Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis
Abstract
:Featured Application
Abstract
1. Introduction
2. Materials and Methods
2.1. Protocol
2.2. Strategy and Study Selection
2.3. Data Extraction
2.4. Risk of Bias
2.5. Statistical Analysis
3. Results
3.1. Description of the Included Studies
3.2. Quantitative Analysis
3.3. Risk of Bias
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Grüneboom, A.; Kling, L.; Christiansen, S.; Mill, L.; Maier, A.; Engelke, K.; Quick, H.H.; Schett, G.; Gunzer, M. Next-Generation Imaging of the Skeletal System and Its Blood Supply. Nat. Rev. Rheumatol. 2019, 15, 533–549. [Google Scholar] [CrossRef] [PubMed]
- Griffith, J.F.; Genant, H.K. New Advances in Imaging Osteoporosis and Its Complications. Endocrine 2012, 42, 39–51. [Google Scholar] [CrossRef] [PubMed]
- Hsu, J.-T.; Chen, Y.-J.; Tsai, M.-T.; Lan, H.H.-C.; Cheng, F.-C.; Chen, M.Y.C.; Wang, S.-P. Predicting Cortical Bone Strength from DXA and Dental Cone-Beam CT. PLoS ONE 2012, 7, e50008. [Google Scholar] [CrossRef] [PubMed]
- Khoo, B.C.C.; Brown, K.; Cann, C.; Zhu, K.; Henzell, S.; Low, V.; Gustafsson, S.; Price, R.I.; Prince, R.L. Comparison of QCT-Derived and DXA-Derived Areal Bone Mineral Density and T Scores. Osteoporos. Int. 2009, 20, 1539–1545. [Google Scholar] [CrossRef] [PubMed]
- Bachrach, L.K.; Gordon, C.M.; Sills, I.N.; Lynch, J.L.; Casella, S.J.; DiMeglio, L.A.; Gonzalez, J.L.; Wintergerst, K.; Kaplowitz, P.B. Bone Densitometry in Children and Adolescents. Pediatrics 2016, 138, e20162398. [Google Scholar] [CrossRef] [PubMed]
- Crabtree, N.; Ward, K. Bone Densitometry: Current Status and Future Perspective. In Calcium and Bone Disorders in Children and Adolescents; Karger Publishers: Berlin, Germany, 2015; pp. 72–83. [Google Scholar]
- Link, T.M. Osteoporosis Imaging: State of the Art and Advanced Imaging. Radiology 2012, 263, 3–17. [Google Scholar] [CrossRef]
- Yepes, J.F.; Al-Sabbagh, M. Use of Cone-Beam Computed Tomography in Early Detection of Implant Failure. Dent. Clin. N. Am. 2015, 59, 41–56. [Google Scholar] [CrossRef]
- Jeong, K.-I.; Kim, S.-G.; Oh, J.-S.; Jeong, M.-A. Consideration of Various Bone Quality Evaluation Methods. Implant. Dent. 2013, 22, 55–59. [Google Scholar] [CrossRef]
- Güngör, E.; Yildirim, D.; Çevik, R. Evaluation of Osteoporosis in Jaw Bones Using Cone Beam CT and Dual-Energy X-ray Absorptiometry. J. Oral Sci. 2016, 58, 185–194. [Google Scholar] [CrossRef]
- Shokri, A.; Ghanbari, M.; Maleki, F.H.; Ramezani, L.; Amini, P.; Tapak, L. Relationship of Gray Values in Cone Beam Computed Tomography and Bone Mineral Density Obtained by Dual Energy X-ray Absorptiometry. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2019, 128, 319–331. [Google Scholar] [CrossRef]
- Mostafa, R.A.; Arnout, E.A.; Abo el-Fotouh, M.M. Feasibility of Cone Beam Computed Tomography Radiomorphometric Analysis and Fractal Dimension in Assessment of Postmenopausal Osteoporosis in Correlation with Dual X-ray Absorptiometry. Dentomaxillofac. Radiol. 2016, 45, 20160212. [Google Scholar] [CrossRef] [PubMed]
- Barngkgei, I.; Al Haffar, I.; Shaarani, E.; Khattab, R.; Mashlah, A. Assessment of Jawbone Trabecular Bone Structure amongst Osteoporotic Women by Cone-Beam Computed Tomography: The OSTEOSYR Project. J. Investig. Clin. Dent. 2016, 7, 332–340. [Google Scholar] [CrossRef]
- Barngkgei, I.; Joury, E.; Jawad, A. An Innovative Approach in Osteoporosis Opportunistic Screening by the Dental Practitioner: The Use of Cervical Vertebrae and Cone Beam Computed Tomography with Its Viewer Program. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. 2015, 120, 651–659. [Google Scholar] [CrossRef]
- Barngkgei, I.; Al Haffar, I.; Khattab, R. Osteoporosis Prediction from the Mandible Using Cone-Beam Computed Tomography. Imaging Sci. Dent. 2014, 44, 263. [Google Scholar] [CrossRef] [PubMed]
- Jeong, K.; Ko, H.; Lee, C.-H.; Lee, M.; Yoon, K.-H.; Lee, J. A Novel Method for Estimation of Femoral Neck Bone Mineral Density Using Forearm Images from Peripheral Cone Beam Computed Tomography. Appl. Sci. 2016, 6, 113. [Google Scholar] [CrossRef]
- Ko, H.; Lee, C.H.; Jeong, K.; Lee, M.S.; Nam, Y.; Yoon, K.H.; Lee, J. A Pilot Study on Hip Bone Mineral Densities Estimation from Forearm CBCT Images. KSII Trans. Internet Inf. Syst. 2017, 11, 6054–6068. [Google Scholar] [CrossRef]
- Sghaireen, M.G.; Ganji, K.K.; Alam, M.K.; Srivastava, K.C.; Shrivastava, D.; Ab Rahman, S.; Patil, S.R.; Al Habib, S. Comparing the Diagnostic Accuracy of CBCT Grayscale Values with DXA Values for the Detection of Osteoporosis. Appl. Sci. 2020, 10, 4584. [Google Scholar] [CrossRef]
- Maffezzoni, F.; Maddalo, M.; Frara, S.; Mezzone, M.; Zorza, I.; Baruffaldi, F.; Doglietto, F.; Mazziotti, G.; Maroldi, R.; Giustina, A. High-Resolution-Cone Beam Tomography Analysis of Bone Microarchitecture in Patients with Acromegaly and Radiological Vertebral Fractures. Endocrine 2016, 54, 532–542. [Google Scholar] [CrossRef]
- Nemtoi, A.; Nemtoi, A.; Fochi, A.; Sirghe, A.E.; Preda, C.; Earar, K.; Beznea, A.; Onisor, C.; Iorgulescu, G.; Haba, D. CBCT Evaluation of the Mandibular Bone Quality in Relation to Skeletal Status after Treatment with Strontium Renelate in Diabetic Patients. Rev. Chim. 2019, 70, 4113–4118. [Google Scholar] [CrossRef]
- Guerra, E.N.S.; Almeida, F.T.; Bezerra, F.V.; Figueiredo, P.T.D.S.; Silva, M.A.G.; De Luca Canto, G.; Pachêco-Pereira, C.; Leite, A.F. Capability of CBCT to Identify Patients with Low Bone Mineral Density: A Systematic Review. Dentomaxillofac. Radiol. 2017, 46, 20160475. [Google Scholar] [CrossRef]
- Adler, R.A. Update on Osteoporosis in Men. Best Pract. Res. Clin. Endocrinol. Metab. 2018, 32, 759–772. [Google Scholar] [CrossRef] [PubMed]
- Liu, C.; Lv, H.; Niu, P.; Tan, J.; Ma, Y. Association between Diabetic Neuropathy and Osteoporosis in Patients: A Systematic Review and Meta-Analysis. Arch. Osteoporos. 2020, 15, 125. [Google Scholar] [CrossRef] [PubMed]
- Anthony, J.R.; Ioachimescu, A.G. Acromegaly and Bone Disease. Curr. Opin. Endocrinol. Diabetes Obes. 2014, 21, 476–482. [Google Scholar] [CrossRef]
- Eckstein, F.; Lochmüller, E.-M.; Lill, C.A.; Kuhn, V.; Schneider, E.; Delling, G.; Müller, R. Bone Strength at Clinically Relevant Sites Displays Substantial Heterogeneity and Is Best Predicted from Site-Specific Bone Densitometry. J. Bone Min. Res. 2002, 17, 162–171. [Google Scholar] [CrossRef] [PubMed]
- Ibrahim, N.; Parsa, A.; Hassan, B.; van der Stelt, P.; Aartman, I.H.A.; Wismeijer, D. The Effect of Scan Parameters on Cone Beam CT Trabecular Bone Microstructural Measurements of the Human Mandible. Dentomaxillofac. Radiol. 2013, 42, 20130206. [Google Scholar] [CrossRef]
- Ibrahim, N.; Parsa, A.; Hassan, B.; van der Stelt, P.; Aartman, I.H.A.; Nambiar, P. Influence of Object Location in Different FOVs on Trabecular Bone Microstructure Measurements of Human Mandible: A Cone Beam CT Study. Dentomaxillofac. Radiol. 2014, 43, 20130329. [Google Scholar] [CrossRef]
Author, Year of Publication | Location Analyze with CBCT | Location Analyze with DXA | Software Used to Analyze CBCT Scans | Information about FOV and Voxel Size | Information about CBCT Equipment | Information about DXA Equipment | Methods | Control Group Analyzed | Case Group Analyzed | Main Results |
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Barngkgei et al., 2016 [13] | Dens and first and second vertebrae | Femoral neck and lumbar vertebrae | White Fox Imaging ® Version 3 (Acteon Group Ltd., Milan, Italy) | FOV: 13 × 15 cm Voxel size: 0.25 mm | WhiteFox ® Imaging v.3 (Acteon Group Ltd., Milan, Italy) | Hologic Discovery QDR ® (Hologic Inc., Bedford, MA, USA) | 3 groups for FN and LV were assessed Radiographic density values were assessed from the dens and first and second vertebrae | Post-menopausal normal BMD females plus osteopenic females regarding LV T-score (n = 25) and FN T-score (n = 28) and normal BMD females concerning LV T-score (n = 10) and FN T-score (n = 17) | Post-menopausal osteoporotic females concerning LV T-score (n = 13) and FN T-score (n = 10) and osteoporotic plus osteopenic females concerning LV T-score (n = 28) and FN T-score (n = 21) | Radiographic density derived from CBCT analysis of the first and second vertebrae show high accuracy (90.8% for LV and 86.4% from FN) in predicting osteoporosis |
Barngkgei et al., 2014 [15] | Body and ramus of the mandible | Lumbar vertebrae (L1–L4) e Femoral Neck | WhiteFox ® Imaging v.3 (Acteon Group Ltd., Milan, Italy) | FOV: 13 × 15 cm; Voxel size: 0.25 mm | WhiteFox ® Imaging v.3 (Acteon Group Ltd., Milan, Italy) | Hologic Discovery QDR ® (Hologic Inc., Bedford, MA, USA) | 3 Groups for FN and LV were assessed Radiographic Density values of body and ramus of the mandible was evaluated | Post-menopausal normal BMD females and osteopenic females concerning to LV T-score (n = 25) and FN T-score (n = 28) | Post-menopausal osteoporotic females concerning LV T-score (n = 13) and FN T-score (n = 10) | Osteoporosis can be predicted with accuracy (75% for LV and 78.4% for FN) from radiographic density using CBCT |
Barngkgei et al., 2015 [14] | Jawbones and odontoid process | Lumbar Spine (L1–L4) and Femoral Neck | WhiteFox ® Imaging v.3 (Acteon Group Ltd., Milan, Italy) | FOV: 13 ×15 cm; Voxel size: 0.25 mm | WhiteFox ® Imaging v.3 (Acteon Group Ltd., Milan, Italy) | Hologic Discovery QDR ® (Hologic Inc., Bedford, MA, USA) | 3 groups for FN and LV were assessed Histomorphometric analysis was extracted from ImageJ (Tb.Th, Tb.Ts, BV/TV, BV/TV); Cuboids from jawbones extracted from CBCT scans and connectivity density were calculated by BoneJ | Post-menopausal normal BMD females and osteopenic females concerning to LV T-score (n = 25) and FN T-score (n = 28) | Post-menopausal osteoporotic females concerning LV T-score (n = 13) and FN T-score (n = 10) | Measures extracted from dens showed high accuracy of osteoporosis prediction (78.9% for LV and 84.2% for FN) |
Güngör et al., 2016 [10] | Jawbones | Lumbar vertebra (L1–L3) or hip | i-Cat Vision (Imaging Sciences International Inc.) software, using 0.21 mm slices | FOV: 13 × 10 cm Voxel size: 0.3 mm | i-CAT vision (Imaging Sciences International Inc., Hatfield, PA, USA) | Hologic Discovery QDR; Hologic Inc., Belford, MA | 3 groups were assessed Histomorphometric analysis and Fractal dimension analysis were taken using ImageJ. CT values and radiomorphometric index measurements (CTMI, CTI(S), CTI(I) were assessed | Normal BMD patients (n = 31) | Osteoporotic patients (n = 26) and Osteopenic patients (n = 33) | Histomorphometric analysis and Fractal dimension analysis, CT values and radiomorphometric index measurements can evaluated changes in the jawbones associated to osteoporosis |
Jeong et al., 2016 [16] | Forearm (carpal bone to the elbow) | Femoral neck | - | - | Peripheral CBCT (Phion, Nano Forcus Ray, Jeonju, Republic of Korea) | Discovery-W scanner, Hologic Inc., Bedford, MA, USA | 2 groups were assessed Ratio between Bone Volume/Trabecular volume, mean trabecular thickness, mean trabecular separation, cortical thickness and cortical porosity were calculated from High-Resolution CBCT | Healthy Volunteers (n = 21; 10 females and 11 males) | Acromegaly patients (n = 40; 24 females and 16 males) | High- Resolution CBCT may be a useful tool to measure the deleterious effects on trabecular and cortical bone microarchitecture of acromegaly patients |
Ko et al., 2017 [17] | Forearm (carpal bone to the elbow; with included forearm mid-shaft) | Total femur, femoral neck, femoral trochanter, femoral inter-trochanter and femoral ward’s triangle | - | - | Peripheral CBCT (PHION, Nano Focus Ray, Jeonju, Republic of Korea) | Discovery-W scanner, Hologic Inc., Bedford, MA | 2 groups were assessed Bone Mineral density values of forearm were estimated though the ratio of the forearm cortical bone to the cross-sectional area measured by CBCT | Non-osteoporosis patients (n = 14; 7 male and 7 females) | Osteoporosis Patients (n = 14; 1 male and 13 females) | Forearm CBCT images can be used to estimate hip bone mineral density and be a useful tool for screening osteoporosis |
Maffezzoni et al., 2016 [19] | Distal epiphysis border of radius | Lumbar spine, total hip, femoral neck and distal radius | BoneJ 1.3.9 program, (U.S. National Institutes of Health, Bethesda, MD, USA) | FOV: 8 × 8 cm2 Voxel size: 0.75 mm | High-resolution CBCT system (Newtom 5 G; QR, Verona, Italy) | Explorer Hologic Inc., Waltham, MA | 2 groups were assessed Ratio between Bone Volume/Trabecular volume, mean trabecular thickness, mean trabecular separation, cortical thickness and cortical porosity were calculated from High-Resolution CBCT | Healthy Volunteers (n = 21; 10 females and 11 males) | Acromegaly patients (n = 40; 24 females and 16 males) | High- Resolution CBCT may be a useful tool to measure the deleterious effects on trabecular and cortical bone microarchitecture of acromegaly patients |
Mostafa et al., 2016 [12] | Mandible | Lumbar spine | Planmeca Romexis ® (Helsinki, Finland) | FOV: 8 × 8 cm Voxel size: 0.2 mm | Planmeca ProMax ® 3D Classic, Helsinki, Finland. | - | 2 groups were assessed Fractal Dimension analysis were assessed using ImageJ; Radiomorphometric index measurements (CTMI, CTCI, CTI) were assessed | Normal BMD females (n = 25) | Osteoporotic females (n = 25) | Radiomorphometric index measurements obtain though CBCT can help refer patients at risk of osteoporosis |
Nemtoi et al., 2019 [20] | Cortical and cancellous bone of the mandible | Lumbar spine (L1–L4) and Left femur | Romexis 3.0.1 (Helsink, Finland) | FOV: 4 × 4 cm Voxel size: 0.4 mm | Planmeca Promax 3D mid CBCT (Helsinki, Finland) | Hologic Delphi W densitometer DEXA scan | 3 groups were assessed Radiomorphometric indices and mandibular bone density were obtained in CBCT images. | 20 osteoporotic male patients) | 40 diabetic male patients (16- type I DM; 24 type II DM | CBCT examination offer sufficient radiographic information detect patients with mandibular osteoporosis. |
Sghaireen et al., 2020 [18] | Jaws bones (anterior and posterior maxilla and anterior and posterior mandible) | Lumbar Spine (L1–L4) | OnDemand 3D (Yuseong-gu, Daejeon, Republic of Korea) | FOV: Medium Voxel size: 0.2 mm | SORDEX, Nahkelantie 160 Tuusula, Filand | - | 2 groups were assessed CBCT grayscale values of BMD jaws bones were measure in CBCT radiographs and compared to the results of DXA examinations | Non- osteoporosis patients (n = 39; 16 males and 23 females) | Osteoporosis Patients (n = 42; 6 males and 36 females) | CBCT grayscale values of BMD can be used to predict DXA T-score values |
Shokri et al., 2019 [11] | Anterior, premolar, retromolar and tuberosity areas of mandible and maxilla | Femoral Neck and Lumbar spine | OnDemand 3-D Dental Software (CyberMed, Seoul, Republic of Korea) | FOV: 13 × 14 cm | Scanora 3-D CBCT system (Soredex, Tuusula, Finland) | Osteocore Bone Densitometer (Medilink, Paris, France) | 3 groups were assessed Mean gray value of CBCT Cross-sectional images of anterior, premolar, retromolar and tuberosity areas of mandible and maxilla were used to calculated Bone mineral density | Post-menopausal non-osteoporosis females according to FN T-score (n = 32) and LV T-score (n = 27) | Post-menopausal osteoporotic and osteopenia females concerning LV T-score (n = 34; 24 with osteopenia and 10 with osteoporosis) and FN T-score (n = 29; 28 with osteopenia and 1 with osteoporosis) | A strong correlation was found between CBCT gray values of different parts of the maxilla and BMD values determinated by DXA. |
Author, Year of Publication | Coefficients of Correlation |
---|---|
Barngkgei et al., 2016 [13] | Pearson correlation between Dens CBCT derived values and DEXA values: in osteoporotic group: r = 0.34–0.38 [p value = 0.02–0.036]; Non-osteoporotic group: r = 0.48–0.61 [p value ≤ 0.003] |
Barngkgei et al., 2014 [15] | Pearson’s correlation coefficients were 0.5 and 0.6 (p value = 0.037 and 0.009) between RD of bone area of the mandible and T-scores obtained from FN and LV, respectively |
Barngkgei et al., 2015 [14] | Correlation Coefficients between CBCT-derived RD values of the left part of first cervical vertebra and the dens: r = 0.7, 0.6; p < 0.001 |
Güngör et al., 2016 [10] | Lumbar vertebrae DXA-derived measures and CTMI (r = 0.48, p ≤ 0.01), CTI(I) (r = 0.40, p ≤ 0.01), and CTI(S) (r = 0.32, p ≤ 0.01) Femoral head DXA-derived measures and CTMI (r = 0.32, p ≤ 0.01) |
Jeong et al., 2016 [16] | Correlation factor of r = 0.857 between femoral neck BMD and the ratio of the cortical and total bone areas |
Ko et al., 2017 [17] | RAFC and total femur (r = 0.889), RAFC and femoral neck (r = 0.924), RAFC and femoral trochanter (r = 0.821), RAFC and femoral inter-trochanter (r = 0.867), RAFC and femoral ward’s triangle (r = 0.895) |
Maffezzoni et al.,2016 [19] | Spearman correlation factor between BV/TV and lumbar spine, total hip, femoral neck and distal radius, respectively: 0.08, 0.26, 0.17 and 0.32. |
Mostafa et al., 2016 [12] | Correlation found between CTI and CTMI with lumber spine BMD: p < 0.05, r = 0.340 and p < 0.001, r = 0.463, respectively |
Nemtoi et al., 2019 [20] | Pearson correlation between lumbar spine BMD and cortical mandibular bone density and cancellous bone density in case group (diabetic male patients) was r = 0.63, p < 0.01 and r = 0.607, p < 0.01, respectively. |
Sghaireen et al., 2020 [18] | Pearson’s correlation between the T-scores of lumbar spine and the CBCT GS values at posterior maxilla: r2 = 0.849 |
Shokri et al., 2019 [11] | Pearson’s correlation between the T-scores of femoral neck and the gray values of cancellous and cortical bone at the site of maxillary tuberosity areas: r = 0.411, p < 0.001 |
Randomization Process | Deviations from the Intended | Missing Outcome Data | Measurement of Outcome | Selection of the Reported Result | Overall Bias | |
---|---|---|---|---|---|---|
Güngör et al., 2016 [10] | Y | Y | Y | Y | Y | Y |
Bias Due to Confounding | Selection of Participants | Classification of Interventions | Deviations from Intended Interventions | Missing Data | Measurement of Outcomes | Selection of the Reported Result | Overall Bias | |
---|---|---|---|---|---|---|---|---|
Barngkgei et al., 2014 [15] | Y | Y | Y | N | Y | Y | Y | Y |
Barngkgei et al., 2016 [13] | Y | Y | Y | Y | Y | Y | Y | Y |
Barngkgei et al., 2015 [14] | Y | Y | Y | Y | Y | Y | Y | Y |
Jeong et al., 2016 [16] | Y | Y | Y | Y | Y | Y | Y | Y |
Ko et al., 2017 [17] | Y | Y | Y | Y | Y | Y | Y | Y |
Maffezzoni et al., 2016 [19] | N | Y | Y | Y | Y | Y | Y | Y |
Mostafa et al., 2016 [12] | Y | Y | Y | Y | Y | Y | Y | Y |
Nemtoi et al., 2019 [20] | N | Y | Y | Y | Y | Y | Y | Y |
Sghaireen et al., 2020 [18] | Y | Y | Y | Y | Y | Y | Y | Y |
Shokri et al., 2019 [11] | Y | Y | Y | Y | N | Y | Y | Y |
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Francisco, I.; Nunes, C.; Pereira, F.; Travassos, R.; Ribeiro, M.P.; Marques, F.; McEvoy, M.; Santos, M.; Oliveira, C.; Marto, C.M.; et al. Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis. Appl. Sci. 2023, 13, 5962. https://doi.org/10.3390/app13105962
Francisco I, Nunes C, Pereira F, Travassos R, Ribeiro MP, Marques F, McEvoy M, Santos M, Oliveira C, Marto CM, et al. Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis. Applied Sciences. 2023; 13(10):5962. https://doi.org/10.3390/app13105962
Chicago/Turabian StyleFrancisco, Inês, Catarina Nunes, Flávia Pereira, Raquel Travassos, Madalena Prata Ribeiro, Filipa Marques, Mariana McEvoy, Mariana Santos, Catarina Oliveira, Carlos Miguel Marto, and et al. 2023. "Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis" Applied Sciences 13, no. 10: 5962. https://doi.org/10.3390/app13105962
APA StyleFrancisco, I., Nunes, C., Pereira, F., Travassos, R., Ribeiro, M. P., Marques, F., McEvoy, M., Santos, M., Oliveira, C., Marto, C. M., Caramelo, F., Paula, A. B., & Vale, F. (2023). Bone Mineral Density through DEXA and CBCT: A Systematic Review with Meta-Analysis. Applied Sciences, 13(10), 5962. https://doi.org/10.3390/app13105962