Journal of Periodontology; Copyright 2015
DOI: 10.1902/jop.2015.140584
Sensitivity and Specificity of Radiographic Methods for Predicting Insertion Torque of Dental Implants Arthur Rodriguez Gonzalez Cortes, DDS, PhD*, Hazem Eimar, DDS, MS†, Jorge de Sá Barbosa, DDS, MS*, Claudio Costa, DDS, PhD*, Emiko Saito Arita, DDS, PhD*, Faleh Tamimi, DDS, PhD†
*Department of Stomatology, School of Dentistry, University of São Paulo, São Paulo, Brazil. †
Faculty of Dentistry, McGill University, Montreal, Quebec, Canada.
Background: Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aimed to identify quantitative bone features influencing IT, and to use these findings to develop an objective radiographic classification for predicting IT. Methods: Demographics, panoramic radiographs (taken at the beginning of dental treatment) and cone beam computed tomographic scans (taken for implant surgical planning) of a total of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, micro-computed tomography and histology. Odds ratio, sensitivity and specificity of all variables to predict high peak IT were assessed. Results: A ridge cortical thickness greater than .75mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. Conclusion: Within the limitations of this study, the present results suggest that it is possible to predict IT accurately, based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.
KEYWORDS: Endosseous dental implants, insertion torque, panoramic radiography, cone beam computed tomography, bone mineral density.
Success of dental implant osseointegration depends on the density and amount of available bone, and on primary implant stability, that is, the absence of implant mobility in the bone bed after surgical placement.1 One of the indicators of primary stability is the implant insertion torque (IT).2, 3 An adequate insertion torque should be ensured to avoid implant micromotion and consequent failure during the osseointegration process.4 In addition, a high IT is one of the factors recommended for immediate loading of the implant, leading to shorter treatments.5-8 Therefore, it could be hypothesized that the ability to predict IT would improve treatment planning, allowing the clinician to choose an adequate implant design, drilling sequence and loading time. The influence of alveolar bone characteristics on implant IT has been assessed using different bone density classifications.9-13 One of the most commonly used classifications is based on the amount of cortical and trabecular bone shown in preoperative panoramic and periapical radiographs generating four scores.14 However, this classification has been found to be inaccurate for prediction of IT,15 as it is subjective, and it depends on the opinion of the professional.11 Other measurements such as cortical thickness of the alveolar ridge have been found to correlate with IT.16
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However, the quantitative relationship, as well as sensitivity and specificity of this and other diagnostic methods to predict torque are not yet available in the literature. Cone beam computed tomography (CBCT) allows performing 3D pre-surgical morphological assessment of the cortical and trabecular alveolar bone available for placing dental implants.17 Compared with other computed tomographic (CT) methods, CBCT offers advantages such as reduced effective radiation doses, shorter acquisition scan time, easier imaging, and lower costs.17, 18 CBCT has been validated19 and clinically used20 to assess bone density at implant sites by measuring pixel grayscale values. This analysis has been termed “radiographic bone density”.20-23 The radiographic bone density obtained with CBCT and peak IT has been found to be significantly correlated in both animal10 and human bone samples.21, 24. However, none of the above-mentioned studies assessed the relative contribution of cortical and trabecular bone on insertion torque. Previous laboratory studies using simulation models,16, 25 suggest that cortical bone thickness, as well as trabecular bone elastic modulus and strength may influence implant IT and primary stability. Panoramic radiographs are useful to diagnose systemic26 and alveolar27 bone quality by assessing the width and shape of the inferior mandibular cortex. These measurements have been described as indices to predict osteoporosis, as they are correlated with systemic bone mineral density (BMD) values measured with dualenergy x-ray absorptiometry (DXA).28 Nevertheless, the relation between these indices and implant peak IT remains unknown. We hypothesized that quantitative values from radiographic measurements could be used as diagnostic tools for predicting peak insertion torque. Thus, the aims of this diagnostic study were: to identify alveolar and systemic bone features that influence peak IT and use this information to develop a clinical method for prediction of insertion torque.
MATERIALS AND METHODS Approval was obtained from the Ethics Committee of the University of São Paulo (protocol number: 104/11). All patients willing to participate in this study signed an informed consent form. The Standards for the Reporting of Diagnostic accuracy studies (STARD)29 and the guidelines of the Helsinki Declaration were followed in this investigation. Inclusion and Exclusion Criteria This diagnostic study was conducted on partially edentulous patients attending a private dental clinic that partners in research with the School of Dentistry, University of São Paulo. The subjects selected had been diagnosed and indicated either for one or two implant placement procedures (maximum of one implant per dental arch) between June 2011 and October 2012. Only implant sites with more than 5 mm in width were included. Patients with a recent tooth extraction (less than 6 months of follow-up) were excluded to avoid the socket remodeling period, following previously adopted criteria.30 Patients with metabolic disorders, such as diabetes and vitamin D deficiency, or with insufficient alveolar bone volume for implant placement were excluded. History of ridge augmentation with grafts was also considered as exclusion criteria.
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Radiographic Analyses Digital panoramic radiographs‡ of all patients were taken at the beginning of dental treatment, since it is an examination recommended for general screening.31 Images were taken using the following exposure conditions: 60kV, 4mA, 0.5-mm copper filter), and were analyzed using an imaging processing software§. The mandibular cortical width (MCW) was measured at both mental foramen regions, according to previous methodology.26 Briefly, images were corrected using a magnification factor of 1.3. Spatial calibration was set at a scale of 1 pixel per 96 μm. Next, a line parallel to the long axis of the mandible and tangential to the inferior border of the mandible was drawn. A line perpendicular to this tangent intersecting the inferior border of the mental foramen was constructed, along which the mandibular cortical width was measured (Figures 1A and E). The mandibular cortical shape index (MCI) was assessed by evaluating the appearance of the cortical bone below the mandibular foramen, using a previously described classification.32 Briefly, the inferior mandibular cortex was classified as ‘C1’ or normal (Figure 1E), when presenting an even and distinct endosteal margin, ‘C2’ or moderately eroded, when presenting evidence of lacunar resorption or endosteal cortical residues, and ‘C3’ or severely eroded (Figure 1A), when unequivocal porosity was observed. All patients underwent a CBCTII scan, required for implant three-dimensional surgical planning,17 with a diagnostic protocol used for dental implants (0.25-mm voxel, 120kVp, 8mA, exposure time of 8.5 seconds and field of view of 16-cm in diameter and 6-cm in height).30 The aforementioned field of view included only one full dental arch in standard resolution, allowing for a low effective radiation dose (approximately 35 microsieverts), as reported by a study using the same CBCT device.33 DICOM (Digital Imaging Communication in Medicine) images were assessed using a DICOM viewer software¶. The edentulous areas of the ridge, planned for receiving dental implants, were identified in sagittal CBCT images as rectangular regions of interest (ROIs) of 6 mm in length and 3 mm in width, matching the implant placement site. Ridge cortical thickness at the alveolar crest (in mm) and mean radiographic bone density (in grayscale values) were measured in the ROI images, with the linear measurement and gray scale analysis tools of the DICOM viewer software¶, respectively). The selected CBCT images and defined ROIs were also used to make a custom stereolithography surgical guide using a rapid prototyping machine#. The surgical guides had specific drill sleeves to avoid angle deviations during the drilling procedure. This ensured bone sample collection and implant placement in the same CBCT ROI used for radiographic measurements, according to previous methodology.20, 21 All panoramic radiographic and CBCT measurements were performed in random order by two trained observers (i.e. dentists with expertise in oral radiology). Intraobserver reliability was assessed between measurements performed 2 weeks apart to eliminate memory bias. Intra and interobserver agreement were assessed using the intraclass correlations coefficient (ICC) and the kappa test for continuous and categorical variables respectively. Treatment Timetable All patients received amoxicillin (2.0g) one hour before surgery, as prophylaxis, and were treated by the same surgeon using the same surgical procedure. Under local anesthesia, a crestal incision was performed slightly palatal to the crest midline and
