Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels.

Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model.

Materials And Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance.

Diagnostic performance of the 2021 Korean thyroid imaging reporting and data system in pediatric thyroid nodules.

Objectives: To evaluate the diagnostic performance of 2021 K-TIRADS biopsy criteria for detecting malignant thyroid nodules in a pediatric population, making comparisons with 2016 K-TIRADS.

Methods: This retrospective study included pediatric patients with histopathologically confirmed diagnoses. The diagnostic performance of 2021 K-TIRADS was compared with that of 2016 K-TIRADS.

Diagnostic Performance of Five Adult-based US Risk Stratification Systems in Pediatric Thyroid Nodules.

Background The validation of adult-based US risk stratification systems (RSSs) in the discrimination of malignant thyroid nodules in a pediatric population remains lacking. Purpose To estimate and compare the diagnostic performance of pediatric US RSSs based on five adult-based RSSs in the discrimination of malignant thyroid nodules in a pediatric sample. Materials and methods Pediatric patients (age ≤18 years) with histopathologically confirmed US-detected thyroid nodules at a tertiary referral hospital between January 2000 and April 2020 were analyzed retrospectively.

Accuracy of attenuation imaging in the assessment of pediatric hepatic steatosis: correlation with the controlled attenuation parameter.

Purpose: This study evaluated the accuracy of attenuation imaging (ATI) for the assessment of hepatic steatosis in pediatric patients, in comparison with the FibroScan vibration-controlled transient elastography controlled attenuation parameter (CAP).

Methods: Consecutive pediatric patients referred for evaluation of obesity who underwent both ATI and FibroScan between February 2020 and September 2021 were included. The correlation between attenuation coefficient (AC) and CAP values was assessed using the Spearman test.

Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method.

Purpose: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods.

Materials And Methods: We collected 485 hand radiographs of healthy children aged 2-17 years (262 boys) between 2008 and 2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA assessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs.