Invited Review

DOI :10.26650/eor.20241450729 IUP :10.26650/eor.20241450729 Full Text (PDF)

Advancements in the MRI technology for identification of dentomaxillofacial pathologies

The high-resolution imaging capabilities of Magnetic Resonance Imaging (MRI) make it highly suitable for visualizing a wide range of dentomaxillofacial pathologies, including tumors, inflammatory conditions, and vascular abnormalities. This review focuses to the role of MRI in imaging head and neck pathologies, highlighting its advantages over traditional radiodiagnostics in dentistry. MRI's ability to detect periapical lesions, differentiate between various cysts and tumors, and assess the characteristics of odontogenic and non-odontogenic lesions is discussed. Special consideration is given to the differentiation of odontogenic keratocysts and ameloblastomas, as well as the evaluation of odontogenic fibromas and myxomas using dynamic contrast-enhanced MRI. Additionally, the review explores the potential of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values in distinguishing benign from malignant lesions, emphasizing the significance of these techniques in characterizing salivary gland tumors. Future advancements in MRI technology, including the application of high-field MRI and radiomics, are also considered. Radiomics, driven by artificial intelligence, offers a promising approach to extracting quantitative features from medical images, potentially enhancing the accuracy of diagnosis and prognosis in oral cancer. The review concludes by underscoring the transformative impact of MRI in dentomaxillofacial radiodiagnostics, advocating for its broader adoption in clinical practice to improve diagnostic accuracy and patient outcomes.

Keywords: diffusion-weighted imaging, magnetic resonance imaging, odontogenic cysts, odontogenic tumors, radiomics

DOI :10.26650/eor.20241450729 IUP :10.26650/eor.20241450729 Full Text (PDF)

Dentomaksillofasiyal Patolojilerin Değerlendirilmesinde MRG Teknolojisindeki Gelişmeler

Melisa Öçbe

Manyetik Rezonans Görüntüleme (MRG), yüksek çözünürlüklü görüntüleme yetenekleri sayesinde tümörler, enflamatuar durumlar ve vasküler anormallikler de dahil olmak üzere geniş bir yelpazede dentomaksillofasiyal patolojilerin görüntülenmesi için son derece uygundur. Bu derleme, MRG'nin baş ve boyun patolojilerini görüntülemedeki rolünü incelemekte ve diş hekimliğinde geleneksel radyodiagnostiğe göre avantajlarını vurgulamaktadır. MRG'nin periapikal lezyonları tespit etme, çeşitli kistler ve tümörler arasında ayrım yapma ve odontojenik ve non-odontojenik lezyonların özelliklerini değerlendirme yeteneği ele alınmaktadır. Odontojenik keratokistler ile ameloblastomların ayrımı ve dinamik kontrastlı MRG kullanarak odontojenik fibromlar ve miksomaların değerlendirilmesine özel bir vurgu yapılmaktadır. Ayrıca, diffüzyon ağırlıklı görüntüleme (DWI) ve görünür diffüzyon katsayısı (ADC) değerlerinin benign ve malign lezyonları ayırt etmedeki potansiyeli, tükürük bezi tümörlerinin karakterizasyonunda bu tekniklerin önemi vurgulanmaktadır. Gelecekteki MRG teknolojisi gelişmeleri, yüksek alanlı MRG ve radyomiks uygulamaları da ele alınmaktadır. Yapay zeka tarafından yönlendirilen radyomiks, tıbbi görüntülerden nicel özellikler çıkarmada umut verici bir yaklaşım sunmakta ve oral kanserde teşhis ve prognoz doğruluğunu artırma potansiyeline sahiptir. Derleme, MRG'nin dentomaksillofasiyal radyodiagnostikteki dönüştürücü etkisini vurgulayarak, teşhis doğruluğunu ve hasta sonuçlarını iyileştirmek için klinik pratikte daha geniş bir şekilde benimsenmesini savunarak son bulmaktadır.

