To explore the evolving role of magnetic resonance imaging (MRI) in dental diagnostics and clinical applications, highlighting its advantages as a radiation-free modality and assessing its integration across various dental disciplines.
A narrative review was conducted using peer-reviewed studies from 2011 to 2025, sourced from databases such as PubMed, Scopus, and Google Scholar. Key themes included MRI's diagnostic capabilities, technological advancements, and comparative benefits over traditional imaging modalities.
MRI demonstrates significant promise in evaluating temporomandibular joint disorders, salivary gland pathology, oral mucosal lesions, periodontal and periapical diseases, endodontics, and implantology. Innovations in MRI-compatible coils, ultrashort echo sequences, and artificial intelligence (AI)-enhanced image analysis are expanding its clinical utility. Compared with cone-beam computed tomography (CBCT), MRI provides superior soft tissue contrast and eliminates radiation risks.
MRI is emerging as a valuable diagnostic tool in dentistry. While the current limitations include cost, accessibility, and metal artifacts, continued technological developments and interdisciplinary collaboration are expected to make MRI an integral component of precision dental care.
Citation: Gerta Halilaj, Nebi Cemeta. Beyond radiation: Emerging applications of MRI in dental diagnostics and clinical practice[J]. Journal of Dentistry and Multidisciplinary Sciences, 2025, 1(1): 31-46. doi: 10.3934/jdms.2025004
To explore the evolving role of magnetic resonance imaging (MRI) in dental diagnostics and clinical applications, highlighting its advantages as a radiation-free modality and assessing its integration across various dental disciplines.
A narrative review was conducted using peer-reviewed studies from 2011 to 2025, sourced from databases such as PubMed, Scopus, and Google Scholar. Key themes included MRI's diagnostic capabilities, technological advancements, and comparative benefits over traditional imaging modalities.
MRI demonstrates significant promise in evaluating temporomandibular joint disorders, salivary gland pathology, oral mucosal lesions, periodontal and periapical diseases, endodontics, and implantology. Innovations in MRI-compatible coils, ultrashort echo sequences, and artificial intelligence (AI)-enhanced image analysis are expanding its clinical utility. Compared with cone-beam computed tomography (CBCT), MRI provides superior soft tissue contrast and eliminates radiation risks.
MRI is emerging as a valuable diagnostic tool in dentistry. While the current limitations include cost, accessibility, and metal artifacts, continued technological developments and interdisciplinary collaboration are expected to make MRI an integral component of precision dental care.
| [1] | N. Bromberg, M. Brizuela, Dental Cone Beam Computed Tomography, StatPearls Publishing, 2023. |
| [2] |
S. Friedlander-Barenboim, W. Hamed, A. Zini, N. Yarom, I. Abramovitz, H. Chweidan, et al., Patterns of cone-beam computed tomography (CBCT) utilization by various dental specialties: A 4-year retrospective analysis from a dental and maxillofacial specialty center, Healthcare (Basel), 9 (2021), 1042. https://doi.org/10.3390/healthcare9081042 doi: 10.3390/healthcare9081042
