnetic resonance imaging features.

Techniques, Tricks, and Stratagems of Oral Cavity Computed Tomography and Magnetic Resonance Imaging

The oral cavity constitutes a complex anatomical area that can be affected by many developmental, inflammatory, and tumoural diseases. MultiSlice Computed Tomography (MSCT) and Magnetic Resonance Imaging (MRI) currently represent the essential and complementary imaging techniques for detecting oral cavity abnormalities. Advanced MRI with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) has recently increased the ability to characterise oral lesions and distinguish disease recurrences from post therapy changes. The analysis of the oral cavity area via imaging techniques is also complicated both by mutual close appositions of different mucosal surfaces and metal artifacts from dental materials. Nevertheless, an exact identification of oral lesions is made possible thanks to dynamic manoeuvres and specific stratagems applicable on MSCT and MRI acquisitions. This study summarises the currently available imaging techniques for oral diseases, with particular attention to the role of DWI, DCE-PWI, and dynamic manoeuvres. We also propose MSCT and MRI acquisition protocols for an accurate study of the oral cavity area.

Multifrequency magnetic resonance elastography-based tomoelastography of the parotid glands-feasibility and reference values

OBJECTIVES

Accurate radiological differentiation of parotid tumors remains challenging despite recent technical advances in quantitative medical imaging. Multifrequency magnetic resonance elastography (MRE) could provide additional information on viscoelastic properties of normal and abnormal biological tissues. This study investigates the feasibility of MRE of the parotid glands in healthy participants and provides first reference values.

METHODS

20 healthy participants underwent multifrequency MRE of both parotid glands at 3 Tesla. Shear waves at frequencies of 25, 30, 40, and 50 Hz were introduced into the participants' heads through the occiput using pressurized-air actuators. Shear wave speed (SWS) and loss angle of the shear modulus (φ) were reconstructed by tomoelastography post-processing as surrogate parameters for tissue stiffness and viscosity or fluidity. 10 participants underwent repeated MRE to determine test-retest reliability based on intraclass correlation coefficients.

RESULTS

All MRE datasets acquired could be included in the analysis. Mean SWS was 0.97 ± 0.13 m/s, and mean φ was 0.59 ± 0.05 rad, each for both sides combined and without notable lateral difference (p = 0.88/0.87). Test-retest reliability was good for SWS (ICC = 0.84 for both sides/ICC = 0.77 for the right side/ICC = 0.79 for the left side) and good to excellent for φ(ICC = 0.94/0.86/0.90).

CONCLUSIONS

Multifrequency MRE of the parotid glands is feasible and reliable. This technique, therefore, is a promising method for investigating the viscoelastic properties of salivary gland tumors in future studies.

Quantitative Analysis and Pathological Basis of Signal Intensity on T2-Weighted MR Images in Benign and Malignant Parotid Tumors

Objective

To investigate the value of the signal intensity on T2-weighted magnetic resonance (MR) imaging using quantitative analysis in the differentiation of parotid tumors.

Materials and Methods

MR data of 80 pleomorphic adenomas (PAs), 68 Warthin tumors (WTs), and 34 malignant tumors (MTs) confirmed by surgery and histology were retrospectively analyzed. The signal intensities of tumor, normal parotid gland, spinal cord, and buccal subcutaneous fat were measured, and the signal intensity ratios (SIRs) between the tumor and the three references were calculated. Receiver operating characteristic curve was used to determine the optimal threshold and diagnostic efficiency of SIR for differentiating PAs, WTs, and MTs.

Results

The area under the curve (AUC) of tumor to parotid gland SIR (SIR_P), tumor to spinal cord SIR (SIR_C), and tumor to buccal subcutaneous fat SIR (SIR_F) for differentiating PAs and WTs was 0.922, 0.918, and 0.934, respectively. The sensitivity and specificity at an optimal SIR threshold were 86.3% and 91.2%, 80.0% and 97.1%, and 85.0% and 94.1%, respectively. The AUC of SIR_P, SIR_C, and SIR_F for distinguishing PAs from MTs was 0.793, 0.802, and 0.774, respectively. The sensitivity and specificity at an optimal SIR threshold was 86.3% and 61.8%, 80.0% and 73.5%, and 82.5% and 73.5%, respectively. The AUC of SIR_P, SIR_C, and SIR_F for distinguishing WTs from MTs was 0.716, 0.709, and 0.759, respectively. The sensitivity and specificity at an optimal SIR threshold were 61.8% and 82.4%, 55.9% and 82.4%, and 64.7% and 86.8%, respectively.

Conclusion

SIR_P, SIR_C, and SIR_F on T2-weighted MR images had high diagnostic efficiency for differentiating between PAs and WTs, while SIR_P and SIR_C for differentiating between PAs and MTs, and SIR_F for differentiating between WTs and MTs had relatively high diagnostic efficiency.