Clinical analysis of submandibular triangle masses in the past 10 years

Clinical analysis of submandibular triangle masses in the past 10 years | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Clinical analysis of submandibular triangle masses in the past 10 years Donghai Huang, Yu Wu, Zhiying He This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3860361/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives Lack of retrospective studies on submandibular triangle masses with large Chinese sample. Methods Basic demographic informations, history, physical examination, imaging data and histopathological results of 608 patients who underwent surgery in submandibular triangle in Xiangya Hospital of Central South University from January 2009 to June 2019 were collected. Statistical analysis were performed. Differences between malignant and benign masses were assessed by univariate and multivariate analysis. Results 405 males and 203 females were included. The average age was 43.17 ± 19.6 years old (range from 1–80). Congenital masses, inflammatory masses and tumors accounted for 2.6%, 63.5%, 33.9%, respectively. Benign tumors ,borderline tumors ,malignant tumors accounted for 48.4%, 1.6%, 50.0%, respectively. Pleomorphic adenoma and lymphoma were the most common benignancy and malignancy. Metastatic tumors were mostly originated from the head and neck cancers. Univariate analysis showed that there were significantly differences in gender, age, smoking, drinking, chewing betel nut, characteristics of the masses (pain, mobility, texture), and cervical lymph nodes. Multivariate analysis showed that age, drinking and chewing betel nut were high risk factors for malignancy. Conclusion Comprehensive analysis of the clinical parameters was helpful for preopreative diagnosis of submandibular triangle masses. Health sciences/Diseases/Cancer Health sciences/Diseases/Oral diseases Health sciences/Oncology/Surgical oncology Submandibular triangle masses malignant tumor benign tumor preopreative examination diagnosis Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The submandibular triangle, also referred to as the submandibular region, is an area surrounded by the anterior and posterior abdomen of the digastric muscle and the lower margin of the mandible, with the submandibular gland as the base, reaching the level of the hyoid bone( 1 – 3 ). The anatomy of the submandibular region is complex, including submandibular glands, lymph nodes, adipose tissue, muscle tissue, nerves and vessels, etc. In addition, any pathological changes of submandibular gland, parotid gland, sublingual gland, mandible or lymphoid tissue can cause swellings in the submandibular triangle. Glandular diseases account for the majority of pathologies in submandibular triangle( 3 ). Surgery is the first choice for most submandibular triangle masses, and it is necessary to distinguish lesions in this region. Malignant tumors and metastases usually received aggressive tumor resections, with possible sacrifice of surrounding functional structures, further treatment like radiotherapy or chemotherapy, and further follow up ( 4 ). In contrast, benign lesions always have limited excision of lesions and the surrounding functional structures were preserved. Surgery scope and procedures were different between benign and malignant tumors( 3 , 5 , 6 ). At present, pre-operate diagnosis is mainly based on history, physical examination and imaging examination ( 3 , 5 ), which is empirical and inefficient. Despite a lot of studies on distinguishing masses in the submandibular triangle, there haven’t been a reliable and comprehensive one so far. A certain number of submandibular triangle tumors, including benign and malignant tumors, only present as asymptomatic masses ( 3 , 5 ). Literatures have shown that characteristics like pain, fixing to the skin or deep tissue and rapid growth are more common in malignant tumors, but there was no reliable evidence to confirm( 1 , 7 ). Because of various pathological types and the similarity in symptom and clinical manifestation, it is relatively difficult to identify masses in this region before operation, which makes challenging to individualized diagnosis and treatment( 6 , 8 ). MRI and CT images can clearly show relationship between tumors and surrounding healthy tissues, which contributes to distinguishing benign tumors from malignant tumors( 3 ). Ultrasonography is the most widely used examination of superficial tumors, with the advantages of non-invasive, rapid, and cheap. The research of multimodal ultrasonographic algorithm in the differentiation of submandibular masses and parotid gland tumors ( 4 , 9 ) were effectively validated. Thyroid Imaging Reporting and Data System (TI-RADS) is a relatively reliable standard for preliminary diagnosis of thyroid gland diseases, and ultrasound features are also helpful for the diagnosis of benign and malignant breast nodules( 10 , 11 ). This study intends to summarize the clinical data including masses characteristics, imaging data and final pathological results of submandibular triangle masses through a retrospective study with a large sample. RESULTS 1 Patient characteristics There were 608 cases, with a male-to-female ratio of about 2:1. They were aged from 1 to 80 with an average age of 43.2 ± 17.5 years old. 46 children are included who were less than 14 years old (7.6%). The rates of smoking, drinking and betel nut chewing were 41.7%, 36.1% and 28%, respectively. The course of disease less than 1 month accounted for 10.4%, from 1 month to less than 1 year accounted for 31.4%, and more than 1 year accounted for 58.2%. There were four kinds of frequently-used preoperative examinations of lesions in submandibular triangle: ultrasound, MRI, CT and FNAB. Before operation, 267, 163, 53 and 50 patients underwent ultrasound, MRI, CT and FNAB, respectively. Accuracy rate for differentiating of each examination were 18.7%, 42.7%, 20.8% and 72%, respectively. Besides, the diagnostic accuracy of cone beam computed tomography (CBCT) in patients with sialolithiasis was 100%. The characteristics of patients were detailed in Table 1 . Table 1 Characteristics Characteristics No.of patients % Sex Male 405 66.6% Female 203 33.4% Age(years) ≤ 14 42 6.9% > 14 566 93.1% Habits Smoking 184 41.7% Drinking 158 36.1% chewing betel nut 121 28% Courses 1 year 354 58.2% Clinical examination FNAB 50 8.2% CT 53 8.7% MRI 163 26.8% Ultrasound 267 43.9% 2 Pathological classification All of them were classified into three categories according to the histopathological reports: congenital masses, inflammatory masses and tumors. Then the inflammatory masses were further divided into specific inflammatory classes and non-specific inflammatory classes, tumors into benign tumors, borderline tumors and malignant tumors, and then malignant tumors into primary malignant tumors and secondary malignant tumors. Congenital tumors accounted for 2.6%, inflammatory tumors accounted for 33.9%, and neoplastic tumors accounted for 63.5%. The most common congenital mass was lymphangioma, accounting for 37.5% (6/16). In addition, lymphatic hemangioma, congenital parotid