The impact of implant-related characteristics on dental implant blooming: An in vitro study

The effect of a blooming artifact reduction filter on the dimensional analysis of implants

OBJECTIVE

To assess the effect of a blooming artifact reduction (BAR) filter on cone beam computed tomography (CBCT) images in the dimensional analysis of dental implants.

STUDY DESIGN

Six types of implants (n = 5 for each type) composed of titanium (3 types), titanium-zirconia alloy, zirconium oxide, and titanium-aluminum-vanadium alloy, and made with 2 manufacturing processes (milled and printed) were individually installed in a bovine rib block according to the manufacturer's protocol. CBCT images were acquired with i-CAT and Carestream scanners, randomized, and analyzed without and with the e-Vol DX BAR filter (60 images for each scanner). Implant length, diameter, and thread-to-thread distance were measured by two radiologists, with a stereomicroscopic image of each implant as the reference standard for calculation of distortion in measurements. Repeated measures ANOVA with Bonferroni corrections and intraclass correlation coefficients (ICC) were applied (α = 0.05).

RESULTS

The BAR filter significantly reduced distortion in various parameters for specific implants, aligning closely with stereomicroscopic measurements. Titanium and printed implants showed reduced dimensional distortion regardless of BAR filter use. Carestream measurements presented smaller dimensional differences than i-CAT for most implants and parameters, especially without BAR (P < .05). Interexaminer reliability was good to excellent, with ICC ranging from 0.80 to 0.95.

CONCLUSIONS

The BAR filter can enhance implant dimensional analysis, although variations based on implant material and manufacturing process were observed.

Influence of CBCT filters and contrast adjustments on peri-implant buccal bone thickness measurement and blooming expression

OBJECTIVES

To assess whether filter and contrast adjustments can improve the accuracy of CBCT in measuring the buccal bone thickness (BBT) adjacent to dental implants by reducing blooming artifacts.

MATERIALS AND METHODS

Homogeneous bone blocks with peri-implant BBT of 0.3 mm, 0.5 mm, and 1 mm were scanned using the Orthophos SL system. Three dentists measured the BBT in 234 CBCT scans under different settings of contrast adjustments and 'Sharpen' filter activation. Additionally, implant diameter measurements were taken to assess blooming artifact expression. The differences between tomographic and actual measurements of BBT and implant diameter [(CBCT - actual) * 100 / actual] were subjected to Mixed ANOVA (α = 0.05).

RESULTS

The group with the thinnest BBT (0.3 mm) had the greatest difference between tomographic and actual measurements (79.9% ± 29.0%). Conversely, the 0.5 mm (36.1% ± 38.4%) and 1 mm (29.4% ± 12.3%) groups exhibited lower differences (p < 0.05). 'Sharpen' filter activation reduced blooming expression since it resulted in a lower difference for implant diameter (p < 0.05), but it did not influence BBT measurements (p = 0.673). Contrast settings had no impact on BBT (p = 0.054) or implant diameter measurements (p = 0.079).

CONCLUSION

Although filter activation reduced blooming artifacts, neither filter nor contrast adjustments improved the accuracy of CBCT in measuring peri-implant BBT; actual BBT influenced this task.

CLINICAL RELEVANCE

When assessing the peri-implant buccal bone plate in the CBCT system studied, dental surgeons may find it beneficial to adjust contrast and apply filters according to their preferences, since such adjustments were found to have no adverse effects on the diagnostic accuracy of this task. The use of the 'Sharpen' filter may lead to improved representation of implant dimensions.

Volumetric analysis of artifacts from fiducial markers under cone beam computed tomography

Abstract Background/purpose

Computer aided implant surgery has been widely adopted in modern implant dentistry. However, absence of reliable anatomic landmarks for superimposing digital data sets for patients with terminal dentition or complete edentulism remained challenging. Utilization of additional fiducial markers intraorally as the reference points for the improvement of accuracy became crucial in implant digital workflow. Nevertheless, the choice of the material for fiducial markers should present the least radiographic artifacts under cone beam computed tomography (CBCT) for better accuracy. The aim of this in vitro study was to investigate the volume of radiographic artifacts generated through different materials under the image of CBCT.

