METHODS: Retrospective data from clinical worksheets given to participants during two implant courses held between the periods of 2013 to 2014 were evaluated. A total of 61 implants were considered based on the inclusion criteria. The effects of parameters such as implant diameter, implant length, age, gender, implant location and osteotomy protocol on ISQ values were analyzed.
RESULTS: Mean ISQ value for all implants was 67.21±9.13. Age of patients (P=0.016) and location of implants (P=0.041) had a significant linear relationship with the ISQ values. Within the age limit of the patients in this study, it was found that an increase in one year of patient's age results in 0.20 decrease in ISQ value (95% CI: -0.36, -0.04). However, placing an implant in the posterior maxilla may negatively affect the ISQ with a likely decrease in primary stability by 6.76 ISQ value (95% CI: -13.22, -0.30).
CONCLUSIONS: The results suggest that the mean ISQ achieved by the participants were comparable with the range reported for this particular type of implants. The patient's age and location of implants were elucidated as the determinant factors of primary implant stability.
MATERIALS AND METHODS: Twenty-one patients with implants were included in this study and implants were assessed by resonance frequency analysis (RFA). Bone levels of the implants were assessed by measuring mesial and distal bone levels from the periapical radiograph, and soft tissue was assessed from probing depth using a periodontal probe. Implants were assessed for stability and probing depth at pre-loading, at 3 months and 6 months post-loading. RFA and probing depth were statistically compared from different time points. Correlation of probing depth and marginal bone loss with implant stability was also determined.
RESULTS: The average change in implant stability quotient (ISQ) measurements from pre-loading to 6 months post-loading was found to be statistically significant (p <0.005). The average probing depth reduced from 1.767 mm at pre-loading to 1.671 mm at post-loading 3 months, and 1.600 mm at post-loading 6 months. At 6 months of function, radiographic examination yielded 0.786 mm mesial bone loss and 0.8 mm distal bone loss. It was found to be statistically significant (p <0.005) but within an acceptable range. No significant correlation was found between implant stability and bone loss; and implant stability and probing depth.
CONCLUSION: The study revealed an increasing trend in implant stability values with the time that indicates successful osseointegration. Increasing mean values for mesial and distal bone loss were also found.
CLINICAL SIGNIFICANCE: The success of dental implants is highly dependent on the quality of bone and implant-bone interface, i.e., osseointegration. The most important factors that influence the survival rate of an implant is initial stability. The present study found the changes in the peri-implant hard and soft tissues and implant stability. This article, while being a prospective study, may show the evidence of successful osseointegration by increasing trend in implant stability (RFA) values with time which can help to the clinician in the long-term management of implants.
METHODS: Twenty patients with two adjacent missing posterior teeth were recruited. Patients were assigned equally and randomly into two groups; Bicon(®) (6 or 8 mm) and Ankylos(®) (8 mm) implants. A two-stage surgical approach and single crowns were used for implant placement and loading. Outcomes included peri-implant clinical parameters, implant stability (Periotest values; PTVs) and peri-implant bone changes, which were assessed at baseline, 2, 6 and 12 months post-loading.
RESULTS: No implant loss was encountered up to 12 months post-loading. No significant difference in the clinical or radiographic parameters was observed except for PTVs (p < 0.05) that was lower in Ankylos(®) implants.
CONCLUSIONS: The use of short dental implants was associated with excellent 12 months clinical and radiographic outcomes. Ankylos(®) and Bicon(®) implants demonstrated similar peri-implant soft tissue and alveolar bone changes. However, Ankylos(®) implants demonstrated better implant stability at all evaluation intervals.
MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.