fistula, angiolipoma and hamartoma were included. Among the inflammatory masses, non-specific infection accounted for 91.7% (189/206), and specific infection accounted for 8.3% (17/206). All the patients who had specific infection were lymph node tuberculosis. Among the non-specific infection, chronic lymphadenitis was the most common, accounting for 36.5% (69/189), followed by sialolithiasis (22.2%) and chronic submandibular inflammation (20.1%). The proportion of benign tumors, borderline tumors and malignant tumors were 48.4% (187/386), 1.6% (6/386) and 50.0% (193 /386), respectively. Pleomorphic adenoma were the most common benign tumors, accounting for 53.5% (100/187). Six borderline tumors included five mandibular ameloblastoma and one spindle cell tumor. Among malignant tumors, 99 cases of malignant primary tumors were observed, of which lymphoma were the most common, accounting for 40.4% (40/99). And there were 94 cases of malignant metastatic tumors. Except for 5 cases of lung origin and 3 cases of unknown primary tumors, the other 91.5% (86/94) all originated from head and neck malignant tumors, including tongue carcinoma (48.8%), buccal carcinoma (14.0%), gingival carcinoma (10.5%) and nasopharyngeal carcinoma (8.1%) (Table 2 ). Most of the lesions in submandibular triangle originated from submandibular gland and lymphatic system, respectively accounting for 36.7% (223/608) and 34.4% (209/ 608) (Fig. 1 ). Tumors were most common of submandibular gland masses (64.2%), followed by inflammatory lesions (35.8%) in this study. Among submandibular gland tumors, benign tumors accounted for 80.0%, of which mixed tumors accounted for 87.0% (100/115). And malignant tumors accounted for the remaining 20.0% (28/115) with adenoid cystic carcinoma (n = 17), mucoepidermoid carcinoma (n = 4), adenocarcinoma (n = 4) and ductal carcinoma (n = 2) included. Tumors originating from lymphatic system were divided into lymphadenitis (n = 99) and tumors (n = 110), the latter including benign tumors (n = 8), malignant primary tumors (n = 46) and malignant metastatic tumors (n = 56). Table 2 Pathological distribution of submandibular triangle masses Pathological diagnosis No.of patients % Congenital mass 16 2.6 Inflammatory mass 206 33.9 Specific inflammatory mass 189 91.7 Non-specific inflammatory class 17 8.3 Tumor 386 63.5 Benign tumor 187 48.4 Borderline tumor 6 1.6 Malignant tumor 193 50 Primary malignant tumor 99 51.3 Secondary malignant tumor 94 48.7 3 Clinical characteristics analysis According to previous researches and clinical experiences, the following ultrasonic features were took into account: the maximum diameters of node, multiple or single nodes, echo structure, well-defined or ill-defined borders, echogenicity, vascularization, having cervical lymph nodes or not. Univariate analysis showed that gender, age, bad habits (smoking, drinking and chewing betel nut), characteristics of the masses (pain, mobility, and borders), and accompanying multiple lymphadenopathy of the neck were significantly different between benign and malignant tumors(p<0.05;Table 3 ). Other factors including pain, course, maximum diameters of node, borders and vascularization were not significantly different in malignant tumors with benign masses (p = 0.185;0.106;0.04;0.085;0.241 respectively; Table 3 ). All masses presented as cystic, moderate and high echo were finally diagnosed as benign, and there was no significant difference between low and mixed echo (p = 0.967) or between solid and mixed echo structure (p = 0.748). The results of multivariate analysis showed that age, drinking and chewing betel nut were high risk factors for malignant tumors in submandibular region, the odds ratio was 4.321(95%CI 1.367–13.666), 0.110(95%CI 0.015–0.797) and 12.616(95%CI 2.081–76.492) respectively (p < 0.05; Fig. 3 ). Table 3 Univariate analysis of clinical characteristics and pathological diagnosis of masses Benign masses Malignant masses Total P-value Sex < 0.001 Male 255(61.4) 150(77.7) 405 Female 160(38.6) 43(22.3) 203 Tobacco use < 0.001 Yes 104(35.5) 80(54.1) 184 No 189(54.5) 68(45.9) 257 Alcohol use < 0.001 Yes 88(30.3) 70(47.3) 158 No 202(69.7) 78(52.7) 280 Betel nut use < 0.001 Yes 59(20.4) 62(43.4) 121 No 230(79.6) 81(56.6) 311 Pain 0.185 Yes 72(25.4) 43(31.6) 115 No 211(74.6) 93(68.4) 304 Adhesion < 0.001 Yes 109(36.0) 89(54.9) 198 No 194(64.0) 73(45.1) 267 Texture 0.005 Hard 138(39.1) 86(52.1) 224 Soft 215(60.9) 79(47.9) 294 Age(year) <0.001 Mean ± SD 40.0 ± 17.9 49.6 ± 14.9 43.2 ± 17.5 Course(day) 0.400 Mean ± SD 1016 ± 1411.2 1080.3 ± 1804.0 1037.2 ± 1549.9 Maximum diameters of nodule (cm) 0.106 Mean ± SD 2.6 ± 1.3 2.8 ± 1.4 2.7 ± 1.3 Multiplicity 0.004 Yes 56(62.9) 33(37.1) 89 No 131(79.4) 34(20.6) 165 Echo structure - Solid 84(79.2) 22(20.8) 106 Mixed 27(81.8) 6(18.2) 33 Cystic 17(100) 0(0) 17 Borders 0.085 Well-defined 18(72.0) 7(28.0) 25 Ill-defined 148(85.5) 25(14.5) 173 • Echogenicity - Hypoechoic 91(73.6) 24(26.4) 115 Isoechoic 2(100) 0(0) 2 Hyperechoic 1(100) 0(0) 1 Mixed 47(81.0) 11(19.0) 58 Vascularization 0.241 Yes 50(76.6) 15(23.4) 65 No 37(86.0) 6(14.0) 43 Cervical lymph nodes 0.038 Yes 130(80.7) 31(19.3) 161 No 79(90.8) 8(9.2) 87 (%) = percent of column. DISCUSSION The study found that both benign and malignant lesions were more common in males. The peak incidence of benign lesions was at the 41–50 age group, while the peak incidence of malignant lesions was at the 51–60 age group(Fig. 2 ), which is broadly consistent with the study of Taipei, China. But there was a study found that benign tumors in the submandibular region were more common in women, with a peak incidence at 51–60 age group( 3 , 5 ). The differences may caused by different races and external environment( 12 ). Inflammatory masses were the most common classes (59.6%) in the patients under the age of 14, followed by tumors (40.4%), and benign tumors were more common than carcinomas, which was consistent with previous studies( 13 ). Tumors account for the majority of lesions in this region (64.2%), followed by inflammatory masses (32.9%). Some reserachers supported that inflammatory masses, accounting for more than a half, was the most common type of masses in submandibular triangle ( 3 , 14 , 15 ). Congenital lesions were rare. The numbers of patients who suffered from benign and malignant tumors in the submandibular region were similar (187 vs. 193). Adenoid cystic carcinoma accounted for more than a half of benign tumors (53.5%). Lymphoma was the most common primary malignant tumor (20.7%). Submandibular tumors were one of the most common clinical manifestations in the early stage of lymphoma( 8 ) Primary carcinomas of the head and neck frequently cause metastases in submandibular triangle ( 4 ). About 91.5% of the metastases were from primary tumors in head and neck in the study. These findings were almost consistent with previous reports( 3 , 7 , 15 ). Submandibular gland masses were the most common in the submandibular triangle( 3 , 7 , 14 ). Malignant tumors accounted for 20.0% of submandibular glands lesions, which were slightly lower than that reported in literature ( 3 , 7 , 14 ). Pathological classification is a prominent prognostic marker for submandibular gland masses, especially for malignant tumors ( 16 , 17 ). Adenoid cystic carcinoma was the most common malignant tumor in submandibular gland, and surgery plus postoperative radiotherapy is the standard treatment. It is characterized by slow growth but invasive, easy to local recurrence and distant metastasis. The second common malignancy was mucoepidermoid carcinoma, which was thought to have a poor prognosis. Malignant submandibular gland tumors also included adenocarcinoma, undifferentiated carcinoma, et al.