OBJECTIVE: To provide surgical references for selecting appropriate parotidectomy incisions, reviewing modified approaches, incision designs, and associated complications.
METHODS: We have systematically searched 5 medical literature databases examining parotidectomy incision designs and postoperative complications from 2008 to 2021.
RESULTS: There are a total of 9 novel incision designs: 1) posterior auricular hairline incision (PAHI); 2) combined preauricular and retroauricular incision (CPRI); 3) V-shaped incision (VI); 4) N-shaped incision (NI); 5) postaural incision (PI); 6) preauricular crutch incision (PCI); and 7) endaural incision (EI). Simultaneously, there are a total of 8 postoperative complications: 1) infection; 2) salivary fistula; 3) facial nerve palsy/paresis; 4) ear lobule numbness; 5) Frey syndrome; 6) facial deformity; 7) hematoma; and 8) tumor reoccurrence.
CONCLUSIONS: Over the last decade, a surge in modified parotidectomy incisions has been witnessed in clinical practice. This expansion is attributed to rapid technical advancements and a deeper understanding of anatomy and histopathology. These modified approaches contribute significantly to improving cosmetic outcomes, minimizing associated complications, and enhancing patient satisfaction.

BACKGROUND: Salivary duct carcinoma (SDC) is an aggressive form of cancer, with cutaneous metastasis being a rare occurrence. Furthermore, cutaneous metastasis of SDC secondary to a scald is even rarer, and to the best of our knowledge, our case represents the first such instance. Considering the involvement of the fingers in the metastatic site, which may affect limb function and quality of life, we present this case to explore the reason why scald could lead to distant recurrence and better treatment options.
METHODS: An 85-year-old man diagnosed with SDC in the parotid gland found enlarged masses at the fingertips as a consequence of a burn, 6 years after his initial treatment.
METHODS: Cutaneous metastasis of SDC in the parotid gland and left thumb loss due to surgery.
METHODS: Radiotherapy was offered, targeting at the masses on the fingers, with dose at 15 Gy in 3 fractions, 12 Gy in 3 fractions, 15 Gy in 3 fractions for both hands and additional 21 Gy in 7 fractions only for left hand.
RESULTS: The tumors shrank after 2 months of radiotherapy and the patient recovered well. Side effects included nail hyperplasia and paronychia.
CONCLUSIONS: Connections between scald and distant metastasis of malignant tumors in this case needed further investigation. Considering reserving function of the fingers while dealing with metastasis, radiotherapy is recommended rather than surgery.

OBJECTIVE: To summarize the ultrasound, CT and MRI manifestations of Warthin-like mucoepidermoid carcinoma (WT-MEC), and to explore its imaging characteristics, so as to provide reference for clinical and preoperative diagnosis.
METHODS: The clinical information and imaging data of ultrasound, CT and MRI of 12 patients with WT-MEC diagnosed by pathology in Shanghai Ninth People\'s Hospital, Shanghai Jiao Tong University School of Medicine from January 2017 to December 2021 were collected, and their specific characteristics were retrospectively summarized.
RESULTS: Among the 12 WT-MEC patients, there were 7 males and 5 females, with an average age of (42.7±16) years. Seven cases underwent ultrasound examination, 6 cases underwent CT examination, and 2 cases underwent MRI examination. Radiologically, all the lesions presented as a solitary mass. 11/12 lesions(91.7%) were identified as well-defined margins, and 10/12(83.3%) as solid-cystic masses. All solid-cystic lesions contained multiple cystic areas with variable sizes. On US images, most lesions showed mixed-echoic echogenicity(5/7, 71.4%), poor vascularization (6/7, 85.7%) and acoustic enhancement (6/7, 85.7%). CT revealed all the lesions (6/6, 100%) as a soft-tissue mass with heterogeneous enhancement (5/6, 83.3%). MRI imaging demonstrated the neoplasm with low or iso-signal intensity on plain T1WI and hyperintensity on T2WI. The heterogeneous enhancement was shown on contrast-enhanced T1WI.
CONCLUSIONS: Most WT-MECs represent as a solitary, well-defined, solid-cystic mass in the parotid gland. The neoplasm may be characterized by the multiple and variable-sized cystic components within the tumor.

