Automated Metrics for the Diagnosis of Instability Between the 2nd and 7th Cervical Vertebrae.

Diagnosing cervical spine instability with flexion-extension radiographs is challenging, as current guidelines are based on limited cadaver studies and do not adequately account for level, vertebral size, or patient effort. There is a need for automated cervical instability metrics anchored to normative reference data, accompanied by evidence on how often abnormal findings occur in real clinical populations and which soft-tissue injury patterns they can detect. We developed and evaluated fully automated, radiographic-based cervical intervertebral motion (IVM) metrics-adapted from prior lumbar methods-using an FDA-cleared analysis pipeline that segments C2-C7 and derives rotation, translation, disc heights, and regression-based instability indices. Normative reference data were first established from flexion-extension radiographs of 341 asymptomatic volunteers after excluding radiographically degenerated levels. Abnormality prevalence was then estimated in two symptomatic cohorts: pooled preoperative clinical-trial radiographs and 881 patients with symptoms attributed to motor-vehicle accidents, excluding levels with <5° rotation to reduce unreliable data due to insufficiently stressed spines. Finally, potential diagnostic performance was assessed in a controlled cadaveric ligament-sectioning model (12 cadavers) using ROC analysis and Youden's J thresholds. Across clinical cohorts, objective IVM abnormalities were uncommon. Prevalence increased when studies demonstrated adequate total C2-C7 motion, emphasizing the importance of patient effort. In cadavers, vertical instability metrics were most discriminative (AUC 0.96-0.97) with high sensitivity (0.89) and perfect specificity at optimal thresholds, whereas translation changed minimally with sectioning. These results support regression-based instability indices as promising candidates for standardized, physiology-guided cervical instability assessment.