|Year : 2019 | Volume
| Issue : 7 | Page : 982-987
Evaluating cortico-cancellous ratio using virtual implant planning and its relation with immediate and long-term stability of a dental implant- A CBCT-assisted prospective observational clinical study
S Talluri1, SK Vaddamanu2, V Apparaju3, R Vyas2, S Ahuja4, MA Kanji2
1 Department of Periodontology and Oral Implantology, Rambabu Dental Hospital, Ongole, India
2 Department of Dental Technology, College of Applied Medical Science, King Khalid University, Abha, Saudi Arabia
3 Department of Periodontics, Dr. Vijay's Multi Speciality Dental Care, Implant and Laser Center, Bangalore, India
4 Department of Occupational Health and Safety Management, Lambton College of Applied Arts and Technology, Scarborough, Toronto, Ontario, Canada
|Date of Acceptance||25-Feb-2019|
|Date of Web Publication||11-Jul-2019|
Dr. R Vyas
Department of Dental Technology, College of Applied Sciences, King Khalid University, Abha - 61471
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Primary and long-term implant stabilities are crucial in predicting the success of dental implants. We aimed to evaluate corticocancellous ratio (CCR) around virtual implant using cone beam computed tomography (CT) and assess its relationship with immediate and long-term stability of the implants placed. Materials and Methods: A total of 135 image records of posterior mandibular implant sites planned for dental implant were included in our study. CCR was calculated using CT images and implants were placed after stent preparation. Implant stability was calculated immediately, 4 months later, and 2 years later. Results: Pearson's correlation test showed a significant correlation (P and lt; 0.001) between CCR and implant stability. ANOVA and post-hoc Tukey tests showed a significant difference in implant stability between groups with different CCRs at all follow-up timepoints. No significant difference was found between mean implant stability quotient values for low CCR at 2-year follow-up and high CCR immediately after implant placement. Conclusions: Implant stability is improved with greater CCR. Cortical bone seems to be crucial factor for immediate and long-term stability of a dental implant. Virtual planning using CT can assess implant stability. Further histological studies are required to confirm the relation between CCR and implant stability. The escalating demand of the implant treatment in the dental practice necessitates measuring the several predictors of procedure success. This study introduces a novel predictor (CCR) around virtual implant for detecting the immediate and long-term stability of a dental implant.
Keywords: Cancellous bone, cone-beam computed tomography, cortical bone, dental implant
|How to cite this article:|
Talluri S, Vaddamanu S K, Apparaju V, Vyas R, Ahuja S, Kanji M A. Evaluating cortico-cancellous ratio using virtual implant planning and its relation with immediate and long-term stability of a dental implant- A CBCT-assisted prospective observational clinical study. Niger J Clin Pract 2019;22:982-7
|How to cite this URL:|
Talluri S, Vaddamanu S K, Apparaju V, Vyas R, Ahuja S, Kanji M A. Evaluating cortico-cancellous ratio using virtual implant planning and its relation with immediate and long-term stability of a dental implant- A CBCT-assisted prospective observational clinical study. Niger J Clin Pract [serial online] 2019 [cited 2020 Jul 5];22:982-7. Available from: http://www.njcponline.com/text.asp?2019/22/7/982/262514
| Introduction|| |
Replacing missing teeth without disturbing adjacent environment is vital. Previously, removable and fixed dentures were treatments of choice. With improvements in the field of dentistry, dental implants became a new treatment modality with promising results. Advantages of dental implants caused oral rehabilitation using dental implants to be more popular. Numerous factors affect success of a dental implant. First of all are patient-related factors such as age, gender, systemic diseases, smoking, and harmful oral habits. Also contributing are implant site-related factors like quality and quantity of bone at implant site. In addition, procedure-related factors such as heat management at implant site, angulations, position, and direction of implant placement would affect implant success. Finally, prosthetic and fixture-related factors and occlusion-related factors also affect success of a dental implant.,