|
| [3] |
F. De Felice, G. Di Carlo, M. Saccucci, V. Tombolini, A. Polimeni, Dental cone beam computed tomography in children: Clinical effectiveness and cancer risk due to radiation exposure, Oncology, 96 (2019), 173–178. https://doi.org/10.1159/000497059 doi: 10.1159/000497059
|
| [4] |
D. Idiyatullin, C. Corum, S. Moeller, H. S. Prasad, M. Garwood, D. R. Nixdorf, Dental magnetic resonance imaging: making the invisible visible, J. Endod., 37 (2011), 745–752. https://doi.org/10.1016/j.joen.2011.02.022 doi: 10.1016/j.joen.2011.02.022
|
| [5] | M. G. Piancino, S. Cirillo, G. Frongia, F. Cena, A. A. Bracco, P. Dalmasso, et al., Sensitivity of magnetic resonance imaging and computed axiography in the diagnosis of temporomandibular joint disorders in a selected patient population, Int. J. Prosthodont., 25 (2012), 120–126. |
| [6] |
X. Xiong, Z. Ye, H. Tang, Y. Wei, L. Nie, X. Wei, et al., MRI of temporomandibular joint disorders: recent advances and future directions, J. Magn. Reson. Imaging, 54 (2021), 1039–1052. https://doi.org/10.1002/jmri.27338 doi: 10.1002/jmri.27338
|
| [7] |
D. Talmaceanu, L. M. Lenghel, N. Bolog, M. Hedesiu, S. Buduru, H. Rotar, et al., Imaging modalities for temporomandibular joint disorders: an update, Clujul. Med., 91 (2018), 280–287. https://doi.org/10.15386/cjmed-970 doi: 10.15386/cjmed-970
|
| [8] |
A. Manoliu, G. Spinner, M. Wyss, S. Erni, D. A. Ettlin, D. Nanz, et al., Quantitative and qualitative comparison of MR imaging of the temporomandibular joint at 1.5 and 3.0 T using an optimized high-resolution protocol, Dentomaxillofac. Radiol., 45 (2016), 20150240. https://doi.org/10.1259/dmfr.20150240 doi: 10.1259/dmfr.20150240
|
| [9] |
K. Y. Cheng, D. Moazamian, Y. Ma, H. Jang, S. Jerban, J. Du, et al., Clinical application of ultrashort echo time (UTE) and zero echo time (ZTE) magnetic resonance (MR) imaging in the evaluation of osteoarthritis, Skeletal. Radiol., 52 (2023), 2149–2157. https://doi.org/10.1007/s00256-022-04269-1 doi: 10.1007/s00256-022-04269-1
|
| [10] |
M. Nozawa, H. Ito, Y. Ariji, M. Fukuda, C. Igarashi, M. Nishiyama, et al., Automatic segmentation of the temporomandibular joint disc on magnetic resonance images using a deep learning technique, Dentomaxillofac. Radiol., 51 (2022), 20210185. https://doi.org/10.1259/dmfr.20210185 doi: 10.1259/dmfr.20210185
|
| [11] |
S. Y. Kim, U. Borner, J. H. Lee, F. Wagner, D. W. Tshering Vogel, Magnetic resonance imaging of parotid gland tumors: a pictorial essay, BMC Med. Imaging, 22 (2022), 191. https://doi.org/10.1186/s12880-022-00924-0 doi: 10.1186/s12880-022-00924-0
|
| [12] |
A. A. K. Abdel Razek, S. Mukherji, Imaging of sialadenitis, Neuroradiol. J., 30 (2017), 205–215. https://doi.org/10.1177/1971400916682752 doi: 10.1177/1971400916682752
|
| [13] |
Y. Takagi, I. Katayama, S. Eida, M. Sasaki, T. Shimizu, S. Sato, et al., Three signs to help detect Sjögren's syndrome: incidental findings on magnetic resonance imaging and computed tomography, J. Clin. Med., 12 (2023), 6487. https://doi.org/10.3390/jcm12206487 doi: 10.3390/jcm12206487
|
| [14] |