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the mucogingival flap was elevated. Implant sites were prepared using the surgical guide with trephine burs in order to obtain bone cores (3.0mm diameter and 6.0mm in length) from the implant sites. The bone samples were fixed and stored in 4% formaldehyde buffer solution. An additional surgical drill of 3.5mm in diameter was used to complete implant site preparation. Dental implants** with 4.1mm in diameter and 10.0mm in length were placed using a ratchet adapted to the torquimeter of the corresponding implant system. This torquimeter shows values of 0Ncm, 15Ncm and 35Ncm. Therefore, the peak insertion torque at final implant position was classified into three categories: 35Ncm. All implants were placed at soft tissue level, and restored after two months of healing. DXA Analysis Bone biopsies were analyzed with DXA††. Acquisition lines were set at a distance of 0.254 mm, and the space between each point was 0.127 mm. The acquisition window had a maximum width of 4 cm and a length of 6 cm. Bone samples were placed flat, with their long axis parallel to the progression axis during image acquisition, and with a density control hydroxyapatite besides them. BMD values were determined and expressed in g/cm2. Micro-Computed Tomography (μ-CT) Bone biopsies were also analyzed with a μ-CT machine‡‡ set up at 100 KeV and 100 micro-amperes, and a resolution of 6.0 μm, with a 0.5 mm Al filter. Time exposure per frame was 450 ms. X-ray images were reconstructed with the manufacturer software§§ before analyzing them for bone volume per total volume (BV/TV). This is a variable that refers to the total amount of bone present within the biopsy, including cortical and trabecular bone.20, 21 Histology Fixed biopsies were dehydrated in ascending concentrations of ethanol and resin infiltrated and embedded before final polymerization. Longitudinal histological sections crossing the center of the cylindrical biopsy were taken using a micro sawIIII, and stained with methylene blue and basic fuchsine. Pictures of histological sections were taken with a digital camera¶¶ installed on an optical microscope##. The images were processed using a morphometry software*** and stitched with an image processing software†††. Optical images of longitudinal sections crossing the cylindrical biopsies in the centre were used to perform the histomorphometrical analysis of each implanted area.34 Images were analyzed using the image processing software§. For each slice, the area occupied by bone tissue was outlined and calculated as a percentage of the total area of the slice. Since standard histomorphometry is a two-dimensional analysis, four sections per biopsy with same direction and thickness were averaged.35 For each histological section, the percentage of area occupied by bone was calculated as BV/TV values. Statistical Analysis Sample size was determined using the uncorrected chi-square test, to detect a minimum odds ratio of 5 and to give the study a power of 80%, at a level of significance of 5%. Correlation analyses were performed among all variables 4
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analyzed in the study. Normality was assessed for continuous variables (age, MCW, radiographic bone density, ridge cortical thickness, BMD, μ-CT BV/TV and histology BV/TV) using the Shapiro-Wilk test. Pearson’s test was used for correlations involving continuous variables, while correlations involving categorical variables (MCI and peak IT), were analyzed with Spearman’s test. Conditional logistic regression was used to assess associations between peak insertion torque and the rest of variables. All variables were stratified using cut-off points. For continuous variables, optimal cut-off points were chosen using receiver operating characteristic curve analysis (Figure 2), at the point where sum of specificity and sensitivity is maximum, and equal weight is given to both.36 For MCI, “C1” category was selected as the cut-off point, since this is the only category representing the absence of alterations in the inferior mandibular cortex.32 Finally, a peak insertion torque of 35Ncm was chosen as cut-off point, since this is a value recommended for immediate loading using the implant system of our study.37, 38 Risk estimates were presented as odds ratios (ORs) with 95% confidence intervals (CIs). The ORs were adjusted for potential confounders of age and gender. Adjustment for clusters (implant/patient) were performed using generalized estimated equations (GEE). Sensitivity and specificity of each imaging method for screening high peak insertion torque of each variable were also calculated using the selected cut-off points. Finally, we attempted to develop a clinical classification to enable clinicians to predict peak insertion torque using only panoramic radiographs and CBCT. For this purpose, sensitivity and specificity of significant variables from these imaging methods were combined for predicting high insertion torque. All statistical analyses were performed using the same software‡‡‡.
RESULTS A total of 25 patients (13 men and 12 women, mean age of 59.3 ± 11.5 years) receiving 31 implants (25 mandibular; 7 in the interforaminal region and 18 in posterior regions and 6 maxillary; 3 anterior to the maxillary sinuses, and 3 in posterior regions) were analyzed. Descriptive statistics of continuous variables are presented in Table 1. Intraobserver reproducibility and interobserver reliability were confirmed for the MCW, radiographic bone density and ridge cortical thickness measurements (ICC between 0.82 and 0.89), as well as for MCI categorical measurements (kappa index 0.87, P=0.01). Normal distribution was confirmed for all continuous variables according to the Shapiro-Wilk test (p>0.05). Of the 31 implants included in this study, 16 presented a high peak insertion torque (T>35Ncm). Of these, 14 were mandibular (4 in the interforaminal region and 10 in posterior regions) and 2 were maxillary (1 anterior to the maxillary sinuses and 1 in a posterior region). All correlations assessed are shown in Table 2. Scatterplots for parametric correlations are shown in Supplementary figure 1. MCI was significantly correlated with peak IT, age, and MCW. Peak IT was also significantly correlated to ridge cortical thickness, BMD, μ-CT-BV/TV and histology-BV/TV. In addition, μ-CTBV/TV and radiographic bone density were strongly correlated with histology-
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BV/TV (r=.817, p=.001 and r=.795, p=.001, respectively) (Figure 1). No other correlations were significant (P > 0.05). Cut-off points of each variable and risk associations with peak insertion torque are shown in Table 3. Adjusted odds ratio (AOR) analysis showed that ridge cortical thickness (AOR = 33.42; 95%CI = 2.99 to 373.72; P = 0.004; post-hoc power = 96.46%), MCI (AOR = 13.32; 95%CI = 1.32 to 134.47; P = 0.028; post-hoc power = 90.05%), μ-CT-BV/TV (AOR = 13.57; 95%CI = 1.85 to 99.65; P = 0.01; post-hoc power = 91.43%), histology-BV/TV (AOR = 7.23; 95%CI = 1.25 to 41.76; P = 0.027; post-hoc power = 86.47%), and BMD (AOR = 7.84; 95%CI = 1.43 to 43.01; P = 0.018; post-hoc power = 83.83%) were significantly associated with peak insertion torque. MCW and radiographic bone density from CBCT were not significantly associated with peak insertion torque (P > 0.05). Sensitivity and specificity for screening high peak insertion torque was calculated for all variables (Table 3). The most sensitive tests were ridge cortical thickness (84.6%) and MCI (75%), whereas the most specific tests were μ-CT-BV/TV (87.5%) and histology-BV/TV (81.2%). According to odds ratio analysis, ridge cortical thickness and MCI were the only clinical parameters (i.e. from panoramic radiographs and CBCT) that showed significant association with peak IT. Therefore, the combination of these two variables was assessed for screening high insertion torque and used to develop a classification for prediction of torque. The proposed combination of the tests presented a sensitivity of 100% (Table 3). The results led to the development of a classification, based on these variables (Table 4). In this classification, patients are divided in three categories, according to the probability of having a high insertion torque: “class I” (Figures 1E-H), when both variables reach the cut-off point (0.75mm for ridge cortical thickness and C1 category for MCI); “class II”, when only one of the variables reaches the cut-off point; and “class III” (Figures 1A-D), when none of the variables reach the cut-off point. No procedure-related complications were observed in this study. The study implant survival rate was 100% with a mean 23-month follow-up (range of 9–34 months).
