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Gökçe E, Beyhan M. Advanced magnetic resonance imaging findings in salivary gland tumors. World J Radiol 2022; 14:256-271. [PMID: 36160835 PMCID: PMC9453317 DOI: 10.4329/wjr.v14.i8.256] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/22/2022] [Accepted: 08/07/2022] [Indexed: 02/08/2023] Open
Abstract
Salivary gland tumors (SGTs) make up a small portion (approximately 5%) of all head and neck tumors. Most of them are located in the parotid glands, while they are less frequently located in the submandibular glands, minor salivary glands or sublingual gland. The incidence of malignant or benign tumors (BTs) in the salivary glands varies according to the salivary gland from which they originate. While most of those detected in the parotid gland tend to be benign, the incidence of malignancy increases in other glands. The use of magnetic resonance imaging (MRI) in the diagnosis of SGTs is increasing every day. While conventional sequences provide sufficient data on the presence, localization, extent and number of the tumor, they are insufficient for tumor specification. With the widespread use of advanced techniques such as diffusion-weighted imaging, semi-quantitative and quantitative perfusion MRI, studies and data have been published on the differentiation of malignant or BTs and the specificity of their subtypes. With diffusion MRI, differentiation can be made by utilizing the cellularity and microstructural properties of tumors. For example, SGTs such as high cellular Warthin’s tumor (WT) or lymphoma on diffusion MRI have been reported to have significantly lower apparent diffusion values than other tumors. Contrast agent uptake and wash-out levels of tumors can be detected with semi-quantitative perfusion MRI. For example, it is reported that almost all of the pleomorphic adenomas show an increasing enhancement time intensity curve and do not wash-out. On quantitative perfusion MRI studies using perfusion parameters such as Ktrans, Kep, and Ve, it is reported that WTs can show higher Kep and lower Ve values than other tumors. In this study, the contribution of advanced MRI to the diagnosis and differential diagnosis of SGTs will be reviewed.
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Affiliation(s)
- Erkan Gökçe
- Department of Radiology, Faculty of Medicine, Tokat Gaziosmanpasa University, Tokat 60100, Turkey
| | - Murat Beyhan
- Department of Radiology, Faculty of Medicine, Tokat Gaziosmanpasa University, Tokat 60100, Turkey
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Gökçe E. Multiparametric Magnetic Resonance Imaging for the Diagnosis and Differential Diagnosis of Parotid Gland Tumors. J Magn Reson Imaging 2020; 52:11-32. [PMID: 32065489 DOI: 10.1002/jmri.27061] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Revised: 01/02/2020] [Accepted: 01/03/2020] [Indexed: 12/18/2022] Open
Abstract
The majority of salivary gland tumors occur in the parotid glands. Characterization (ie, benign or malignant, and histological type), location (deep or superficial), and invasion into the neighboring tissues of parotid tumors determine preoperative treatment planning. MRI gives more information than other imaging methods about the internal structure, localization, and relationship with other tissues of parotid tumors. Functional MRI methods (diffusion-weighted imaging, dynamic contrast-enhanced MRI, perfusion-weighted MRI, MR spectroscopy, etc.) have been increasingly used recently to increase the power of radiologists to characterize the tumors. Although they increase the workload of radiologists, the combined use of functional MRI methods improves accuracy in the differentiation of the tumors. There are a wide range of studies in the literature dealing with the combined use of different functional imaging methods in combination with conventional sequences. The aim of the present review is to evaluate conventional and functional/advanced MR methods, as well as multiparametric MRI applications combining them in the diagnosis of parotid gland tumors. Evidence Level: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;52:11-32.