( 18 ). MRI and CT are mainly used to clarify extent and relationship with surrounding tissues of the lesions, but the ability to distinguish malignant tumors without obvious malignant biological behavior is limited( 3 , 8 ). It is worth mentioning that the accuracy of CBCT in the diagnosis of sialolithiasis is 100%. Literatures have shown that the average sensitivity and specificity of CBCT in the diagnosis of sialolithiasis were 98.85%, but it has not been widely used because of its radioactivity and high price( 19 ). FNAB is an effective and minimally invasive diagnostic tool for distinguishing salivary gland tumors from non-tumor lesions, but it is not always effective for distinguishing benign from malignant tumors ( 20 ). FNAB has high specificity (94%-96%) but low sensitivity (71%-79%) in the differential diagnosis of malignant tumors( 21 ). When it may be malignancy, FNAB examination should be performed before operation for preliminary diagnosis. In this study, accuracy rates for differentiating of preoperative FNAB, MRI, CT and ultrasound were respectively 72% (36/50) ,42.7% (70/164), 20.8% (11/53) and 18.7% (50/67). Other imaging techniques, such as X- ray, sialography and salivary gland scintigraphy( 4 )were not involved in this study. There have been some researches on distinguishing malignancy from benignancy in the submandibular triangle or of the submandibular gland, such as diffusion-weighted MR( 22 ), contrast-enhanced ultrasound( 23 ) and multimodal ultrasonography( 12 ). However, none of them achieved high predictive value. In our study, clinical and ultrasonic characteristic of patients were statistically evaluated. Finally, age, drinking and chewing betel nut were proved to be high risk factors for malignant tumors in submandibular region. Besides, sex, age, smoking, drinking, betel nut chewing, tenderness, range of activity and texture, multiple nodes and cervical lymph nodes are also helpful. CONCLUSION In a word, this study analyzed the clinical, imaging data and pathological features of 608 cases of submandibular tumors in a single center, and evaluated clinical and ultrasonic characteristic of patients, providing a reference for the clinical diagnosis and treatment of lesions in submandibular triangle. MATERIALS AND METHODS 1 Study population and clinical data All patients who underwent biopsies or excisions of submandibular triangle masses in Xiangya Hospital of Central South University from January 2009 to June 2019 were included. The inclusion criteria were as follows: (1) Masses were located in the submandibular triangle, confirmed by pre-operative investigations and intraoperative findings. (2) Patients had definite pathological diagnosis. Basic demographic informations, history, physical examination, imaging data and histopathological results were collected. Then they were classified in details according to the histopathological reports. In the process of multivariate analysis, 254 of 608 patients with comparatively complete ultrasonographic data were included. The ratio of the number of patients who were accurately differentiated benign masses from carcinoma by a kind of examination and the number of patients who did the examination was defined as accuracy rate for differentiating of the examination. All methods were conducted in accordance with relevant guidelines and regulations. 2 Ethical Statement Approval for this retrospective observational study was obtained from Xiangya hospital research ethics board, and the need to obtain informed consent was waived.(NO.202012231) 3 Statistical analysis Ultrasound was selected for further statistical analysis owing to the wide use of it and enough sample size. SPSS version 25.0 was used for statistical analysis. Independent t-tests and the Chi-square tests (or Fisher’s exact test) were used for univariate analysis to assess the relationship between clinical characteristics and pathologic features. A multivariate analysis was performed using a binary logistic regression model to assess the relationship between the pathologic features and characteristics proved to be to significantly different by univariate analysis mentioned above. P < 0.05 was considered as statistically significant difference. Every factor came from medical history in Electronic Medical Record and ultrasonic reports. Declarations Acknowledgment: Funds for the Central Universities of Central South University (Project No.2022ZZTS0907). Author Contributions Statement: Y.W. and ZY.H. collected all the data, analysed the results and finished the draft. DH.H. reviewed the manuscript. Conflict of Interest Statement : We declare that we have no conflict of interest. Data Availability Statement: Data available on request from the authors. The data that support the findings of this study are available from the corresponding author, upon reasonable request. References Grewal JS, Jamal Z and Ryan J: Anatomy, Head and Neck, Submandibular Gland. 2022. Casale J and Varacallo M: Anatomy, Head and Neck, Submandibular Triangle. 2022. Munir N and Bradley PJ: Diagnosis and management of neoplastic lesions of the submandibular triangle. Oral Oncol 44: 251–260, 2008. Knopf A, Cortolezis N, Bas M, Mansour N and Hofauer B: Multimodal ultrasonographic algorithm in the differentiation of submandibular masses. Acta Oto-Laryngol 137: 640–645, 2017. Rinaldo A, Ferlito A, Pellitteri PK, Robbins KT, Shaha AR, Bradley PJ, Kowalski LP and Wei WI: Management of malignant submandibular gland tumors. Acta Oto-Laryngol 123: 896–904, 2003. Laskawi R, Ellies M, Arglebe C, Schott A. Surgical management of benign tumors of the submandibular gland: a follow-up study. 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Schmidt RL, Hunt JP, Hall BJ, Wilson AR and Layfield LJ: A systematic review and meta-analysis of the diagnostic accuracy of frozen section for parotid gland lesions. Am J Clin Pathol 136: 729–738, 2011. Razek A: Prediction of malignancy of submandibular gland tumors with apparent diffusion coefficient. Oral Radiol 35: 11–15, 2019. Strieth S, Siedek V, Rytvina M, Gurkov R, Berghaus A and Clevert DA: Dynamic contrast-enhanced ultrasound for differential diagnosis of submandibular gland disease. Eur Arch Oto-Rhino-L 271: 163–169, 2014. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3860361","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":267415739,"identity":"f88051c1-ce1e-489d-aced-4a46a262f164","order_by":0,"name":"Donghai Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBACAzDJBsQSDAwHPiALEqXl4AyStTDzEKPFXCL52cMvZTZ58tHNDw/b1NQlNrA3b5NgqLmDU4vljDRzY5lzacWGd44ZHM45djixgedYmQTDsWe4HXYjwUxasu1w4sYZCQaHcxsOJDZI5JhJMDYcxqMl/RtUS/qHw5YNQIfJvyGkJcdM8iNQy3yJHIPDjA3MQFt4CGg586ZMmuFcWuIGiZyCgz3HDhu38aQVWyQcw6PlePo2yR9lNonzZ6Rv/vCjpk62n/3wxhsfanBrAQFwdBgcgPJAccSQgFcDAwPjDyAh30BA1SgYBaNgFIxcAABTZlsXubvDswAAAABJRU5ErkJggg==","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Donghai","middleName":"","lastName":"Huang","suffix":""},{"id":267415740,"identity":"66dc6592-df04-4a9d-b5b1-dfff16d94ea8","order_by":1,"name":"Yu Wu","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wu","suffix":""},{"id":267415741,"identity":"956f8d4e-1db1-45e5-a5f4-4dcf1adc8fb3","order_by":2,"name":"Zhiying He","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Zhiying","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2024-01-13 14:14:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3860361/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3860361/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49824581,"identity":"f304d235-58fd-48c5-b2cd-870036c6c900","added_by":"auto","created_at":"2024-01-18 15:37:48","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53437,"visible":true,"origin":"","legend":"\u003cp\u003eHistopathologic origin distribution of submandibular triangle masses\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3860361/v1/2f81d39233599050e030e2fe.jpeg"},{"id":49823153,"identity":"43bb6f17-549b-4dca-a37b-e85702e1dd82","added_by":"auto","created_at":"2024-01-18 15:29:48","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":152053,"visible":true,"origin":"","legend":"\u003cp\u003eAge and sex distribution of benign and malignant submandibular masses.\u003c/p\u003e\n\u003cp\u003eA, The peak age group of benign masses in this region was in the 4th decade, and that of malignant masses was in the 5th.B,The peak age group of benign and malignant masses was 31-40 and 41-50 in female patients. C, The peak age group of benign and malignant masses was 41-50 and 51-60 in male patients. B and C, Both benign and malignant masses in this region were more common in male.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3860361/v1/a410d19de23be6daedf843cf.jpeg"},{"id":49823151,"identity":"e6d3425d-de11-4ab5-9bef-72d1cec8111d","added_by":"auto","created_at":"2024-01-18 15:29:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103399,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate analysis of clinical characteristics and pathological diagnosis of submandibular triangle masses\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3860361/v1/f9c91da00c2bb77428d2c999.png"},{"id":68753558,"identity":"e0305631-f258-48b7-839b-6c419dc74738","added_by":"auto","created_at":"2024-11-11 16:31:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":957494,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3860361/v1/c95349dd-8ed1-4dce-b9b0-ad7b6c32c961.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical analysis of submandibular triangle masses in the past 10 years","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe submandibular triangle, also referred to as the submandibular region, is an area surrounded by the anterior and posterior abdomen of the digastric muscle and the lower margin of the mandible, with the submandibular gland as the base, reaching the level of the hyoid bone(\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The anatomy of the submandibular region is complex, including submandibular glands, lymph nodes, adipose tissue, muscle tissue, nerves and vessels, etc. In addition, any pathological changes of submandibular gland, parotid gland, sublingual gland, mandible or lymphoid tissue can cause swellings in the submandibular triangle. Glandular diseases account for the majority of pathologies in submandibular triangle(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSurgery is the first choice for most submandibular triangle masses, and it is necessary to distinguish lesions in this region. Malignant tumors and metastases usually received aggressive tumor resections, with possible sacrifice of surrounding functional structures, further treatment like radiotherapy or chemotherapy, and further follow up (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In contrast, benign lesions always have limited excision of lesions and the surrounding functional structures were preserved. Surgery scope and procedures were different between benign and malignant tumors(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt present, pre-operate diagnosis is mainly based on history, physical examination and imaging examination (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), which is empirical and inefficient. Despite a lot of studies on distinguishing masses in the submandibular triangle, there haven\u0026rsquo;t been a reliable and comprehensive one so far. A certain number of submandibular triangle tumors, including benign and malignant tumors, only present as asymptomatic masses (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Literatures have shown that characteristics like pain, fixing to the skin or deep tissue and rapid growth are more common in malignant tumors, but there was no reliable evidence to confirm(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Because of various pathological types and the similarity in symptom and clinical manifestation, it is relatively difficult to identify masses in this region before operation, which makes challenging to individualized diagnosis and treatment(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). MRI and CT images can clearly show relationship between tumors and surrounding healthy tissues, which contributes to distinguishing benign tumors from malignant tumors(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Ultrasonography is the most widely used examination of superficial tumors, with the advantages of non-invasive, rapid, and cheap. The research of multimodal ultrasonographic algorithm in the differentiation of submandibular masses and parotid gland tumors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) were effectively validated. Thyroid Imaging Reporting and Data System (TI-RADS) is a relatively reliable standard for preliminary diagnosis of thyroid gland diseases, and ultrasound features are also helpful for the diagnosis of benign and malignant breast nodules(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study intends to summarize the clinical data including masses characteristics, imaging data and final pathological results of submandibular triangle masses through a retrospective study with a large sample.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1 Patient characteristics\u003c/h2\u003e \u003cp\u003eThere were 608 cases, with a male-to-female ratio of about 2:1. They were aged from 1 to 80 with an average age of 43.