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AI-powered spinal cord injury detection on MRI. Identify cord edema, hemorrhage, compression, and myelopathy signal changes. 4 AI models assess injury severity and evaluate canal compromise across multiple levels.
Spinal cord injury encompasses traumatic and non-traumatic damage to the spinal cord that can result in motor, sensory, and autonomic dysfunction below the level of injury. MRI is the definitive imaging modality for evaluating cord pathology, detecting intramedullary signal abnormalities, hemorrhage, edema, and cord compression. The extent of cord signal change on MRI correlates with neurological prognosis. Our AI consortium analyzes cord morphology, signal characteristics, canal compromise, and associated ligamentous and osseous injuries to provide a comprehensive assessment of spinal cord integrity and the surrounding structural damage.
T2 hyperintensity in the cord indicates edema and has a variable prognosis. The presence of T1 hypointensity or hemorrhage within the cord is associated with more severe injury and poorer neurological recovery. The length of the cord signal abnormality also correlates with outcome. Our AI characterizes both the type and extent of cord signal changes to provide detailed reporting.
MRI uniquely visualizes the posterior ligamentous complex, disc integrity, and soft tissue structures that determine spinal stability. Disruption of these structures is a key component of classification systems such as TLICS (Thoracolumbar Injury Classification and Severity) that guide surgical decision-making. Our AI evaluates ligamentous integrity and identifies features suggesting instability.
Yes. Chronic cord injury manifests as cord atrophy, myelomalacia (persistent T2 signal change with volume loss), and post-traumatic syrinx formation (fluid-filled cavity within the cord). These findings indicate irreversible damage but are important to document as a baseline and to detect complications such as expanding syrinx that may require intervention.
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