Design and optimization of a novel patient-specific subperiosteal implant additively manufactured in yttria-stabilized zirconia.

Objective: To design a patient-specific subperiosteal implant for a severely atrophic maxillary ridge using yttria-stabilized additively manufactured zirconia (3YSZ) and evaluate its material properties by applying topology optimization (TO) to replace bulk material with a lattice structure.

Materials: A contrast-based segmented skull model from anonymized computed tomography data of a patient was used for the initial anatomical design of the implant for the atrophic maxillary ridge. The implant underwent finite element analysis (FEA) and TO under different occlusal load-bearing conditions.

Clinical performance of additively manufactured subperiosteal implants: a systematic review.

Purpose: The aim of this study was to assess implant survival and complications rate of modern subperiosteal implants (CAD designed and additively manufactured).

Methods: A systematic review was conducted using three electronic databases; Medline (Pubmed), Cochrane library, and SCOPUS, following the PRISMA statement recommendations to answer the PICO question: "In patients with bone atrophy (P), do additively manufactured subperiosteal implants (I), compared to subperiosteal implants manufactured following traditional approaches (c), present satisfactory implant survival and complication rates (O)? The study was pre-registered in PROSPERO (CRD42023424211). Included articles quality was assessed using the "NIH quality assessment tools".

Machine learning based prediction of perioperative blood loss in orthognathic surgery.

The aim of this study was to evaluate, if and with what accuracy perioperative blood loss can be calculated by a machine learning algorithm prior to orthognathic surgery. The investigators implemented a random forest algorithm to predict perioperative blood loss. 1472 patients who underwent orthognathic surgery from 01/2006 to 06/2017 at our institution were screened and 950 patients were included and separated 80%/20% in a training set - utilized to generate the prediction model - and a testing set - utilized to estimate the accuracy of the model.

Improving comprehension of genetic counseling for hereditary breast and ovarian cancer clients with a visual tool.

Objective: Genetic counseling and testing can be offered to individuals who are at high risk of carrying a breast cancer (BRCA) gene mutation. However, the content of genetic counseling could be difficult to understand due to complex medical information. The aim of this study was to investigate if comprehension can be improved with a new genetic counseling tool (NGCT hereafter; a tool that combines complex medical information with pictures, diagrams and tables) as compared to conventional oral-only genetic counseling (CGC).

Gamma-glutamyltransferase as novel biomarker in patients with uterine leiomyosarcoma.

Gamma-glutamyltransferase (GGT) is an established marker for proliferative/apoptotic balance and has been associated with cancer risk and prognosis. The aim of this study was to evaluate the value of pre-treatment GGT serum levels as prognostic biomarker in patients with primary uterine leiomyosarcoma (ULMS). Data of women with ULMS were extracted from a multi-center database.