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Microleakage and Marginal Integrity of Ormocer/Methacrylate-Based Bulk-Fill Resin Restorations in MOD Cavities: SEM and Stereomicroscopic Evaluation.

Ayşe Aslı ŞenolBüşra Karabulut GençerBilge TarçınErkut KahramanoğluPınar Yılmaz Atalı
Published in: Polymers (2023)
This in vitro study aimed to compare the microleakage and marginal integrity of methacrylate/ormocer-based bulk-fill composite (BFC) restorations used in cervical marginal relocation with two different layering thicknesses in mesio-occlusal-distal (MOD) cavities exposed to thermo-mechanical loading. Standard MOD cavities were prepared in 60 mandibular molars and assigned into three groups: x-tra fil/AF + x-tra base/XB, Tetric N-Ceram Bulk Fill/TNB + Tetric N-Flow Bulk Fill/TFB, and Admira Fusion x-tra/AFX + Admira Fusion x-base/AFB. Each group was further divided into two subgroups (2 mm and 4 mm) based on the thickness of flowable BFCs ( n = 10). The specimens were subjected to thermo-mechanical loading (240,000 cycles) and immersed in 0.2% methylene blue. Following mesiodistal sectioning, the specimens were examined under stereomicroscope (×25) and scored (0-3) for microleakage. Marginal integrity was examined using a scanning electron microscope (SEM). Descriptive statistical methods and the chi-square test were used to evaluate the data ( p < 0.05). While there was no statistically significant difference in gingival cement microleakage in the XB and AFB specimens with a 4 mm thickness, microleakage was significantly increased in the TFB specimen ( p = 0.604, 0.481, 0.018 respectively). A significantly higher amount of score 0 coronal microleakage was detected in the AFX2 mm + AFB4 mm compared to the TNB2 mm + TFB4 mm ( p = 0.039). The SEM examination demonstrated better marginal integrity in groups with 2 mm thick flowable BFCs. Ormocer and methacrylate-based materials can be used in marginal relocation with thin layers.
Keyphrases
  • optical coherence tomography
  • deep learning
  • electronic health record
  • mass spectrometry
  • high resolution
  • cross sectional
  • machine learning
  • minimally invasive
  • artificial intelligence