K. Mao, L. M. Wong, R. Zhang, T. Y. So, Z. Shan, K. F. Hung, et al., Radiomics analysis in characterization of salivary gland tumors on MRI: A systematic review, Cancers (Basel), 15 (2023), 4918. https://doi.org/10.3390/cancers15204918 doi: 10.3390/cancers15204918
|
| [15] | S. Y. Kim, M. Beer, D. W. Tshering Vogel, Imaging in head and neck cancers: update for non-radiologist, Oral Oncol., 120 (2021). https://doi.org/10.1016/j.oraloncology.2021.105434 |
| [16] | M. Gabelloni, L. Faggioni, S. Attanasio, V. Vani, A. Goddi, S. Colantonio, et al., Can magnetic resonance radiomics analysis discriminate parotid gland tumors? A pilot study, Diagnostics, 10 (2020). https://doi.org/10.3390/diagnostics10110900 |
| [17] |
D. Maraghelli, M. Pietragalla, L. Calistri, L. Barbato, L. G. Locatello, M. Orlandi, et al., Techniques, tricks, and stratagems of oral cavity computed tomography and magnetic resonance imaging, Appl. Sci., 12 (2022), 1473. https://doi.org/10.3390/app12031473 doi: 10.3390/app12031473
|
| [18] |
N. Guo, W. Zeng, H. Deng, H. Hu, Z. Cheng, Z. Yang, et al., Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma, BMC Med. Imaging, 20 (2020), 117. https://doi.org/10.1186/s12880-020-00516-w doi: 10.1186/s12880-020-00516-w
|
| [19] |
K. M. Johannsen, J. M. C. E. S. Fuglsig, L. H. Matzen, J. Christensen, R. Spin-Neto, Magnetic resonance imaging in the diagnosis of periodontal and periapical disease, Dentomaxillofac. Radiol., 52 (2023), 20230184. https://doi.org/10.1259/dmfr.20230184 doi: 10.1259/dmfr.20230184
|
| [20] |
M. Probst, E. Burian, T. Robl, D. Weidlich, D. Karampinos, T. Brunner, et al., Magnetic resonance imaging as a diagnostic tool for periodontal disease: A prospective study with correlation to standard clinical findings—Is there added value?, J. Clin. Periodontol., 48 (2021), 1052–1060. https://doi.org/10.1111/jcpe.13458 doi: 10.1111/jcpe.13458
|
| [21] |
M. A. Geibel, E. S. Schreiber, A. K. Bracher, E. Hell, J. Ulrici, L. K. Sailer, et al., Assessment of apical periodontitis by MRI: a feasibility study, Rofo, 187 (2015), 269–275. https://doi.org/10.1055/s-0034-1385808 doi: 10.1055/s-0034-1385808
|
| [22] |
G. C. Feuerriegel, E. Burian, N. Sollmann, Y. Leonhardt, G. Burian, M. Griesbauer, et al., Evaluation of 3D MRI for early detection of bone edema associated with apical periodontitis, Clin. Oral Investig., 27 (2023), 5403–5412. https://doi.org/10.1007/s00784-023-05159-z doi: 10.1007/s00784-023-05159-z
|
| [23] |
A. T. Assaf, T. A. Zrnc, C. C. Remus, A. Khokale, C. R. Habermann, D. Schulze, et al., Early detection of pulp necrosis and dental vitality after traumatic dental injuries in children and adolescents by 3-Tesla magnetic resonance imaging, J. Craniomaxillofac. Surg., 43 (2015), 1088–1093. https://doi.org/10.1016/j.jcms.2015.06.010 doi: 10.1016/j.jcms.2015.06.010
|
| [24] |
A. Juerchott, C. Jelinek, D. Kronsteiner, J. M. E. Jende, F. T. Kurz, M. Bendszus, et al., Quantitative assessment of contrast-enhancement patterns of the healthy dental pulp by magnetic resonance imaging: a prospective in vivo study, Int. Endod. J., 55 (2022), 252–262. https://doi.org/10.1111/iej.13662 doi: 10.1111/iej.13662
|
| [25] |
