Knee osteoarthritis (KOA) is a leading cause of chronic pain and disability. Although genicular nerve block (GNB) is an effective treatment for many patients, treatment response varies considerably. Identifying imaging biomarkers that predict clinical response may improve patient selection and optimize treatment outcomes.

This prospective observational study aims to evaluate whether the Sonographic Thigh Adjustment Ratio (STAR), calculated as anterior quadriceps muscle thickness divided by body mass index (BMI), and subcutaneous fat thickness are associated with pain relief following genicular nerve block in patients with symptomatic knee osteoarthritis. Ultrasound measurements will be obtained before the procedure, and clinical outcomes will be assessed during follow-up. The primary objective is to determine whether sonographic muscle parameters can predict treatment response after GNB.

Knee osteoarthritis is one of the most common musculoskeletal disorders worldwide and is frequently associated with chronic pain, impaired mobility, and reduced quality of life. Genicular nerve block has become an established minimally invasive treatment for patients with persistent pain despite conservative management. However, substantial variability exists in treatment response, highlighting the need for reliable predictors of clinical success.

Recent studies have suggested that ultrasound-derived muscle measurements may provide objective information regarding muscle quality and sarcopenia. The Sonographic Thigh Adjustment Ratio (STAR), defined as anterior quadriceps muscle thickness normalized to body mass index (BMI), has been proposed as an ultrasound-based indicator of muscle mass. Nevertheless, its potential role in predicting the response to interventional pain procedures has not been investigated.

This prospective observational cohort study will enroll patients with symptomatic knee osteoarthritis who undergo ultrasound-guided genicular nerve block as part of routine clinical care. Before the procedure, ultrasound measurements of anterior quadriceps muscle thickness and subcutaneous fat thickness will be obtained. STAR will be calculated by dividing anterior quadriceps muscle thickness by BMI. Clinical outcomes will be assessed using validated pain and functional outcome measures during follow-up.

The primary objective is to evaluate whether STAR predicts treatment response after genicular nerve block. Secondary objectives include investigating the predictive value of quadriceps muscle thickness and subcutaneous fat thickness individually and exploring their relationship with pain reduction and functional improvement.

Inclusion Criteria:

• Age ≥45 years.
• Symptomatic bilateral knee osteoarthritis with Kellgren-Lawrence grade 3 or 4.
• Visual Analog Scale (VAS) pain score ≥4 at rest or during movement.
• Scheduled to undergo first ultrasound-guided genicular nerve block.
• No intra-articular knee injection within the previous 3 months.
• Considered unsuitable for or awaiting total knee arthroplasty.
• Ability to provide written informed consent.

Exclusion Criteria:

• Inflammatory arthritis, rheumatoid arthritis, or crystal arthropathy.
• Previous knee surgery or knee prosthesis.
• Active local or systemic infection.
• Anticoagulant therapy or bleeding disorders.
• Contraindication to corticosteroids (including uncontrolled diabetes mellitus).
• Allergy to study medications.
• Neurological disorders causing neuropathic knee pain.
• Dementia or inability to complete study assessments.
• Additional interventional procedures or surgery during follow-up.

Adults with symptomatic bilateral Kellgren-Lawrence grade 3-4 knee osteoarthritis referred from the Department of Physical Medicine and Rehabilitation to the Pain Medicine Clinic for ultrasound-guided genicular nerve block after failure of conservative treatment. Consecutive eligible patients meeting the inclusion criteria will be enrolled prospectively.

The investigators have not yet made a final decision regarding individual participant data (IPD) sharing. Data sharing will be considered after study completion in accordance with institutional policies, ethical requirements, and applicable data protection regulations.