A novel computer-aided method for direct measurements and visualization of gingival margin changes.

AIM: To introduce and validate a computer-aided method for direct measurements and visualization of gingival margin (GM) changes. MATERIALS AND METHODS: The method consists of five main steps: digital model acquisition, superimposition, computer-aided GM detection, distance calculation between the GM curves, and visualization. The precision of the method was evaluated with repeatability and reproducibility analysis (n = 78 teeth). The method's repeatability was evaluated by repeating the algorithm on the same digital models by two operators. The reproducibility was evaluated by repeating the algorithm on two consecutive digital models obtained with a scan-rescan process at the same time point on the same patient. For demonstration, the proposed method for direct measurements of GM changes was performed on patients who had undergone root coverage procedures and treatment of periodontal disease. RESULTS: Excellent repeatability was found for both intra- and inter-operator variability, that is, 0.00 mm, regarding computer-aided GM detection. The reproducibility of computer-aided GM detection evaluated on scan-rescan models was 0.10 mm. CONCLUSIONS: The presented method enables the evaluation of GM changes in a simple, precise, and comprehensive manner through non-invasive acquisition and superimposition of digital models.

Gingival shape analysis using surface curvature estimation of the intraoral scans.

BACKGROUND: Despite many advances in dentistry, no objective and quantitative method is available to evaluate gingival shape. The surface curvature of the optical scans represents an unexploited possibility. The present study aimed to test surface curvature estimation of intraoral scans for objective evaluation of gingival shape. METHODS: The method consists of four main steps, i.e., optical scanning, surface curvature estimation, region of interest (ROI) definition, and gingival shape analysis. Six different curvature measures and three different diameters were tested for surface curvature estimation on central (n = 78) and interdental ROI (n = 88) of patients with advanced periodontitis to quantify gingiva with a novel gingival shape parameter (GS). The reproducibility was evaluated by repeating the method on two consecutive intraoral scans obtained with a scan-rescan process of the same patient at the same time point (n = 8). RESULTS: Minimum and mean curvature measures computed at 2 mm diameter seem optimal GS to quantify shape at central and interdental ROI, respectively. The mean (and standard deviation) of the GS was 0.33 ± 0.07 and 0.19 ± 0.09 for central ROI using minimum, and interdental ROI using mean curvature measure, respectively, computed at a diameter of 2 mm. The method's reproducibility evaluated on scan-rescan models for the above-mentioned ROI and curvature measures was 0.02 and 0.01, respectively. CONCLUSIONS: Surface curvature estimation of the intraoral optical scans presents a precise and highly reproducible method for the objective gingival shape quantification enabling the detection of subtle changes. A careful selection of parameters for surface curvature estimation and curvature measures is required.

Assessment of reference areas for superimposition of serial 3D models of patients with advanced periodontitis for volumetric soft tissue evaluation.

AIM: This study aimed to determine the optimal reference area for superimposition of serial 3D dental models of patients with advanced periodontitis. MATERIALS AND METHODS: Ten pre- and post-periodontal treatment 3D models (median time lapse: 13.1 months) of patients with advanced periodontitis were acquired by intraoral scanning. Superimposition was performed with the iterative closest point algorithm using four reference areas: (A) all stable teeth, (B) all teeth, (C) third palatal rugae and (D) the whole model. The superimposition accuracy was evaluated at two stable evaluation regions using the mean absolute distance and evaluated with two-way ANOVA and post-hoc multivariate model. The intra- and inter-operator reproducibility was calculated by intraclass correlation coefficient (ICC). RESULTS: Superimposition accuracy evaluated at stable tooth evaluation region were 71 ± 29 µm, 73 ± 21 µm, 127 ± 52 µm and 113 ± 53 µm for areas A, B, C and D, respectively. All reference areas showed similarly high ICC values >0.990, except for reference area C showing ICC of 0.821 (intra-operator) and 0.767 (inter-operator) for tooth evaluation area. CONCLUSIONS: Area A and B provide the highest accuracy for superimposition of serial 3D dental models acquired by intraoral scanning of patients with advanced periodontitis.