Keywords: Difüzyon ağırlıklı görüntüleme, manyetik rezonans görüntüleme, odontojenik kistler, odontojenik tümörler, radyomiks

References

1. Kiljunen T, Kaasalainen T, Suomalainen A, Kortesniemi M. Dental cone beam CT: A review. Phys Med 2015;31:844-60. doi: 10.1016/j.ejmp.2015.09.004. google scholar
2. Hisatomi M, Asaumi J, Konouchi H, Shigehara H, Yanagi Y, Kishi K. MR imaging of epithelial cysts of the oral and maxillofacial region. Eur J Radiol 2003;48:178-82. doi: 10.1016/S0720-048X(02)00218-8. google scholar
3. Al-Haj Husain A, Schönegg D, Valdec S, Stadlinger B, Piccirelli M, Winklhofer S. Appearance of nasopalatine duct cysts on dental magnetic resonance imaging using a mandibular coil: Two case reports with a literature review. Imaging Sci Dent 2023;53:161-8. doi: 10.5624/isd.20220215. google scholar
4. Juerchott A, Pfefferle T, Flechtenmacher C, Mente J, Bendszus M, Heiland S, Hilgenfeld T. Differentiation of periapical granulomas and cysts by using dental MRI: a pilot study. Int J Oral Sci 2018;10:17. doi: 10.1038/s41368-018-0017-y. google scholar
5. Probst FA, Probst M, Pautke Ch, Kaltsi E, Otto S, Schiel S, Troeltzsch M, Ehrenfeld M, Cornelius CP, Müller-Lisse UG. Magnetic resonance imaging: a useful tool to distinguish between keratocystic odontogenic tumours and odontogenic cysts. Br J Oral Maxillofac Surg 2015;53:217-22. doi: 10.1016/j.bjoms.2014.10.014 google scholar
6. Fujita M, Matsuzaki H, Yanagi Y, Hara M, Katase N, Hisatomi M, Unetsubo T, Konouchi H, Nagatsuka H, Asaumi JI. Diagnostic value of MRI for odontogenic tumours. Dentomaxillofac Radiol 2013;42:20120265. doi: 10.1259/dmfr.20120265. google scholar
7. Han Y, Fan X, Su L, Wang Z. Diffusion-Weighted MR Imaging of Unicystic Odontogenic Tumors for Differentiation of Unicystic Ameloblastomas from Keratocystic Odontogenic Tumors. Korean J Radiol 2018;19:79-84. doi: 10.3348/kjr.2018.19.1.79. google scholar
8. Minami M, Kaneda T, Ozawa K, Yamamoto H, Itai Y, Ozawa M, Yoshikawa K, Sasaki Y. Cystic lesions of the maxillomandibular region: MR imaging distinction of odontogenic keratocysts and ameloblastomas from other cysts. AJR Am J Roentgenol 1996;166:943-9. doi: 10.2214/ajr.166.4.8610578. google scholar
9. Yanagi Y, Asaumi J, Unetsubo T, Ashida M, Takenobu T, Hisatomi M, Matsuzaki H, Konouchi H, Katase N, Nagatsuka H. Usefulness of MRI and dynamic contrast-enhanced MRI for differential diagnosis of simple bone cysts from true cysts in the jaw. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2010;110:364-9. doi: 10.1016/j.tripleo.2010.05.001. google scholar
10. Spinelli HM, Isenberg JS, O'Brien M. Nasopalatine duct cysts and the role of magnetic resonance imaging. J Craniofac Surg 1994;5:57-60. doi: 10.1097/00001665-199402000-00013. google scholar
11. Hisatomi M, Asaumi J, Konouchi H, Matsuzaki H, Kishi K. MR imaging of nasopalatine duct cysts. Eur J Radiol 2001;39:73-6. doi: 10.1016/s0720-048x(01)00279-0. google scholar
12. Grover VP, Tognarelli JM, Crossey MM, Cox IJ, Taylor-Robinson SD, McPhail MJ. Magnetic Resonance Imaging: Principles and Techniques: Lessons for Clinicians. J Clin Exp Hepatol 2015;5:246-55. doi: 10.1016/j.jceh.2015.08.001. google scholar
13. El-Gerby KM, El-Anwar MW. Differentiating Benign from Malignant Sinonasal Lesions: Feasibility of Diffusion Weighted MRI. Int Arch Otorhinolaryngol 2017;21:358-65. doi: 10.1055/s-0036-1597323. google scholar
14. Koontz NA, Wiggins RH 3rd. Differentiation of Benign and Malignant Head and Neck Lesions With Diffusion Tensor Imaging and DWI. AJR Am J Roentgenol 2017;208:1110-15. doi: 10.2214/AJR.16.16486. google scholar
15. Panyaping T, Tepkidakarn N, Kiatthanabumrung S, Wattanatranon D, Tritanon O. Usefulness of apparent diffusion coefficient values for distinguishing between squamous cell carcinoma and malignant salivary ^gland tumor of the head and neck. Neuroradiol J 2023;36:548-54. doi: 10.1177/19714009231163561. google scholar
