Correlating Age and Hematoma Volume with Extent of Midline Shift in Acute Subdural Hematoma Patients: Validation of an Artificial Intelligence Tool for Volumetric Analysis

This study aimed to evaluate the use of AI-based automated volumetric analysis (qER-Quant, Qure.ai) to measure hematoma volume and midline shift (MLS) in 1,789 acute subdural hematoma patients and assess their relationship with age. The analysis showed that older patients (>70 years) had a higher average hematoma volume (62.2 mL vs. 46.8 mL, P < 0.0001) but a lower MLS (6.6 mm vs. 7.4 mm, P = 0.025) and MLS:hematoma volume ratio (0.11 mm/mL vs. 0.15 mm/mL, P < 0.0001) compared to younger patients. Notably, younger patients had 1.5 mm greater MLS per hematoma volume than older patients, and the MLS:hematoma volume ratio decreased significantly with age (P = 0.0002). These findings confirm that AI-based tools provide valid and quantitative radiographic measurements, supporting their use in clinical decision-making for acute subdural hematoma management.