The precision of gingival recession measurements is increased by an automated curvature analysis method.

BACKGROUND: The extent of gingival recession represents one of the most important measures determining outcome of periodontal plastic surgery. The accurate measurements are, thus, critical for optimal treatment planning and outcome evaluation. Present study aimed to introduce automated curvature-based digital gingival recession measurements, evaluate the agreement and reliability of manual measurements, and identify sources of manual variability. METHODS: Measurement of gingival recessions was performed manually by three examiners and automatically using curvature analysis on representative cross-sections (n = 60). Cemento-enamel junction (CEJ) and gingival margin (GM) measurement points selection was the only variable. Agreement and reliability of measurements were analysed using intra- and inter-examiner correlations and Bland-Altman plots. Measurement point selection variability was evaluated with manual point distance deviation from an automatic point. The effect of curvature on manual point selection was evaluated with scatter plots. RESULTS: Bland-Altman plots revealed a high variability of examiner's recession measurements indicated by high 95% limits of agreement range of approximately 1 mm and several outliers beyond the limits of agreement. CEJ point selection was the main source of examiner's variability due to smaller curvature values than GM, i.e., median values of - 0.98 mm- 1 and - 4.39 mm- 1, respectively, indicating straighter profile for CEJ point. Scatter plots revealed inverse relationship between curvature and examiner deviation for CEJ point, indicating a threshold curvature value around 1 mm- 1. CONCLUSIONS: Automated curvature-based approach increases the precision of recession measurements by reproducible measurement point selection. Proposed approach allows evaluation of teeth with indistinguishable CEJ that could be not be included in the previous studies.

3D computer-aided treatment planning in periodontology: A novel approach for evaluation and visualization of soft tissue thickness.

OBJECTIVE: Current approaches for soft tissue thickness evaluation and visualization still represent a challenge for full extent evaluation and visualization. The aim of this clinical technique article is to introduce a novel approach for comprehensive visualization and precise evaluation of oral soft tissue thickness utilizing a fusion of optical 3D and cone-beam computed tomography (CBCT) images. CLINICAL CONSIDERATIONS: 3D models of the maxilla were obtained by CBCT imaging and intraoral scanning. The CBCT images were reconstructed to standard tessellation language (STL) file format models by segmentation of teeth and bone using implants planning software. 3D soft tissues and teeth models were obtained by intraoral scanning and were exported in STL file format as well. 3D multimodal models were then superimposed using best-fit matching on teeth. Soft tissue thickness was then visualized and evaluated with a 3D color-coded thickness map of gingival and palatal areas created by surface comparison of both 3D models. Additionally, threshold color-coding was used to increase comprehensibility. Palatal areas were further visualized and evaluated for the optimal donor site. CONCLUSIONS: A novel approach for 3D evaluation and visualization of masticatory mucosa thickness presents all available 3D data in a comprehensible, "clinician-friendly" manner, using threshold regions and clinically relevant views. CLINICAL SIGNIFICANCE: Proposed approach could provide comprehensive presurgical treatment planning in periodontal plastic surgery and implantology without additional invasive procedures for the patient, resulting in more predictable treatment, improved outcomes, and reduced risk for complications.

Retentive design of a small surgical guide for implant surgery: An in-vitro study.

OBJECTIVES: Instability of the surgical guide is an overlooked factor that can result in a difference between the planned and the actual positions of an implant. Our aim was to compare the stability of the retentive surgical guide (RSG) with a conventional surgical guide (CSG) in an in-vitro experiment. METHODS: A platform to evaluate the stability of the surgical guide was designed using 3D-modelling software (Meshmixer 3.5, Autodesk). Imaging data from 15 patients with a single missing tooth were used to plan the virtual implant. Two surgical guides were designed (Blue Sky Plan 4.8, Blue Sky Bio) and 3D printed (Form2, Dental SG resin, Formlabs) for each case: the CSG with the default, predetermined software settings, and the RSG, designed on a dental model with a 0.1-mm undercut and altered production parameters (reduced guide-to-teeth offset of 0.07 mm, reduced guide thickness of 2.3 mm and a retentive clasp in a marginal area). The dental models were reproducibly secured on the testing platform using a digital force gauge, and the surgical guides were positioned. An increasing force of 0.1 N, 1 N, 2.5 N, and 5 N was sequentially applied from the buccal and the oral directions to the surgical guide via a drill handle. For each force, either the magnitude of the guide's displacement was captured with an intra-oral scanner (CEREC Omnicam AC, Dentsply Sirona; software version: SW 4.5.2) or the dislodgement of the guide was recorded. Scans were imported for analysis (GOM Inspect 2018, GOM GmbH), and library files of the surgical guides and implants were superimposed as a joined complex. The deviation of the implant's position was calculated from the displacement of the guide's position RESULTS: Three-way repeated measures using ANOVA revealed a more significant guide displacement and virtually projected implant deviation in the CSG group than the RSG group and with increasing force in all the deviation parameters. Both groups showed greater resistance to the displacement with the force applied from the oral direction than the buccal direction. The application of the force in the buccal direction resulted in guide dislodgements of 13% and 0% for the CSG and RSG, respectively. In the oral direction, the dislodgement rates were 33% and 7% for the CSG and RSG, respectively. CONCLUSIONS: Within the limitations of this study, the retentive design increased the stability of the surgical guide and, consequently, the accuracy of the virtually projected implants in comparison to the conventional surgical guide designed using the default settings. Clinical trials are needed to confirm its advantages in clinical use. CLINICAL SIGNIFICANCE: With a simple modification to the design, the surgical guide retention provided greater stability, with smaller deviations under loading; this resulted in improved implant precision parameters without requiring additional materials or software. Further studies are needed to assess the clinical feasibility of this surgical guide with improved retention and function.

Methods and parameters for digital evaluation of gingival recession: A critical review.

OBJECTIVES: The aim of the present review was to find, compare, and critically discuss digital methods for quantitative evaluation of gingival recessions dimensions. DATA: Collection of articles and classification related to digital evaluation of gingival recessions. SOURCES: A search of PubMed, Web of Science, Scopus, and reference lists of articles was conducted up to April 2021. STUDY SELECTION: Twenty-two articles used digital evaluation of gingival recessions dimensions. The methods in the included articles were extracted, compared, and categorized. RESULTS: Digital measurements were performed on 2D intraoral photographs, 3D models, or cross-sections obtained from 3D models. Baseline measurement were performed for diagnostic and treatment planning and categorised into distance and area measurements. Follow-up evaluation of treatment was based either on repeating the "baseline" measurements and calculating differences or measuring differences directly on composite images, composed from two superimposed images obtained at two time-points. Direct measurements were categorised into distance, area, and volume measurements. CONCLUSIONS: Digital evaluation predominantly means just digitalization of the established evaluation methods; therefore, increasing measurements accuracy and maintaining comparability with past studies. At present, a large variability of digital evaluation workflow among the included studies renders the comparison among different studies difficult if not impossible. The potential of digital evaluation seems not to have been fully exploited as only a few novel measurements and parameters introduced, i.e., volumetric evaluation of soft tissue dynamics. For reproducible and comparable studies in the future, the research should be aimed at evaluation, optimization and standardization of all phases of the digital evaluation. CLINICAL SIGNIFICANCE: Digital evaluation, based on 3D image superimposition is a promising approach as it increases measurements accuracy, maintains compatibility with past studies and simultaneously introduces novel evaluation possibilities.

Evaluation of gingival recessions with conventional versus digital methods.

