Knee replacement surgery is a common and effective treatment for pain and mobility loss, yet up to 1 in 5 patients remain dissatisfied after surgery due to ongoing pain or difficulty with daily activities. Currently, clinicians cannot reliably predict which patients will experience these challenges.
This study uses MRI scan of the brain to investigate whether specific patterns of brain activity can predict patient satisfaction after total knee arthroplasty (TKA). By comparing brain networks before surgery and afterward, and linking these changes to patient-reported pain and function, we aim to identify brain-based markers that can help predict outcomes, to improve satisfaction after knee replacement surgery.
Male and female patients aged 18 years or older
Primary TKA
Diagnosis of osteoarthritis, inflammatory arthritis, or osteonecrosis
Inability or refusal to sign informed consent form
Non-English or French speaking, and no licensed translator, family member or substitute decision maker available
History of major neurological disorders (e.g traumatic brain injury, epilepsy, multiple sclerosis
Cognitive impairment or dementia
Single group
fMRI Brain Scan
Procedure/SurgeryA research brain MRI scan will be performed on a 3T scanner. The MRI session will take approximately 50 minutes of scanning time. The MRI scan will be repeated again 2 months after surgery.
Preoperative Resting-State fMRI Brain connectivity as a Predictor of Patient operative Satisfaction after Total Knee Arthroplasty measured by Patient-Reported Outcomes Measurement Information System (PROMIS )
Using 50 pre-operative brain networks derived from advanced brain imaging will be assessed as predictors of postoperative patient satisfaction. Patient satisfaction measured by PROMIS questionnaire Preoperative resting-state fMRI brain connectivity will be assessed as a predictor of postoperative patient satisfaction measured using PROMIS questionnaires, which assess pain and function.
Preoperative Resting-State fMRI Brain connectivity as a Predictor of Patient operative Satisfaction after Total Knee Arthroplasty measured by Oxford Knee Score (OKS)
Preoperative resting-state fMRI brain connectivity will be assessed as a predictor of postoperative patient satisfaction measured using the Oxford Knee Score, which assesses knee function and pain.
Longitudinal Change in Brain Network Connectivity from Preoperative to 12 months after total knee arthroplasty
50 brain networks derived from advanced brain imaging will be assessed longitudinally to characterize changes in brain networks from baseline to 12 months. Brain regions will be defined using the Schaefer functional atlas and the Allen Brain Atlas. Longitudinal changes in connectivity will be assessed using linear mixed-effects models with individual satisfaction change scores as continuous dependent variables. These models will include fixed effects for time and satisfaction, as well as random effects for subject ID to account for repeated measures. Changes will be computed by subtracting baseline from 12-month connectivity values, and these difference matrices will serve as the input features for modeling. The machine learning models for longitudinal change will follow the same 2:1 training/test split, k-fold cross-validation strategy, and performance evaluation.
Identification of Key Brain Network Nodes Associated with Postoperative Dissatisfaction after total knee arthroplasty
Brain network nodes will be identified from rsfMRI-derived brain networks that are associated with postoperative dissatisfaction. Network nodes will be analyzed to identify potential neuroimaging biomarkers relevant to postoperative outcomes and future therapeutic targeting. Nodes will be ranked based on their contribution to predictive models and graph-theoretical importance metrics.
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