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5 years old. 46 children are included who were less than 14 years old (7.6%). The rates of smoking, drinking and betel nut chewing were 41.7%, 36.1% and 28%, respectively. The course of disease less than 1 month accounted for 10.4%, from 1 month to less than 1 year accounted for 31.4%, and more than 1 year accounted for 58.2%. There were four kinds of frequently-used preoperative examinations of lesions in submandibular triangle: ultrasound, MRI, CT and FNAB. Before operation, 267, 163, 53 and 50 patients underwent ultrasound, MRI, CT and FNAB, respectively. Accuracy rate for differentiating of each examination were 18.7%, 42.7%, 20.8% and 72%, respectively. Besides, the diagnostic accuracy of cone beam computed tomography (CBCT) in patients with sialolithiasis was 100%. The characteristics of patients were detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.6%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.4%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e566\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e93.1%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHabits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e184\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e41.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDrinking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e158\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e36.1%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003echewing betel nut\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e121\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e28%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCourses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;1 month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1 month-1 year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e191\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e31.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;1 year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e354\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e58.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical examination\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFNAB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMRI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e163\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e26.8%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUltrasound\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e267\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e43.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2 Pathological classification\u003c/h2\u003e \u003cp\u003eAll of them were classified into three categories according to the histopathological reports: congenital masses, inflammatory masses and tumors. Then the inflammatory masses were further divided into specific inflammatory classes and non-specific inflammatory classes, tumors into benign tumors, borderline tumors and malignant tumors, and then malignant tumors into primary malignant tumors and secondary malignant tumors. Congenital tumors accounted for 2.6%, inflammatory tumors accounted for 33.9%, and neoplastic tumors accounted for 63.5%. The most common congenital mass was lymphangioma, accounting for 37.5% (6/16). In addition, lymphatic hemangioma, congenital parotid fistula, angiolipoma and hamartoma were included. Among the inflammatory masses, non-specific infection accounted for 91.7% (189/206), and specific infection accounted for 8.3% (17/206). All the patients who had specific infection were lymph node tuberculosis. Among the non-specific infection, chronic lymphadenitis was the most common, accounting for 36.5% (69/189), followed by sialolithiasis (22.2%) and chronic submandibular inflammation (20.1%). The proportion of benign tumors, borderline tumors and malignant tumors were 48.4% (187/386), 1.6% (6/386) and 50.0% (193 /386), respectively. Pleomorphic adenoma were the most common benign tumors, accounting for 53.5% (100/187). Six borderline tumors included five mandibular ameloblastoma and one spindle cell tumor. Among malignant tumors, 99 cases of malignant primary tumors were observed, of which lymphoma were the most common, accounting for 40.4% (40/99). And there were 94 cases of malignant metastatic tumors. Except for 5 cases of lung origin and 3 cases of unknown primary tumors, the other 91.5% (86/94) all originated from head and neck malignant tumors, including tongue carcinoma (48.8%), buccal carcinoma (14.0%), gingival carcinoma (10.5%) and nasopharyngeal carcinoma (8.1%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most of the lesions in submandibular triangle originated from submandibular gland and lymphatic system, respectively accounting for 36.7% (223/608) and 34.4% (209/ 608) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Tumors were most common of submandibular gland masses (64.2%), followed by inflammatory lesions (35.8%) in this study. Among submandibular gland tumors, benign tumors accounted for 80.0%, of which mixed tumors accounted for 87.0% (100/115). And malignant tumors accounted for the remaining 20.0% (28/115) with adenoid cystic carcinoma (n\u0026thinsp;=\u0026thinsp;17), mucoepidermoid carcinoma (n\u0026thinsp;=\u0026thinsp;4), adenocarcinoma (n\u0026thinsp;=\u0026thinsp;4) and ductal carcinoma (n\u0026thinsp;=\u0026thinsp;2) included. Tumors originating from lymphatic system were divided into lymphadenitis (n\u0026thinsp;=\u0026thinsp;99) and tumors (n\u0026thinsp;=\u0026thinsp;110), the latter including benign tumors (n\u0026thinsp;=\u0026thinsp;8), malignant primary tumors (n\u0026thinsp;=\u0026thinsp;46) and malignant metastatic tumors (n\u0026thinsp;=\u0026thinsp;56).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePathological distribution of submandibular triangle masses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.of patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital mass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflammatory mass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpecific inflammatory mass\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e189\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e91.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-specific inflammatory class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e386\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e63.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBenign tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e187\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e48.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBorderline tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMalignant tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e193\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary malignant tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e51.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecondary malignant tumor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e48.