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Quantitative assessment of the mandibular condyle in patients with diabetes mellitus using diffusion-weighted magnetic resonance imaging



The purpose of this study was to quantitatively assess the mandibular condyle in patients with diabetes mellitus (DM) using the apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DWI).

Study Design

102 patients with DM and temporomandibular joint (TMJ) pain who underwent magnetic resonance imaging (MRI) examination of the TMJs at our hospital between August 2006 and March 2020 were included in this study. 112 patients with temporomandibular disorders (TMD) who underwent MRI examination at our hospital between April 2019 and March 2020 were included as controls. The MRI findings were compared between the two groups.


The mean ADC values of the mandibular condyle in patients with DM were significantly greater than the controls (P < 0.01). Receiver operating characteristic (ROC) curve analysis revealed a cutoff of 0.98 for the ADC values of the mandibular condyle in patients with DM.


This study found that the ADC on DWI could be used for the quantitative assessment of the mandibular condyle in patients with DM. DWI might serve as a new and noninvasive method to assess the presence of DM.

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Diabetes mellitus


Type 1 diabetes mellitus


Type 2 diabetes mellitus


International Diabetes Federation




Temporomandibular joint


Temporomandibular disorders


Magnetic resonance imaging


Apparent diffusion coefficient


Diffusion weighted magnetic resonance imaging


Japan Diabetes Society


Receiver operating characteristic


Area under the roc curve


Intraclass correlation coefficient


  1. Han W, Shengqi Y, Zhangqin H, et al. Type 2 diabetes mellitus prediction model based on data mining. Inform Med Unlocked. 2018;10:100–7.

    Article  Google Scholar 

  2. Lamster IB, Lalla E, Borgnakke WS, Taylor GW. The relationship between oral health and diabetes mellitus. J Am Dent Assoc. 2008;139:19–24.

    Article  Google Scholar 

  3. Lalla E, Papapanou PN. Diabetes mellitus and periodontitis: a tale of two common interrelated diseases. Nat Rev Endocrinol. 2011;7:738–48.

    Article  Google Scholar 

  4. Otomo-Corgel J, Pucher JJ, Rethman MP, Reynolds MA. State of the science: chronic periodontitis and systemic health. J Evid Based Dent Pract. 2012;12:20–8.

    Article  Google Scholar 

  5. Patterson CC, Dahlquist GG, Gyurus E, et al. Incidence trends for childhood type 1 diabetes in Europe during 1989–2003 and predicted new cases 2005–20: a multicentre prospective registration study. Lancet. 2009;373:2027–33.

    Article  Google Scholar 

  6. Dahlquist GG, Nystrom L, Patterson CC. Incidence of type 1 diabetes in Sweden among individuals aged 0–34 years, 1983–2007: an analysis of time trends. Diabetes Care. 2011;34:1754–9.

    Article  Google Scholar 

  7. Almgren P, Lehtovirta M, Isomaa B, et al. Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study. Diabetologia. 2011;54:2811–9.

    Article  Google Scholar 

  8. Vivian AF. Defining and characterizing the progression of type 2 diabetes. Diabetes Care. 2009;32:151–6.

    Google Scholar 

  9. American Diabetes Association. Standards of medical care in diabetes-2019 abridged for primary care providers. Clin Diabetes. 2019;37:11–34.

    Article  Google Scholar 

  10. Davies MJ, D’Alessio DA, Fradkin J, et al. Management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia. 2018;2018(61):2461–98.

    Article  Google Scholar 

  11. Lingyan Z, Chi Y, Weijie Z, et al. Is there association between severe multispace infections of the oral maxillofacial region and diabetes mellitus? J Oral Maxillofac Surg. 2012;70:1565–72.

    Article  Google Scholar 

  12. Wenche SB. IDF Diabetes Atlas: diabetes and oral health—A two-way relationship of clinical importance. Diabetes Res Clin Pract. 2019;157:107839.

    Article  Google Scholar 

  13. Danjun C, Liangjun Z, Yuan L, et al. Wenhai LianChanges in serum inflammatory factor interleukin-6 levels and pathology of carotid vessel walls of rats with chronic periodontitis and diabetes mellitus after the periodontal intervention. Saudi J Biol Sci. 2020;27:1679–84.

    Article  Google Scholar 

  14. Ji RK, Jung HJ, Jin WC, Ji WP. Upper cervical spine abnormalities as a radiographic index in the diagnosis and treatment of temporomandibular disorders. Oral Surg Oral Med Oral Pathol Oral Radiol. 2020;129:514–22.

    Article  Google Scholar 

  15. Smith HJ, Larheim TA, Aspestrand F. Rheumatic and nonrheumatic disease in the temporomandibular joint: gadolinium-enhanced MR imaging. Radiology. 1992;185:229–34.