DISCUSSION The present diagnostic study assessed odds ratio, sensitivity and specificity of multiple variables from different radiographic methods for association and diagnostic performance to predict peak IT. Histological morphometric analysis was also employed as a gold standard to correlate with bone findings from the radiographic methods included in this study. Implant insertion torque is influenced by bone quality and quantity, implant design and surgical technique.2, 5, 12 The last two factors were fixed in this study, since all surgeries were performed by the same surgeon using the same implant system, surgical drills and implant dimensions. Therefore, we were able to evaluate the solely influence of alveolar bone characteristics on implant insertion torque. In the present study, all methods quantifying trabecular bone (radiographic bone density, μ-CT-BV/TV and histology-BV/TV) presented either none or poor correlations with peak insertion torque, whereas most methods assessing cortical bone (DXA, MCI and ridge cortical thickness) presented strong significant correlations
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with the same parameter. These findings support a histomorphometric study that found no significant correlation between BV/TV and peak insertion torque,13 and another study concluding that implant insertion torque is dependent on the quantity of cortical bone in contact with the implant.9 Furthermore, our quantitative results confirm the evidences of the influence of alveolar cortical layer on the drilling resistance experienced by the surgeon and on implant stability, presented by previous studies using subjective bone classifications.14, 39, 40 There is a controversy in the literature regarding the use of CBCT to determine Hounsfield Units. The Hounsfield scale was originally designed for spiral CT.41 Unless calibration and attenuation coefficients are used, this scale is not compatible with CBCT and therefore was not considered in this study. Instead, grayscale values provided by the DICOM viewer software were used for correlation analyses, as described by similar studies.10, 20, 24 In the present study, there was no significant correlation between radiographic bone density taken from CBCT and peak IT. This finding is in agreement with a previous study.21 In contrast, other studies found weak,42 moderate,43 and strong10, 24 significant correlations between radiographic bone density and peak IT. Since radiographic bone density assess trabecular bone structure by means of grayscale analysis, the aforementioned findings lead to a controversy in the literature regarding the influence of the ridge cortical layer on peak IT, observed and discussed herein. In our study, radiographic bone density from pre-operative CBCT scans presented strong significant correlations with BV/TV values obtained from both μ-CT and histology, as observed by another study.20 Furthermore, among the laboratorial methods assessed herein, μ-CT presented a stronger significant association with peak IT, compared with DXA and histology. This finding supports use of μ-CT as a suitable tool for bone morphometric measurements, as previously described in the literature.44 This is the first study addressing the correlation of panoramic radiographic indices with peak insertion torque (MCI) and patient’s age (MCI and MCW). MCI presented a weak to moderate inverse correlation with torque (r= -0.373, p=0.039). However, this variable was found to be strongly associated with peak insertion torque outcomes according to the adjusted odds ratio analysis (AOR=13.32, 95% CI=1.32-134.47). Despite the fact that MCI is an indicator for peripheral bone quality,28 it has also been found to play a decisive role in the diagnostic performance of our classification, according to the sensitivity and specificity analyses presented in table 3. Furthermore, the correlation between MCI and MCW and patients’ age observed in this study supports results from articles that validated these indices to predict bone alterations such as osteoporosis, since bone density is expected to decrease as the patient grow older.26 To our knowledge, the present study is the first to assess sensitivity and specificity of methods to predict insertion torque. In contrast with linear correlations, sensitivity and specificity evaluate the diagnostic performance of a variable to predict or detect an outcome. Therefore, we were able to describe the critical values from radiographic measurements that could be used by clinicians and researchers as cut-off points to predict high peak IT. In addition, the present study proposed the first radiographic classification developed to predict high insertion torque of implants, using digital panoramic radiographs, commonly used for general screening after an initial clinical examination,31 and pre-operative CBCT, in accordance with the “as low a dose as
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reasonably achievable” (ALARA) principle,45 and with the guidelines of the European Academy of Osseointegration (EAO) for the use of diagnostic imaging in implant dentistry.46 According to the EAO guidelines, cross-sectional imaging may not be decisive for planning implants in cases where clinical examination and conventional radiographs provided sufficient data for the surgeon. However, there are a number of clinical situations that benefit from a CBCT scan for implant planning.46 For these situations, our classification to predict torque could be indicated as a diagnostic parameter. The classification based on MCI and ridge cortical thickness divided alveolar bone in 3 categories: class I, when both variables reach the cut-off point; class II, when one of the variables reaches the cut-off point; and class III, when none of the variables reach the cut-off point. Implants placed in class I have 90% probability of having a high torque and could be planned for immediate loading. Similarly, implants placed in class III are predicted to have 100% probability of having a low torque. Such cases would require additional clinical measures to enhance the primary stability of implants, such as using tapered implant bodies or decreasing the diameter of the last drill. As a result, our radiographic classification could be decisive for planning immediate loaded implants. Future clinical studies would be required to address the effect of our classification on drilling sequence, and implant diameter and type selection. Implant insertion torque has been significantly correlated with survival rates of immediate loaded implants.8 A study on single-tooth implants found that a torque greater than 32 Ncm was necessary to achieve osseointegration in cases of immediate loading.47 Therefore, although we did not assess the impact of our radiographic classification on immediate loading, our data indicates that this classification could be useful to enhance treatment plan of such cases. Nevertheless, since success of immediate loading does not depend solely on insertion torque, future randomized clinical trials would be recommended to test the clinical application of our classification in patients receiving immediately loaded implants. Furthermore, although an appropriate sample size was achieved to test our hypothesis, the number of implants in each region of the jaws was low. In addition, none of the implants were lost. As a result, the present diagnostic study was not able to address the impact of the proposed radiographic classification on implant survival rates. Future cohort studies with larger sample sizes and using different implant systems would be required to evaluate our classification as a risk factor for implant loss in cases of immediate and conventional loading. Another limitation of this study is that the dimensions of bone samples taken from implant sites (3x6mm) did not match proper implant dimensions (4.1x10mm). This methodology was adopted to finish implant site preparation using the last drill of the implant system used, following its guidelines.20 Furthermore, our radiographic classification was developed for cylindrical implants. Future studies would have to be performed to assess it with tapered implants, as they provide higher torque than cylindrical ones.48 In conclusion, within the limitations of this study, the findings observed using the present implant system and following its surgical guidelines suggest that the radiographic classification developed herein could be considered to predict insertion torque of cylindrical dental implants. This could be useful in the treatment plan of immediate loading cases. Finally, CBCT scans taken with the device of this study could be considered to assess alveolar bone density, since the radiographic bone
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density obtained with this method was strongly correlated with morphometric measurements from both micro-CT and histology. ACKNOWLEDGEMENTS A Ph.D. scholarship was granted to A.R.G.C. by the National Council for Scientific and Technological Development (CNPq – Brazil, N° 140291/2011 3). F.T. received grants by The Network for Oral and Bone Health Research (RSBO, Quebec, Canada) and by the Natural Sciences and Engineering Research Council of Canada (NSERC RGPIN 418617-12).
CONFLICT OF INTEREST STATEMENT The authors declare that there are no conflicts of interest in this study.
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34. Particelli F, Mecozzi L, Beraudi A, Montesi M, Baruffaldi F, Viceconti M. A comparison between micro-CT and histology for the evaluation of cortical bone: effect of polymethylmethacrylate embedding on structural parameters. J Microsc 2012;245:302-310. 35. Chappard D, Retailleau-Gaborit N, Legrand E, Basle MF, Audran M. Comparison insight bone measurements by histomorphometry and microCT. J Bone Miner Res 2005;20:1177-1184. 36. Kumar R, Indrayan A. Receiver operating characteristic (ROC) curve for medical researchers. Indian Pediatr 2011;48:277-287. 37. Buttel AE, Gratwohl DA, Sendi P, Marinello CP. Immediate loading of two unsplinted mandibular implants in edentulous patients with an implant-retained overdenture: an observational study over two years. Schweiz Monatsschr Zahnmed 2012;122:392-397. (english) 38. Kinsel RP, Liss M. Retrospective analysis of 56 edentulous dental arches restored with 344 singlestage implants using an immediate loading fixed provisional protocol: statistical predictors of implant failure. Int J Oral Maxillofac Implants 2007;22:823-830. 39. Misch CE. Bone classification, training keys to implant success. Dent Today 1989;8:39-44. 40. Branemark PI, Hansson BO, Adell R, et al. Osseointegrated implants in the treatment of the edentulous jaw. Experience from a 10-year period. Scand J Plast Reconstr Surg Suppl 1977;16:1132. 41. Norton MR, Gamble C. Bone classification: an objective scale of bone density using the computerized tomography scan. Clin Oral Implants Res 2001;12:79-84. 42. Sennerby L, Andersson P, Pagliani L, et al. Evaluation of a Novel Cone Beam Computed Tomography Scanner for Bone Density Examinations in Preoperative 3D Reconstructions and Correlation with Primary Implant Stability. Clin Implant Dent Relat Res 2013. 43. Arisan V, Karabuda ZC, Avsever H, Ozdemir T. Conventional multi-slice computed tomography (CT) and cone-beam CT (CBCT) for computer-assisted implant placement. Part I: relationship of radiographic gray density and implant stability. Clin Implant Dent Relat Res 2013;15:893-906. 44. Martin-Badosa E, Amblard D, Nuzzo S, Elmoutaouakkil A, Vico L, Peyrin F. Excised bone structures in mice: imaging at three-dimensional synchrotron radiation micro CT. Radiology 2003;229:921-928. 45. Dykstra BA. ALARA and radiation in the dental office: current state of affair. Dent Today 2011;30:14, 16, 18. 46. Harris D, Horner K, Grondahl K, et al. E.A.O. guidelines for the use of diagnostic imaging in implant dentistry 2011. A consensus workshop organized by the European Association for Osseointegration at the Medical University of Warsaw. Clin Oral Implants Res 2012;23:12431253. 47. Ottoni JM, Oliveira ZF, Mansini R, Cabral AM. Correlation between placement torque and survival of single-tooth implants. Int J Oral Maxillofac Implants 2005;20:769-776. 48. Elias CN, Rocha FA, Nascimento AL, Coelho PG. Influence of implant shape, surface morphology, surgical technique and bone quality on the primary stability of dental implants. J Mech Behav Biomed Mater 2012;16:169-180.
Corresponding author: Prof. Dr. Faleh Tamimi, Faculty of Dentistry, McGill University, Room M60C, Strathcona Anatomy & Dent, 3640 University Street, Montreal, Quebec H3A 0C7, CANADA, Phone: +1-514-398-7203 ext.009654 / Fax: +1 514-398-8900, Email: [email protected] Submitted October 12, 2014; accepted for publication January 02, 2015. Figure 1. Correlations among diagnostic methods. Panoramic radiographs (A,E), CBCT (B, F), histology (C, G) and Micro-CT images (D, H) for a case with low peak insertion torque (A,B. C, and D respectively), and for a case with high peak insertion torque (E, F, G and H respectively). Figures 1A and D are depicting measurements for MCW (3.0mm and 4.2mm, respectively) and present MCI of C3 and C1,
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respectively (note the lack of integrity of the inferior mandibular cortex on Figure 1A). The rectangle area on CBCT scans represent the ROI analyzed by the software, and have 3mm in width and 6mm in length. Scale bar on histology figures represents 500μm. Scale bar on μ-CT figures represents 1 mm. Figure 2. Receiver operating characteristic curve for ridge cortical thickness used to identify the exact cut-off point with optimized sensitivity and specificity for predicting torque > 35 Ncm. The optimal cut-off point was found to be at 0.75mm, and it was later used for stratification of values into two categories in the odds ratio analysis. Supplementary figure 1. Scatterplots of the significant parametric correlations (Pearson correlation test) presented by the study. Abbreviations: MCW, mandibular cortical width; MCI, mandibular cortical index; RBD, radiographic bone density; RCT, ridge cortical thickness; BMD, bone mineral density. Table 1. Descriptive statistics for the continuous variables analyzed. Parameters analyzed Mean ± SD Unit of measurement MCW 3.20 ± 0.55 mm RBD 618.79 ± 208.90 grayscale values RCT 0.83 ± 0.57 mm BMD 0.06 ± 0.03 g/cm2 BV/TV (μ-CT) 72.82 ± 15.32 Percentage BV/TV (Histology) 65.54 ± 17.99 Percentage Abbreviations: RBD, radiographic bone density, RCT, ridge cortical thickness;, SD, Standard deviation. Table 2: Correlations assessed in this study. Analyzed Variables
Age
Age
1
MCW
r=-.533
Analyzed Variables BMD RBD RCT (DXA)
BV/TV (μ-CT)
BV/TV (Histology)
Peak IT
MCW
MCI
r=-.533
r=.702
r=.210
r=.119
r=.143
r=-.101
r=.170
r=.038
p=.002
p=.001
p=.257
p=.523
p=.444
p=.588
p=.405
p=.841
r=-.578
r=.235
r=.515
r=.265
r=.321
r=.290
r=.167
p=.001
p=.203
p=.003
p=.150
p=.078
p=.150
p=.370
r=-.081
r=.-250
r=.-076
r=.-278
r=.-230
r=-.373
p=.667
p=.175
p=.684
p=.056
p=.258
p=.039
r=.366
r=.425
r=.504
r=.795
r=.178
p=.053
p=.017
p=.004
p=.001
p=.339
r=.631
r=.447
r=.501
r=.609
p=.001
p=.012
p=.009
p=.001
r=.484
r=.557
r=.679
p=.006
p=.001
p=.001
r=.817
r=.359
p=.001
p=.047
1
p=.002 r=.702
r=-.578
p=.001
p=.001
r=.210
r=.235
r=-.081
p=.257
p=.203
p=.667
r=.119
r=.515
r=.-250
r=.366
p=.523
p=.003
p=.175
p=.053
r=.143
r=.265
r=.-076
r=.425
r=.631
p=.444
p=.150
p=.684
p=.017
p=.001
BV/TV (μCT)
r=-.101
r=.321
r=.-278
r=.504
r=.447
r=.484
p=.588
p=.078
p=.156
p=.004
p=.012
p=.006
BV/TV (histology)
r=.170
r=.290
r=.-230
r=.795
r=.501
r=.557
r=.817
p=.405
p=.150
p=.258
p=.001
p=.009
p=.001
p=.001
MCI
RBD RCT BMD
1
1
12
1
1
1
1
r=.367 p=.033
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Peak IT
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r=-.038
r=.167
r=-.373
r=.178
r=.609
r=.679
r=.359
r=.367
p=.841
p=.370
p=.039
p=.339
p=.001
p=.001
p=.047
p=.033
p 35Ncm).
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Variables
Peak IT >35N ≤35N
MCW > 3.5 mm 5 6 ≤ 3.5 mm 11 9 MCI Normal (C1) 12 7 Erosion 4 8 (C2/C3) RBD > 700 gsv 10 6 ≤ 700 gsv 6 9 RCT > .75 mm 14 4 ≤ .75 mm 2 11 BMD > 0.07 g/cm2 13 5 ≤ 0.07 g/cm2 3 10 μ-CT-BV/TV > 70% 14 6 ≤ 70% 2 9 Histology-BV/TV > 70% 13 6 ≤ 70% 3 9 MCI=C1 and RCT>.75** Yes 10 1 No 6 14 MCI=C1 and/or RCT>.75** Yes 16 6 No 0 6
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AOR (95% CI)
p
GEE
True + -
False + -
Sensitivity
Specificity
1 0.64 (0.07-5.78)
.691
0.656
5
9
6 11
31.2%
60.0%
13.32 (1.32-134.47)
.028
0.095
12
8
7
4
75.0%
53.3%
1 2.87 (0.56-14.62)
.204
0.223
10
9
6
6
62.5%
60.0%
1 33.42 (2.99-373.72)
.004
0.01
14
11
4
2
87.5%
73.3%
1 7.84 (1.43-43.01)
.018
0.018
13
10
5
3
66.6%
81.2%
1 13.57 (1.85-99.65)
.010
0.010
14
9
6
2
60.0%
87.5%
1 7.23 (1.25-41.76)
.027
0.025
13
9
6
3
60.0%
81.2%
23.33 (2.41-225.22) 1
.002
0.038
10
14
1
6
62.5%
93.3%
*** 1
.001
***
16
6
6
0
100%
50%
1
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Abbreviations: RBD, radiographic bone density; RCT, ridge cortical thickness; +=high torque *Statistically significant (P < 0.05) ** Assessment of cut-off points for index presented in table 4 *** Odds ratio infinity Table 4. Classification developed by Tamimi & Cortes for prediction of insertion torque using radiographic measurements. The table also indicates the distribution of each group within the study group as well as the percentage of high torque implants in each group Implants having high insertion Implants allocated to each torque (>35Ncm) within each Classification classification (prevalence) classification n Percentage n Percentage Class I MCI =1 AND RCT >0.75 11 35% 10 90.9% Class II MCI =1 OR RCT >0.75 11 35% 6 54.5% Class III MCI =1 NOR RCT >0.75 9 29.0% 0 0.0% Abbreviations: RCT, ridge cortical thickness ‡ Veraviewepocs 2D®, Morita, Tokyo, Japan § ImageJ® software, National Institute of Health, Bethesda, MD II i-CAT Classic®, Image Sciences International, Hatfield, PA ¶ OsiriX® 3.9.4 version, Pixmeo, Geneva, Switzerland # Bioparts, São Paulo, Brazil ** SLA, Straumann® AG, Basel, Switzerland †† QDR 2000, Hologic Inc, Waltham, MA ‡‡ SkyScan1172®; SkyScan; Kontich, Belgium §§ Nrecon®, Sky-Scan, Kontich, Belgium IIII sp1600, Leica® Microsystems GmbH, Wetzlar; Germany ¶¶ ProgRes 10 Plus, Jenoptik®, Jena, Germany ## Leica® DMR Mikroskopie und Systeme GmbH, Wetzlar, Germany *** Bioquant Nova Prime, BIOQUANT Image Analysis Corporation, Nashville, TN ††† PTGui®, New House Internet Services B.V., Rotterdam; The Netherlands ‡‡‡ IBM SPSS Statistics 17, SPSS®, Inc, Chicago, IL
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16
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Sensitivity and Specificity of Radiographic Methods for Predicting Insertion Torque of Dental Implants Arthur Rodriguez Gonzalez Cortes, DDS, PhD*, Hazem Eimar, DDS, MS†, Jorge de Sá Barbosa, DDS, MS*, Claudio Costa, DDS, PhD*, Emiko Saito Arita, DDS, PhD*, Faleh Tamimi, DDS, PhD†
*Department of Stomatology, School of Dentistry, University of São Paulo, São Paulo, Brazil. †
Faculty of Dentistry, McGill University, Montreal, Quebec, Canada.
