Evaluation of a metal artifact reduction algorithm and an adaptive image noise optimization filter in the estimation of peri-implant fenestration defects using cone beam computed tomography: an in-vitro study

Objective

The aim of this study is to assess the effects of metal artifact reduction (MAR) and adaptive image noise enhancer (AINO) in CBCT imaging on the detection accuracy of artificially created fenestration defects in proximity to titanium and zirconium implants in sheep jaw.

Methods

Six zirconium and 10 titanium implants were planted on mandibular jaws of three sheep, and artificial defects were created. All images were obtained with a standard voxel size (0.150 mm³) and with 4 scan modes: (1) without MAR/without AINO; (2) with MAR/without AINO; (3) without MAR/with AINO; and (4) with MAR/with AINO during CBCT scanning. A total of 60 CBCT scans were produced.

Results

For all types of implants, intra- and inter-observer kappa values were the highest for MAR filter. The scan mode of with MAR filter was found to have the highest area under the curve (AUC), whereas the scan mode of without both MAR and AINO filters was found to have the lowest AUC values with statistical significance (p?≤?0.05). Titanium implants were found to have higher AUC values than zirconium (p?≤?0.05).

Conclusion

Both MAR module and AINO filters enhance the accuracy of the detection of peri-implant fenestrations; however, the use of MAR filter solely can be recommended for detection of peri-implant fenestrations.

     

Body Image and Sexual Self-confidence in Patients with Chronic Urticaria

Sexuality and Disability - Body image and sexual life are often adversely affected in patients with chronic urticaria. The number of studies on this topic is limited. We aimed to determine the body...     

The effects of topical everolimus and sunitinib on corneal neovascularization

Purpose: To evaluate the effects of topical everolimus and sunitinib on corneal neovascularization (CNV).

Methods: CNV was induced by application of silver nitrate to the cornea for all groups. Rats were divided into four groups of 10 rats each, and two corneas were obtained from each rat. Group I received 1?mg/ml everolimus, Group II received 0.5?mg/ml sunitinib, Group IV received no treatment (control group) and Group IV received 1% Dimethylsulfoxide (DMSO). All treatments were administrated twice daily for 2 weeks. The right corneas were used for extracellular signal-regulated kinase 1/2 (ERK 1/2) protein analysis by western blot analysis and the left corneas were used for ERK 1/2 and vascular endothelial growth factor-receptor (VEGFR-2) gene expression analysis by quantitative real-time PCR.

Results: VEGFR-2 mRNA expression levels (ΔCt, median, min-max) were reduced in the everolimus 1.0 (0.25–1.81) and sunitinib 1.06 (0.24–2.68) treated groups compared with the control 4.74 (1.02–14.74) and DMSO groups 7.41 (0.72–13.10). The expression of ERK 1/2 protein and mRNA levels were reduced in everolimus group compared with the control group (p?<?0.05). These differences were not seen between the sunitinib and control groups.

Conclus?on: Topical administration of both everolimus and sunitinib reduced VEGFR-2 levels and inhibited CNV. In additon, everolimus reduced ERK 1/2 levels and seems to be more effective than sunitinib on CNV.     

Influence of voxel size and filter type on detecting vertical root fracture using cone-beam computed tomography

Vertical root fractures (VRFs) can start at any level of the root and progress longitudinally to the coronal attachment. This study aimed to investigate the effects of different exposure parameters used when obtaining CBCT scans in detecting simulated VRFs. Hence, 80 intact human mandibular single-rooted pre-molar teeth without root fractures were included in the study. No statistically significant difference was found between the filters in terms of VRF detection in the group with the roots with only root canal filling (Groups 1 and 5); however, 100 voxels were found to be more successful in terms of VRF detection than other voxel sizes. Results of this study suggest that using lower voxel sizes leads to an accurate diagnosis of vertical root fracture, in addition, our results revealed that using AR filters did not improve the diagnostic accuracy in detecting VRFs.