Automated Measurements of Long Leg Radiographs in Pediatric Patients: A Pilot Study to Evaluate an Artificial Intelligence-Based Algorithm.

ABSTRACT:

Background

Assessment of long leg radiographs (LLRs) in pediatric orthopedic patients is an important but time-consuming routine task for clinicians. The goal of this study was to evaluate the performance of artificial intelligence (AI)-based leg angle measurement assistant software (LAMA) in measuring LLRs in pediatric patients, compared to traditional manual measurements.

Methods

Eligible patients, aged 11 to 18 years old, referred for LLR between January and March 2022 were included. The study comprised 29 patients (58 legs, 377 measurements). The femur length, tibia length, full leg length (FLL), leg length discrepancy (LLD), hip-knee-ankle angle (HKA), mechanical lateral distal femoral angle (mLDFA), and mechanical medial proximal tibial angle (mMPTA) were measured auto

SUBMITTER: van der Lelij TJN 

PROVIDER: S-EPMC11505924 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature