The CBI-M framework is a clinical model used to classify the severity of traumatic brain injuries (TBI) to help guide targeted treatment strategies. It is one of several complementary frameworks used in modern diagnostic standards to provide more granularity than traditional acute care guidelines.
Key features of the CBI-M framework include:
- Advanced Neuroimaging: It relies heavily on advanced MRI sequences, specifically Diffusion Tensor Imaging (DTI) and Susceptibility Weighted Imaging (SWI), to detect microstructural damage such as diffuse axonal injury.
- Severity Classification: The primary goal of the framework is to categorize the extent of the injury, allowing clinicians to stratify patients for the most appropriate treatment approach.
- Diagnostic Scope: Unlike the 2026 AAN/CDC guidelines or the “four-pillar” model, the CBI-M framework focuses on imaging findings and does not explicitly define the use of serum biomarkers (such as GFAP or UCH-L1) in its classification process.
By utilizing quantitative DTI data and automated microbleed detection, this framework helps identify injuries that are frequently missed by conventional CT and MRI scans.
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