Assessment of Instant Loss of Elbow Flexion in Children with Untreated Gartland IIA Humeral Supracondylar Fractures-A Simulation Study with Lateral Elbow Radiographs.

OBJECTIVE: The suitability of in situ cast fixation for treating Gartland IIA humeral supracondylar fractures has remained controversial due to concerns regarding loss of elbow flexion. This study aimed to assess the instant loss of elbow flexion after Gartland IIA humeral supracondylar fractures based on the relationship between the anterior marginal line of the humerus and capitellum in the lateral view. METHODS: This simulation study was conducted with normal radiographs using Adobe Photoshop 14.0, followed by verification using clinical cases. Standard lateral views of normal elbows of children were collected from January 2008 to February 2020. Adobe Photoshop was used to simulate Gartland IIA supracondylar fractures with different degrees of angulation in the sagittal plane. A formula was deduced to assess flexion loss, and this method was verified in three cases. The data were grouped by age, and the relationship between elbow flexion loss and age, as well as the angulation of the fracture, was analyzed using a one-way or multivariate ANOVA. RESULTS: There was a flexion loss of 19° (11-30°) when the anterior margin line of the humerus was tangential to the capitellum. This loss increased with age at injury (r = 0.731, P = 0.000). Moreover, the difference in angulation in the sagittal plane also influenced the extent of elbow flexion loss (r = -0.739, P = 0.000). The more horizontal the fracture line in the lateral view, the greater the loss of elbow flexion. CONCLUSION: Instant elbow flexion loss after Gartland IIA humeral supracondylar fractures increases with age at the time of injury and decreases with angulation in the sagittal plane. When the anterior margin of the humerus is tangential to the capitellum, there will be an average loss of 19° in elbow flexion. These findings provide a quantitative reference for clinical decision-making in the treatment of Gartland IIA supracondylar fractures.

An Experimental Strategy for Capturing the Margins of Prepared Single Teeth with an Intraoral Scanner: A Prospective Clinical Study on 30 Patients.

Purpose: To present an experimental strategy for successfully capturing the margins of prepared single teeth with an intraoral scanner (IOS). Methods: The protocol was as follows: (1) an intraoral impression was captured with an IOS, without taking care of the visibility of the margins; (2) a partial analog impression was taken by means of a 3D-printed custom tray filled with polyvinylsiloxane light, after the removal of a retraction cord; (3) the hollow portion of the analog impression, with the preparation margins clearly visible, was scanned extraorally with the same IOS; (4) the scan of the analog impression was imported into computer-assisted-design (CAD) software, where its normals were inverted; (5) the scan with inverted normals was registered on the first intraoral scan, and replaced it; (6) the technician designed the final restoration, which was fabricated and delivered for application. The study outcomes were: (1) the marginal adaptation of the final crown; (2) the quality of interproximal contacts; and (3) the quality of occlusal contacts. Results: Thirty patients (18 males, 12 females; mean age 51.3 ± 11.6 years) were selected for this study. All these patients were restored with a monolithic translucent zirconia crown, fabricated following the aforementioned protocol. The clinical precision and the marginal adaptation of the crowns were optimal, interproximal contact points were perfect, and the only necessary adaptations were occlusal, with some minor precontacts that had to be polished. Conclusions: The present protocol seems to be compatible with the fabrication of clinically precise zirconia crowns. Further studies are needed to confirm these results.

The extraction method of tooth preparation margin line based on S-Octree CNN.

The tooth preparation margin line has a significant impact on the marginal fitness for dental restoration. Among the previous methods, the extraction of margin line mainly relies on manual interaction, which is complicated and inefficient. Therefore, we propose a method to extract the margin line with the convolutional neural network based on sparse octree (S-Octree) structure. First, the dental preparations are rotated to augment the dataset. Second, the preparation models are treated as the sparse point cloud with labels through the spatial partition method of the S-Octree. Then, based on the feature line, the dental preparation point cloud is automatically divided into two regions by the convolutional neural network (CNN). Third, in order to obtain the margin line, we adopt some methods such as the dense condition random field (dense CRF), point cloud reconstruction, and back projection to the original dental preparation model. Finally, based on the measurement indicators of accuracy, sensitivity, and specificity, the average accuracy of the label predicted by the network model can reach 97.43%. The experimental results show that our method can automatically accomplish the extraction of the tooth preparation margin line.

Digital modeling technology for full dental crown tooth preparation.

A dental defect is one of the most common oral diseases, and it often requires a full crown restoration. In this clinical operation, the dentist must manually prepare the affected tooth for the full crown so that it has a convergence angle between 4° and 10°, no undercuts, and uniform and even shoulder widths and depths using a high speed diamond bur in the patient׳s mouth within one hour, which is a difficult task that requires visual-manual operation. The quality of the tooth preparation has an important effect on the success rate of the subsequent prosthodontic treatment. This study involved research into digital modeling technology for full dental crown tooth preparation. First, the margin line of the tooth preparation was designed using a semi-automatic interactive process. Second, the inserting direction was automatically computed. Then, the characteristic parameters and the constraints on the tooth preparation were defined for the model. Next, the shoulder and axial surface of the tooth preparation were formed using parametric modeling. Finally, the implicit surface of a radial basis function was used to construct the tooth preparation׳s occlusal surface. The experimental results verified that the method of digital modeling for full crown preparation proposed in this study can quickly and accurately implement personalized designs of various parameters, such as the shoulder width and the convergence angle; it provides a digital design tool for full crown preparation.