Publications by authors named "Du Hyun Ro"

Purpose: Knee osteoarthritis (OA) is a common joint disorder assessed using radiographic (X-ray) and magnetic resonance imaging (MRI). While X-rays are accessible, MRI provides detailed insights into meniscus and cartilage. Few studies have evaluated the correlation between X-ray and MRI findings in knee OA longitudinally.

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Background: A single universally accepted protocol does not exist for measuring the posterior tibial slope (PTS), limiting the application of cutoff values for surgical decision-making and risk stratification.

Purpose/hypothesis: This purpose of this study was to validate an online computer vision model using anatomic landmarks for PTS measurement on uncalibrated lateral knee radiographs. It was hypothesized that this model would achieve similar accuracy to manual measurement.

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Background: Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used for osteoarthritis (OA), despite various adverse effects (AEs). Previous studies were often limited by small sample sizes, a focus on only predefined outcomes, and an imbalanced research coverage across NSAID subtypes. These factors can cause confirmation or heterogeneity bias, and in clinical practice, focusing on only well-known AEs may lead to the overlooking of other potential AEs.

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Introduction: Population-based differences in knee alignment patterns may impact osteoarthritis (OA) progression. This study compares lower extremity alignment in knee OA between Middle Eastern (UAE) and East Asian (South Korean) populations using artificial intelligence (AI)-assisted analysis.

Methods: A retrospective review included patients with knee symptoms from South Korea (2009-2019) and the United Arab Emirates (UAE) (2015-2024).

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Backgroud: Allografts are preferred in certain cases of revision anterior cruciate ligament reconstructions to avoid additional graft harvesting and to fill in enlarged tunnels. The clinical outcomes of quadriceps tendon-patellar bone allograft in revision anterior cruciate ligament reconstruction are not well-known. This study was performed to evaluate the clinical outcomes of revision anterior cruciate ligament reconstructions using quadriceps tendon-patellar bone allografts.

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Objective: This study aims to define Kellgren-Lawrence grade (KLG) using OARSI grade and stratify radiographic knee osteoarthritis (KOA) into distinct phenotypes based on radiographic structure changes and compare clinical symptoms and disease progression.

Design: We used radiographic grading data provided by the OAI and MOST study. Decision tree was used to (1) Find OARSI grade criteria for each KLG and (2) Phenotype early osteoarthritic knees (=KLG1, 2) by the radiographic structure changes.

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Background Context: Accurate and consistent measurement of sagittal alignment is challenging, particularly in patients with severe coronal deformities, including degenerative lumbar scoliosis (DLS).

Purpose: This study aimed to develop and validate an artificial intelligence (AI)-based system for automating the measurement of key sagittal parameters, including lumbar lordosis, pelvic incidence, pelvic tilt, and sacral slope, with a focus on its applicability across a wide range of deformities, including severe coronal deformities, such as DLS.

Design: Retrospective observational study.

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Background: Patellofemoral pain syndrome (PFPS) is one of the most common conditions affecting the knee joint, yet its pathomechanics remain unclear. The aim of this study was to investigate changes in muscle activation and gait patterns and to analyze the relationship between muscle activation and kinetic gait patterns in patients with PFPS.

Methods: This study included 31 patients with PFPS and 28 healthy volunteers without any symptoms.

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Introduction: Prosthetic joint infection (PJI) is one of the most common and detrimental complications of total knee replacement arthroplasty (TKA). Despite extensive efforts, including two-stage reimplantation, to eradicate PJI, it still recurs in a substantial number of patients. However, the risk factors of recurrence after two-stage reimplantation of the knee have not been established.

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Background: Studies investigating constitutional alignment across various grades of osteoarthritis (OA) are limited. This study explored the distribution of Coronal Plane Alignment of the Knee (CPAK) types and associated radiographic parameters with increasing OA severity.

Methods: In this retrospective cross-sectional study, 17,365 knees were analyzed using deep learning software for radiographic measurements.

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Article Synopsis
  • Preoperative templating for total knee arthroplasty (TKA) is crucial for surgical preparation, but it currently lacks automation; this study developed an AI model to automate the prediction of implant sizes.
  • The model was trained on over 13,000 knee radiographs and combines predictions from both anteroposterior and lateral views, validating results against actual TKA outcomes to assess accuracy.
  • Results showed the AI model achieved an exact prediction rate of 39.5% for femoral components and 43.2% for tibial components, with an overall accuracy of 88.9% when allowing for a one-size margin of error; this indicates the model is reliable and could speed up the templating process for surgeons.
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Having osteoarthritis in one knee is reported as an independent risk factor for developing contralateral knee osteoarthritis (KOA). However, no study has been designed to predict the development of contralateral KOA (cKOA). The authors hypothesized that specific risk factors for cKOA development exist and that it could be accurately predicted with the assistance of machine learning.