16. Bao D, Zhao Y, Wu W, Zhong H, Yuan M, Li L, Lin M, Zhao X, Luo D. Added value of histogram analysis of ADC in predicting radiation-induced temporal lobe injury of patients with nasopharyngeal carcinoma treated by intensity-modulated radiotherapy. Insights Imaging 2022; 13:197. doi: 10.1186/s13244-022-01338-w. google scholar
17. Baba A, Kurokawa R, Kurokawa M, Srinivasan A. Dynamic contrast-enhanced MRI parameters and apparent diffusion coefficient as treatment response markers of skull base osteomyelitis: a preliminary study. Pol J Radiol 2023;88:319-24. doi: 10.5114/pjr.2023.130383. google scholar
18. Norris CD, Quick SE, Parker JG, Koontz NA. Diffusion MR Imaging in the Head and Neck: Principles and Applications. Neuroimaging Clin N Am 2020;30:261-82. doi: 10.1016/j.nic.2020.04.001. google scholar
19. Li S, Cheng J, Zhang Y, Zhang Z. Differentiation of benign and malignant lesions of the tongue by using diffusion-weighted MRI at 3.0 T. Dentomaxillofac Radiol 2015;44:20140325. doi: 10.1259/dmfr.20140325. google scholar
20. Vidiri A, Minosse S, Piludu F, Curione D, Pichi B, Spriano G, Marzi S. Feasibility study of reduced field of view diffUsion-weighted magnetic resonance imaging in head and neck tumors. Acta Radiol 2017;58:292-300. doi: 10.1177/0284185116652014. google scholar
21. Zheng N, Li R, Liu W, Shao S, Jiang S. The diagnostic value of combining conventional, diffusion-weighted imaging and dynamic contrast-enhanced MRI for salivary gland tumors. Br J Radiol 2018;91:20170707. doi: 10.1259/bjr.20170707. google scholar
22. Yuan Y, Tang W, Jiang M, Tao X. Palatal lesions: discriminative value of conventional MRI and diffusion weighted imaging. Br J Radiol 2016;89:20150911. doi: 10.1259/bjr.20150911. google scholar
23. Baba A, Kurokawa R, Kurokawa M, Ota Y, Srinivasan A. Dynamic Contrast-Enhanced MRI Parameters and Normalized ADC Values Could Aid Differentiation of Skull Base Osteomyelitis from Nasopharyngeal Cancer. AJNR Am J Neuroradiol 2023;44:74-8. doi: 10.3174/ajnr.A7740. google scholar
24. Auinger AB, Dahm V, Stanisz I, Schwarz-Nemec U, Arnoldner C. The challenging diagnosis and follow-up of skull base osteomyelitis in clinical practice. Eur Arch Otorhinolaryngol 2021;278:4681-8. doi: 10.1007/s00405-020-06576-6. Epub 2021 Jan 28. google scholar
25. Clark MP, Pretorius PM, Byren I, Milford CA. Central or atypical skull base osteomyelitis: diagnosis and treatment. Skull Base 2009;19:247-54. doi: 10.1055/s-0028-1115325. google scholar
26. Yousem DM, Kraut MA, Chalian AA. Major salivary gland imaging. Radiology. 2000;216:19-29. doi: 10.1148/radiology.216.1.r00jl4519. google scholar
27. Milad P, Elbegiermy M, Shokry T, Mahmoud H, Kamal I, Taha MS, Keriakos N. The added value of pretreatment DW MRI in characterization of salivary glands pathologies. Am J Otolaryngol 2017;38:13-20. doi: 10.1016/j.amjoto.2016.09.002. google scholar
28. Habermann CR, Gossrau P, Graessner J, Arndt C, Cramer MC, Reitmeier F, Jaehne M, Adam G. Diffusion-weighted echo-planar MRI: a valuable tool for differentiating primary parotid gland tumors? Rofo 2005;177:940-5. doi: 10.1055/s-2005-858297. Erratum in: Rofo. 2005 Sep;177(9):1312. google scholar
29. Swartz JD, Rothman MI, Marlowe FI, Berger AS. MR imaging of parotid mass lesions: attempts at histopathologic differentiation. J Comput Assist Tomogr 1989;13:789-96. doi: 10.1097/00004728-198909000-00007. google scholar
30. Som PM, Biller HF. High-grade malignancies of the parotid gland: identification with MR imaging. Radiology 1989;173:823-6. doi: 10.1148/radiology.173.3.2813793. google scholar
31. Assili S, Fathi Kazerooni A, Aghaghazvini L, Saligheh Rad HR, Pirayesh Islamian J. Dynamic Contrast Magnetic Resonance Imaging (DCE-MRI) and Diffusion Weighted MR Imaging (DWI) for Differentiation between Benign and Malignant Salivary Gland Tumors. J Biomed Phys Eng 2015;5:157-68. google scholar
32. Yabuuchi H, Kamitani T, Sagiyama K, Yamasaki Y, Hida T, Matsuura Y, Hino T, Murayama Y, Yasumatsu R, Yamamoto H. Characterization of parotid gland tumors: added value of permeability MR imaging to DWI and DCE-MRI. Eur Radiol 2020;30:6402-12. doi: 10.1007/s00330-020-07004-3. google scholar
