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Retrospective analysis shows edema-to-hematoma ratio predicts early expansion in small intracerebral hemorrhage, suggesting improved risk stratification.
BACKGROUND AND PURPOSE: Small intracerebral hemorrhage, defined as baseline noncontrast CT (NCCT) hematoma volume <30 mL, is often considered lower risk for early expansion. We tested whether the edema-to-hematoma ratio (EHR) on baseline noncontrast CT (NCCT) independently predicts expansion and whether combining EHR with hematoma volume (HV) enables practical bedside risk stratification. MATERIALS AND METHODS: We retrospectively analyzed 219 conservatively managed patients with small-volume intracerebral hemorrhage. Baseline NCCT underwent AI-assisted 3D volumetry to quantify HV and perihematomal edema and to compute EHR. The primary outcome was binary early hematoma expansion on the first follow-up CT. Multivariable logistic regression included HV, EHR, age, deep location, intraventricular hemorrhage, and anticoagulation status. Discrimination and calibration were assessed with five-fold cross-validation. Youden-index cut points were used to derive a simple bedside rule combining HV and EHR. RESULTS: Early expansion occurred in 20.1% (44/219). Lower EHR and larger HV independently predicted expansion. Per 0.10 increase in EHR, adjusted odds decreased by 23% (aOR, 0.77; 95% CI, 0.66–0.88); per additional 5 mL in HV, odds increased by 37% (aOR, 1.37; 95% CI, 1.09–1.73). A bedside rule (HV ≥9.2 mL plus EHR ≤0.683) identified a high-risk phenotype with a 39.3% expansion rate versus 4.4% in the low-risk reference. The multivariable model outperformed either predictor alone (AUC, 0.748 vs 0.700 and 0.672) with acceptable calibration (intercept, −0.17; slope, 0.92; Brier score, 0.141). CONCLUSIONS: A lower baseline EHR independently predicts early expansion in small-volume intracerebral hemorrhage. Pairing EHR with HV yields a practical bedside rule with a large risk gradient and improves discrimination beyond volume alone, supporting targeted monitoring and timely repeat imaging.
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Shi et al. (2026) studied this question.
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