Jiangvedel7920

To assess the use of a three-dimensional (3D) printed, multilayer facial flap model for use in trainee education as an alternative method of teaching surgical techniques of facial reconstruction.

Cohort study.

A 3D printed facial flap simulator was designed from a computed tomography scan and manufactured out of silicone for low-cost, high-fidelity simulation. This simulator was tested by a group of Otolaryngology-Head and Neck Surgery trainees at a single institution. The simulator group was compared to a control group who completed an exercise on a traditional paper facial flap exercise. Both groups underwent didactic lectures prior to completing their respective exercises. Disodium Cromoglycate molecular weight Pre- and post-exercise Likert scale surveys measuring experience, understanding, effectiveness, and realism were completed by both groups. Central tendency, variability, and confidence intervals were measured to evaluate the outcomes.

Trainees completing the facial flap simulator reported a statistically significant (p < 0.05) improvement in overall expertise in facial flap procedures, design of facial flaps, and excision of standing cutaneous deformities. No statistically significant improvement was seen in the control group.

Trainees found the facial flap simulator to be an effective and useful training tool with a high level of realism in surgical education of facial reconstruction. Surgical simulators can serve as an adjunct to trainee education, especially during extraordinary times such as the novel coronavirus disease 2019 pandemic, which significantly impacted surgical training.

NA Laryngoscope, 131E2444-E2448, 2021.

NA Laryngoscope, 131E2444-E2448, 2021.

The aim of this study is to share our experience in the prenatal diagnosis and characteristics of double aortic arc and neonatal consequences.

We retrospectively analyzed 2153 fetal echocardiography reports between 2014 and 2019 years. Records of 14 fetuses with double aortic arc were examined. Prenatal and postnatal medical records, sonographic images, genetic reports, associated cardiac and extracardiac anomalies, and neonatal clinical results of affected fetuses were reviewed retrospectively.

DAA was isolated in 9 of 14 (64.2%) cases, while the other five cases had cardiac or extracardiac accompanying ultrasound findings. Three of cases (21.4%) were associated with other heart pathologies, including ventricular septal defect, double outlet right ventricle, and persistent left superior vena cava. In 10 cases (71.43%), the right aortic arch diameter was dominant. The left aortic arc was dominant in two cases and both arcs were symmetrical in the remaining two cases. 22q11 microdeletion was the only chromosomal abnormality and was detected in two of nine patients who accepted genetic analysis. Intrauterine fetal death occurred in two of the cases. After birth, in 58.3% (7/12) of the live born cases various degrees of symptoms. Surgical repair was performed with the division of the aorta to all symptomatic cases at different times according to severity of the complaints.

Since it can cause severe respiratory distress in the postnatal period and may accompany chromosomal anomalies, it is important to provide antenatal diagnosis of double aortic arc and adequate counseling to the family.

Since it can cause severe respiratory distress in the postnatal period and may accompany chromosomal anomalies, it is important to provide antenatal diagnosis of double aortic arc and adequate counseling to the family.

Basal cell carcinoma (BCC) is the most common type of skin cancer with incidence rates rising each year. Mohs micrographic surgery (MMS) is most often chosen as treatment for BCC on the face for which each frozen section has to be histologically analysed to ensure complete tumor removal. This causes a heavy burden on health economics.

To develop and evaluate a deep learning model for the automated detection of BCC-negative slides and classification of BCC in histopathology slides of MMS based on whole-slide image (WSI).

Two deep learning models were developed on the basis of 171 digitized H&E frozen slides from 70 different patients. The first model had a U-Net architecture and was used for the segmentation of BCC. A subsequent convolutional neural network used the segmentation to classify the whole slide as BCC or BCC-negative.

Quantitative evaluation over manually labelled ground truth data resulted in a Dice score of 0.66 for the segmentation of BCC and an area under the receiver operating characteristic curve (AUC) of 0.90 for the slide-level classification.

This study demonstrates that through WSIs deep learning models may be a feasible option to improve the clinical workflow and reduce costs in histological analysis of BCC in MMS.

This study demonstrates that through WSIs deep learning models may be a feasible option to improve the clinical workflow and reduce costs in histological analysis of BCC in MMS.

In the past two centuries, generations of dermatologists around the world have created an enormous number of publications. To our knowledge, no bibliometric analysis of these publications has been performed so far, nor have registered trials been analysed to anticipate future publication trends.

To determine the global distribution of national publication productivity, most published topics, institutions and funding sources contributing most to publications and to anticipate future trends based on registered clinical trials.

Following pre-assessment on PubMed, Embase, Web of Science and Scopus, the number of publications for 'dermatology' was determined for each of 195 countries, normalized per 1 Mio inhabitants and bibliometrically analysed. Dermatology-related trials registered at clinicaltrials.gov were specified by the top-10 diagnoses for the top-10 countries.

The search yielded 1071518 publications between 1832 and 2019 with the top-5 diagnoses being melanoma, basal cell carcinoma, psoriasis, prina and India appear to prioritize their scope towards other topics.

The top-10 countries including the USA, Canada, a few European and Asian countries contributed more than 3/4 of all publications. The USA hold the dominant leader position both in past publication productivity and currently registered trials. While most Western countries continue to focus their research on the top-10 topics, China and India appear to prioritize their scope towards other topics.