Parotid gland carcinoma: 32 years’ experience from a single institute

Parotid Gland Segmentation Using Purely Transformer-Based U-Shaped Network and Multimodal MRI

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.

Survival in Patients with Primary Parotid Gland Carcinoma after Surgery—Results of a Single-Centre Study

This study aims to analyse a single-centre cohort series of patients who underwent parotidectomy for primary malignant parotid tumours. A retrospective chart review of 64 consecutive patients treated from November 2010 to March 2022 was performed. Outcomes were analysed by Kaplan-Meier curves. Sixty-four patients with a primary parotid malignancy were included in the study, with one bilateral case in this cohort. Patients were classified as stage I–II in 39 cases and stage III–IV in 26 cases. The five-year overall survival (OS), disease-specific survival (DSS), local relapse-free survival (LRFS), and distant metastasis-free survival (DMFS) rates were 78.4%, 89%, 92.5%, and 87.1%, respectively. Univariate analysis showed that high-risk histology, stage IV disease, lymphovascular invasion, perineural invasion, node metastasis, skin involvement, facial nerve involvement, and positive or close margins were risk factors associated with poorer outcomes. At present, the best evidence suggests that radical surgery should be the standard approach, and adjuvant therapy, in terms of radiotherapy/chemoradiotherapy, is recommended in patients with risk factors.

Estimating survival after salvage surgery for recurrent salivary gland cancers: Systematic review

Recurrent salivary gland carcinomas (RSCs) are poorly characterized and their clinical features and treatment options have not yet been fully described. The goal of this study was to analyze the therapeutic strategies and oncological outcomes of RSC patients through a literature review analysis. This systematic review was performed according to the PRISMA statements. Inclusion criteria for the systematic review were based on the population, intervention, comparison, and outcomes according to (PICO) framework. Two thousand seven hundred and four records were selected and 1817 recurrences were studied. Three hundred and sixty-five patients underwent salvage surgery (20.1%) and their 5-year mortality rate, overall survival and disease-free survival were 35%, 70%, and 42%, respectively. RSCs are aggressive neoplasms with a high rate of distant metastases (28.9%). Salvage surgery can be considered in patients with limited local and/or regional recurrences, even in case of single distant relapse, appearing within the first 3 years of follow-up.

Nomogram Predicting Cancer-Specific Death in Parotid Carcinoma: a Competing Risk Analysis

Purpose

Multiple factors have been shown to be tied to the prognosis of individuals with parotid cancer (PC); however, there are limited numbers of reliable as well as straightforward tools available for clinical estimation of individualized mortality. Here, a competing risk nomogram was established to assess the risk of cancer-specific deaths (CSD) in individuals with PC.

Methods

Data of PC patients analyzed in this work were retrieved from the Surveillance, Epidemiology, and End Results (SEER) data repository and the First Affiliated Hospital of Nanchang University (China). Univariate Lasso regression coupled with multivariate Cox assessments were adopted to explore the predictive factors influencing CSD. The cumulative incidence function (CIF) coupled with the Fine-Gray proportional hazards model was employed to determine the risk indicators tied to CSD as per the univariate, as well as multivariate analyses conducted in the R software. Finally, we created and validated a nomogram to forecast the 3- and 5-year CSD likelihood.

Results

Overall, 1,467 PC patients were identified from the SEER data repository, with the 3- and 5-year CSD CIF after diagnosis being 21.4% and 24.1%, respectively. The univariate along with the Lasso regression data revealed that nine independent risk factors were tied to CSD in the test dataset (n = 1,035) retrieved from the SEER data repository. Additionally, multivariate data of Fine-Gray proportional subdistribution hazards model illustrated that N stage, Age, T stage, Histologic, M stage, grade, surgery, and radiation were independent risk factors influencing CSD in an individual with PC in the test dataset (p < 0.05). Based on optimization performed using the Bayesian information criterion (BIC), six variables were incorporated in the prognostic nomogram. In the internal SEER data repository verification dataset (n = 432) and the external medical center verification dataset (n = 473), our nomogram was well calibrated and exhibited considerable estimation efficiency.

Conclusion

The competing risk nomogram presented here can be used for assessing cancer-specific mortality in PC patients.

Predicting cancer-specific mortality in patients with parotid gland carcinoma by competing risk nomogram

BACKGROUND

The aim of the present study was to establish a competing risk nomogram to predict parotid gland cancer-specific mortality (PGC-SM).

METHODS

Seven thousand nine hundred and sixty-two patients extracted from SEER database were randomly categorized into training and validation sets. The competing risk model was used to identify factors associated with PGC-SM. The nomogram was evaluated via concordance indexes (C-indexes), calibration plots, and decision curve analysis (DCA).

RESULTS

Male, elderly, white, widowed, larger tumor, no surgery, advanced tumor grade, lymph node (LN) metastasis, adenocarcinoma (ADC), and higher TNM stage were associated with higher incidence of PGC-SM. Calibration plots showed that the nomogram was well calibrated. C-indexes for nomogram were 0.84 (95% CI: 0.81-0.86) and 0.84 (95% CI: 0.82-0.86) in training and validation sets, respectively. DCA demonstrated the clinical usefulness of nomogram.

CONCLUSIONS

The competing risk nomogram shows high performance in predicting PGC-SM, which might enable clinicians formulate suitable treatment protocols for patients with parotid gland carcinoma (PGC).

Impact of Changing Surgical Strategies on Clinical Outcomes in Patients with Parotid Carcinoma: A 53-Year Single-Institution Experience

Background and Objectives: We investigated the clinical outcomes of patients who underwent surgery for parotid carcinoma in a single institution during a 53-year period. This study aimed to estimate the impact of changing the surgical approach to parotid carcinoma on clinical outcomes including the incidence rate of the facial nerve palsy. Materials and Methods: Sixty-seven patients with parotid carcinoma who underwent surgery between 1966 and 2018 were retrospectively reviewed. Group A consisted of 29 patients who underwent surgery from 1966 to 2002, and Group B consisted of 38 patients from 2002 to 2018. Treatment outcomes were estimated. Additionally, candidate prognostic factors of Group B, the current surgical approach group, were evaluated. Results: Partial parotidectomy and total parotidectomy were performed in 35 and 32 patients, respectively. Partial parotidectomy was performed in 4 patients in Group A and 31 patients in Group B, with a predominant increase in Group B. The facial nerve was preserved in 43 patients, among whom 8 in Group A (8/17; 47.1%) and 7 in Group B (7/26; 26.9%) had temporary postoperative facial nerve palsy. Postoperative radiotherapy was performed on 35 patients. The 5-year OS, DSS, and DFS rates for Group A were 77.1%, 79.9%, and 71.5%, respectively. The 5-year OS, DSS, and DFS rates for Group B were 77.1%, 77.1%, and 72.4%, respectively. Clinical T4 stage, clinical N+ stage, stage IV disease, and tumor invasion of the facial nerve were independent prognostic factors in Group B. Conclusions: The incidence of facial nerve palsy in the current surgical approach group decreased compared with that in the previous surgical approach group. The current surgical management and treatment policies for parotid carcinoma have led to improved outcomes.

Pretherapeutic Predictive Factors for Histological High-Grade Parotid Gland Carcinoma

OBJECTIVE

The histological grade of parotid gland carcinoma (PGC) is an important prognostic factor; however, the diagnosis prior to treatment has been challenging to make. This study aimed to investigate whether the pretreatment clinical findings, including hematological inflammatory, nutritional, and immune markers, could predict the histological grade of PGC.

STUDY DESIGN

Retrospective study.

METHODS

We retrospectively enrolled 111 patients with PGC and evaluated the correlation between histological grade and pretreatment clinical findings such as age, sex, tumor staging, facial nerve paralysis, pain or tenderness, adhesion to the surrounding tissues or tumor immobility, and hematological markers.

RESULTS

Sixty patients (54%) were diagnosed with histological high-grade PGC. Univariate analysis revealed that age, T classification, N classification, TNM stage, facial nerve paralysis, adhesion/immobility, C-reactive protein (CRP), and CRP-to-albumin ratio (CAR) were significant predictors of PGC histological grade. On multivariate analysis, high T classification (T3, 4), high N classification (≥1), and elevated CRP (≥0.22 mg/dL) were independent predictors of high-grade PGC.