Materials and methods

Fifteen dental materials were selected and configured into cubic shape. All the materials were scanned initially with the laboratory scanner as the control groups. The samples were scanned by CBCT machine as test groups and the volume of artifact generated under CBCT images were compared and analyzed using 3D modeling software.

Results

Eleven out of fifteen materials could be recognized under CBCT images. Volumetric analysis reported that statistically significant differences among the materials could be noted, and the flowable composite resin presented the least volumetric difference. Lithium disilicate glass-ceramic, flowable composite resin, and gutta-percha presented the least deformation and maintained their cubic shapes.

Conclusion

The results of the present study may imply that flowable composite resin compared to all ceramic materials, amalgam and gutta-percha may be a preferable choice when utilized as fiducial markers under CBCT images.

Deep learning-based segmentation of dental implants on cone-beam computed tomography images: A validation study

OBJECTIVES

To train and validate a cloud-based convolutional neural network (CNN) model for automated segmentation (AS) of dental implant and attached prosthetic crown on cone-beam computed tomography (CBCT) images.

METHODS

A total dataset of 280 maxillomandibular jawbone CBCT scans was acquired from patients who underwent implant placement with or without coronal restoration. The dataset was randomly divided into three subsets: training set (n = 225), validation set (n = 25) and testing set (n = 30). A CNN model was developed and trained using expert-based semi-automated segmentation (SS) of the implant and attached prosthetic crown as the ground truth. The performance of AS was assessed by comparing with SS and manually corrected automated segmentation referred to as refined-automated segmentation (R-AS). Evaluation metrics included timing, voxel-wise comparison based on confusion matrix and 3D surface differences.

RESULTS

The average time required for AS was 60 times faster (<30 s) than the SS approach. The CNN model was highly effective in segmenting dental implants both with and without coronal restoration, achieving a high dice similarity coefficient score of 0.92±0.02 and 0.91±0.03, respectively. Moreover, the root mean square deviation values were also found to be low (implant only: 0.08±0.09 mm, implant+restoration: 0.11±0.07 mm) when compared with R-AS, implying high AI segmentation accuracy.

CONCLUSIONS

The proposed cloud-based deep learning tool demonstrated high performance and time-efficient segmentation of implants on CBCT images.

CLINICAL SIGNIFICANCE

AI-based segmentation of implants and prosthetic crowns can minimize the negative impact of artifacts and enhance the generalizability of creating dental virtual models. Furthermore, incorporating the suggested tool into existing CNN models specialized for segmenting anatomical structures can improve pre-surgical planning for implants and post-operative assessment of peri‑implant bone levels.

Influence of metal artefact reduction on the diagnosis of contact between implant and mandibular canal in cone beam computed tomography: An ex-vivo study

OBJECTIVE

To evaluate the influence of metal artefact reduction (MAR) in the diagnosis of dental implant contact with the mandibular canal (MC) using cone beam computed tomography (CBCT).

METHODS

Dental implants were installed with surgical guides in the posterior hemiarches of 10 dry human mandibles: 0.5 mm above to the MC cortex (G1/n = 8) and 0.5 mm inside the MC (G2/n = 10). The experimental set-up was scanned with two CBCT equipment using 85 kV and 90 kV, MAR ON or OFF, and different tube currents (4 mA, 8 mA and 10 mA). Two dentomaxillofacial radiologists (DMFRs) and two dentists (DDS) scored the relation between the dental implant and MC. Descriptive statistics were used to observe the absolute frequency of scores. Sensitivity, specificity and accuracy were calculated considering the known relation between the dental implant and the MC interior. McNemar's test (α = .05) was applied to compare the diagnostic efficacy of MAR ON versus MAR OFF.

RESULTS

Overall specificity was higher than sensitivity for both DDS and DMFR (97% vs. 50% and 92.0% vs. 78.0% respectively). There was a significant effect of MAR (p = .031) for DMFR in the case of contact between the dental implant with the MC interior, in which sensitivity decreased with MAR activation from 90% to 40%. DMFR observers showed a better diagnostic performance compared with the DDS observers (accuracy of 84.0% and 71.0%, respectively).

CONCLUSIONS

Due to the limited efficacy of MAR, it should not be used when conducting CBCT scans for the evaluation of contact between the implant and the mandibular canal.