Apical Leakage Evaluation of Two Different Coated Carrier Systems for Root Canal Obturation Using a Dye Penetration Evaluation Method.

AIM: The carrier-based obturation is a reliable technique for sealing the endodontic space. The GuttaCore with a pink internal core of cross-linked gutta-percha, named GuttaCore Pink, has been recently introduced into the market. The aim of this in vitro study was to compare the quality of the apical seal of two-carrier-based system, Soft Core and the GuttaCore Pink, through the measurement of apical dye leakage. MATERIALS AND METHODS: Eighty-six extracted human teeth with single canals were used. Samples were shaped using ProTaper Universal rotary files up to a #30 apical size and randomly divided into four groups. Group SC (n = 40) was obturated with #30 Soft Core Obturators; Group GCP (n = 40) was obturated with #30 GuttaCore Pink obturators; Group CT+ (n = 3) and CT- (n = 3) left nonobturated used as positive and negative controls, respectively. The samples underwent a process of passive/active dye penetration and after a clearing procedure. The extent of the dye was measured under stereomicroscope. RESULTS: The Mann-Whitney U test showed a statistically significant difference (p <0.05) between Soft Core and GuttaCore Pink in terms of apical dye leakage, both considering the mean and the maximum infiltration value with a greater infiltration rate for Soft Core. CONCLUSION: In vitro GuttaCore Pink showed less apical dye leakage than Soft Core. CLINICAL SIGNIFICANCE: The apical leakage of carrier-based obturation materials, observed in both GuttaCore Pink and Soft Core, may be considered material-dependent.

TOF-PET Image Reconstruction With Multiple Timing Kernels Applied on Cherenkov Radiation in BGO.

Today Time-of-Flight (TOF), in PET scanners, assumes a single, well-defined timing resolution for all events. However, recent BGO-Cherenkov detectors, combining prompt Cherenkov emission and the typical BGO scintillation, can sort events into multiple timing kernels, best described by the Gaussian mixture models. The number of Cherenkov photons detected per event impacts directly the detector time resolution and signal rise time, which can later be used to improve the coincidence timing resolution. This work presents a simulation toolkit which applies multiple timing spreads on the coincident events and an image reconstruction that incorporates this information. A full cylindrical BGO-Cherenkov PET model was compared, in terms of contrast recovery and contrast-to-noise ratio, against an LYSO model with a time resolution of 213 ps. Two reconstruction approaches for the mixture kernels were tested: 1) mixture Gaussian and 2) decomposed simple Gaussian kernels. The decomposed model used the exact mixture component applied during the simulation. Images reconstructed using mixture kernels provided similar mean value and less noise than the decomposed. However, typically, more iterations were needed. Similarly, the LYSO model, with a single TOF kernel, converged faster than the BGO-Cherenkov with multiple kernels. The results indicate that the model complexity slows down convergence. However, due to the higher sensitivity, the contrast-to-noise ratio was 26.4% better for the BGO model.

Improving depth-of-interaction resolution in pixellated PET detectors using neural networks.

Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation position and therefore degrades the spatial resolution. A way to address this issue is depth-of-interaction (DOI) estimation. In this work we propose two machine learning-based algorithms, a dense and a convolutional neural network (NN), as well as a multiple linear regression (MLR)-based method to estimate DOI in depolished PET detector arrays with single-sided readout. The algorithms were tested on an 8× 8 array of 1.53× 1.53× 15 mm3 crystals and a 4× 4 array of 3.1× 3.1× 15 mm3 crystals, both made of Ce:LYSO scintillators and coupled to a 4× 4 array of 3× 3 mm3 silicon photomultipliers (SiPMs). Using the conventional linear DOI estimation method resulted in an average DOI resolution of 3.76 mm and 3.51 mm FWHM for the 8× 8 and the 4× 4 arrays, respectively. Application of MLR outperformed the conventional method with average DOI resolutions of 3.25 mm and 3.33 mm FWHM, respectively. Using the machine learning approaches further improved the DOI resolution, to an average DOI resolution of 2.99 mm and 3.14 mm FWHM, respectively, and additionally improved the uniformity of the DOI resolution in both arrays. Lastly, preliminary results obtained by using only a section of the crystal array for training showed that the NN-based methods could be used to reduce the number of calibration steps required for each detector array.

GuttaCore Pink, Thermafil and Warm Vertically compacted gutta-percha retreatment: Time required and quantitative evaluation by using ProTaper files.

The goal of non-surgical treatment is to obtain an access to the root canal system in order to remove the previous filling. We analized 45 human single-canal roots, mesial roots of mandibular molars and distal roots of maxillary molars without previous endodontic treatment, fractures, resorptive defects or open apices. We evaluated the time required to retreat root canals obturated by a new generation of GuttaCore, GuttaCore Pink®, compared to Thermafil® and Warm Vertically compacted gutta-percha, by using ProTaper® Retreatment and ProTaper® Universal. Moreover, a quantitative analysis of residual filling material in the canal after retreating and shaping was performed. The Kruskal-Wallis and Dunn's test were used to determine significant differences. Our data show that the GuttaCore Pink® can be removed from the root canal system in a lower amount of time compared to the Thermafil®. Concerning the amount of residual filling material, there are no significant differences between the three groups.