K. Cankar, J. Vidmar, L. Nemeth, I. Serša, T2 mapping as a tool for assessment of dental pulp response to caries progression: An in vivo MRI study, Caries Res., 54 (2020), 24–35. https://doi.org/10.1159/000501901 doi: 10.1159/000501901
|
| [26] |
A. S. Tesfai, A. Vollmer, A. C. Özen, M. Braig, W. Semper-Hogg, M. J. Altenburger, et al., Inductively coupled intraoral flexible coil for increased visibility of dental root canals in magnetic resonance imaging, Invest. Radiol., 57 (2022), 163–170. https://doi.org/10.1097/RLI.0000000000000826 doi: 10.1097/RLI.0000000000000826
|
| [27] |
A. K. Bracher, C. Hofmann, A. Bornstedt, E. Hell, F. Janke, J. Ulrici, et al., Ultrashort echo time (UTE) MRI for the assessment of caries lesions, Dentomaxillofac. Radiol., 42 (2013), 20120321. https://doi.org/10.1259/dmfr.20120321 doi: 10.1259/dmfr.20120321
|
| [28] |
T. Flügge, U. Ludwig, G. Winter, P. Amrein, F. Kernen, K. Nelson, Fully guided implant surgery using magnetic resonance imaging – An in vitro study on accuracy in human mandibles, Clin. Oral Implants Res., 31 (2020), 737–746. https://doi.org/10.1111/clr.13622 doi: 10.1111/clr.13622
|
| [29] |
N. Kamona, B. C. Jones, H. Lee, H. K. Song, C. S. Rajapakse, C. S. Wagner, et al., Cranial bone imaging using ultrashort echo-time bone-selective MRI as an alternative to gradient-echo based "black-bone" techniques, MAGMA, 37 (2024), 83–92. https://doi.org/10.1007/s10334-023-01125-8 doi: 10.1007/s10334-023-01125-8
|
| [30] |
S. Jerban, D. G. Chang, Y. Ma, H. Jang, E. Y. Chang, J. Du, An update in qualitative imaging of bone using ultrashort echo time magnetic resonance, Front. Endocrinol., 11 (2020), 555756. https://doi.org/10.3389/fendo.2020.555756 doi: 10.3389/fendo.2020.555756
|
| [31] |
F. Wiesinger, M. L. Ho, Zero-TE MRI: principles and applications in the head and neck, Br. J. Radiol., 95 (2022), 20220059. https://doi.org/10.1259/bjr.20220059 doi: 10.1259/bjr.20220059
|
| [32] |
F. A. R. Laurino, I. G. G. Choi, J. H. Kim, I. O. Gialain, R. Ferraço, R. G. Haetinger, et al., Correlation between magnetic resonance imaging and cone-beam computed tomography for maxillary sinus graft assessment, Imaging Sci. Dent., 50 (2020), 93–98. https://doi.org/10.5624/isd.2020.50.2.93 doi: 10.5624/isd.2020.50.2.93
|
| [33] |
U. Ludwig, A. K. Eisenbeiss, C. Scheifele, K. Nelson, M. Bock, J. Hennig, et al., Dental MRI using wireless intraoral coils, Sci. Rep., 6 (2016), 23301. https://doi.org/10.1038/srep23301 doi: 10.1038/srep23301
|
| [34] |
T. Hilgenfeld, M. Prager, F. S. Schwindling, J. M. E. Jende, P. Rammelsberg, M. Bendszus, et al., Protocol for the evaluation of MRI artifacts caused by metal implants to assess the suitability of implants and the vulnerability of pulse sequences, J. Vis. Exp., 135 (2018), 57394. https://doi.org/10.3791/57394 doi: 10.3791/57394
|
| [35] | H. D. Kocasarac, E. S. Kursun-Cakmak, G. Ustaoglu, S. Bayrak, K. Orhan, M. Noujeim, Assessment of signal-to-noise ratio and contrast-to-noise ratio in 3 T magnetic resonance imaging in the presence of zirconium, titanium, and titanium-zirconium alloy implants, Oral Surg. Oral Med. Oral Pathol. Oral Radiol., 129 (2020), 80–86. https://doi.org/10.1016/j.oooo.2019.08.020 |
| [36] |
