Ultrasound-guided core biopsy in the diagnosis of parotid neoplasia: an overview and update with a review of the literature

Application of the Milan system for reporting salivary gland cytopathology to core needle biopsies of the parotid gland

AIMS

The Milan system for reporting salivary gland cytopathology was developed by an international group of experts and first published in 2018 with the goal to standardise reporting of salivary gland aspirates. Seven categories with distinct risks of malignancy were proposed. Core needle biopsies (CNB) of salivary glands are also common, but reporting lacks standardisation. Here we explore the feasibility of a Milan-like reporting system on CNB of the parotid gland.

METHODS AND RESULTS

Our laboratory information system was searched for parotid gland CNBs from 2010 to 2021. Reports were translated into a Milan-like reporting system. When available, CNB findings were correlated with cytology and resection specimens. In order to compare the performance of CNB with fine-needle aspirations (FNA), we established a second cohort of cases consisting of parotid FNA with surgical follow-up. The risk of neoplasia (RON) and risk of malignancy (ROM) was calculated for FNA and CNB Milan categories using cases with follow-up resection. We analysed 100 cases of parotid gland CNB. Of these cases, 32 underwent subsequent resection, while 52 had concurrent FNA. A total of 20 cases had concurrent FNA and underwent follow-up resection. In 63 (63%) cases, a specific diagnosis was provided on CNB, with 18 cases undergoing follow-up resection having an accuracy rate of 94%.

CONCLUSIONS

This study confirms the feasible of using a Milan-like system in the setting of parotid gland CNB with differentiation in RON and ROM. CNB allows assessment of architectural features that may allow more specific diagnoses in some cases.

Hub biomarkers in ultrasound-guided bladder cancer and osteosarcoma: Myosin light chain kinase and caldesmon

Bladder cancer and osteosarcoma are 2 types of cancers that originate from epithelial tissues inside the bladder and bone or muscle tissues. Ultrasound-guided biopsies provide crucial support for the diagnosis and treatment of bladder cancer and osteosarcoma. However, the relationship between myosin light chain kinase (MYLK) and caldesmon (CALD1) and bladder cancer and osteosarcoma remains unclear. The bladder cancer datasets GSE65635 and GSE100926, the osteosarcoma dataset GSE39058, were obtained from gene expression omnibus. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis. Gene expression heat map was drawn and immune infiltration analysis was performed. The comparative toxicogenomics database analysis were performed to find disease most related to core gene. Western blotting experiments were performed. TargetScan screened miRNAs that regulated central DEGs. We obtained 54 DEGs. Functional enrichment analysis revealed significant enrichment in terms of cellular differentiation, cartilage development, skeletal development, muscle actin cytoskeleton, actin filament, Rho GTPase binding, DNA binding, fibroblast binding, MAPK signaling pathway, apoptosis, and cancer pathways. Gene set enrichment analysis indicated that DEGs were primarily enriched in terms of skeletal development, cartilage development, muscle actin cytoskeleton, MAPK signaling pathway, and apoptosis. The immune infiltration analysis showed that when T cells regulatory were highly expressed, Eosinophils exhibited a similar high expression, suggesting a strong positive correlation between T cells regulatory and Eosinophils, which might influence the disease progression in osteosarcoma. We identified 6 core genes (SRF, CTSK, MYLK, VCAN, MEF2C, CALD1). MYLK and CALD1 were significantly correlated with survival rate and exhibited lower expression in bladder cancer and osteosarcoma samples compared to normal samples. Comparative toxicogenomics database analysis results indicated associations of core genes with osteosarcoma, bladder tumors, bladder diseases, tumors, inflammation, and necrosis. The results of Western blotting showed that the expression levels of MYLK and CALD1 in bladder cancer and osteosarcoma were lower than those in normal tissues. MYLK and CALD1 likely play a role in regulating muscle contraction and smooth muscle function in bladder cancer and osteosarcoma. The lower expression of MYLK and CALD1 is associated with poorer prognosis.

Current management and future challenges in salivary glands cancer

Salivary gland cancers (SGCs) are rare, accounting for less than 5% of all malignancies of the head and neck region, and are morphologically heterogeneous. The diagnosis is mainly based on histology, with the complementary aid of molecular profiling, which is helpful in recognizing some poorly differentiated, borderline, or atypical lesions. Instrumental imaging defines the diagnosis, representing a remarkable tool in the treatment plan. Ultrasound and magnetic resonance are the most common procedures used to describe the primary tumour. The treatment of SGCs is multimodal and consists of surgery, radiotherapy, and systemic therapy; each treatment plan is, however, featured on the patient and disease's characteristics. On 24 June 2022, in the meeting "Current management and future challenges in salivary gland cancers" many experts in this field discussed the state of the art of SGCs research, the future challenges and developments. After the meeting, the same pool of experts maintained close contact to keep these data further updated in the conference proceedings presented here. This review collects the insights and suggestions that emerged from the discussion during and after the meeting per se.

CT-based radiomics with various classifiers for histological differentiation of parotid gland tumors

Objective

This study assessed whether radiomics features could stratify parotid gland tumours accurately based on only noncontrast CT images and validated the best classifier of different radiomics models.