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3 Clinical characteristics analysis\u003c/h2\u003e \u003cp\u003eAccording to previous researches and clinical experiences, the following ultrasonic features were took into account: the maximum diameters of node, multiple or single nodes, echo structure, well-defined or ill-defined borders, echogenicity, vascularization, having cervical lymph nodes or not. Univariate analysis showed that gender, age, bad habits (smoking, drinking and chewing betel nut), characteristics of the masses (pain, mobility, and borders), and accompanying multiple lymphadenopathy of the neck were significantly different between benign and malignant tumors(p\u0026lt;0.05;Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Other factors including pain, course, maximum diameters of node, borders and vascularization were not significantly different in malignant tumors with benign masses (p\u0026thinsp;=\u0026thinsp;0.185;0.106;0.04;0.085;0.241 respectively; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). All masses presented as cystic, moderate and high echo were finally diagnosed as benign, and there was no significant difference between low and mixed echo (p\u0026thinsp;=\u0026thinsp;0.967) or between solid and mixed echo structure (p\u0026thinsp;=\u0026thinsp;0.748). The results of multivariate analysis showed that age, drinking and chewing betel nut were high risk factors for malignant tumors in submandibular region, the odds ratio was 4.321(95%CI 1.367\u0026ndash;13.666), 0.110(95%CI 0.015\u0026ndash;0.797) and 12.616(95%CI 2.081\u0026ndash;76.492) respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis of clinical characteristics and pathological diagnosis of masses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenign masses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMalignant masses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255(61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150(77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160(38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104(35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189(54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68(45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88(30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70(47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202(69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78(52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetel nut use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62(43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230(79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81(56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72(25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211(74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93(68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdhesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109(36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89(54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194(64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTexture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138(39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86(52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215(60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79(47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.0\u0026thinsp;\u0026plusmn;\u0026thinsp;17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCourse(day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1016\u0026thinsp;\u0026plusmn;\u0026thinsp;1411.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1080.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1804.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1037.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1549.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum diameters of nodule (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiplicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131(79.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEcho structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSolid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCystic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell-defined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIll-defined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148(85.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Echogenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoechoic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91(73.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(26.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsoechoic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperechoic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47(81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascularization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50(76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(86.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical lymph nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130(80.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79(90.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e(%)\u0026thinsp;=\u0026thinsp;percent of column.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe study found that both benign and malignant lesions were more common in males. The peak incidence of benign lesions was at the 41\u0026ndash;50 age group, while the peak incidence of malignant lesions was at the 51\u0026ndash;60 age group(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which is broadly consistent with the study of Taipei, China. But there was a study found that benign tumors in the submandibular region were more common in women, with a peak incidence at 51\u0026ndash;60 age group(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The differences may caused by different races and external environment(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Inflammatory masses were the most common classes (59.6%) in the patients under the age of 14, followed by tumors (40.4%), and benign tumors were more common than carcinomas, which was consistent with previous studies(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTumors account for the majority of lesions in this region (64.2%), followed by inflammatory masses (32.9%). Some reserachers supported that inflammatory masses, accounting for more than a half, was the most common type of masses in submandibular triangle (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Congenital lesions were rare. The numbers of patients who suffered from benign and malignant tumors in the submandibular region were similar (187 vs. 193). Adenoid cystic carcinoma accounted for more than a half of benign tumors (53.5%). Lymphoma was the most common primary malignant tumor (20.7%). Submandibular tumors were one of the most common clinical manifestations in the early stage of lymphoma(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Primary carcinomas of the head and neck frequently cause metastases in submandibular triangle (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). About 91.5% of the metastases were from primary tumors in head and neck in the study. These findings were almost consistent with previous reports(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSubmandibular gland masses were the most common in the submandibular triangle(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Malignant tumors accounted for 20.0% of submandibular glands lesions, which were slightly lower than that reported in literature (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Pathological classification is a prominent prognostic marker for submandibular gland masses, especially for malignant tumors (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Adenoid cystic carcinoma was the most common malignant tumor in submandibular gland, and surgery plus postoperative radiotherapy is the standard treatment. It is characterized by slow growth but invasive, easy to local recurrence and distant metastasis. The second common malignancy was mucoepidermoid carcinoma, which was thought to have a poor prognosis. Malignant submandibular gland tumors also included adenocarcinoma, undifferentiated carcinoma, et al.