CONCLUSIONS

Pretreatment T classification, N classification, and CRP are significant predictors of the histological grading of PGC. Our results are useful for treatment planning and obtaining appropriate informed consent from the patients before treatment.

LEVEL OF EVIDENCE

4 Laryngoscope, 2021.

Survival outcomes in patients with parotid gland carcinoma treated with postoperative therapies using risk stratification

BACKGROUND

To evaluate the role of postoperative treatment in parotid gland carcinoma (PGC) based on risk stratification.

MATERIAL AND METHODS

A total of 301 PGC patients were retrospectively analyzed using risk stratification. The Kaplan-Meier method and Cox analysis were performed to conduct survival analysis.

RESULTS

In the high-risk group, those treated with postoperative radiotherapy (RT) had a better 5-year disease-free survival (DFS) than those treated with surgery alone. In the low-risk group, both surgery + RT and surgery +  chemotherapy (CT) significantly improved DFS when compared with surgery alone. Cox analysis showed that patients who underwent surgery + RT or surgery + CT had a lower risk of disease progression than those who underwent surgery alone in the low-risk group. In the high-risk group, patients who underwent surgery + RT had a lower risk of disease progression.

CONCLUSIONS

Postoperative RT showed considerable benefit in improving disease control in patients with PGC, even in those without high-risk factors.

Management of Salivary Gland Malignancy: ASCO Guideline

PURPOSE

To provide evidence-based recommendations for practicing physicians and other healthcare providers on the management of salivary gland malignancy.

METHODS

ASCO convened an Expert Panel of medical oncology, surgical oncology, radiation oncology, neuroradiology, pathology, and patient advocacy experts to conduct a literature search, which included systematic reviews, meta-analyses, randomized controlled trials, and prospective and retrospective comparative observational studies published from 2000 through 2020. Outcomes of interest included survival, diagnostic accuracy, disease recurrence, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations.

RESULTS

The literature search identified 293 relevant studies to inform the evidence base for this guideline. Six main clinical questions were addressed, which included subquestions on preoperative evaluations, surgical diagnostic and therapeutic procedures, appropriate radiotherapy techniques, the role of systemic therapy, and follow-up evaluations.

RECOMMENDATIONS

When possible, evidence-based recommendations were developed to address the diagnosis and appropriate preoperative evaluations for patients with a salivary gland malignancy, therapeutic procedures, and appropriate treatment options in various salivary gland histologies.Additional information is available at www.asco.org/head-neck-cancer-guidelines.

Texture analysis in the characterization of parotid salivary gland lesions: A study on MR diffusion weighted imaging

BACKGROUND AND PURPOSE

Parotid lesions show overlaps of morphological findings, apparent diffusion coefficient (ADC) values and types of time/intensity curve. This research aimed to evaluate the role of diffusion weighted imaging texture analysis in differentiating between benign and malignant parotid lesions and in characterizing pleomorphic adenoma (PA), Warthin tumor (WT), epithelial malignancy (EM), and lymphoma (LY).

METHODS

Texture analysis of 54 parotid lesions (19 PA, 14 WT, 14 EM, and 7 LY) was performed on ADC map images. An ANOVA test was used to estimate both the difference between benign and malignant lesions and the texture feature differences among PA, WT, EM, and LY. A P-value≤0.01 was considered to be statistically significant. A cut-off value defined by ROC curve analysis was found for each statistically significant texture parameter. The diagnostic accuracy was obtained for each texture parameter with AUC ≥ 0.5. The agreement between each texture parameter and histology was calculated using the Cohen's kappa coefficient.

RESULTS

The mean kappa values were 0.61, 0.34, 0.26, 0.17, and 0.48 for LY, EM, WT, PA, and benign vs. malignant lesions respectively. Long zone emphasis cut-off values >1.870 indicated EM with an accuracy of 81 % and values >2.630 revealed LY with an accuracy of 93 %. Long run emphasis values >1.050 and >1.070 indicated EM and LY with a diagnostic accuracy of 79% and 93% respectively.

CONCLUSIONS

Long zone emphasis and long run emphasis texture parameters allowed the identification of LY and the differentiation between benign and malignant lesions. WT and PA were not accurately recognized.