OBJECTIVES: The present study aimed to compare the conventional clinical and a digital method for evaluating differences in gingival recession (ΔREC) in patients with advanced periodontitis treated with the non-surgical treatment protocol. METHODS: Agreement between the methods was evaluated on a sample of ten patients with periodontitis (stage III/IV, grade B/C) with acquired clinical measurements and digital models from baseline (T0) and 12-months after non-surgical treatment of periodontitis (T1). The evaluation was performed on maxillary teeth from right to left second premolar resulting in overall 99 teeth. Clinical evaluation was performed by subtracting the distance measurements between gingival margin and cemento-enamel junction, obtained at T0 and T1 by a calibrated examiner (intra-examiner agreement >90%). The digital evaluation was performed directly by measuring the distance between the gingival margins on superimposed T0 and T1 digital models. Using Bland-Altman and statistical analysis, all six measurements sites around each included tooth (n=594) acquired with both methods were compared. RESULTS: Median ΔREC (5th and 95th percentile) acquired with a conventional clinical and digital method was 0.0mm (-2.0 - 1.0) and -0.4mm (-1.6 - 0.8), respectively (p<0.0001). The complete agreement between rounded digital and clinical ΔREC values was only 38%, revealing high disagreement also confirmed by Bland-Altman analysis with 95% limits of agreement ranging from -2.6 to 1.8mm. Absolute differences between the methods higher than 0.5 and 1 mm, was found in 61% and 38% of measurement sites, respectively. CONCLUSIONS: The conventional clinical method for ΔREC evaluation exhibits lower sensitivity and accuracy than the digital method. CLINICAL SIGNIFICANCE: The quality of both clinical and research data in periodontology and implantology can be considerably improved by the digital method while still preserving the compatibility with the conventional clinical method.

A Critical Review of Methods for Quantitative Evaluation of Root Canal Transportation.

INTRODUCTION: A comparison between root canal transportation studies is nearly impossible because of nonstandardized transportation evaluation methods. The aim of the present review was to search, compare, and critically discuss transportation evaluation methods. METHODS: A search of PubMed, Web of Science, Scopus, ScienceDirect, and reference lists of articles was conducted up to March 2020 using appropriate key words to identify transportation evaluation methods. The methods in the included articles were extracted, compared, and categorized. RESULTS: Seventy-four articles using original methods were selected. All studies share 3 main steps: image acquisition, image measurements, and calculation of parameters. Images were acquired by photography, radiography, and computed tomographic imaging. Two types of measurements were used: the amount of removed material and the canal center point distance. The parameters were calculated and reported as distance or ratio. Relationships between the different transportation parameters were found and confirmed with mathematical simulation. CONCLUSIONS: Although methods were proposed as being novel, similarities between them were found, enabling the classification of the methods and identifying correlations. The canal center point distance is the most suitable for the description of canal transportation because it is comprehensible and it relates to the mathematical concept of translation. Removed material-based measurements are double the value of the canal center point distance. Ratio parameters are not suitable for reporting transportation.

Bone and soft tissue changes associated with a removable partial denture. A novel method with a fusion of CBCT and optical 3D images.

BACKGROUND: The purpose of this study was to propose a novel method for 3D evaluation of bone and mucosal changes in removable partial denture (RPD) foundation area using a fusion of cone beam computed tomography (CBCT) and optical 3D images. METHOD: Two CBCT scans and three impressions, taken at insertion and after ten months of wearing the RPD, were acquired from five patients. 3D models of bone and surface were created from CBCT images and gypsum casts, respectively, spatially aligned and saved in Standard Tessellation Language file format. Visual and numerical analysis of differences between the models allows evaluation of surface, mucosal and bone changes in regions of interest (ROI) defined as narrow ROI (nROI), denture foundation area ROI (dROI) and wide ROI (wROI). Site-specific analysis was performed in mesiodistal and buccolingual direction. RESULTS: Visual evaluation of 3D color-coded deviation maps showed irregular distribution of bone and surface changes. The differences between mandibles and also between left and right sides were found. Mean volume of bone change in dROI was -135.86 (range = -456.18 to 21.20) mm3. The average bone change thickness in dROI was -0.26 (range = -0.96 to 0.07) mm. The mean volume changes in nROI were -38.31 (range = -118.26 to 45.87) mm3, -51.96 (range = -182.54 to 5.6) mm3 and 13.66 (range = -80.62 to 79.46) mm3 for surface, bone and mucosa, respectively. CONCLUSIONS: The proposed method facilitates separate visual and numerical evaluation of surface, mucosa and bone changes. It opens possibilities for a better understanding of denture-supporting tissues remodeling, objective evaluation and comparison of different treatment options.