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMRI and CT are mainly used to clarify extent and relationship with surrounding tissues of the lesions, but the ability to distinguish malignant tumors without obvious malignant biological behavior is limited(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). It is worth mentioning that the accuracy of CBCT in the diagnosis of sialolithiasis is 100%. Literatures have shown that the average sensitivity and specificity of CBCT in the diagnosis of sialolithiasis were 98.85%, but it has not been widely used because of its radioactivity and high price(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). FNAB is an effective and minimally invasive diagnostic tool for distinguishing salivary gland tumors from non-tumor lesions, but it is not always effective for distinguishing benign from malignant tumors (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). FNAB has high specificity (94%-96%) but low sensitivity (71%-79%) in the differential diagnosis of malignant tumors(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). When it may be malignancy, FNAB examination should be performed before operation for preliminary diagnosis. In this study, accuracy rates for differentiating of preoperative FNAB, MRI, CT and ultrasound were respectively 72% (36/50) ,42.7% (70/164), 20.8% (11/53) and 18.7% (50/67). Other imaging techniques, such as X- ray, sialography and salivary gland scintigraphy(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)were not involved in this study.\u003c/p\u003e \u003cp\u003eThere have been some researches on distinguishing malignancy from benignancy in the submandibular triangle or of the submandibular gland, such as diffusion-weighted MR(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), contrast-enhanced ultrasound(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and multimodal ultrasonography(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, none of them achieved high predictive value. In our study, clinical and ultrasonic characteristic of patients were statistically evaluated. Finally, age, drinking and chewing betel nut were proved to be high risk factors for malignant tumors in submandibular region. Besides, sex, age, smoking, drinking, betel nut chewing, tenderness, range of activity and texture, multiple nodes and cervical lymph nodes are also helpful.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn a word, this study analyzed the clinical, imaging data and pathological features of 608 cases of submandibular tumors in a single center, and evaluated clinical and ultrasonic characteristic of patients, providing a reference for the clinical diagnosis and treatment of lesions in submandibular triangle.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003e1 Study population and clinical data\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll patients who underwent biopsies or excisions of submandibular triangle masses in Xiangya Hospital of Central South University from January 2009 to June 2019 were included. The inclusion criteria were as follows: (1) Masses were located in the submandibular triangle, confirmed by pre-operative investigations and intraoperative findings. (2) Patients had definite pathological diagnosis. Basic demographic informations, history, physical examination, imaging data and histopathological results were collected. Then they were classified in details according to the histopathological reports. In the process of multivariate analysis, 254 of 608 patients with comparatively complete ultrasonographic data were included. The ratio of the number of patients who were accurately differentiated benign masses from carcinoma by a kind of examination and the number of patients who did the examination was defined as accuracy rate for differentiating of the examination. All methods were conducted in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2 Ethical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval for this retrospective observational study was obtained from Xiangya hospital research ethics board, and the need to obtain informed consent was waived.(NO.202012231)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUltrasound was selected for further statistical analysis owing to the wide use of it and enough sample size. SPSS version 25.0 was used for statistical analysis. Independent t-tests and the Chi-square tests (or Fisher\u0026rsquo;s exact test) were used for univariate analysis to assess the relationship between clinical characteristics and pathologic features. A multivariate analysis was performed using a binary logistic regression model to assess the relationship between the pathologic features and characteristics proved to be to significantly different by univariate analysis mentioned above. P \u0026lt; 0.05 was considered as statistically significant difference. Every factor came from medical history in Electronic Medical Record and ultrasonic reports.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunds for the Central Universities of Central South University (Project No.2022ZZTS0907).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.W. and ZY.H. collected all the data, analysed the results and finished the draft. DH.H. reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare that we have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData available on request from the authors. The data that support the findings of this study are available from the corresponding author, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGrewal JS, Jamal Z and Ryan J: Anatomy, Head and Neck, Submandibular Gland. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasale J and Varacallo M: Anatomy, Head and Neck, Submandibular Triangle. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunir N and Bradley PJ: Diagnosis and management of neoplastic lesions of the submandibular triangle. Oral Oncol 44: 251\u0026ndash;260, 2008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnopf A, Cortolezis N, Bas M, Mansour N and Hofauer B: Multimodal ultrasonographic algorithm in the differentiation of submandibular masses. Acta Oto-Laryngol 137: 640\u0026ndash;645, 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRinaldo A, Ferlito A, Pellitteri PK, Robbins KT, Shaha AR, Bradley PJ, Kowalski LP and Wei WI: Management of malignant submandibular gland tumors. Acta Oto-Laryngol 123: 896\u0026ndash;904, 2003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaskawi R, Ellies M, Arglebe C, Schott A. Surgical management of benign tumors of the submandibular gland: a follow-up study. J Oral Maxillofac Surg 1995;53(5):506\u0026ndash;8; discussion 509.