BACKGROUND: Parotid gland carcinoma (PGC) is a rare malignant tumor. The purpose of this study was to investigate the role of immune-inflammatory-nutrition indicators and age-adjusted Charlson comorbidity index score (ACCI) of PGC and develop the nomogram model for predicting prognosis.
METHODS: All patients diagnosed with PGC in two tertiary hospitals, treated with surgical resection, from March 2012 to June 2018 were obtained. Potential prognostic factors were identified by univariate and multivariate Cox regression analyses. The nomogram models were established based on these identified independent prognostic factors. The performance of the developed prognostic model was estimated by related indexes and plots.
RESULTS: The study population consisted of 344 patients with PGC who underwent surgical resection, 285 patients without smoking (82.8%), and 225 patients (65.4%) with mucoepidermoid carcinoma, with a median age of 50.0 years. American Joint Committee on Cancer (AJCC) stage (p < 0.001), pathology (p = 0.019), tumor location (p < 0.001), extranodal extension (ENE) (p < 0.001), systemic immune-inflammation index (SII) (p = 0.004), prognostic nutrition index (PNI) (p = 0.003), ACCI (p < 0.001), and Glasgow prognostic Score (GPS) (p = 0.001) were independent indicators for disease free survival (DFS). Additionally, the independent prognostic factors for overall survival (OS) including AJCC stage (p = 0.015), pathology (p = 0.004), tumor location (p < 0.001), perineural invasion (p = 0.009), ENE (p < 0.001), systemic immune-inflammation index (SII) (p = 0.001), PNI (p = 0.001), ACCI (p = 0.003), and GPS (p = 0.033). The nomogram models for predicting DFS and OS in PGC patients were generated based on these independent risk factors. All nomogram models show good discriminative capability with area under curves (AUCs) over 0.8 (DFS 0.802, and OS 0.825, respectively). Decision curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification index (NRI) show good clinical net benefit of the two nomograms in both training and validation cohorts. Kaplan-Meier survival analyses showed superior discrimination of DFS and OS in the new risk stratification system compared with the AJCC stage system. Finally, postoperative patients with PGC who underwent adjuvant radiotherapy had a better prognosis in the high-, and medium-risk subgroups (p < 0.05), but not for the low-risk subgroup.
CONCLUSIONS: The immune-inflammatory-nutrition indicators and ACCI played an important role in both DFS and OS of PGC patients. Adjuvant radiotherapy had no benefit in the low-risk subgroup for PGC patients who underwent surgical resection. The newly established nomogram models perform well and can provide an individualized prognostic reference, which may be helpful for patients and surgeons in proper follow-up strategies.

OBJECTIVE: To investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation.
METHODS: From January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong\'s test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application.
RESULTS: Age and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145).
CONCLUSIONS: ECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

Objective: To establish patient-derived organoid models of pleomorphic adenomas (PA) of the parotid gland and preliminarily characterize their histology, related biomarkers and functions. Methods: Fresh tumor tissue specimens were collected from surgical procedures of Oral and Maxillofacial Department. The harvested tissues were processed and cultured in a head and neck tumor organoid culture system to establish organoid models from parotid gland pleomorphic adenomas. The in vitro growth of PA organoids was recorded by light microscopy. The successfully established organoids were passaged and cryopreserved, and the cryopreserved PA organoids were revived and re-cultured to observe their viability and organoid regeneration ability. Histological characterization, as well as characterization and detection of related markers and functional proteins, were performed on the organoids, comparing them with the patient-derived tissues. Results: The constructed organoid model of pleomorphic adenoma exhibited a dense and compact three-dimensional spherical structure. Hematoxylin and eosin staining indicated morphological similarities between the organoid and its tissue of origin. Immunohistochemistry showed positive cytoplasmic staining for Calponin, cytokeratin 7, and epithelial membrane antigen in both the organoid and the source tumor tissue, suggesting consistent histopathological characteristics between the organoid and its tissue of origin. Periodic acid-Schiff staining of the organoid showed positive staining for glycogen, with positive staining located in the interior and periphery of the organoid, indicating that the organoid possessed secretory functions like the salivary gland. Conclusions: This study successfully constructed organoids of pleomorphic adenoma derived from patient samples. This model faithfully replicates the tissue morphology and biomarkers of the source tissue and exhibits biological functions associated with mucus secretion. It serves as a valuable in vitro model for studying the development and progression of salivary gland tumors.
目的： 构建患者来源腮腺多形性腺瘤（PA）类器官模型，并对其组织学、相关标志物和功能进行初步表征。 方法： 收集大连大学附属中山医院口腔颌面外科术中取材新鲜肿瘤组织标本，采用头颈部肿瘤类器官培养体系进行体外培养，构建腮腺PA类器官。观察PA类器官的体外生长情况并进行光镜拍摄。对培养成功的类器官进行传代和冻存，并对冻存的PA类器官进行复苏再培养，观测其活性和PA类器官再形成能力。对比患者来源组织，对PA类器官进行组织学表征，相关标志和功能蛋白进行表征与检测，评价PA类器官对来源组织的复现性。 结果： 构建的腮腺PA类器官形成紧实致密球状结构，HE染色提示类器官与其来源组织形态相似，免疫组化可见类器官及其来源肿瘤组织钙调蛋白、细胞角蛋白7、上皮膜抗原胞质阳性，提示类器官与其来源组织的病理学特征一致；PA类器官过碘酸希夫（PAS）染色及淀粉酶消化后PAS染色呈阳性，阳性着色位于类器官球体内部及外周，提示PA类器官具有类似于腮腺的分泌功能。 结论： 成功构建患者来源PA类器官，该模型在组织形态和标志物上可高度复现来源组织情况，并具有黏液分泌的生物学功能，是研究腮腺肿物发生发展的良好体外模型。.

