Accuracy of FNAC and CT in the differentiation of benign and malignant parotid tumours in a case series

Development and validation of CT-based radiomics nomogram for the classification of benign parotid gland tumors

PURPOSE

Accurate preoperative diagnosis of parotid tumor is essential for the formulation of optimal individualized surgical plans. The study aims to investigate the diagnostic performance of radiomics nomogram based on contrast-enhanced computed tomography (CT) images in the differentiation of the two most common benign parotid gland tumors.

METHODS

One hundred and ten patients with parotid gland tumors including 76 with pleomorphic adenoma (PA) and 34 with adenolymphoma (AL) confirmed by histopathology were included in this study. Radiomics features were extracted from contrast-enhanced CT images of venous phase. A radiomics model was established and a radiomics score (Rad-score) was calculated. Clinical factors including clinical data and CT features were assessed to build a clinical factor model. Finally, a nomogram incorporating the Rad-score and independent clinical factors was constructed. Receiver operator characteristics (ROC) curve was generated and the area under the ROC curve (AUC) was calculated to quantify the discriminative performance of each model on both the training and validation cohorts. Decision curve analysis (DCA) was conducted to evaluate the clinical usefulness of each model.

RESULTS

The radiomics model showed good discrimination in the training cohort [AUC, 0.89; 95% confidence interval (CI), 0.80-0.98] and validation cohort (AUC, 0.89; 95% CI, 0.77-1.00). The radiomics nomogram showed excellent discrimination in the training cohort (AUC, 0.98; 95% CI, 0.96-1.00) and validation cohort (AUC, 0.95; 95% CI, 0.88-1.00) and displayed better discrimination efficacy compared with the clinical factor model (AUC, 0.93; 95% CI, 0.88-0.99) in the training cohort (p < 0.05). The DCA demonstrated that the combined radiomics nomogram provided superior clinical usefulness than clinical factor model and radiomics model.

CONCLUSIONS

The CT-based radiomics nomogram combining Rad-score and clinical factors exhibits excellent predictive capability for differentiating parotid PA from AL, which might hold promise in assisting radiologists and clinicians in the exact differential diagnosis and formulation of appropriate treatment strategy.

Oncological outcomes of preoperatively unexpected malignant tumors of the parotid gland

PURPOSE

Unexpected parotid cancers are often encountered due to inaccuracies in the preoperative evaluation. This study aimed to examine the clinical characteristics and oncological outcomes of these cancers and to propose the appropriate management strategy.

METHODS

This is a multicenter case series study in which a total of 302 patients were diagnosed postoperatively with parotid cancers between 2003 and 2017. Of these, 85 cases without evidence of malignancy prior to surgery but identified as malignant on postoperative pathology were included.

RESULTS

Of 85 patients, 76 and 9 underwent superficial and total parotidectomy, respectively. A positive resection margin was present in 24.7% of the cases. Postoperative radiotherapy was administered to 43.6% of patients; 4.2% had a local recurrence, and no patients died of the disease. The 5-year overall and relapse-free survival rates were 100.0% and 95.2%, respectively. Patients who underwent piecemeal resection had significantly poorer oncologic outcomes. Age, sex, histologic grade, T stage, extracapsular extension, resection margin status, and postoperative radiotherapy did not affect recurrence and survival.

CONCLUSION

Preoperatively unexpected parotid cancers had excellent local control and overall survival despite positive or close resection margin, with or without postoperative radiotherapy. Therefore, patients with unexpected parotid malignancies may benefit from less aggressive postoperative management option.