    Article  Google Scholar 

  16. Suenaga S, Ogura T, Matsuda T, Noikura T. Severity of synovium and bone marrow abnormalities of the temporomandibular joint in early rheumatoid arthritis: role of gadolinium-enhanced fat-suppressed T1-weight spin echo MRI. J Comput Assist Tomogr. 2000;24:461–5.

    Article  Google Scholar 

  17. Karampinos DC, Ruschke S, Dieckmeyer M, et al. Quantitative MRI and spectroscopy of bone marrow. J Magn Reson Imaging. 2018;47(2):332–53.

    Article  PubMed  Google Scholar 

  18. Baur A, Reiser MF. Diffusion-weighted imaging of the musculoskeletal system in humans. Skeletal Radiol. 2000;29:555–62.

    Article  Google Scholar 

  19. Herneth A, Ringl H, Memarsadeghi M, et al. Diffusion weighted imaging in osteoradiology. Top Magn Reson Imaging. 2007;18:203–12.

    Article  Google Scholar 

  20. Şerifoğlu İ, Oz İİ, Damar M, et al. Diffusion-weighted imaging in the head and neck region: usefulness of apparent diffusion coefficient values for characterization of lesions. Diagn Interv Radiol. 2015;21:208–14.

    Article  Google Scholar 

  21. Ariji Y, Taguchi A, Sakuma S, et al. Magnetic resonance T2-weighted IDEAL water imaging for assessing changes in masseter muscles caused by low-level static contraction. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2010;109:908–16.

    Article  Google Scholar 

  22. Schiffman E, Ohrbach R, Truelove E, et al. Diagnostic criteria for temporomandibular disorders (DC/TMD) for clinical and research applications: recommendations of the International RDC/TMD Consortium Network and Orofacial Pain Special Interest Group. J Oral Facial Pain Headache. 2014;28:6–27.

    Article  Google Scholar 

  23. Khoo MM, Tyler PA, Saifuddin A, Padhani AR. Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review. Skeletal Radiol. 2011;40:665–81.

    Article  Google Scholar 

  24. Nikkuni Y, Nishiyama H, Hayashi T. Clinical significance of T2 mapping MRI for the evaluation of masseter muscle pain in patients with temporomandibular joint disorders. Oral Radiol. 2012;29:50–5.

    Article  Google Scholar 

  25. Raya JG, Dietrich O, Birkenmaier C, et al. Feasibility of a RARE-based sequence for quantitative diffusion-weighted MRI of the spine. Eur Radiol. 2007;17:2872–9.

    Article  Google Scholar 

  26. Jeromel M, Jevtič V, Serša I, et al. Quantification of synovitis in the cranio-cervical region: dynamic contrast enhanced and diffusion weighted magnetic resonance imaging in early rheumatoid arthritis—a feasibility follow up study. Eur J Radiol. 2012;81:3412–9.

    Article  Google Scholar 

  27. Gaspersic N, Sersa I, Jevtic V, et al. Monitoring ankylosing spondylitis therapy by dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging. Skeletal Radiol. 2008;37:123–31.

    Article  Google Scholar 

  28. Hirahara N, Kaneda T, Muraoka H, et al. Characteristic MR imaging findings of the temporomandibular joint in diabetes mellitus: focus on abnormal bone marrow signal of the mandibular condyle and lymph node swelling in the parotid glands. Int J Oral-Med Sci. 2020;19:179–83.

    Article  Google Scholar 

  29. Rubin MR. Bone cells and bone turnover in diabetes mellitus. Curr Osteoporos Rep. 2015;13:186–91.

    Article  Google Scholar 

  30. Patsch JM, Burghardt AJ, Yap SP, et al. Increased cortical porosity in type 2 diabetic postmenopausal women with fragility fractures. J Bone Miner Res. 2013;28:313–24.

    Article  Google Scholar 

  31. Santos TR, Foss-Freitas MC, Nogueira-Filho GR. Impact of periodontitis on the diabetes-related inflammatory status. J Can Dent Assoc. 2010;76:a35.

    Google Scholar 

  32. Ito K, Muraoka H, Hirahara N, et al. Computed tomography texture analysis of mandibular condylar bone marrow in diabetes mellitus patients. Oral Radiol. 2021;37:693–9.

    Article  Google Scholar 

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Correspondence to Naohisa Hirahara.

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I have no financial relationships to disclose.

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This article does not contain any studies with animal subjects performed by the any of the authors.

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We designed and conducted a retrospective cohort study, which was approved by nihon university ethics committee (EC15-12-009-1).

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All procedures followed the guidelines of the Declaration of Helsinki, Ethical Principles for Medical Research Involving Human Subjects.

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Hirahara, N., Muraoka, H., Ito, K. et al. Quantitative assessment of the mandibular condyle in patients with diabetes mellitus using diffusion-weighted magnetic resonance imaging. Oral Radiol (2022).

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  • Diabetes mellitus
  • Temporomandibular joint
  • Magnetic resonance imaging
  • Diffusion weighted magnetic resonance imaging
  • Apparent diffusion coefficient value