33. Yabuuchi H, Fukuya T, Tajima T, Hachitanda Y, Tomita K, Koga M. Salivary gland tumors: diagnostic value of gadolinium-enhanced dynamic MR imaging with histopathologic correlation. Radiology 2003;226:345-54. doi: 10.1148/radiol.2262011486. Erratum in: Radiology. 2003;227(3):909. google scholar
34. Eida S, Sumi M, Nakamura T. Multiparametric magnetic resonance imaging for the differentiation between benign and malignant salivary gland tumors. J Magn Reson Imaging 2010;31:673-9. doi: 10.1002/jmri.22091. google scholar
35. Zhu X, Shao L, Liu Z, Liu Z, He J, Liu J, Ping H, Lu J. MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer. J Zhejiang Univ Sci B 2023;24:663-81. doi: 10.1631/jzus.B2200619. google scholar
36. Liu S, Zhang A, Xiong J, Su X, Zhou Y, Li Y, Zhang Z, Li Z, Liu F. The application of radiomics machine learning models based on multimodal MRI with different sequence combinations in predicting cervical lymph node metastasis in oral tongue squamous cell carcinoma patients. Head Neck 2024;46:513-27. doi: 10.1002/hed.27605. google scholar
37. Mossinelli C, Tagliabue M, Ruju F, Cammarata G, Volpe S, Raimondi S, Zaffaroni M, Isaksson JL, Garibaldi C, Cremonesi M, Corso F, Gaeta A, Emili I, Zorzi S, Alterio D, Marvaso G, Pepa M, De Fiori E, Maffini F, Preda L, Benazzo M, Jereczek-Fossa BA, Ansarin M. The role of radiomics in tongue cancer: A new tool for prognosis prediction. Head Neck 2023;45:849-61. doi: 10.1002/hed.27299. google scholar
38. Chen J, Lu S, Mao Y, Tan L, Li G, Gao Y, Tan P, Huang D, Zhang X, Qiu Y, Liu Y. An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study. Eur Radiol 2022;32:1548-57. doi: 10.1007/s00330-021-08292-z. google scholar
39. Bseiso A, Saqib M, Saigol MS, Rehman A, Sare A, Yagoub AE, Mumtaz H. Patient survival prediction in locally advanced cervical squamous cell carcinoma using MRI-based radiomics: retrospective cohort study. Ann Med Surg (Lond) 2023;85:5328-36. doi: 10.1097/MS9.0000000000001288. google scholar
40. Bae S, Choi YS, Sohn B, Ahn SS, Lee SK, Yang J, Kim J. Squamous Cell Carcinoma and Lymphoma of the Oropharynx: Differentiation Using a Radiomics Approach. Yonsei Med J 2020;61:895-900. doi: 10.3349/ymj.2020.61.10.895. google scholar
41. Lu S, Ling H, Chen J, Tan L, Gao Y, Li H, Tan P, Huang D, Zhang X, Liu Y, Mao Y, Qiu Y. MRI-based radiomics analysis for preoperative evaluation of lymph node metastasis in hypopharyngeal squamous cell carcinoma. Front Oncol 2022;12:936040. doi: 10.3389/fonc.2022.936040. google scholar
42. Caprini E, D'Agnese G, Brennan PA, Rahimi S. Human papilomaviru-related oropharyngeal squamous cell carcinoma and radiomics: A new era? J Oral Pathol Med 2023;52:300-4. doi: 10.1111/jop.13419. google scholar
43. Chen X, Qu L, Xie Y, Ahmad S, Yap PT. A paired dataset of T1- and T2-weighted MRI at 3 Tesla and 7 Tesla. Sci Data 2023;10:489. doi: 10.1038/s41597-023-02400-y. google scholar
44. Trattnig S, Springer E, Bogner W, Hangel G, Strasser B, Dymerska B, Cardoso PL, Robinson SD. Key clinical benefits of neuroimaging at 7T. Neuroimage 2018;168:477-89. doi: 10.1016/j.neuroimage.2016.11.031. google scholar
45. Clarke MA, Witt AA, Robison RK, Fleishman S, Combes AJE, Houston D, Prock LE, Sweeney G, O'Grady KP, McKnight CD, Smith SA. Cervical spinal cord susceptibility-weighted MRI at 7T: Application to multiple sclerosis. Neuroimage 2023;284:120460. doi: 10.1016/j.neuroimage.2023.120460. google scholar
46. de Rotte AA, Groenewegen A, Rutgers DR, Witkamp T, Zelissen PM, Meijer FJ, van Lindert EJ, Hermus A, Luijten PR, Hendrikse J. High resolution pituitary gland MRI at 7.0 tesla: a clinical evaluation in Cushing's disease. Eur Radiol 2016;26:271-7. doi: 10.1007/s00330-015-3809-x. google scholar
47. Bonacchi R, Pagani E, Meani A, Cacciaguerra L, Preziosa P, De Meo E, Filippi M, Rocca MA. Clinical Relevance of Multiparametric MRI Assessment of Cervical Cord Damage in Multiple Sclerosis. Radiology 2020;296:605-15. doi: 10.1148/radiol.2020200430. google scholar

