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Research Roadmap 2022-2023
CDMI Mission
The mission of the Center for Disruptive Musculoskeletal Innovations (CDMI) is to address pressing societal needs associated with the growing burden of musculoskeletal disorders (MSDs).
Area of interest across all priority areas – Meta-analysis & development of new test standards, approaches, and test methods; prediction and prevention of MSK injury; prediction and prevention of treatment complications; understanding the multidimensionality of MSK pain; Cross-site validation of computational modeling and simulation
MSD Prevention | Healthcare Data | Biomedical Sciences | Clinical Medicine |
|---|---|---|---|
•Mechanisms of Back Pain, Disc Degeneration | •Tools for Analyzing Electronic Health Records (NLP, AI, ML, etc.) | •Regenerative Medicine, Ortho Biological | •Strategies to Improve Success with Osteoporotic Patients (including treatment) |
•Exposures for Secondary Back Injury | •Evaluation of ROI and Economic Value (potential for translation into application)
| •Musculoskeletal tissue engineering | •Early Onset Scoliosis / Adolescent Idiopathic Scoliosis / Spinal Deformity |
•Injury Causal Pathway Interactions (pain-function, biology-mechanics, psychosocial influences-tissue load, genetics) | •Predictive Models for Outcomes of Clinical Therapies | •Biomaterials | •Technologically Advanced Clinical Screening and Intervention Methods |
•Biomechanical Shoulder Modeling (as a function of job demands) | •Patient Risk Stratification | •Bone substitute materials providing structural integrity | •Integrating Data Representing the Whole Patient (bio-psycho-social model and disease) |
•Musculoskeletal Fatigue (causes, recovery from) | •Quantifying Complications of Standard Spinal Procedures (infection, non-union) | •Biocompatibility and resorption of biomaterials | |
•Issues with the Aging Population (changes in tissue tolerances, tissue recovery) | •Surface modification of materials for better antibacterial or osseo-integration properties | ||
•Bioresorbable cements suitable for fracture healing, drug delivery, etc. | |||
•High -strength, -stiffness, -elongation metallic alloys (e.g., MoRe alloy) | |||
•Relationship between material properties and bone growth, inflammation, infection | |||
•Orthopedic Biomechanics | |||
•Bone Fracture Prevention |
•Ergonomics Interventions | •Clinical Data | •3D printing of tissues to reduce need for metal / screws | •Clinical Outcomes |
•Improved methods to: | •Clarifying reimbursement pathways | •Quantifying health disparities on access to care and clinical outcomes | |
Estimate return-on-investment | •Patient preference (risk, treatment and outcome) | •Functional testing (in clinic biomechanics) | |
Determine trade-offs between potential ergo improvements | •Automated image segmentation | •Metrics and diagnostic tools for determining patient improvement / safe RTW practices | |
Assess added push-pull task factors | •Advanced MRI sequences for identifying tissues of interest | •Predictive analytics | |
•Employee-Centered Training | •Novel biomarker identification (saliva, blood, imaging, biomechanics, biobehavioral, etc.) |
Artificial intelligence to determine the ‘right’ procedure and success potential for a specific patient / pathology | |
•Patient Handling | •COVID/telehealth |
Advance Sciences
Applications
•Composite Injury Risk Indices (whole body, body-part specific) | •Access to Large EHR Datasets (UC system-wide clinical data, UCSF Information Commons) | •Image-Guided / Robotic Surgery | •Imaging Technology in Orthopedics |
•Biomechanical Evaluations (e.g., exo¬skeletons, exosuits) | •Incorporating New Information Streams into Clinical Decision-Making (e.g., expert augmented machine learning) | •Implantable Sensors / Stimulators | (e.g.,device loosening, detection of disc degeneration, osteoporosis assessment, fracture risk evaluation) |
•Prediction of Workplace Injury (using big data, IoT technology, imagery surveillance AI, etc.) | •Software Tools to Integrate Novel Bio¬markers with Electronic Health Record Data | •Bone Healing and Fusion Sensing Devices | •Digital Health / Methods to Quantify Pain and Future Digital / Sensor-Based Outcome Measures (wearables) |
•Validation Studies (risk assessment accuracy, data from wearables) | •Infection (technologies to minimize infections, implant surface treatments) | •Tools / Techniques for FDA-Required Unique Identifiers | •SMART Devices |
Innovative Technologies & Testing
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