D. Du, G. M. Bydder, Qualitative and quantitative ultrashort-TE MRI of cortical bone, NMR Biomed., 26 (2013), 489–506. https://doi.org/10.1002/nbm.2906 doi: 10.1002/nbm.2906
|
| [37] |
K. D. Kocasarac, G. Ustaoglu, S. Bayrak, R. Katkar, H. Geha, S. T. Deahl, et al., Evaluation of artifacts generated by titanium, zirconium, and titanium–zirconium alloy dental implants on MRI, CT, and CBCT images: A phantom study, Oral Surg. Oral Med. Oral Pathol. Oral Radiol., 127 (2019), 535–544. https://doi.org/10.1016/j.oooo.2019.01.074 doi: 10.1016/j.oooo.2019.01.074
|
| [38] |
A. A. de Magalhães, A. T. Santos, Advancements in diagnostic methods and imaging technologies in dentistry: A literature review of emerging approaches, J. Clin. Med., 14 (2025), 1277. https://doi.org/10.3390/jcm14041277 doi: 10.3390/jcm14041277
|
| [39] |
A. Gliga, M. Imre, S. Grandini, C. Marruganti, C. Gaeta, D. Bodnar, et al., The limitations of periapical X-ray assessment in endodontic diagnosis—A systematic review, J. Clin. Med., 12 (2023), 4647. https://doi.org/10.3390/jcm12144647 doi: 10.3390/jcm12144647
|
| [40] | W. Kazimierczak, R. Wajer, O. Komisarek, A. Wajer, N. Kazimierczak, J. Janiszewska-Olszowska, et al., Enhanced cone-beam computed tomography imaging through deep learning model reconstruction: noise reduction and image quality optimization in dental diagnostics, 2023. https://doi.org/10.21203/rs.3.rs-3650822/v1 |
| [41] | A. Meto, G. Halilaj, The integration of cone beam computed tomography, artificial intelligence, augmented reality, and virtual reality in dental diagnostics, surgical planning, and education: A narrative review, Appl. Sci., 15 (2025), 6308. https://doi.org/10.3390/app15116308 |
| [42] |
E. Burian, N. Lenhart, T. Greve, J. Bodden, G. Burian, B. Palla, et al., Detection of caries lesions using a water-sensitive STIR sequence in dental MRI, Sci. Rep., 14 (2024), 663. https://doi.org/10.1038/s41598-024-51151-2 doi: 10.1038/s41598-024-51151-2
|
| [43] |
B. Han, N. Chen, J. Luo, F. Afkhami, O. A. Peters, X. Wang, Magnetic resonance imaging for dental pulp assessment: A comprehensive review, J. Magn. Reson. Imaging, 2025 (2025). https://doi.org/10.1002/jmri.29742 doi: 10.1002/jmri.29742
|
| [44] |
T. Hilgenfeld, A. Juerchott, J. M. E. Jende, P. Rammelsberg, S. Heiland, M. Bendszus, et al., Use of dental MRI for radiation-free guided dental implant planning: a prospective, in vivo study of accuracy and reliability, Eur. Radiol., 30 (2020), 6392–6401. https://doi.org/10.1007/s00330-020-07262-1 doi: 10.1007/s00330-020-07262-1
|
| [45] |
D. A. Tyndall, J. B. Price, L. Gaalaas, R. Spin-Neto, Surveying the landscape of diagnostic imaging in dentistry's future: Four emerging technologies with promise, J. Am. Dent. Assoc., 155 (2024), 364–378. https://doi.org/10.1016/j.adaj.2024.01.005 doi: 10.1016/j.adaj.2024.01.005
|
| [46] |
T. J. Schuurmans, D. R. Nixdorf, D. S. Idiyatullin, A. S. Law, B. D. Barsness, S. H. Roach, et al., Accuracy and reliability of root crack and fracture detection in teeth using magnetic resonance imaging, J. Endod., 45 (2019), 750–755. https://doi.org/10.1016/j.joen.2019.03.009 doi: 10.1016/j.joen.2019.03.009
|
| [47] |
