This study aims to develop and validate an artificial intelligence (AI)-assisted platform for musculoskeletal knee ultrasonography and to establish an interpretable prediction model for clinical outcomes following ultrasound-guided injection therapies in patients with degenerative knee disorders. The project seeks to improve the standardization, reproducibility, and clinical utility of knee ultras…
This study aims to develop and validate an artificial intelligence (AI)-assisted platform for musculoskeletal knee ultrasonography and to establish an interpretable prediction model for clinical outcomes following ultrasound-guided injection therapies in patients with degenerative knee disorders. The project seeks to improve the standardization, reproducibility, and clinical utility of knee ultrasound by reducing operator dependency and providing quantitative image analysis and outcome prediction.
The study will be conducted in three phases. First, an AI foundation model for knee ultrasonography will be developed using standardized image acquisition protocols to enable automated localization, segmentation, and quantitative assessment of major anatomical structures, including tendons, ligaments, cartilage, fat pads, and peripheral nerves. Second, supervised machine learning models will be trained to classify normal and pathological ultrasound findings, including common degenerative and inflammatory abnormalities affecting the knee. Third, retrospective and prospective clinical data from approximately 150 patients receiving ultrasound-guided injection therapies will be integrated to develop and validate a predictive model for treatment outcomes using imaging biomarkers and clinical variables. Treatment response will be evaluated using validated patient-reported outcome measures, and explainable AI methods will be applied to improve model interpretability.
The anticipated outcome of this study is the development of a comprehensive AI-assisted knee ultrasound platform that supports standardized image interpretation, quantitative assessment of musculoskeletal pathology, and personalized prediction of treatment response to ultrasound-guided injection therapies in degenerative knee disorders.
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Eligibility Criteria
Objective 1: Development of an AI-Based Normative Model for the Healthy Knee
Inclusion Criteria:
* Clinical diagnosis of healthy adult without major systemic disease
* Age ≥18 years
* Able to understand and follow study instructions
* Ambulatory without walking aids
* No pain in either knee for at…
Objective 1: Development of an AI-Based Normative Model for the Healthy Knee
Inclusion Criteria:
* Clinical diagnosis of healthy adult without major systemic disease
* Age ≥18 years
* Able to understand and follow study instructions
* Ambulatory without walking aids
* No pain in either knee for at least 6 months before enrollment
Exclusion Criteria:
* Previous knee surgery
* Rupture of one or more cruciate ligaments
* Knee injection within the preceding 6 months
* Major trauma involving the knee or periarticular region
* Rheumatic or autoimmune disease
Objective 2: Development of an AI-Based Model for the Identification of Pathological Knee Structures
Inclusion Criteria:
* Clinical diagnosis of radiographic knee osteoarthritis
* Age ≥18 years
* Knee pain in at least one knee during the preceding year
* Medical records confirming knee pain, soreness, or stiffness within 1 month before enrollment
* Radiographic evidence of knee osteoarthritis, defined by at least one of the following:
* Kellgren-Lawrence grade ≥2 on anteroposterior radiographs
* Kellgren-Lawrence grade ≥2 on skyline (patellofemoral) radiographs
* Superior or inferior patellar osteophytes or posterior tibial osteophytes on lateral radiographs
Exclusion Criteria:
* Systemic rheumatic disease (e.g., rheumatoid arthritis or ankylosing spondylitis)
* Malignancy
* Previous major knee trauma (including fracture)
* Previous knee surgery
* Intra-articular corticosteroid injection within the preceding 3 months
Objective 3: Development of an AI-Assisted Predictive Model for Injection Treatment Outcomes
Inclusion Criteria:
* Clinical diagnosis of radiographic knee osteoarthritis requiring ultrasound-guided injection therapy
* Age ≥18 years
* Knee pain in at least one knee during the preceding year
* Medical records confirming knee pain, soreness, or stiffness within 1 month before enrollment
* Radiographic evidence of knee osteoarthritis, defined by at least one of the following:
* Kellgren-Lawrence grade ≥2 on anteroposterior radiographs
* Kellgren-Lawrence grade ≥2 on skyline (patellofemoral) radiographs
* Superior or inferior patellar osteophytes or posterior tibial osteophytes on lateral radiographs
* Willingness to undergo ultrasound-guided injection therapy and complete scheduled follow-up assessments
Exclusion Criteria:
* Systemic rheumatic disease (e.g., rheumatoid arthritis or ankylosing spondylitis)
* Malignancy
* Previous major knee trauma (including fracture)
* Previous knee surgery
* Intra-articular corticosteroid injection within the preceding 3 months
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