Development of a novel dental shade determination application

Revolutionizing Chinese medicine granule placebo with a machine learning four-color model

With the development of new Chinese medicines and the need for clinical double-blind experiments, the use of placebos in Chinese medicine is becoming increasingly important. However, due to the diverse colors and complex color gamut of these particles, existing simulation methods rely on manual comparison and color mixing, leading to high subjectivity and errors. This study addresses this issue by developing a prediction model to accurately simulate the colors of Chinese medicine granules. In this study, 52 commercially available herbal particles were collected. And more than 320 simulated granules were prepared using fillers and four pigments (lemon yellow, carmine, indigo and caramel colors). Their RGB colors were collected using visible light imaging. A granule color prediction model was constructed by machine learning. First, the best clustering model was obtained by optimising the k-value of the Kmeans model. Subsequently, multiple regression models, including Gradient Boosting Regression (GBR), Support Vector Regression (SVR), and Random Forest, were evaluated through network search and cross-validation methods. Among these models, the average R2 of the random forest model reached 0.9249, outperforming other models. The prediction model accurately simulated the color of Chinese medicine granules, with an average color difference (ΔE) of 2.7734 and a high RGB value cosine similarity of 0.9999, alongside a 0.9366 similarity in artificial color scoring. This study introduces an innovative approach for the rapid and accurate prediction of granule colors, facilitating the development of clinically applicable placebos in traditional Chinese medicine.

Digital Shade Matching in Dentistry: A Systematic Review

The pursuit of aesthetic excellence in dentistry, shaped by societal trends and digital advancements, highlights the critical role of precise shade matching in restorative procedures. Although conventional methods are prevalent, challenges such as shade guide variability and subjective interpretation necessitate a re-evaluation in the face of emerging non-proximity digital instruments. This systematic review employs PRISMA protocols and keyword-based search strategies spanning the Scopus®, PubMed.gov, and Web of ScienceTM databases, with the last updated search carried out in October 2023. The study aimed to synthesise literature that identified digital non-proximity recording instruments and associated colour spaces in dentistry and compare the clinical outcomes of digital systems with spectrophotometers and conventional visual methods. Utilising predefined criteria and resolving disagreements between two reviewers through Cohen's kappa calculator, the review assessed 85 articles, with 33 included in a PICO model for clinical comparisons. The results reveal that 42% of studies employed the CIELAB colour space. Despite the challenges in study quality, non-proximity digital instruments demonstrated more consistent clinical outcomes than visual methods, akin to spectrophotometers, emphasising their efficacy in controlled conditions. The review underscores the evolving landscape of dental shade matching, recognising technological advancements and advocating for methodological rigor in dental research.

Clinical Performance of Newly Developed Android Mobile Digital Application on Tooth Shade Reproduction: A Multicenter Randomized Controlled Clinical Trial

Aim

This study aimed to determine the clinical effectiveness of android mobile digital application shade matching on tooth shade reproduction.

Setting and Design

This was a double-blind randomized controlled clinical trial (REF/2021/03/042258).

Materials and Methods

Thirty participants were selected from the two dental centers. The participant who required full-coverage restorations in one of the central incisors with adjacent central incisor untouched was the main inclusion criteria. Three metal-ceramic or all-ceramic crowns were fabricated with reference shades from Vita Three-Dimensional (3D) Master shade guide, Vita Easyshade spectrophotometer, and mobile application for each participant. ΔE values between reference maxillary central incisor and metal-ceramic and all-ceramic crowns were measured for each participant. In addition, two operators and participants observed the clinical agreement between for each crown on a visual analog scale.

Statistical Analysis Used

ANOVA statistics and Turkey's post hoc test were used for ΔE value. Kappa statistics was used for clinical agreement.

Results

Mean ΔE value of fabricated metal-ceramic and all-ceramic crowns and reference maxillary central incisor of Vita 3D Master shade guide was significantly higher than Vita Easyshade spectrophotometer and mobile digital application (P = 0.004). However, ΔE values of Vita Easyshade and mobile digital application were contiguous. However, ΔE value of Vita 3D Master was lower than clinically acceptable value of intraoral color difference. Kappa value figured moderate agreement for Vita Easyshade and mobile digital application and slight to no agreement for Vita 3D Master.

Conclusion

Within the limitations of the study, the Android mobile digital application can turn up as a reliable method for shade selection.

A comparison of ceramic crown color difference between different shade selection methods: Visual, digital camera, and smartphone

STATEMENT OF PROBLEM

The light source stability of digital cameras and smartphones is important in shade matching in restorative and prosthetic dentistry to communicate objectively with the dental laboratory. Techniques that standardize the light source of such devices are lacking, and this limitation can lead to color mismatches, difficulties in color communication, and treatment documentation.

PURPOSE

The purpose of this clinical study was to compare the magnitude of color difference (ΔE) among 3 shade selection methods during the fabrication of ceramic crowns: visual shade selection with a shade guide, digital shade selection with a digital camera and cross-polarizing filter, and digital shade selection with a smartphone and a light-correcting device.

MATERIAL AND METHODS

Forty-five patients in need of ceramic crowns were enrolled, and shade selection was evaluated according to different protocols: visual shade selection (A-D shade guide and IPS Natural Die Material Shade Guide, sent to the dental laboratory technician via a laboratory prescription); digital shade selection with a digital camera (D7000; Nikon Corp) with an 85-mm lens and wireless close-up flash, with and without a cross-polarizing filter (Polar eyes); and digital shade selection with a smartphone and a light-correcting device (iPhone XS attached to Smile Lite MDP, with and without its cross-polarizing filter accessory). Information from the smartphone was imported to an app (IPS e.max Shade Navigation App; Ivoclar Vivadent AG) that converted the reading to a shade and level of translucency for the ceramic restoration. For all photographs, a gray reference card with known color values was positioned by the mandibular teeth and was used for white balancing of the digital photographs with a software program. All photographs were edited and sent to the dental laboratory: white-balanced with the shade guide; white-balanced with the substrate shade guide; black and white; saturated; and cross-polarized. Ceramic crowns were made with the same lithium disilicate material (IPS e.max CAD; Ivoclar Vivadent AG) and cemented with the same resin cement (RelyX Ultimate Clicker, A3 shade; 3M). The ΔE values between the crown and the adjacent tooth were determined. The data were analyzed by using a 1-way analysis of variance (ANOVA) and Tukey posthoc tests (α=.05).

RESULTS

The mean ΔE between a cemented ceramic crown and the adjacent tooth in the visual shade selection group was 5.32, significantly different than both digital camera (ΔE=2.75; P=.002) and smartphone (ΔE=2.34; P=.001), which were not different from each other (P=.857).

CONCLUSIONS

The digital shade selection with photographs acquired with both a digital camera and a smartphone with a light-correcting device showed a threshold within the acceptable values (ΔE<3.7), whereas the visual shade selection showed an average ΔE above the threshold for acceptable values (ΔE>3.7). The use of a gray reference card helped standardize the white balance from the digital images.