BACKGROUND: Lymph node (LN) status is an important prognostic factor for parotid gland cancer (PGC). This study aimed to analyze the impact of extranodal extension (ENE) of intraparotid LN and LN metastasis burden on survival in PGC.
METHODS: Patients with surgically treated PGC and at least one metastatic cervical LN were retrospectively enrolled. Primary outcome variables were distant metastasis-free survival (DMFS), disease-specific survival (DSS), and overall survival (OS). The impact of ENE and LN metastasis burden was assessed using the Cox model.
RESULTS: A total of 292 patients were included. ENE in cervical or intraparotid LN was not associated with DMFS, DSS, or OS. Intraparotid LN metastasis had a significant impact on prognosis, and the presence of only one metastatic intraparotid LN offered an approximately 1.5-fold risk of distant metastasis. Prognostic models based on the number of positive LNs (1 vs. 2-3 vs. 4+) were superior to the AJCC N stage in terms of DMFS, DSS, and OS.
CONCLUSIONS: ENE of cervical or intraparotid LN has a limited effect on the prognosis of PGC, and the number of positive LNs is better than the AJCC N stage in LN status evaluation.

Intraductal papillomas have been mostly described in minor salivary glands but are extremely rare in the parotid gland. Consequently, limited information is available to guide otolaryngologists and pathologists in managing intraductal papillomas, specifically in the parotid gland. Diagnosing intraductal papillomas in this location poses significant challenges. In this report, the authors present a new case and first conduct a systematic literature review of the intraductal papillomas originating from the parotid gland. This study contributes valuable insights that can improve diagnostic accuracy, providing more precise treatments, and patient outcomes in cases of intraductal papillomas in the parotid gland.

Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Segmentation of parotid glands and tumors on magnetic resonance images is essential in accurately diagnosing and selecting appropriate surgical plans. However, segmentation of parotid glands is particularly challenging due to their variable shape and low contrast with surrounding structures. Recently, deep learning has developed rapidly, and Transformer-based networks have performed well on many computer vision tasks. However, Transformer-based networks have yet to be well used in parotid gland segmentation tasks. We collected a multi-center multimodal parotid gland MRI dataset and implemented parotid gland segmentation using a purely Transformer-based U-shaped segmentation network. We used both absolute and relative positional encoding to improve parotid gland segmentation and achieved multimodal information fusion without increasing the network computation. In addition, our novel training approach reduces the clinician\'s labeling workload by nearly half. Our method achieved good segmentation of both parotid glands and tumors. On the test set, our model achieved a Dice-Similarity Coefficient of 86.99%, Pixel Accuracy of 99.19%, Mean Intersection over Union of 81.79%, and Hausdorff Distance of 3.87. The purely Transformer-based U-shaped segmentation network we used outperforms other convolutional neural networks. In addition, our method can effectively fuse the information from multi-center multimodal MRI dataset, thus improving the parotid gland segmentation.

BACKGROUND: To develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis.
METHODS: A total of 2211 ultrasound images of 980 pathologically confirmed PTs (Training set: n = 721; Validation set: n = 82; Internal-test set: n = 89; External-test set: n = 88) from 907 patients were retrospectively included in this study. The optimal model was selected and the diagnostic performance evaluation is conducted by utilizing the area under curve (AUC) of the receiver-operating characteristic(ROC) based on five different DL networks constructed at varying depths. Furthermore, a comparison of different seniority radiologists was made in the presence of the optimal auxiliary diagnosis model. Additionally, the diagnostic confusion matrix of the optimal model was calculated, and an analysis and summary of misjudged cases\' characteristics were conducted.
RESULTS: The Resnet18 demonstrated superior diagnostic performance, with an AUC value of 0.947, accuracy of 88.5%, sensitivity of 78.2%, and specificity of 92.7% in internal-test set, and with an AUC value of 0.925, accuracy of 89.8%, sensitivity of 83.3%, and specificity of 90.6% in external-test set. The PTs were subjectively assessed twice by six radiologists, both with and without the assisted of the model. With the assisted of the model, both junior and senior radiologists demonstrated enhanced diagnostic performance. In the internal-test set, there was an increase in AUC values by 0.062 and 0.082 for junior radiologists respectively, while senior radiologists experienced an improvement of 0.066 and 0.106 in their respective AUC values.
CONCLUSIONS: The DL model based on ultrasound images demonstrates exceptional capability in distinguishing between benign and malignant PTs, thereby assisting radiologists of varying expertise levels to achieve heightened diagnostic performance, and serve as a noninvasive imaging adjunct diagnostic method for clinical purposes.