Methods

In this single-centre study, we retrospectively recruited 249 patients with a diagnosis of pleomorphic adenoma (PA), Warthin tumour (WT), basal cell adenoma (BCA) or malignant parotid gland tumours (MPGTs) from June 2020 to August 2022. Each patient was randomly classified into training and testing cohorts at a ratio of 7:3, and then, pairwise comparisons in different parotid tumour groups were performed. CT images were transferred to 3D-Slicer software and the region of interest was manually drawn for feature extraction. Feature selection methods were performed using the intraclass correlation coefficient, t test and least absolute shrinkage and selection operator. Five common classifiers, namely, random forest (RF), support vector machine (SVM), logistic regression (LR), K-nearest neighbours (KNN) and general Bayesian network (Gnb), were selected to build different radiomics models. The receiver operating characteristic curve, area under the curve (AUC), accuracy, sensitivity, specificity and F-1 score were used to assess the prediction performances of these models. The calibration of the model was calculated by the Hosmer–Lemeshow test. DeLong’s test was utilized for comparing the AUCs.

Results

The radiomics model based on the RF, SVM, Gnb, LR, LR and RF classifiers obtained the highest AUC in differentiating PA from MPGTs, WT from MPGTs, BCA from MPGTs, PA from WT, PA from BCA, and WT from BCA, respectively. Accordingly, the AUC and the accuracy of the model for each classifier were 0.834 and 0.71, 0.893 and 0.79, 0.844 and 0.79, 0.902 and 0.88, 0.602 and 0.68, and 0.861 and 0.94, respectively.

Conclusion

Our study demonstrated that noncontrast CT-based radiomics could stratify refined pathological types of parotid tumours well but could not sufficiently differentiate PA from BCA. Different classifiers had the best diagnostic performance for different parotid tumours. Our study findings add to the current knowledge on the differential diagnosis of parotid tumours.

Current Salivary Glands Biopsy Techniques: A Comprehensive Review

Biopsy is a surgical procedure performed to collect a portion of tissue or organ for diagnostic studies. The aim of the present manuscript is to describe state-of-the-art major and minor salivary gland biopsy techniques and assess the indications and complications of other salivary gland biopsy techniques. A search was performed using the following MeSH terms: biopsy, fine-needle biopsies, image-guided biopsies, frozen sections, and salivary glands disease. A current overview of major and minor salivary glands biopsy techniques was provided. In the oncological field, a comparison was made between the most widely used biopsy method, ultrasound-guided fine-needle aspiration biopsy (US-FNAB), and an alternative method, ultrasound-guided core needle biopsy (US-guided CNB), highlighting the advantages and disadvantages of each. Finally, intra-operative frozen sections (IOFSs) were presented as an additional intraoperative diagnostic method. Minor salivary gland biopsy (MSGB) is the simplest diagnostic method used by clinicians in the diagnosis of inflammatory and autoimmune diseases. In neoplastic lesions, US-FNAB represents the most performed method; however, due to its low diagnostic accuracy for non-neoplastic specimens, US-guided CNB has been introduced as an alternative method.

Multiphasic CT-Based Radiomics Analysis for the Differentiation of Benign and Malignant Parotid Tumors

Objective

This study aims to investigate the value of machine learning models based on clinical-radiological features and multiphasic CT radiomics features in the differentiation of benign parotid tumors (BPTs) and malignant parotid tumors (MPTs).

Methods

This retrospective study included 312 patients (205 cases of BPTs and 107 cases of MPTs) who underwent multiphasic enhanced CT examinations, which were randomly divided into training (N = 218) and test (N = 94) sets. The radiomics features were extracted from the plain, arterial, and venous phases. The synthetic minority oversampling technique was used to balance minority class samples in the training set. Feature selection methods were done using the least absolute shrinkage and selection operator (LASSO), mutual information (MI), and recursive feature extraction (RFE). Two machine learning classifiers, support vector machine (SVM), and logistic regression (LR), were then combined in pairs with three feature selection methods to build different radiomics models. Meanwhile, the prediction performances of different radiomics models based on single phase (plain, arterial, and venous phase) and multiphase (three-phase combination) were compared to determine which model construction method and phase were more discriminative. In addition, clinical models based on clinical-radiological features and combined models integrating radiomics features and clinical-radiological features were established. The prediction performances of the different models were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and the drawing of calibration curves.

Results

Among the 24 established radiomics models composed of four different phases, three feature selection methods, and two machine learning classifiers, the LASSO-SVM model based on a three-phase combination had the optimal prediction performance with AUC (0.936 [95% CI = 0.866, 0.976]), sensitivity (0.78), specificity (0.90), and accuracy (0.86) in the test set, and its prediction performance was significantly better than with the clinical model based on LR (AUC = 0.781, p = 0.012). In the test set, the combined model based on LR had a lower AUC than the optimal radiomics model (AUC = 0.933 vs. 0.936), but no statistically significant difference (p = 0.888).

Conclusion

Multiphasic CT-based radiomics analysis showed a machine learning model based on clinical-radiological features and radiomics features has the potential to provide a valuable tool for discriminating benign from malignant parotid tumors.