Correlation of bone density of individual jaw sections according to Hounsfield with the length of the adentiary section in the cone-beam computer tomography program
DOI:
https://doi.org/10.14739/2310-1237.2023.3.288644Keywords:
computer tomography, bone density, medical image processingAbstract
Aim. To study the existence of a relationship between the density of bone tissue and the length of the edentulous part of the tooth row.
Materials and methods. Evaluation of the density of the spongy substance of the jaws by the maximum and average value of HU. The density of cancellous bone was evaluated only in the areas available for implant placement. The groups consisted of the localization and extent of the dentition defect. Statistical methods included the estimation of the arithmetic mean (M), standard deviation (σ), error of the mean (m), confidence interval (95 % CI), estimation of the median (Me) and interquartile range ([Q1; Q2]), Student’s test (t criterion).
Results. Maximum and average indicators of cancellous bone density in defects of the upper (562.4 [347.1; 777.8] and 301.5 [163.0; 439.9], respectively (р = 0.84) and lower (1379.0 [1116.2; 1641.9] HU and 848.6 [630.6; 1066.6] HU, respectively, p = 0.96) jaws in the areas of molars and premolars with “large” defects are significantly different from the indicators “small” defects (299.7 [176.9; 422.4] and 642.6 [470.4; 814.9], 1061.1 [866.5; 1255.7] and 608.3 [440.5; 776.1, respectively). The average bone density of the alveolar process of the upper jaw is almost the same in defects of different lengths. The average density of the cancellous bone of the alveolar part of the lower jaw in “large” defects has significant differences from “average” ones (p = 0.02) and “small” (p = 0.005) defects.
Conclusions. The average density of cancellous bone of the alveolar part of the lower jaw in “large” defects has significant differences from “medium” (p = 0.02) and “small” (p = 0.005) defects, and regardless of the extent of the dentition defect corresponds to class D3 (350–850 HU) according to the Misch classification. The average density of cancellous bone of the alveolar process of the upper jaw in the areas of molars and premolars does not have significant differences depending on the extent of the dentition defect and corresponds to class D4 (150–350 HU) according to the Misch classification. Since one class includes a large range of values, the clinical classification of Misch does not allow taking into account individual bone density indicators that have statistically significant differences in different areas of the dentition.
References
Dye, B. A., Weatherspoon, D. J., & Lopez Mitnik, G. (2019). Tooth loss among older adults according to poverty status in the United States from 1999 through 2004 and 2009 through 2014. Journal of the American Dental Association (1939), 150(1), 9-23.e3. https://doi.org/10.1016/j.adaj.2018.09.010
Saghiri, M. A., Freag, P., Fakhrzadeh, A., Saghiri, A. M., & Eid, J. (2021). Current technology for identifying dental implants: a narrative review. Bulletin of the National Research Centre, 45(1). https://doi.org/10.1186/s42269-020-00471-0
Jargalsaikhan, A., Sengee, N., Telue, B., & Ochirkhvv, S. (2019). Estimation of Lower Jaw Density using CT data. Journal of Multimedia Information System, 6(2), 67-74. https://doi.org/10.33851/jmis.2019.6.2.67
Kim, J. M., Kim, S. J., Han, I., Shin, S. W., & Ryu, J. J. (2009). A comparison of the implant stability among various implant systems: clinical study. The journal of advanced prosthodontics, 1(1), 31-36. https://doi.org/10.4047/jap.2009.1.1.31
Sundell, G., Dahlin, C., Andersson, M., & Thuvander, M. (2017). The bone-implant interface of dental implants in humans on the atomic scale. Acta biomaterialia, 48, 445-450. https://doi.org/10.1016/j.actbio.2016.11.044
Mohajerani, H., Roozbayani, R., Taherian, S., & Tabrizi, R. (2017). The Risk Factors in Early Failure of Dental Implants: a Retrospective Study. Journal of dentistry (Shiraz, Iran), 18(4), 298-303.
Weiss, R., 2nd, & Read-Fuller, A. (2019). Cone Beam Computed Tomography in Oral and Maxillofacial Surgery: An Evidence-Based Review. Dentistry journal, 7(2), 52. https://doi.org/10.3390/dj7020052
Wang, S. H., Shen, Y. W., Fuh, L. J., Peng, S. L., Tsai, M. T., Huang, H. L., & Hsu, J. T. (2020). Relationship between Cortical Bone Thickness and Cancellous Bone Density at Dental Implant Sites in the Jawbone. Diagnostics, 10(9), 710. https://doi.org/10.3390/diagnostics10090710
Ganguly, R., Ramesh, A., & Pagni, S. (2016). The accuracy of linear measurements of maxillary and mandibular edentulous sites in cone-beam computed tomography images with different fields of view and voxel sizes under simulated clinical conditions. Imaging science in dentistry, 46(2), 93-101. https://doi.org/10.5624/isd.2016.46.2.93
Halperin-Sternfeld, M., Machtei, E. E., & Horwitz, J. (2014). Diagnostic accuracy of cone beam computed tomography for dimensional linear measurements in the mandible. The International journal of oral & maxillofacial implants, 29(3), 593-599. https://doi.org/10.11607/jomi.3409
Misch, K. A., Yi, E. S., & Sarment, D. P. (2006). Accuracy of cone beam computed tomography for periodontal defect measurements. Journal of periodontology, 77(7), 1261-1266. https://doi.org/10.1902/jop.2006.050367
Tsigarida, A., Toscano, J., de Brito Bezerra, B., Geminiani, A., Barmak, A. B., Caton, J., Papaspyridakos, P., & Chochlidakis, K. (2020). Buccal bone thickness of maxillary anterior teeth: A systematic review and meta-analysis. Journal of clinical periodontology, 47(11), 1326-1343. https://doi.org/10.1111/jcpe.13347
Yasuda, K., Okada, S., Okazaki, Y., Hiasa, K., Tsuga, K., & Abe, Y. (2020). Bone turnover markers to assess jawbone quality prior to dental implant treatment: a case-control study. International journal of implant dentistry, 6(1), 67. https://doi.org/10.1186/s40729-020-00264-0
Takeda, M., Matsuda, Y., Ikebuchi, K., Takeda, M., Abe, T., Tominaga, K., Isomura, M., Nabika, T., & Kanno, T. (2021). Relationship between Oral Health Status and Bone Mineral Density in Community-Dwelling Elderly Individuals: A Cross-Sectional Study. Healthcare, 9(4), 432. https://doi.org/10.3390/healthcare9040432
Barbe, A. G., Javadian, S., Rott, T., Scharfenberg, I., Deutscher, H. C. D., Noack, M. J., & Derman, S. H. M. (2020). Objective masticatory efficiency and subjective quality of masticatory function among patients with periodontal disease. Journal of clinical periodontology, 47(11), 1344-1353. https://doi.org/10.1111/jcpe.13364
Meeta, M., Harinarayan, C. V., Marwah, R., Sahay, R., Kalra, S., & Babhulkar, S. (2020). Clinical practice guidelines on postmenopausal osteoporosis: ∗an executive summary and recommendations-Update 2019-2020. Journal of Mid-Life Health, 11(2), 96-112. https://doi.org/10.4103/jmh.JMH_143_20
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