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeber RS, Byers RM, Petit B, Wolf P, Ang K and Luna M: Submandibular gland tumors. Adverse histologic factors and therapeutic implications. Arch Otolaryngol Head Neck Surg 116: 1055\u0026ndash;1060, 1990.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRapidis AD, Stavrianos S, Lagogiannis G and Faratzis G: Tumors of the submandibular gland: clinicopathologic analysis of 23 patients. J Oral Maxil Surg 62: 1203\u0026ndash;1208, 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMansour N, Stock KF, Chaker A, Bas M and Knopf A: Evaluation of parotid gland lesions with standard ultrasound, color duplex sonography, sonoelastography, and acoustic radiation force impulse imaging - a pilot study. Ultraschall Med 33: 283\u0026ndash;288, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorvath E, Majlis S, Rossi R, Franco C, Niedmann JP, Castro A and Dominguez M: An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocr Metab 94: 1748\u0026ndash;1751, 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStavros AT, Thickman D, Rapp CL, Dennis MA, Parker SH and Sisney GA: Solid breast nodules: use of sonography to distinguish between benign and malignant lesions. Radiology 196: 123\u0026ndash;134, 1995.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlbeck H, Bentzen J, Ockelmann HH, Nielsen NH, Bretlau P and Hansen HS: Familial clusters of nasopharyngeal carcinoma and salivary gland carcinomas in Greenland natives. Cancer-Am Cancer Soc 72: 196\u0026ndash;200, 1993.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHockstein NG, Samadi DS, Gendron K, Carpentieri D and Wetmore RF: Pediatric submandibular triangle masses: a fifteen-year experience. Head Neck-J Sci Spec 26: 675\u0026ndash;680, 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalgic A, Karakoc O, Karahatay S, Hidir Y, Gamsizkan M, Birkent H and Gerek M: Submandibular triangle masses. J Craniofac Surg 24: e529-e531, 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIchimura K, Nibu K and Tanaka T: Nerve paralysis after surgery in the submandibular triangle: review of University of Tokyo Hospital experience. Head Neck-J Sci Spec 19: 48\u0026ndash;53, 1997.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpiro RH, Huvos AG and Strong EW: Adenoid cystic carcinoma of salivary origin. A clinicopathologic study of 242 cases. Am J Surg 128: 512\u0026ndash;520, 1974.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamada K, Honda K, Tamaki H, Tanaka S, Shinohara S, Takebayashi S, Tateya I, Kitamura M, Mizuta M and Maetani T, et al.: Survival in patients with submandibular gland carcinoma - Results of a multi-institutional retrospective study. Auris Nasus Larynx 45: 1066\u0026ndash;1072, 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson L: World Health Organization classification of tumours: pathology and genetics of head and neck tumours. Ent-Ear Nose Throat 85: 74, 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCostan VV, Ciocan-Pendefunda CC, Sulea D, Popescu E and Boisteanu O: Use of Cone-Beam Computed Tomography in Performing Submandibular Sialolithotomy. J Oral Maxil Surg 77: 1651\u0026ndash;1656, 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaleki Z, Baloch Z, Lu R, Shafique K, Song SJ, Viswanathan K, Rao RA, Lefler H, Fatima A and Wiles A, et al.: Application of the Milan System for Reporting Submandibular Gland Cytopathology: An international, multi-institutional study. Cancer Cytopathol 127: 306\u0026ndash;315, 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt RL, Hunt JP, Hall BJ, Wilson AR and Layfield LJ: A systematic review and meta-analysis of the diagnostic accuracy of frozen section for parotid gland lesions. Am J Clin Pathol 136: 729\u0026ndash;738, 2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRazek A: Prediction of malignancy of submandibular gland tumors with apparent diffusion coefficient. Oral Radiol 35: 11\u0026ndash;15, 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrieth S, Siedek V, Rytvina M, Gurkov R, Berghaus A and Clevert DA: Dynamic contrast-enhanced ultrasound for differential diagnosis of submandibular gland disease. Eur Arch Oto-Rhino-L 271: 163\u0026ndash;169, 2014.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Submandibular triangle masses, malignant tumor, benign tumor, preopreative examination, diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-3860361/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3860361/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eLack of retrospective studies on submandibular triangle masses with large Chinese sample.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBasic demographic informations, history, physical examination, imaging data and histopathological results of 608 patients who underwent surgery in submandibular triangle in Xiangya Hospital of Central South University from January 2009 to June 2019 were collected. Statistical analysis were performed. Differences between malignant and benign masses were assessed by univariate and multivariate analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e405 males and 203 females were included. The average age was 43.17\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6 years old (range from 1\u0026ndash;80). Congenital masses, inflammatory masses and tumors accounted for 2.6%, 63.5%, 33.9%, respectively. Benign tumors ,borderline tumors ,malignant tumors accounted for 48.4%, 1.6%, 50.0%, respectively. Pleomorphic adenoma and lymphoma were the most common benignancy and malignancy. Metastatic tumors were mostly originated from the head and neck cancers. Univariate analysis showed that there were significantly differences in gender, age, smoking, drinking, chewing betel nut, characteristics of the masses (pain, mobility, texture), and cervical lymph nodes. Multivariate analysis showed that age, drinking and chewing betel nut were high risk factors for malignancy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eComprehensive analysis of the clinical parameters was helpful for preopreative diagnosis of submandibular triangle masses.\u003c/p\u003e","manuscriptTitle":"Clinical analysis of submandibular triangle masses in the past 10 years","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-18 15:29:43","doi":"10.21203/rs.3.rs-3860361/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d7acdbca-d9d1-450a-80b2-acfa1a506057","owner":[],"postedDate":"January 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28172714,"name":"Health sciences/Diseases/Cancer"},{"id":28172715,"name":"Health sciences/Diseases/Oral diseases"},{"id":28172716,"name":"Health sciences/Oncology/Surgical oncology"}],"tags":[],"updatedAt":"2024-11-11T16:23:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-18 15:29:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3860361","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3860361","identity":"rs-3860361","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}