Biomechanical Impact Profiles and Chronic Traumatic Encephalopathy Phenotype Heterogeneity

SUMMARY

# Biomechanical Impact Profiles and Chronic Traumatic Encephalopathy Phenotype Heterogeneity ## Background and Rationale # Biomechanical Impact Profiles and Chronic Traumatic Encephalopathy Phenotype Heterogeneity: A Computational Systems Approach Traumatic brain injury (TBI) represents a significant public health burden affecting millions globally, with long-term sequelae including chronic traumatic encephalopathy (CTE), a progressive neurodegenerative disease characterized by pathological tau

METHODOLOGY NOTES

**Phase 1: Data Collection and Preprocessing (Weeks 1-4)** • Collect biomechanical impact data from 500+ documented TBI cases across multiple sports and military cohorts • Gather CTE neuropathological assessments including tau protein distribution, neuroinflammation markers, and brain atrophy patterns • Compile clinical phenotype data including cognitive assessments (MMSE, MoCA), behavioral evaluations (NPI), and functional outcomes (GOS-E) • Standardize impact metrics: peak linear acceleration (g-force), rotational velocity (rad/s), impact duration, and cumulative exposure indices • Perform quality control and missing data imputation using multiple imputation methods **Phase 2: Biomechanical Profile Classification (Weeks 5-8)** • Apply unsupervised machine learning algorithms (K-means clustering, hierarchical clustering) to identify distinct impact profile clusters • Validate clustering using silhouette analysis and gap statistic (target ≥3 distinct clusters) • Characterize each clus