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. 2022 Jul 15;13(1):119.
doi: 10.1186/s13244-022-01256-x.

Morphologic CT and MRI features of primary parotid squamous cell carcinoma and its predictive factors for differential diagnosis with mucoepidermoid carcinoma

Xiaohua Ban #  1 , Huijun Hu #  2 , Yue Li  1 , Lingjie Yang  2 , Yu Wang  2 , Rong Zhang  1 , Chuanmiao Xie  1 , Cuiping Zhou  3 , Xiaohui Duan  4
Affiliations

Morphologic CT and MRI features of primary parotid squamous cell carcinoma and its predictive factors for differential diagnosis with mucoepidermoid carcinoma

Xiaohua Ban et al. Insights Imaging. .

Abstract

Background: Primary parotid squamous cell carcinoma (SCC) is a rare entity with a poor prognosis. Pathologically, the diagnosis of it requires the exclusion of parotid mucoepidermoid carcinoma (MEC). Currently, the imaging features of primary parotid SCC and the predictive indicators for differential diagnosis of the two entities have not been well reported. Our purpose was to identify the imaging characteristics of primary parotid SCC and to determine the predictive factors for its' differential diagnosis.

Results: Thirty-one participants with primary parotid SCC and 59 with primary parotid MEC were enrolled. Clinical, CT and MRI features were reviewed and compared by univariate analysis. Then, multinomial logistic regression was used to determine the predictors to distinguish parotid SCC from MEC. Most primary parotid SCCs exhibited irregular shape, ill-defined margin, incomplete or no capsule, heterogeneous and marked or moderate enhancement, necrosis, local tumor invasiveness (LTI). Age, maximal dimension, shape, degree of enhancement, gradual enhancement, necrosis, and LTI were different between the primary parotid SCCs and MECs in univariate analysis (p < 0.05). While in multinomial logistic regression analysis, only age and necrosis were the independent predictors for distinguishing parotid SCC from MEC, and this model exhibited an area under curve of 0.914 in ROC curve analysis.

Conclusions: Primary parotid SCC has some distinct imaging features including the large tumor size, irregular shape, ill-defined margin, and particularly the marked central necrosis. Patients with age ≥ 51.5 years and necrosis on the image of the primary tumor in the parotid gland could be more likely to be SCCs than MECs.

Keywords: Diagnosis; Imaging; Parotid gland; Predictive; Primary; Squamous cell carcinomas.

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Conflict of interest statement

All the authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
A 70 years old patient with primary parotid SCC in the right parotid gland. Axial T2WI (A) and T1WI (B) show a well-defined mass in the superficial part of the right parotid gland exhibiting a hypointense rim with central hyperintensity on T2WI, hypointense on T1WI (arrow). Contrast-enhanced axial (C) and coronal (D) T1WI show heterogeneous ring enhancement with severe central necrosis (arrow)
Fig. 2
Fig. 2
A 37 years old female with primary parotid SCC in the left parotid gland. Axial T2WI (A) and coronal T2WI (B) show an ill-defined, irregular mass in the left parotid gland. The tumor is slightly hypointense with multiple small focal areas of obvious hyperintensity on T2WI (arrow). Contrast-enhanced axial (C) and coronal (D) T1WI show obvious heterogeneous enhancement with multiple small focal areas of necrosis (arrow)
Fig. 3
Fig. 3
A 65 years old male with primary parotid SCC in the right parotid gland. Axial non-contrast CT (A) shows an ill-defined, lobulated and hypodense lesion in the superficial part of the right parotid gland (arrow). Contrast-enhanced CT (B) demonstrates moderate rim enhancement with severe central necrosis (arrow)
Fig. 4
Fig. 4
A 57 years old male with primary parotid MEC in the right parotid gland. Axial T2WI (A) and T1WI (B) show a well-defined, oval mass in the superficial part of the right parotid gland (arrow). The mass is hypointense on T2WI, and hypointense on T1WI. Contrast-enhanced axial (C) T1WI shows the tumor is homogeneous enhancement without necrosis (arrow)
Fig. 5
Fig. 5
The area under the ROC curve of multivariate logistic regression model was 0.914
See this image and copyright information in PMC

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