website: 86th General Session & Exhibition of the IADR

ABSTRACT: 2330  

Influence of Automatic Margin Detection on Fit of Zirconia Restorations

G. HERTLEIN, M. KRAEMER, and T. MEURER, 3M ESPE AG, Seefeld, Germany

Objectives:

The main benefits of CAD/CAM technologies for the manufacturing of Zirconia restorations are precision and the economic processing capabilities. Increasing the level of automation in the dental design software reduces the influence of the operator and decreases the overall design time. The aim of this study was to investigate the influence of a fully-automatic preparation margin detection algorithm in the design software on the marginal adaptation of CAD/CAM manufactured Lava™ Zirconia (LZ) copings.

Methods:

Restorations of 8 different clinical situations of single LZ crown copings were processed with the LAVA system (LS, 3M ESPE) based on digital data designed with a fully-automatic margin detection (AMD) software algorithm as well as with data from a semi-automatic margin detection (SMD). The SMD algorithm needed an interactive software supported masking and trimming of the data underneath the margin beforehand.

After manufacturing each coping was cemented on the scanned dies and subsequently embedded into epoxy (EpoFixKit, Stuers Inc.). Specimens were sectioned faciolingually and mesiodistally. A stereomicroscope and a special analyzing software (analysis, Soft Imaging -System GmbH) were used for the determination of marginal opening (MO) and absolute marginal opening (AMO) of the cross-sections for each crown (acc. to Holmes et.al,,J.Prosth.Dent.1989;62:405-408) resulting in 4 data points for each coping. The means and standard deviations of MO and AMO of all data points (n=32) obtained with AMD were compared to the data processed with SMD.

Results:

            MO (µm)         AMO (µm)

SMD   19+/-15           35+-25

AMD   15+/-15           26+/-25

There is no significant difference of the MO and AMO values obtained for the copings designed with AMD or SMD (Mann-Whitney Test, p>0.05).

 

Conclusions: With a mean MO mean value less than 20µm and  a mean AMO value less than 30µm the full automatic margin detection algorithm enables the manufacturing of dental restorations of very good marginal fit.

 

 

 

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