D. Idiyatullin, M. Garwood, L. Gaalaas, D. R. Nixdorf, Role of MRI for detecting micro cracks in teeth, Dentomaxillofac. Radiol., 45 (2016), 20160150. https://doi.org/10.1259/dmfr.20160150 doi: 10.1259/dmfr.20160150
|
| [48] |
B. R. Groenke, D. Idiyatullin, L. Gaalaas, A. Petersen, A. Law, B. Barsness, et al., Sensitivity and specificity of MRI versus CBCT to detect vertical root fractures using MicroCT as a reference standard, J. Endod., 49 (2023), 703–709. https://doi.org/10.1016/j.joen.2023.03.011 doi: 10.1016/j.joen.2023.03.011
|
| [49] |
A. Greiser, J. Christensen, J. M. C. S. Fuglsig, K. M. Johannsen, D. R. Nixdorf, K. Burzan, et al., Dental-dedicated MRI, a novel approach for dentomaxillofacial diagnostic imaging: technical specifications and feasibility, Dentomaxillofac. Radiol., 53 (2024), 74–85. https://doi.org/10.1093/dmfr/twad004 doi: 10.1093/dmfr/twad004
|
| [50] |
H. D. Kocasarac, H. Geha, L. R. Gaalaas, D. R. Nixdorf, MRI for dental applications, Dent. Clin. North Am., 62 (2018), 467–480. https://doi.org/10.1016/j.cden.2018.03.006 doi: 10.1016/j.cden.2018.03.006
|
| [51] |
R. Reda, A. Zanza, A. Mazzoni, A. Cicconetti, L. Testarelli, D. Di Nardo, An update of the possible applications of magnetic resonance imaging (MRI) in dentistry: A literature review, J. Imaging, 7 (2021), 75. https://doi.org/10.3390/jimaging7050075 doi: 10.3390/jimaging7050075
|
| [52] |
S. J. Chockattu, D. B. Suryakant, S. Thakur, Unwanted effects due to interactions between dental materials and magnetic resonance imaging: a review of the literature, Restor. Dent. Endod., 43 (2018), e39. https://doi.org/10.5395/rde.2018.43.e39 doi: 10.5395/rde.2018.43.e39
|
| [53] |
T. Flügge, C. Gross, U. Ludwig, J. Schmitz, S. Nahles, M. Heiland, et al., Dental MRI—only a future vision or standard of care? A literature review on current indications and applications of MRI in dentistry, Dentomaxillofac. Radiol., 52 (2023), 20220333. https://doi.org/10.1259/dmfr.20220333 doi: 10.1259/dmfr.20220333
|
| [54] |
Y. Rösner, L. L. Brüning, A. Neff, Can provision of additional arthroscopic video material improve accuracy of assessment of temporomandibular joint disorders by dental Non-experts vs. MRI alone: An exploratory study in 3rd to 5th year German dental students, Oral Maxillofac. Surg, 29 (2025), 74. https://doi.org/10.1007/s10006-025-01369-9 doi: 10.1007/s10006-025-01369-9
|
| [55] |
A. C. Özen, S. Ilbey, F. Jia, D. Idiyatullin, M. Garwood, D. R. Nixdorf, et al., An improved intraoral transverse loop coil design for high-resolution dental MRI, Magn. Reson. Med., 90 (2023), 1728–1737. https://doi.org/10.1002/mrm.29744 doi: 10.1002/mrm.29744
|
| [56] |
M. Khalifa, M. Albadawy, AI in diagnostic imaging: Revolutionising accuracy and efficiency, Comput. Methods Programs Biomed., 2024 (2024) 100146. https://doi.org/10.1016/j.cmpbup.2024.100146 doi: 10.1016/j.cmpbup.2024.100146
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Figures(3) / Tables(1)
Gerta Halilaj, Nebi Cemeta. Beyond radiation: Emerging applications of MRI in dental diagnostics and clinical practice[J]. Journal of Dentistry and Multidisciplinary Sciences, 2025, 1(1): 31-46. doi: 10.3934/jdms.2025004
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