3Shape (Denmark)

Compare the diagnostic accuracy of measuring gingival recession (GR) using a digital ruler on intraoral scans with clinical measurements using a UNC-15 probe. A prospective, observational, examiner-blinded, single-arm, cross-sectional, single-site study in adults aged 18+ with minimum of 20 teeth. All participants underwent an intraoral scan. Clinical GR was recorded on 6-sites (non-molar teeth) and 8-sites (molar teeth) by the principal examiner. Anonymised scans were assessed by the principal examiner twice (Ex1a, 1b) and two additional examiners (Ex2 and 3). 109 participants were assessed; all had at least one site of buccal GR. Ex1a on-scan measurements compared to clinical measurements showed 66.9% sensitivity and 92.5% specificity. There were considerable differences between central and proximal sites, central sites showed greater sensitivity 77.0% and specificity 81.4% compared to proximal sites 38.5% and 97.2% respectively. Diagnostic precision was robust, agreement for intra-examiner variability (Examiner-1a vs 1b) was 98.5% (95% CI 98.1%-98.8%). Inter-examiner variability was 78.9% (95% CI, 77.0%-80.6%) for Ex-1a-Ex-2 and 86.2% (95% CI, 84.8%-87.5%) for Ex-1a-Ex-3. Intraoral scan measurements are reproducible and can be utilised with accuracy. Measuring GR clinically is the current gold standard despite the limitations, intraoral scans can be utilised to overcome these limitations.

BackgroundDental caries is a common chronic disease in children. Digital tools such as intraoral scanners (IOSs) may offer an efficient, scalable alternative to conventional visual examination for dental caries detection. IOSs are handheld devices that generate 3-dimensional (3D) models of the teeth and surrounding structures. Recent advances incorporating fluorescence technology into scanner hardware offer the potential for supporting dental caries detection. However, the performance of digital caries detection methods using 3D models that include both color and fluorescence in children’s teeth remains unknown.ObjectiveThis study aimed to assess the diagnostic agreement between visual examination and on-screen assessment of 3D models generated by an IOS in color and supplemented with fluorescence for caries detection in primary teeth.MethodsChildren participating in a clinical trial (n=216, mean age 5.6, SD 0.4 y) underwent visual examination using the International Caries Detection and Assessment System (ICDAS) and intraoral scanning using the TRIOS 4 IOS. Four trained registered dental practitioners independently assessed each participant’s 3D models in color and then supplemented with fluorescence, using a previously validated ICDAS index modified for on-screen assessments of 3D models. All 3D models were assessed again after 4 weeks. The time taken for intraoral scanning and on-screen assessment was recorded. Multilevel logistic regression was used to estimate and compare the likelihood of detecting caries between methods, and Bland-Altman plots were used to visualize agreement. Analyses were performed at the initial (ICDAS ≥01), moderate (ICDAS ≥03), and extensive (ICDAS ≥05) dental caries thresholds. Intraclass correlation coefficient (ICC) estimated method agreement and examiner reliability.ResultsOf 219 children enrolled, 216 completed dental assessments. A total of 9470 visible primary tooth surfaces were included in the analysis. The average time taken for on-screen assessment of each 3D model (color with fluorescence) was 3.5 (SD 2.3) minutes. The likelihood of detecting caries using color assessment of 3D models was similar to visual examination at all disease thresholds: initial (odds ratio [OR] 1.1, 95% CI 1.0‐1.3), moderate (OR 0.9, 95% CI 0.7‐1.1), and extensive (OR 1.0, 95% CI 0.7‐1.3). When color assessments were supplemented with fluorescence, the likelihood of detecting caries was 30% higher at the initial threshold relative to visual examination (OR 1.3, 95% CI 1.1‐1.5) and similar at the moderate (OR 0.9, 95% CI 0.7‐1.1) and extensive thresholds (OR 0.9, 95% CI 0.7‐1.3). Bland-Altman plots showed a high level of agreement at both moderate and extensive thresholds. Agreement between methods was high (ICC 0.9, 95% CI 0.9‐1.0). Intra- and inter-examiner reliability using intraoral scans ranged from good to excellent (ICC 0.8‐1.0).ConclusionsOn-screen assessment of 3D models in color demonstrated the highest agreement with visual examination for caries detection across all disease thresholds.

Digital dentistry has made significant advancements, yet numerous challenges remain. This paper introduces the FDI 16 dataset, an extensive collection of tooth meshes and point clouds. Additionally, we present a novel approach: Variational FoldingNet (VF-Net), a fully probabilistic variational autoencoder for point clouds. Notably, prior latent variable models for point clouds lack a one-to-one correspondence between input and output points. Instead, they rely on optimizing Chamfer distances, a metric that lacks a normalized distributional counterpart, rendering it unsuitable for probabilistic modeling. We replace the explicit minimization of Chamfer distances with a suitable encoder, increasing computational efficiency while simplifying the probabilistic extension. This allows for straightforward application in various tasks, including mesh generation, shape completion, and representation learning. Empirically, we provide evidence of lower reconstruction error in dental reconstruction and interpolation, showcasing state-of-the-art performance in dental sample generation while identifying valuable latent representations

Objectives: To develop an automated fluorescence-based caries scoring system for an intraoral scanner and totest the performance of the system compared to state-of-the-art methods. Methods: Seventy-three permanent posterior teeth were scanned with a three-dimensional (3D) intraoral scanner prototype which emitted light at 415 nm. An overlay representing the fluorescence signal from the tissue was mapped onto 3D models of the teeth. Multiple examination sites (n = 139) on the occlusal surfaces were chosen, and their red and green fluorescence signal components were extracted. These components were used to calculate 4 mathematical functions upon which a caries scoring system for the scanner prototype could be based. Visual-tactile (International Caries Detection and Assessment System, ICDAS), radiographic (ICDAS), and histological assessments were conducted on the same examination sites. Results: Most index tests showed significant correlation with histology. The strongest correlation was observed for the visual-tactile examination (r_s = 0.80) followed by the scanner supported by the caries classification function that quantifies the overall fluorescence compared to sound surfaces (r_s = 0.78). Additionally, this function resulted in the highest intra-examiner reliability (κ = 0.964), and the highest sum of sensitivity (SE) and specificity (SP) (sum SE-SP: 1.60–1.84) at the 2 histological levels where the comparison with visual-tactile assessment was possible (κ = 0.886, sum SE-SP = 1.57–1.81) and at the 3 out of 4 histological levels where the comparison with radiographic assessment was possible (κ = 0.911, sum SE-SP = 1.37–1.78); the only exception was for the lesions in the outer third of dentin, where the radiographic assessment showed the highest sum SE-SP (1.78). Conclusion: A fluorescence-based caries scoring system was developed for the intraoral scanner showing promising performance compared to state-of-the-art caries detection methods. The intraoral scanner accompanied by an automated caries scoring system may improve objective caries detection and increase the efficiency and effectiveness of oral examinations. Furthermore, this device has the potential to support reliable monitoring of early caries lesions.

To assess the impact of head motion artefacts and an automated artefact-correction system on cone beam CT (CBCT) image quality and interpretability for simulated diagnostic tasks. A partially dentate human skull was mounted on a robot simulating four types of head movement (anteroposterior translation, nodding, lateral rotation, and tremor), at three distances (0.75, 1.5, and 3 mm) based on two movement patterns (skull returning/not returning to the initial position). Two diagnostic tasks were simulated: dental implant planning and detection of a periapical lesion. Three CBCT units were used to examine the skull during the movements and no-motion (control): Cranex 3Dx (CRA), Orthophos SL 3D (ORT), and X1 without (X1wo) and with (X1wi) an automated motion artefact-correction system. For each diagnostic task, 88 examinations were performed. Three observers, blinded to unit and movement, scored image quality: presence of stripe artefacts (present/absent), overall unsharpness (present/absent), and image interpretability (interpretable/non-interpretable). κ statistics assessed interobserver agreement, and descriptive statistics summarized the findings. Interobserver agreement for image interpretability was good (average κ = 0.68). Regarding dental implant planning, X1wi images were interpretable by all observers, while for the other units mainly the cases with tremor were non-interpretable. Regarding detection of a periapical lesion, besides tremor, most of the 3 mm movements based on the "not returning" pattern were also non-interpretable for CRA, ORT, and X1wo. For X1wi, two observers scored 1.5 mm tremor and one observer scored 3 mm tremor as non-interpretable. The automated motion artefact-correction system significantly enhanced CBCT image quality and interpretability.

People with HIV have been encouraged to take control of their health and the monitoring and treatment of their illnesses. Many claim the right to choose the time and manner of death.

I propose to begin with a very unusual bird (Fig. 1). This is no chicken. Nor is it a recent Biotech scandal. It is a Tyrolean allegory of the theme of self-recognition made some 200 years ago, which can be seen today in a folk-art museum in Innsbruck.