Background: Subjective radiographic classifications of alveolar bone have been proposed and correlated with implant insertion torque (IT). The present diagnostic study aimed to identify quantitative bone features influencing IT, and to use these findings to develop an objective radiographic classification for predicting IT. Methods: Demographics, panoramic radiographs (taken at the beginning of dental treatment) and cone beam computed tomographic scans (taken for implant surgical planning) of a total of 25 patients receiving 31 implants were analyzed. Bone samples retrieved from implant sites were assessed with dual x-ray absorptiometry, micro-computed tomography and histology. Odds ratio, sensitivity and specificity of all variables to predict high peak IT were assessed. Results: A ridge cortical thickness greater than .75mm and a normal appearance of the inferior mandibular cortex were the most sensitive variables for predicting high peak IT (87.5% and 75%, respectively). A classification based on the combination of both variables presented high sensitivity (90.9%) and specificity (100%) for predicting IT. Conclusion: Within the limitations of this study, the present results suggest that it is possible to predict IT accurately, based on radiographic findings of the patient. This could be useful in the treatment plan of immediate loading cases.
KEYWORDS: Endosseous dental implants, insertion torque, panoramic radiography, cone beam computed tomography, bone mineral density.
Success of dental implant osseointegration depends on the density and amount of available bone, and on primary implant stability, that is, the absence of implant mobility in the bone bed after surgical placement.1 One of the indicators of primary stability is the implant insertion torque (IT).2, 3 An adequate insertion torque should be ensured to avoid implant micromotion and consequent failure during the osseointegration process.4 In addition, a high IT is one of the factors recommended for immediate loading of the implant, leading to shorter treatments.5-8 Therefore, it could be hypothesized that the ability to predict IT would improve treatment planning, allowing the clinician to choose an adequate implant design, drilling sequence and loading time. The influence of alveolar bone characteristics on implant IT has been assessed using different bone density classifications.9-13 One of the most commonly used classifications is based on the amount of cortical and trabecular bone shown in preoperative panoramic and periapical radiographs generating four scores.14 However, this classification has been found to be inaccurate for prediction of IT,15 as it is subjective, and it depends on the opinion of the professional.11 Other measurements such as cortical thickness of the alveolar ridge have been found to correlate with IT.16
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However, the quantitative relationship, as well as sensitivity and specificity of this and other diagnostic methods to predict torque are not yet available in the literature. Cone beam computed tomography (CBCT) allows performing 3D pre-surgical morphological assessment of the cortical and trabecular alveolar bone available for placing dental implants.17 Compared with other computed tomographic (CT) methods, CBCT offers advantages such as reduced effective radiation doses, shorter acquisition scan time, easier imaging, and lower costs.17, 18 CBCT has been validated19 and clinically used20 to assess bone density at implant sites by measuring pixel grayscale values. This analysis has been termed “radiographic bone density”.20-23 The radiographic bone density obtained with CBCT and peak IT has been found to be significantly correlated in both animal10 and human bone samples.21, 24. However, none of the above-mentioned studies assessed the relative contribution of cortical and trabecular bone on insertion torque. Previous laboratory studies using simulation models,16, 25 suggest that cortical bone thickness, as well as trabecular bone elastic modulus and strength may influence implant IT and primary stability. Panoramic radiographs are useful to diagnose systemic26 and alveolar27 bone quality by assessing the width and shape of the inferior mandibular cortex. These measurements have been described as indices to predict osteoporosis, as they are correlated with systemic bone mineral density (BMD) values measured with dualenergy x-ray absorptiometry (DXA).28 Nevertheless, the relation between these indices and implant peak IT remains unknown. We hypothesized that quantitative values from radiographic measurements could be used as diagnostic tools for predicting peak insertion torque. Thus, the aims of this diagnostic study were: to identify alveolar and systemic bone features that influence peak IT and use this information to develop a clinical method for prediction of insertion torque.
MATERIALS AND METHODS Approval was obtained from the Ethics Committee of the University of São Paulo (protocol number: 104/11). All patients willing to participate in this study signed an informed consent form. The Standards for the Reporting of Diagnostic accuracy studies (STARD)29 and the guidelines of the Helsinki Declaration were followed in this investigation. Inclusion and Exclusion Criteria This diagnostic study was conducted on partially edentulous patients attending a private dental clinic that partners in research with the School of Dentistry, University of São Paulo. The subjects selected had been diagnosed and indicated either for one or two implant placement procedures (maximum of one implant per dental arch) between June 2011 and October 2012. Only implant sites with more than 5 mm in width were included. Patients with a recent tooth extraction (less than 6 months of follow-up) were excluded to avoid the socket remodeling period, following previously adopted criteria.30 Patients with metabolic disorders, such as diabetes and vitamin D deficiency, or with insufficient alveolar bone volume for implant placement were excluded. History of ridge augmentation with grafts was also considered as exclusion criteria.
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Radiographic Analyses Digital panoramic radiographs‡ of all patients were taken at the beginning of dental treatment, since it is an examination recommended for general screening.31 Images were taken using the following exposure conditions: 60kV, 4mA, 0.5-mm copper filter), and were analyzed using an imaging processing software§. The mandibular cortical width (MCW) was measured at both mental foramen regions, according to previous methodology.26 Briefly, images were corrected using a magnification factor of 1.3. Spatial calibration was set at a scale of 1 pixel per 96 μm. Next, a line parallel to the long axis of the mandible and tangential to the inferior border of the mandible was drawn. A line perpendicular to this tangent intersecting the inferior border of the mental foramen was constructed, along which the mandibular cortical width was measured (Figures 1A and E). The mandibular cortical shape index (MCI) was assessed by evaluating the appearance of the cortical bone below the mandibular foramen, using a previously described classification.32 Briefly, the inferior mandibular cortex was classified as ‘C1’ or normal (Figure 1E), when presenting an even and distinct endosteal margin, ‘C2’ or moderately eroded, when presenting evidence of lacunar resorption or endosteal cortical residues, and ‘C3’ or severely eroded (Figure 1A), when unequivocal porosity was observed. All patients underwent a CBCTII scan, required for implant three-dimensional surgical planning,17 with a diagnostic protocol used for dental implants (0.25-mm voxel, 120kVp, 8mA, exposure time of 8.5 seconds and field of view of 16-cm in diameter and 6-cm in height).30 The aforementioned field of view included only one full dental arch in standard resolution, allowing for a low effective radiation dose (approximately 35 microsieverts), as reported by a study using the same CBCT device.33 DICOM (Digital Imaging Communication in Medicine) images were assessed using a DICOM viewer software¶. The edentulous areas of the ridge, planned for receiving dental implants, were identified in sagittal CBCT images as rectangular regions of interest (ROIs) of 6 mm in length and 3 mm in width, matching the implant placement site. Ridge cortical thickness at the alveolar crest (in mm) and mean radiographic bone density (in grayscale values) were measured in the ROI images, with the linear measurement and gray scale analysis tools of the DICOM viewer software¶, respectively). The selected CBCT images and defined ROIs were also used to make a custom stereolithography surgical guide using a rapid prototyping machine#. The surgical guides had specific drill sleeves to avoid angle deviations during the drilling procedure. This ensured bone sample collection and implant placement in the same CBCT ROI used for radiographic measurements, according to previous methodology.20, 21 All panoramic radiographic and CBCT measurements were performed in random order by two trained observers (i.e. dentists with expertise in oral radiology). Intraobserver reliability was assessed between measurements performed 2 weeks apart to eliminate memory bias. Intra and interobserver agreement were assessed using the intraclass correlations coefficient (ICC) and the kappa test for continuous and categorical variables respectively. Treatment Timetable All patients received amoxicillin (2.0g) one hour before surgery, as prophylaxis, and were treated by the same surgeon using the same surgical procedure. Under local anesthesia, a crestal incision was performed slightly palatal to the crest midline and