Quality and quantity of bone at implant site is a crucial determining factor of dental implant success. Cortical bone tissue is more abundant in mandible rather than maxilla, this could be the cause why implant success rates are higher at mandibular rather than maxillary sites., Presurgical evaluation of quality of implant site is vital in predicting success rate of a dental implant. Previously, periapical radiographs and orthopantographs, which are two-dimensional radiographs, were used to assess bone quality., Alhough three-dimensional radiographs like computed tomography (CT) scans became popular, high radiation dosage curbed its usage in the field of dentistry. Currently, cone beam computed tomography (CBCT) can be used for three-dimensional visualization of implant site with minimal radiation exposure.,
Among many other aspects, initial stabilization and final osseointegration were proposed to be determining factors of dental implant success., Initial primary stability is vital for successful final osseointegration. Several methods were proposed in the last few decades to measure implant stability. Among these are clinical perception during osteotomy site preparations, percussion test, cutting torque resistant analysis, and reverse torque application. These methods are not used frequently due to their lack of quality analysis., Another method of measuring implant stability is using Periotest device (Medizintechnik Gulden, Modautal, Germany). However, one concern with using Periotest device is that it measures hardness of bone surrounding implant rather than osseointegration itself. In absence of a standard reliable way of measuring implant stability, popularity of using resonance frequency analysis (RFA) is increasing. RFA using Osstell device (Integration Diagnostics AB, Goteborgsvagen, Sweden) is expected to be reliable and reproducible.
Virtual implant planning before implant placement can be carried out using most CBCT softwares. A software tool can be used to plan future implant position and angulations using a virtual 3D implant replica before placing actual implant in a patient. Assessment of cortical and cancellous bone at implant site is proposed to be beneficial for predicting immediate and long-term stability of an implant. Some researchers suggest that cortical bone is more important than cancellous bone for implant stability. Conversely, few researchers highlighted the importance of cancellous bone for long-term stability. However, little evidence is available on relationship between corticocancellous ratio (CCR) around the virtual implant and success rate of the actual implant. In this study, we aimed to evaluate CCR circumferentially around the virtual implant and assess its relationship to immediate and long-term stability of dental implants placed in patients.
| Materials and Methods|| |
We conducted a longitudinal observational clinical study from January 2012 to August 2016. Institutional review board approved study protocol before commencing the study. Written informed consents were obtained to use patient's records for research purpose. Cone beam computed tomography (CBCT) records of patients aged 25--45 years without any gender discrimination were included in this study.
CBCT scans were obtained from patients in Department of Oral Medicine and Radiology before implant placement, at 0.1 × 0.1 × 0.1 mm 3 resolution, 120 kVp, and 5 mA as projection parameters. Only high-resolution scans were considered for inclusion in this study. Oral D software (CS 3D imaging, v3.3, NY, USA) with inbuilt rulers was used to calculate measurements. Each measured slice thickness was 1 mm.
Patients who were generally healthy with partially edentulous mandibular posterior areas had scanning records ≥6 months after tooth extraction, and adequate bone volume (minimum 13 mm height, 9 mm width, and 8 mm interdental space) were considered for inclusion in this study.
Patients who were smokers, pregnant, breastfeeding, taking medications such as bisphosphonates, osteoporotic changes in alveolar bone, whose CBCT scans showed healing sockets at implant planned sites, or had a systemic disease (contraindicating dental implant surgery) were excluded from this study.