Citations

Copy and paste a formatted citation or use one of the options to export in your chosen format

EXPORT

APA

Öçbe, M. (2024). Advancements in the MRI technology for identification of dentomaxillofacial pathologies. European Oral Research, 0(0), -. https://doi.org/10.26650/eor.20241450729

AMA

Öçbe M. Advancements in the MRI technology for identification of dentomaxillofacial pathologies. European Oral Research. 2024;0(0):-. https://doi.org/10.26650/eor.20241450729

ABNT

Öçbe, M. Advancements in the MRI technology for identification of dentomaxillofacial pathologies. European Oral Research, [Publisher Location], v. 0, n. 0, p. -, 2024.

Chicago: Author-Date Style

Öçbe, Melisa,. 2024. “Advancements in the MRI technology for identification of dentomaxillofacial pathologies.” European Oral Research 0, no. 0: -. https://doi.org/10.26650/eor.20241450729

Chicago: Humanities Style

Öçbe, Melisa,. “Advancements in the MRI technology for identification of dentomaxillofacial pathologies.” European Oral Research 0, no. 0 (Nov. 2024): -. https://doi.org/10.26650/eor.20241450729

Harvard: Australian Style

Öçbe, M 2024, 'Advancements in the MRI technology for identification of dentomaxillofacial pathologies', European Oral Research, vol. 0, no. 0, pp. -, viewed 22 Nov. 2024, https://doi.org/10.26650/eor.20241450729

Harvard: Author-Date Style

Öçbe, M. (2024) ‘Advancements in the MRI technology for identification of dentomaxillofacial pathologies’, European Oral Research, 0(0), pp. -. https://doi.org/10.26650/eor.20241450729 (22 Nov. 2024).

MLA

Öçbe, Melisa,. “Advancements in the MRI technology for identification of dentomaxillofacial pathologies.” European Oral Research, vol. 0, no. 0, 2024, pp. -. [Database Container], https://doi.org/10.26650/eor.20241450729

Vancouver

Öçbe M. Advancements in the MRI technology for identification of dentomaxillofacial pathologies. European Oral Research [Internet]. 22 Nov. 2024 [cited 22 Nov. 2024];0(0):-. Available from: https://doi.org/10.26650/eor.20241450729 doi: 10.26650/eor.20241450729

ISNAD

Öçbe, Melisa. “Advancements in the MRI technology for identification of dentomaxillofacial pathologies”. European Oral Research 0/0 (Nov. 2024): -. https://doi.org/10.26650/eor.20241450729

TIMELINE

Submitted	11.03.2024
Accepted	24.06.2024
Published Online	16.08.2024

LICENCE

Attribution-NonCommercial (CC BY-NC)

This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.

European Oral Research