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the mucogingival flap was elevated. Implant sites were prepared using the surgical guide with trephine burs in order to obtain bone cores (3.0mm diameter and 6.0mm in length) from the implant sites. The bone samples were fixed and stored in 4% formaldehyde buffer solution. An additional surgical drill of 3.5mm in diameter was used to complete implant site preparation. Dental implants** with 4.1mm in diameter and 10.0mm in length were placed using a ratchet adapted to the torquimeter of the corresponding implant system. This torquimeter shows values of 0Ncm, 15Ncm and 35Ncm. Therefore, the peak insertion torque at final implant position was classified into three categories: 35Ncm. All implants were placed at soft tissue level, and restored after two months of healing. DXA Analysis Bone biopsies were analyzed with DXA††. Acquisition lines were set at a distance of 0.254 mm, and the space between each point was 0.127 mm. The acquisition window had a maximum width of 4 cm and a length of 6 cm. Bone samples were placed flat, with their long axis parallel to the progression axis during image acquisition, and with a density control hydroxyapatite besides them. BMD values were determined and expressed in g/cm2. Micro-Computed Tomography (μ-CT) Bone biopsies were also analyzed with a μ-CT machine‡‡ set up at 100 KeV and 100 micro-amperes, and a resolution of 6.0 μm, with a 0.5 mm Al filter. Time exposure per frame was 450 ms. X-ray images were reconstructed with the manufacturer software§§ before analyzing them for bone volume per total volume (BV/TV). This is a variable that refers to the total amount of bone present within the biopsy, including cortical and trabecular bone.20, 21 Histology Fixed biopsies were dehydrated in ascending concentrations of ethanol and resin infiltrated and embedded before final polymerization. Longitudinal histological sections crossing the center of the cylindrical biopsy were taken using a micro sawIIII, and stained with methylene blue and basic fuchsine. Pictures of histological sections were taken with a digital camera¶¶ installed on an optical microscope##. The images were processed using a morphometry software*** and stitched with an image processing software†††. Optical images of longitudinal sections crossing the cylindrical biopsies in the centre were used to perform the histomorphometrical analysis of each implanted area.34 Images were analyzed using the image processing software§. For each slice, the area occupied by bone tissue was outlined and calculated as a percentage of the total area of the slice. Since standard histomorphometry is a two-dimensional analysis, four sections per biopsy with same direction and thickness were averaged.35 For each histological section, the percentage of area occupied by bone was calculated as BV/TV values. Statistical Analysis Sample size was determined using the uncorrected chi-square test, to detect a minimum odds ratio of 5 and to give the study a power of 80%, at a level of significance of 5%. Correlation analyses were performed among all variables 4
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analyzed in the study. Normality was assessed for continuous variables (age, MCW, radiographic bone density, ridge cortical thickness, BMD, μ-CT BV/TV and histology BV/TV) using the Shapiro-Wilk test. Pearson’s test was used for correlations involving continuous variables, while correlations involving categorical variables (MCI and peak IT), were analyzed with Spearman’s test. Conditional logistic regression was used to assess associations between peak insertion torque and the rest of variables. All variables were stratified using cut-off points. For continuous variables, optimal cut-off points were chosen using receiver operating characteristic curve analysis (Figure 2), at the point where sum of specificity and sensitivity is maximum, and equal weight is given to both.36 For MCI, “C1” category was selected as the cut-off point, since this is the only category representing the absence of alterations in the inferior mandibular cortex.32 Finally, a peak insertion torque of 35Ncm was chosen as cut-off point, since this is a value recommended for immediate loading using the implant system of our study.37, 38 Risk estimates were presented as odds ratios (ORs) with 95% confidence intervals (CIs). The ORs were adjusted for potential confounders of age and gender. Adjustment for clusters (implant/patient) were performed using generalized estimated equations (GEE). Sensitivity and specificity of each imaging method for screening high peak insertion torque of each variable were also calculated using the selected cut-off points. Finally, we attempted to develop a clinical classification to enable clinicians to predict peak insertion torque using only panoramic radiographs and CBCT. For this purpose, sensitivity and specificity of significant variables from these imaging methods were combined for predicting high insertion torque. All statistical analyses were performed using the same software‡‡‡.
RESULTS A total of 25 patients (13 men and 12 women, mean age of 59.3 ± 11.5 years) receiving 31 implants (25 mandibular; 7 in the interforaminal region and 18 in posterior regions and 6 maxillary; 3 anterior to the maxillary sinuses, and 3 in posterior regions) were analyzed. Descriptive statistics of continuous variables are presented in Table 1. Intraobserver reproducibility and interobserver reliability were confirmed for the MCW, radiographic bone density and ridge cortical thickness measurements (ICC between 0.82 and 0.89), as well as for MCI categorical measurements (kappa index 0.87, P=0.01). Normal distribution was confirmed for all continuous variables according to the Shapiro-Wilk test (p>0.05). Of the 31 implants included in this study, 16 presented a high peak insertion torque (T>35Ncm). Of these, 14 were mandibular (4 in the interforaminal region and 10 in posterior regions) and 2 were maxillary (1 anterior to the maxillary sinuses and 1 in a posterior region). All correlations assessed are shown in Table 2. Scatterplots for parametric correlations are shown in Supplementary figure 1. MCI was significantly correlated with peak IT, age, and MCW. Peak IT was also significantly correlated to ridge cortical thickness, BMD, μ-CT-BV/TV and histology-BV/TV. In addition, μ-CTBV/TV and radiographic bone density were strongly correlated with histology-
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BV/TV (r=.817, p=.001 and r=.795, p=.001, respectively) (Figure 1). No other correlations were significant (P > 0.05). Cut-off points of each variable and risk associations with peak insertion torque are shown in Table 3. Adjusted odds ratio (AOR) analysis showed that ridge cortical thickness (AOR = 33.42; 95%CI = 2.99 to 373.72; P = 0.004; post-hoc power = 96.46%), MCI (AOR = 13.32; 95%CI = 1.32 to 134.47; P = 0.028; post-hoc power = 90.05%), μ-CT-BV/TV (AOR = 13.57; 95%CI = 1.85 to 99.65; P = 0.01; post-hoc power = 91.43%), histology-BV/TV (AOR = 7.23; 95%CI = 1.25 to 41.76; P = 0.027; post-hoc power = 86.47%), and BMD (AOR = 7.84; 95%CI = 1.43 to 43.01; P = 0.018; post-hoc power = 83.83%) were significantly associated with peak insertion torque. MCW and radiographic bone density from CBCT were not significantly associated with peak insertion torque (P > 0.05). Sensitivity and specificity for screening high peak insertion torque was calculated for all variables (Table 3). The most sensitive tests were ridge cortical thickness (84.6%) and MCI (75%), whereas the most specific tests were μ-CT-BV/TV (87.5%) and histology-BV/TV (81.2%). According to odds ratio analysis, ridge cortical thickness and MCI were the only clinical parameters (i.e. from panoramic radiographs and CBCT) that showed significant association with peak IT. Therefore, the combination of these two variables was assessed for screening high insertion torque and used to develop a classification for prediction of torque. The proposed combination of the tests presented a sensitivity of 100% (Table 3). The results led to the development of a classification, based on these variables (Table 4). In this classification, patients are divided in three categories, according to the probability of having a high insertion torque: “class I” (Figures 1E-H), when both variables reach the cut-off point (0.75mm for ridge cortical thickness and C1 category for MCI); “class II”, when only one of the variables reaches the cut-off point; and “class III” (Figures 1A-D), when none of the variables reach the cut-off point. No procedure-related complications were observed in this study. The study implant survival rate was 100% with a mean 23-month follow-up (range of 9–34 months).