Measurement of CCR
Three-dimensional virtual dental implant replicas were created at each future implant site with Oral D software. All dental replicas used in this study were of the same dimensions (5 mm diameter and 10 mm length) and were similar to implants actually placed (Nobel Biocare AB, Gothenburg, Sweden). Cortical and cancellous bone thickness around implant replica were measured circumferentially in CBCT images at four specific points a, b, c, and d (buccal, lingual, mesial, and distal, respectively) [Figure 1]. Mean thickness was recorded, and ratios were calculated. All measurements were made in millimeters (mm). Points a and b were measured in cross-sectional views [Figure 2] and points c and d were measured in longitudinal sections of the jaws [Figure 3]. Cases were divided into three groups according to CCR as follows: (a) low quality, CCR < 0.3 (b) medium quality, CCR 0.3--0.6, and (c) high quality, CCR > 0.6.
|Figure 1: Horizontal view in virtual implant planning with four points of measurement|
Click here to view
|Figure 2: The cross-sectional view of mandibular molar area to measure a and b points|
Click here to view
|Figure 3: Longitudinal view in virtual implant planning for measuring c and d points|
Click here to view
Assessment of primary and secondary stability
Implants were planned to be placed at the level of alveolar bone crest. Surgical sites were analyzed with virtual implant planning before placement. Virtual implant planning in CBCT was transferred to the lab to prepare a surgical stent. Implants of predetermined dimensions (5 mm diameter and 10 mm length) (Nobel Biocare AB, Gothenburg, Sweden) were placed in the next visit after oral prophylaxis. Stability was evaluated by RFA using an Osstell Mentor device (Integration Diagnostics AB, Goteborgsvagen, Sweden). Stability was checked immediately after implant installation, and long-term stability was checked 4 months and 2 years later. Implant crowns were gently removed, and a new abutment was fixed for checking implant stability quotient (ISQ) values after 2 years. After taking measurements, abutment was removed, and the prosthesis was re-inserted. ISQ values of primary and long-term implant stability were compared with mean CCR of bone around implants, which was assessed in virtual planning.
Measurements in CBCT were taken by one of the researchers (VA) who has 5 years of experience interpreting CBCT images. Similarly, another researcher (SKV) with experience in using the Osstell device calculated ISQ measurements. Intrarater reliability for both researchers was tested with Cohen's kappa test.
Sample size calculation
Based on the lowest correlation coefficient observed between CCR and stability, effect size was estimated to be 0.75299. With alpha error of 0.05 and power required of 95%, the number of patients required was n = 13. However, 100% power is achieved with number of patients n = 45.
ANOVA was executed to compare groups. Post-hoc Tukey test was conducted to do multiple comparisons between groups. P value of < 0.05 was considered significant. Pearson's correlation coefficient was employed to evaluate correlation between CCR and primary and long-term implant stability.
| Results|| |
Out of 140 initially-evaluated implant sites, three patients lost follow-up leading to missing data (five sites). Hence, the study included a total of 135 posterior mandibular implant sites records (45 in each group) from 94 patients that did not miss any follow-up time points. Some patients had bilateral edentulous areas that needed to be treated with implants. Recruitment continued until estimated sample size for each group was achieved. [Table 1] shows descriptive information of study population. Pearson's correlation coefficient values in [Table 2] show a significant positive correlation between CCR and immediate, 4-month, and 2-year implant stability. Scatter diagram in [Figure 4] shows ISQ values scattered from 0 to 1, suggesting a positive correlation between CCR and implant stability. Cohen's kappa test for intra-rater reliability shows k to be 0.64.
|Table 1: Description of the implant stability and CCR values found in the study|
Click here to view
|Table 2: Results of the Pearson's correlation test demonstrating the significant positive correlation among CCR and implant stability|
Click here to view
|Figure 4: Scattered diagram showing Pearson correlation analysis, indicating the relation between CCR and implant stability|
Click here to view
[Table 3] shows ANOVA results for intergroup comparisons. There is a significant difference in ISQ values among the three CCR groups at all three follow-up time points (P < 0.001). Furthermore, post-hoc Tukey HSD analysis for multiple comparisons between CCR groups showed a statistically significant inter-quality difference in ISQ values (P < 0.001) [Table 4]. Groups with high CCR values showed highest implant stability at all follow-up time points. However, 4-month and 2-year follow-ups in the high quality group did not show any significant difference in mean ISQ values.
| Discussion|| |
Several researchers tested a variety of different methods to assess primary and long-term implant stability of dental implants. Al-Jetaily and Al-Dosari (2011) compared efficacy of Periotest device with RFA by Osstell device for measuring implant stability, and found RFA to be more reliable. Although Osstell device is more reliable when implant is osseointegrated, Periotest is more reliable checking diminished implant stability. A clinical study carried out by Herrero-Climent et al. (2013) also confirms that Osstell device is reliable. Although some systematic reviews question reliability and reproducibility of Osstell device, we still used it due to lack of any other reliable, noninvasive instrument for checking osseointegration of dental implants.