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Background: High tibial osteotomy (HTO) modifies the mechanics of the affected knee but can also affect the nonoperated knee. However, no research has reported on the prognosis and risk factors related to the nonoperated knee after unilateral HTO.

Purpose: To assess the radiological parameters associated with osteoarthritis (OA) progression and the need for surgery in the nonoperated knee after unilateral HTO, with concurrent assessment of the operated knee.

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Purpose: Total knee arthroplasty (TKA) is an effective treatment for advanced osteoarthritis, and achieving optimal outcomes can be challenging due to various influencing factors. Previous research has focused on identifying factors that affect postoperative functional outcomes. However, there is a paucity of studies predicting individual postoperative improvement following TKA.

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Background: Patient-reported satisfaction following total knee arthroplasty (TKA) can be affected by various factors. This study aimed to assess patient satisfaction rates and identify factors related to patients, surgery, and postoperative knee motion associated with satisfaction in posterior-stabilized TKA among Asian patients.

Methods: A retrospective cross-sectional study was conducted in patients with primary osteoarthritis who underwent TKA and had a follow-up period of over 2 years.

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Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive performances. Therefore, the purpose of this study was to design a machine learning model for knee osteoarthritis progression, focusing on high validation quality and clinical applicability.

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: Neglected patellar dislocation in the presence of end-stage osteoarthritis (OA) is a rare condition characterized by the patella remaining laterally dislocated without reduction. Due to the scarcity of reported cases, the optimal management approach is still uncertain. However, primary total knee arthroplasty (TKA) can serve as an effective treatment option.

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Background: Fine-grained classification deals with data with a large degree of similarity, such as cat or bird species, and similarly, knee osteoarthritis severity classification [Kellgren-Lawrence (KL) grading] is one such fine-grained classification task. Recently, a plug-in module (PIM) that can be integrated into convolutional neural-network-based or transformer-based networks has been shown to provide strong discriminative regions for fine-grained classification, with results that outperformed the previous deep learning models. PIM utilizes each pixel of an image as an independent feature and can subsequently better classify images with minor differences.

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Background: Isolated polyethylene insert exchange (IPIE) has not been established as a treatment option for hyperextension instability after primary total knee arthroplasty (TKA). The purpose of the study was to evaluate the survival rate and clinical outcomes of IPIE for the treatment of instability with or without hyperextension after TKA.

Methods: This study retrospectively reviewed 46 patients who underwent IPIE for symptomatic prosthetic knee instability by dividing them into 2 groups based on the presence of hyperextension (without for group I and with for group IH).

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Background: The application of artificial intelligence and large language models in the medical field requires an evaluation of their accuracy in providing medical information. This study aimed to assess the performance of Chat Generative Pre-trained Transformer (ChatGPT) models 3.5 and 4 in solving orthopedic board-style questions.

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Article Synopsis
  • - Electromyography (EMG) is being explored as a way to predict the severity of knee osteoarthritis (OA) by analyzing muscle activation patterns during walking, linked to patient-reported measures like WOMAC and VAS.
  • - This study collected EMG data from the lower leg muscles of 84 patients with advanced knee OA to analyze how muscle activity and co-contraction relate to functional limitations experienced by these patients.
  • - Using machine-learning models, the researchers found high accuracy (coefficient of determination) in predicting WOMAC and VAS scores based on muscle activity, revealing that greater muscle co-contraction correlates with more severe OA symptoms.
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Background: High tibial osteotomy is an established surgical option for medial compartment osteoarthritis of the knee with varus alignment. It can be divided into open wedge and closing wedge by operative technique. Although they have fundamental differences, little is known about the biomechanical consequences of the two surgical methods.

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Purpose: Although the Dejour classification is the primary classification system for evaluating trochlear dysplasia, concerns have been raised about its reliability owing to its qualitative criteria and challenges associated with obtaining accurate radiographs. This study aimed to quantify trochlear dysplasia using three-dimensional (3D) computed tomography (CT) reconstruction with novel parameters related to the transepicondylar axis (TEA).

Methods: Sixty patients were enrolled, including 20 with trochlear dysplasia and 40 healthy controls.

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