DISCUSSION The present diagnostic study assessed odds ratio, sensitivity and specificity of multiple variables from different radiographic methods for association and diagnostic performance to predict peak IT. Histological morphometric analysis was also employed as a gold standard to correlate with bone findings from the radiographic methods included in this study. Implant insertion torque is influenced by bone quality and quantity, implant design and surgical technique.2, 5, 12 The last two factors were fixed in this study, since all surgeries were performed by the same surgeon using the same implant system, surgical drills and implant dimensions. Therefore, we were able to evaluate the solely influence of alveolar bone characteristics on implant insertion torque. In the present study, all methods quantifying trabecular bone (radiographic bone density, μ-CT-BV/TV and histology-BV/TV) presented either none or poor correlations with peak insertion torque, whereas most methods assessing cortical bone (DXA, MCI and ridge cortical thickness) presented strong significant correlations
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with the same parameter. These findings support a histomorphometric study that found no significant correlation between BV/TV and peak insertion torque,13 and another study concluding that implant insertion torque is dependent on the quantity of cortical bone in contact with the implant.9 Furthermore, our quantitative results confirm the evidences of the influence of alveolar cortical layer on the drilling resistance experienced by the surgeon and on implant stability, presented by previous studies using subjective bone classifications.14, 39, 40 There is a controversy in the literature regarding the use of CBCT to determine Hounsfield Units. The Hounsfield scale was originally designed for spiral CT.41 Unless calibration and attenuation coefficients are used, this scale is not compatible with CBCT and therefore was not considered in this study. Instead, grayscale values provided by the DICOM viewer software were used for correlation analyses, as described by similar studies.10, 20, 24 In the present study, there was no significant correlation between radiographic bone density taken from CBCT and peak IT. This finding is in agreement with a previous study.21 In contrast, other studies found weak,42 moderate,43 and strong10, 24 significant correlations between radiographic bone density and peak IT. Since radiographic bone density assess trabecular bone structure by means of grayscale analysis, the aforementioned findings lead to a controversy in the literature regarding the influence of the ridge cortical layer on peak IT, observed and discussed herein. In our study, radiographic bone density from pre-operative CBCT scans presented strong significant correlations with BV/TV values obtained from both μ-CT and histology, as observed by another study.20 Furthermore, among the laboratorial methods assessed herein, μ-CT presented a stronger significant association with peak IT, compared with DXA and histology. This finding supports use of μ-CT as a suitable tool for bone morphometric measurements, as previously described in the literature.44 This is the first study addressing the correlation of panoramic radiographic indices with peak insertion torque (MCI) and patient’s age (MCI and MCW). MCI presented a weak to moderate inverse correlation with torque (r= -0.373, p=0.039). However, this variable was found to be strongly associated with peak insertion torque outcomes according to the adjusted odds ratio analysis (AOR=13.32, 95% CI=1.32-134.47). Despite the fact that MCI is an indicator for peripheral bone quality,28 it has also been found to play a decisive role in the diagnostic performance of our classification, according to the sensitivity and specificity analyses presented in table 3. Furthermore, the correlation between MCI and MCW and patients’ age observed in this study supports results from articles that validated these indices to predict bone alterations such as osteoporosis, since bone density is expected to decrease as the patient grow older.26 To our knowledge, the present study is the first to assess sensitivity and specificity of methods to predict insertion torque. In contrast with linear correlations, sensitivity and specificity evaluate the diagnostic performance of a variable to predict or detect an outcome. Therefore, we were able to describe the critical values from radiographic measurements that could be used by clinicians and researchers as cut-off points to predict high peak IT. In addition, the present study proposed the first radiographic classification developed to predict high insertion torque of implants, using digital panoramic radiographs, commonly used for general screening after an initial clinical examination,31 and pre-operative CBCT, in accordance with the “as low a dose as
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reasonably achievable” (ALARA) principle,45 and with the guidelines of the European Academy of Osseointegration (EAO) for the use of diagnostic imaging in implant dentistry.46 According to the EAO guidelines, cross-sectional imaging may not be decisive for planning implants in cases where clinical examination and conventional radiographs provided sufficient data for the surgeon. However, there are a number of clinical situations that benefit from a CBCT scan for implant planning.46 For these situations, our classification to predict torque could be indicated as a diagnostic parameter. The classification based on MCI and ridge cortical thickness divided alveolar bone in 3 categories: class I, when both variables reach the cut-off point; class II, when one of the variables reaches the cut-off point; and class III, when none of the variables reach the cut-off point. Implants placed in class I have 90% probability of having a high torque and could be planned for immediate loading. Similarly, implants placed in class III are predicted to have 100% probability of having a low torque. Such cases would require additional clinical measures to enhance the primary stability of implants, such as using tapered implant bodies or decreasing the diameter of the last drill. As a result, our radiographic classification could be decisive for planning immediate loaded implants. Future clinical studies would be required to address the effect of our classification on drilling sequence, and implant diameter and type selection. Implant insertion torque has been significantly correlated with survival rates of immediate loaded implants.8 A study on single-tooth implants found that a torque greater than 32 Ncm was necessary to achieve osseointegration in cases of immediate loading.47 Therefore, although we did not assess the impact of our radiographic classification on immediate loading, our data indicates that this classification could be useful to enhance treatment plan of such cases. Nevertheless, since success of immediate loading does not depend solely on insertion torque, future randomized clinical trials would be recommended to test the clinical application of our classification in patients receiving immediately loaded implants. Furthermore, although an appropriate sample size was achieved to test our hypothesis, the number of implants in each region of the jaws was low. In addition, none of the implants were lost. As a result, the present diagnostic study was not able to address the impact of the proposed radiographic classification on implant survival rates. Future cohort studies with larger sample sizes and using different implant systems would be required to evaluate our classification as a risk factor for implant loss in cases of immediate and conventional loading. Another limitation of this study is that the dimensions of bone samples taken from implant sites (3x6mm) did not match proper implant dimensions (4.1x10mm). This methodology was adopted to finish implant site preparation using the last drill of the implant system used, following its guidelines.20 Furthermore, our radiographic classification was developed for cylindrical implants. Future studies would have to be performed to assess it with tapered implants, as they provide higher torque than cylindrical ones.48 In conclusion, within the limitations of this study, the findings observed using the present implant system and following its surgical guidelines suggest that the radiographic classification developed herein could be considered to predict insertion torque of cylindrical dental implants. This could be useful in the treatment plan of immediate loading cases. Finally, CBCT scans taken with the device of this study could be considered to assess alveolar bone density, since the radiographic bone
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density obtained with this method was strongly correlated with morphometric measurements from both micro-CT and histology. ACKNOWLEDGEMENTS A Ph.D. scholarship was granted to A.R.G.C. by the National Council for Scientific and Technological Development (CNPq – Brazil, N° 140291/2011 3). F.T. received grants by The Network for Oral and Bone Health Research (RSBO, Quebec, Canada) and by the Natural Sciences and Engineering Research Council of Canada (NSERC RGPIN 418617-12).
CONFLICT OF INTEREST STATEMENT The authors declare that there are no conflicts of interest in this study.
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34. Particelli F, Mecozzi L, Beraudi A, Montesi M, Baruffaldi F, Viceconti M. A comparison between micro-CT and histology for the evaluation of cortical bone: effect of polymethylmethacrylate embedding on structural parameters. J Microsc 2012;245:302-310. 35. Chappard D, Retailleau-Gaborit N, Legrand E, Basle MF, Audran M. Comparison insight bone measurements by histomorphometry and microCT. J Bone Miner Res 2005;20:1177-1184. 36. Kumar R, Indrayan A. Receiver operating characteristic (ROC) curve for medical researchers. Indian Pediatr 2011;48:277-287. 37. Buttel AE, Gratwohl DA, Sendi P, Marinello CP. Immediate loading of two unsplinted mandibular implants in edentulous patients with an implant-retained overdenture: an observational study over two years. Schweiz Monatsschr Zahnmed 2012;122:392-397. (english) 38. Kinsel RP, Liss M. Retrospective analysis of 56 edentulous dental arches restored with 344 singlestage implants using an immediate loading fixed provisional protocol: statistical predictors of implant failure. Int J Oral Maxillofac Implants 2007;22:823-830. 39. Misch CE. Bone classification, training keys to implant success. Dent Today 1989;8:39-44. 40. Branemark PI, Hansson BO, Adell R, et al. Osseointegrated implants in the treatment of the edentulous jaw. Experience from a 10-year period. Scand J Plast Reconstr Surg Suppl 1977;16:1132. 41. Norton MR, Gamble C. Bone classification: an objective scale of bone density using the computerized tomography scan. Clin Oral Implants Res 2001;12:79-84. 42. Sennerby L, Andersson P, Pagliani L, et al. Evaluation of a Novel Cone Beam Computed Tomography Scanner for Bone Density Examinations in Preoperative 3D Reconstructions and Correlation with Primary Implant Stability. Clin Implant Dent Relat Res 2013. 43. Arisan V, Karabuda ZC, Avsever H, Ozdemir T. Conventional multi-slice computed tomography (CT) and cone-beam CT (CBCT) for computer-assisted implant placement. Part I: relationship of radiographic gray density and implant stability. Clin Implant Dent Relat Res 2013;15:893-906. 44. Martin-Badosa E, Amblard D, Nuzzo S, Elmoutaouakkil A, Vico L, Peyrin F. Excised bone structures in mice: imaging at three-dimensional synchrotron radiation micro CT. Radiology 2003;229:921-928. 45. Dykstra BA. ALARA and radiation in the dental office: current state of affair. Dent Today 2011;30:14, 16, 18. 46. Harris D, Horner K, Grondahl K, et al. E.A.O. guidelines for the use of diagnostic imaging in implant dentistry 2011. A consensus workshop organized by the European Association for Osseointegration at the Medical University of Warsaw. Clin Oral Implants Res 2012;23:12431253. 47. Ottoni JM, Oliveira ZF, Mansini R, Cabral AM. Correlation between placement torque and survival of single-tooth implants. Int J Oral Maxillofac Implants 2005;20:769-776. 48. Elias CN, Rocha FA, Nascimento AL, Coelho PG. Influence of implant shape, surface morphology, surgical technique and bone quality on the primary stability of dental implants. J Mech Behav Biomed Mater 2012;16:169-180.