Virtual implant planning before implant placement is a recent advancement in CBCT imaging. Clinicians can plan dimensions of an implant using virtual implant analogs and can also anticipate possible complications during and after implant surgery. Nickenig and Eitner (2007) assessed reliability of virtual implant planning using CBCT imaging system for placing a dental implant, and concluded that preoperative assessment improved procedure precision. Therefore, we used virtual implant planning to analyze CCR of bone around future implant sites.
Trabecular bone density and cortical bone thickness are crucial factors for dental implant stability., Song et al. (2009) assessed bone quality using CBCT images and compared ISQ values of the implant, and found a strong association between cortical bone thickness and implant stability. Similarly, Roze et al. (2009) evaluated bone structure with micro-CT and histological analysis and compared the results with implant ISQ values. Results showed that primary implant stability ISQ values mainly depend on cortical bone rather than trabecular bone. In addition, an animal study carried out by Isoda et al. (2012) showed a positive correlation between bone quality (estimated by CBCT) and primary implant stability. Although some micro-CT studies support the role of trabecular bone and its elastic modulus in primary stability, it is still a matter of debate. However, trabecular bone seems to uphold implant osseointegration.,
The current study shows a significant difference in primary stability with higher CCR, which is comparable to findings of previous studies.,,, Additionally, in this study, implants were also tested 4 months and 2 years after implant placement to assess effect of cortical and cancellous bone quantities on long-term stability. We observed a significant increase in ISQ values at each follow-up time point among three CCR groups. Study results also show a nonsignificant difference in mean ISQ values at 4 months (75.15) and 2 years (76.06) after implant placement in the high-quality CCR group. This indicates importance of cortical bone for immediate and long-term stability of an implant. Initial stability mean ISQ in the high-quality CCR group is almost equal to long-term stability (2 years later) mean ISQ in the low-quality group. This further ratifies significance of cortical bone. Based on the current study results, virtual implant planning might be safely applied before dental implant placing to prevent surgical related failures.
| Conclusion|| |
Our study results put forward a significant relationship between CCR and implant stability. Indeed, high CCR was accompanied with high stability values at all follow-up time points. This highlights the precedence of cortical over cancellous bone for immediate and long-term stability of a dental implant.
We would like to appreciate and acknowledge Dr. Raghavendra Reddy Nagate for his constant support in literature search.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Fueki K, Yoshida E, Igarashi Y. A systematic review of prosthetic restoration in patients with shortened dental arches. Jpn Dent Sci Rev 2011;47:167-74.
Hong DGK, Oh J. Recent advances in dental implants. Maxillofac Plast Reconstr Surg 2017;39:33.
Gaviria L, Salcido JP, Guda T, Ong JL. Current trends in dental implants. J Korean Assoc Oral Maxillofac Surg 2014;40:50-60.
Raikar S, Talukdar P, Kumari S, Panda SK, Oommen VM, Prasad A. Factors affecting the survival rate of dental implants: A retrospective study. J Int Soc Prev Community Dent 2017;7:351-5.
Kandasamy B, Kaur N, Tomar GK, Bharadwaj A, Manual L, Chauhan M. Long-term retrospective study based on implant success rate in patients with risk factor: 15-year follow-up. J Contemp Dent Pract 2018;19:90-3.
Sakka S, Coulthard P. Bone quality: A reality for the process of osseointegration. Implant Dent 2009;18:480-5.
Ramalingam S, Al-Hindi M, Al-Eid RA, Nooh N. Clinical evaluation of implant survival based on size and site of placement: A retrospective study of immediate implants at single rooted teeth sites. Saudi Dent J 2015;27:105-11.
Becker W, Becker BE, Alsuwyed A, Al-Mubarak S. Long-term evaluation of 282 implants in maxillary and mandibular molar positions: A prospective study. J Periodontol 1999;70:896-901.
Chan HL, Oh TJ, Fu JH, Benavides E, Avila-Ortiz G, Wang HL. Sinus augmentation via transcrestal approach: A comparison between the balloon and osteotome technique in a cadaver study. Clin Oral Implants Res 2013;24:985-90.
Song YD, Jun SH, Kwon JJ. Correlation between bone quality evaluated by cone-beam computerized tomography and implant primary stability. Int J Oral Maxillofac Implants 2009;24:59-64.
Sprecher CM, Gahlert M, Röhling S, Kniha H, Gueorguiev B, Milz S. Comparison of imaging methods used for dental implant osseous integration assessment. J Mater Sci Mater Med 2013;24:2195-200.
Meredith N. Assessment of implant stability as a prognostic determinant. Int J Prosthodont 1998;11:491-501.
Manzano-Moreno FJ, Herrera-Briones FJ, Bassam T, Vallecillo-Capilla MF, Reyes-Botella C. Factors affecting dental implant stability measured using the Ostell mentor device: A systematic review. Implant Dent 2015;24:565-77.
Mistry G, Shetty O, Shetty S, Singh RD. Measuring implant stability: A review of different methods. J Dent Implant 2014;4:165. [Full text]
Al-Jetaily S, Al-dosari AA. Assessment of Osstell ™
and Periotest® systems in measuring dental implant stability (in vitro
study). Saudi Dent J 2011;23:17-21.
Worthington P, Rubenstein J, Hatcher DC. The role of cone-beam computed tomography in the planning and placement of implants. J Am Dent Assoc 2010;141:19S-24S.
Nickenig H-J, Eitner S. Reliability of implant placement after virtual planning of implant positions using cone beam CT data and surgical (guide) templates. J Craniomaxillofac Surg 2007;35:207-11.
Gómez-de Diego R, Mang-de la Rosa M del R, Romero-Pérez MJ, Cutando-Soriano A, López-Valverde-Centeno A. Indications and contraindications of dental implants in medically compromised patients: Update. Med Oral Patol Oral Cir Bucal 2014;19:e483-9.
Herrero-Climent M, Santos-García R, Jaramillo-Santos R, Romero-Ruiz MM, Fernández-Palacin A, Lázaro-Calvo P, et al
. Assessment of Osstell ISQ's reliability for implant stability measurement: A cross-sectional clinical study. Med Oral Patol Oral Cir Bucal 2013;18:e877-82.
Kang S-R, Bok SC, Choi SC, Lee SS, Heo MS, Huh KH, et al
. The relationship between dental implant stability and trabecular bone structure using cone-beam computed tomography. J Periodontal Implant Sci 2016;46:116-27.
Rozé J, Babu S, Saffarzadeh A, Gayet-Delacroix M, Hoornaert A, Layrolle P. Correlating implant stability to bone structure. Clin Oral Implants Res 2009;20:1140-5.
Isoda K, Ayukawa Y, Tsukiyama Y, Sogo M, Matsushita Y, Koyano K. Relationship between the bone density estimated by cone-beam computed tomography and the primary stability of dental implants. Clin Oral Implants Res 2012;23:832-6.
Hsu JT, Huang HL, Fuh LJ, Li RW, Wu J, Tsai MT, et al
. Location of the mandibular canal and thickness of the occlusal cortical bone at dental implant sites in the lower second premolar and first molar. Comput Math Methods Med 2013;2013:608570. doi: 10.1155/2013/608570.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]