Validation of an established TW3 artificial intelligence bone age assessment system: a prospective, multicenter, confirmatory study.

Background: In 2020, our center established a Tanner-Whitehouse 3 (TW3) artificial intelligence (AI) system using a convolutional neural network (CNN), which was built upon 9059 radiographs. However, the system, upon which our study is based, lacked a gold standard for comparison and had not undergone thorough evaluation in different working environments.

Methods: To further verify the applicability of the AI system in clinical bone age assessment (BAA) and to enhance the accuracy and homogeneity of BAA, a prospective multi-center validation was conducted.

Radiomics Signatures of Carotid Plaque on Computed Tomography Angiography : An Approach to Identify Symptomatic Plaques.

Purpose: To develop and validate a combined model incorporating conventional clinical and imaging characteristics and radiomics signatures based on head and neck computed tomography angiography (CTA) to assess plaque vulnerability.

Methods: We retrospectively analyzed 167 patients with carotid atherosclerosis who underwent head and neck CTA and brain magnetic resonance imaging (MRI) within 1 month. Clinical risk factors and conventional plaque characteristics were evaluated, and radiomic features were extracted from the carotid plaques.

[Human umbilical cord mesenchymal stem cells may differentiate into Leydig cells through conditioned medium induction].

Objective: To explore the feasibility of inducing human umbilical cord mesenchymal stem cells (HuMSCs) to differentiate into Leydig cells through conditioned medium derived from Leydig cells.

Methods: HuMSCs and Leydig cells were obtained by tissue blocks culture attachment and enzymatic digestion respectively. HuMSCs were induced by conditioned medium of Leydig cells as an experiment group while those before induction were cultured as a control group.