Corresponding author: Prof. Dr. Faleh Tamimi, Faculty of Dentistry, McGill University, Room M60C, Strathcona Anatomy & Dent, 3640 University Street, Montreal, Quebec H3A 0C7, CANADA, Phone: +1-514-398-7203 ext.009654 / Fax: +1 514-398-8900, Email: [email protected] Submitted October 12, 2014; accepted for publication January 02, 2015. Figure 1. Correlations among diagnostic methods. Panoramic radiographs (A,E), CBCT (B, F), histology (C, G) and Micro-CT images (D, H) for a case with low peak insertion torque (A,B. C, and D respectively), and for a case with high peak insertion torque (E, F, G and H respectively). Figures 1A and D are depicting measurements for MCW (3.0mm and 4.2mm, respectively) and present MCI of C3 and C1,
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respectively (note the lack of integrity of the inferior mandibular cortex on Figure 1A). The rectangle area on CBCT scans represent the ROI analyzed by the software, and have 3mm in width and 6mm in length. Scale bar on histology figures represents 500μm. Scale bar on μ-CT figures represents 1 mm. Figure 2. Receiver operating characteristic curve for ridge cortical thickness used to identify the exact cut-off point with optimized sensitivity and specificity for predicting torque > 35 Ncm. The optimal cut-off point was found to be at 0.75mm, and it was later used for stratification of values into two categories in the odds ratio analysis. Supplementary figure 1. Scatterplots of the significant parametric correlations (Pearson correlation test) presented by the study. Abbreviations: MCW, mandibular cortical width; MCI, mandibular cortical index; RBD, radiographic bone density; RCT, ridge cortical thickness; BMD, bone mineral density. Table 1. Descriptive statistics for the continuous variables analyzed. Parameters analyzed Mean ± SD Unit of measurement MCW 3.20 ± 0.55 mm RBD 618.79 ± 208.90 grayscale values RCT 0.83 ± 0.57 mm BMD 0.06 ± 0.03 g/cm2 BV/TV (μ-CT) 72.82 ± 15.32 Percentage BV/TV (Histology) 65.54 ± 17.99 Percentage Abbreviations: RBD, radiographic bone density, RCT, ridge cortical thickness;, SD, Standard deviation. Table 2: Correlations assessed in this study. Analyzed Variables
Age
Age
1
MCW
r=-.533
Analyzed Variables BMD RBD RCT (DXA)
BV/TV (μ-CT)
BV/TV (Histology)
Peak IT
MCW
MCI
r=-.533
r=.702
r=.210
r=.119
r=.143
r=-.101
r=.170
r=.038
p=.002
p=.001
p=.257
p=.523
p=.444
p=.588
p=.405
p=.841
r=-.578
r=.235
r=.515
r=.265
r=.321
r=.290
r=.167
p=.001
p=.203
p=.003
p=.150
p=.078
p=.150
p=.370
r=-.081
r=.-250
r=.-076
r=.-278
r=.-230
r=-.373
p=.667
p=.175
p=.684
p=.056
p=.258
p=.039
r=.366
r=.425
r=.504
r=.795
r=.178
p=.053
p=.017
p=.004
p=.001
p=.339
r=.631
r=.447
r=.501
r=.609
p=.001
p=.012
p=.009
p=.001
r=.484
r=.557
r=.679
p=.006
p=.001
p=.001
r=.817
r=.359
p=.001
p=.047
1
p=.002 r=.702
r=-.578
p=.001
p=.001
r=.210
r=.235
r=-.081
p=.257
p=.203
p=.667
r=.119
r=.515
r=.-250
r=.366
p=.523
p=.003
p=.175
p=.053
r=.143
r=.265
r=.-076
r=.425
r=.631
p=.444
p=.150
p=.684
p=.017
p=.001
BV/TV (μCT)
r=-.101
r=.321
r=.-278
r=.504
r=.447
r=.484
p=.588
p=.078
p=.156
p=.004
p=.012
p=.006
BV/TV (histology)
r=.170
r=.290
r=.-230
r=.795
r=.501
r=.557
r=.817
p=.405
p=.150
p=.258
p=.001
p=.009
p=.001
p=.001
MCI
RBD RCT BMD
1
1
12
1
1
1
1
r=.367 p=.033
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Peak IT
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r=-.038
r=.167
r=-.373
r=.178
r=.609
r=.679
r=.359
r=.367
p=.841
p=.370
p=.039
p=.339
p=.001
p=.001
p=.047
p=.033
p 35Ncm).
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Variables
Peak IT >35N ≤35N
MCW > 3.5 mm 5 6 ≤ 3.5 mm 11 9 MCI Normal (C1) 12 7 Erosion 4 8 (C2/C3) RBD > 700 gsv 10 6 ≤ 700 gsv 6 9 RCT > .75 mm 14 4 ≤ .75 mm 2 11 BMD > 0.07 g/cm2 13 5 ≤ 0.07 g/cm2 3 10 μ-CT-BV/TV > 70% 14 6 ≤ 70% 2 9 Histology-BV/TV > 70% 13 6 ≤ 70% 3 9 MCI=C1 and RCT>.75** Yes 10 1 No 6 14 MCI=C1 and/or RCT>.75** Yes 16 6 No 0 6
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AOR (95% CI)
p
GEE
True + -
False + -
Sensitivity
Specificity
1 0.64 (0.07-5.78)
.691
0.656
5
9
6 11
31.2%
60.0%
13.32 (1.32-134.47)
.028
0.095
12
8
7
4
75.0%
53.3%
1 2.87 (0.56-14.62)
.204
0.223
10
9
6
6
62.5%
60.0%
1 33.42 (2.99-373.72)
.004
0.01
14
11
4
2
87.5%
73.3%
1 7.84 (1.43-43.01)
.018
0.018
13
10
5
3
66.6%
81.2%
1 13.57 (1.85-99.65)
.010
0.010
14
9
6
2
60.0%
87.5%
1 7.23 (1.25-41.76)
.027
0.025
13
9
6
3
60.0%
81.2%
23.33 (2.41-225.22) 1
.002
0.038
10
14
1
6
62.5%
93.3%
*** 1
.001
***
16
6
6
0
100%
50%
1
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Abbreviations: RBD, radiographic bone density; RCT, ridge cortical thickness; +=high torque *Statistically significant (P < 0.05) ** Assessment of cut-off points for index presented in table 4 *** Odds ratio infinity Table 4. Classification developed by Tamimi & Cortes for prediction of insertion torque using radiographic measurements. The table also indicates the distribution of each group within the study group as well as the percentage of high torque implants in each group Implants having high insertion Implants allocated to each torque (>35Ncm) within each Classification classification (prevalence) classification n Percentage n Percentage Class I MCI =1 AND RCT >0.75 11 35% 10 90.9% Class II MCI =1 OR RCT >0.75 11 35% 6 54.5% Class III MCI =1 NOR RCT >0.75 9 29.0% 0 0.0% Abbreviations: RCT, ridge cortical thickness ‡ Veraviewepocs 2D®, Morita, Tokyo, Japan § ImageJ® software, National Institute of Health, Bethesda, MD II i-CAT Classic®, Image Sciences International, Hatfield, PA ¶ OsiriX® 3.9.4 version, Pixmeo, Geneva, Switzerland # Bioparts, São Paulo, Brazil ** SLA, Straumann® AG, Basel, Switzerland †† QDR 2000, Hologic Inc, Waltham, MA ‡‡ SkyScan1172®; SkyScan; Kontich, Belgium §§ Nrecon®, Sky-Scan, Kontich, Belgium IIII sp1600, Leica® Microsystems GmbH, Wetzlar; Germany ¶¶ ProgRes 10 Plus, Jenoptik®, Jena, Germany ## Leica® DMR Mikroskopie und Systeme GmbH, Wetzlar, Germany *** Bioquant Nova Prime, BIOQUANT Image Analysis Corporation, Nashville, TN ††† PTGui®, New House Internet Services B.V., Rotterdam; The Netherlands ‡‡‡ IBM SPSS Statistics 17, SPSS®, Inc, Chicago, IL
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