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Affiliation(s)
- Erkan Gökçe
- Department of Radiology, Medical School, Tokat Gaziosmanpaşa University, Tokat, Turkey
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Moreira MA, Lessa LS, Bortoli FR, Lopes A, Xavier EP, Ceretta RA, Sônego FGF, Tomasi CD, Pires PDS, Ceretta LB, Perry IDS, Waleska Simões P. Meta-analysis of magnetic resonance imaging accuracy for diagnosis of oral cancer. PLoS One 2017; 12:e0177462. [PMID: 28542622 PMCID: PMC5443513 DOI: 10.1371/journal.pone.0177462] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 04/27/2017] [Indexed: 01/19/2023] Open
Abstract
Objective To establish the diagnostic accuracy of magnetic resonance imaging (MRI) as an auxiliary means for the diagnosis of oral cancer through a systematic review and meta-analysis. Methods An exhaustive search of publications from 1986 to 2016 was performed of Medline, Embase and Cochrane (and related databases), including grey literature. Primary diagnostic accuracy studies that assessed oral cancer (target condition) using MRI (index test) were included. Diagnostic threshold, sensitivity and meta-regression analyses were performed. A meta-analysis was performed using Meta-DiSc® v. 1.4 software. Results A total of 24 primary studies were assessed, comprising 1,403 oral cancer lesions. Nine studies used diffusion-weighted MRI, with a diagnostic odds ratio (DOR) of 30.7 (95% confidence interval [CI]: 12.7–74.3) and area under the curve (AUC) of 0.917 (95% CI: 0.915–0.918); seven studies used dynamic contrast-enhanced MRI, with a DOR of 48.1 (95%CI: 22.4–103.2) and AUC of 0.936 (95% CI: 0.934–0.937); and 13 studies used traditional MRI, with a DOR of 23.9 (95%CI: 13.2–43.3) and AUC of 0.894 (95% CI: 0.894–0.895). Meta-regression analysis indicated that the magnetic field strength may have influenced the heterogeneity of the results obtained (p = 0.0233) using traditional MRI. Sensitivity analysis revealed a discrete reduction of inconsistency in some subgroups. Conclusion The three types of MRI assessed exhibited satisfactory accuracy compared to biopsy. Considering the relevance of early treatment and screening and that better health care results in improved survival rates and quality of life for oral cancer patients, we suggest the use of MRI as a part of the pre-treatment and monitoring protocol at public health services.
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Affiliation(s)
- Marcelo Aldrighi Moreira
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Laboratory of Information and Communications Technology in Health (TISaude), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Luiza Silveira Lessa
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | | | - Abigail Lopes
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Laboratory of Information and Communications Technology in Health (TISaude), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Eduardo Picolo Xavier
- Laboratory of Information and Communications Technology in Health (TISaude), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Renan Antonio Ceretta
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Fernanda Guglielmi Faustini Sônego
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Cristiane Damiani Tomasi
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Patricia Duarte Simões Pires
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Luciane Bisognin Ceretta
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Laboratory of Information and Communications Technology in Health (TISaude), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Ingrid Dalira Schweigert Perry
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
| | - Priscyla Waleska Simões
- Graduate Program in Public Health (PPGSCol), Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Laboratory of Information and Communications Technology in Health (TISaude), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Dentistry Course, Unidade Acadêmica de Ciências da Saúde (UNASAU), Universidade do Extremo Sul Catarinense (UNESC), Criciúma, SC, Brazil
- Engineering, Modeling and Applied Social Sciences Center (CECS), Universidade Federal do ABC (UFABC), São Bernardo do Campo, SP, Brazil
- * E-mail:
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Tao X, Yang G, Wang P, Wu Y, Zhu W, Shi H, Gong X, Gao W, Yu Q. The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours. Dentomaxillofac Radiol 2017; 46:20160434. [PMID: 28299943 DOI: 10.1259/dmfr.20160434] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVES The aim of this study was to determine the value of combining conventional MRI, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE)-MRI in diagnosing solid neoplasms in the parotid gland. METHODS A total of 148 subjects (101 subjects with benign and 47 subjects with malignant tumours) were evaluated with conventional MRI, DWI and DCE-MRI prior to surgery and pathologic verification. The items observed with conventional MRI included the shape, capsule and signal intensity of parotid masses. The apparent diffusion coefficient (ADC) was calculated from DWI that was obtained with a b-factor of 0 and 1000 s mm-2. A time-intensity curve (TIC) was obtained from DCE-MRI. RESULTS There were significant differences (p < 0.01) in the shape, capsule, ADC and TIC between benign and malignant parotid tumours. Irregular neoplasms without a capsule, ADC <1.12 × 10-3 mm2 s-1 and a plateau enhancement pattern were valuable parameters for predicting malignant neoplasms. A combination of all of these parameters yielded sensitivity, specificity, accuracy, positive-predictive value and negative-predictive value of 85.1%, 94.1%, 91.2%, 87.0% and 93.1%, respectively. CONCLUSIONS A combined analysis using conventional MRI, DWI and DCE-MRI is helpful in distinguishing benign from malignant tumours in the parotid gland.
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Affiliation(s)
- Xiaofeng Tao
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Gongxin Yang
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Pingzhong Wang
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yingwei Wu
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wenjing Zhu
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Huimin Shi
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xin Gong
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Weiqing Gao
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qiang Yu
- Department of Radiology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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