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Updated: Feb 4, 2026

Minimally Invasive Endoscopic Intracerebral Hemorrhage Evacuation
Published on: October 15, 2021
Determining the Optimal Shape-Related Indicator on Noncontrast Computed Tomography for Predicting Hematoma Expansion
Zhiyuan Yu1, Jun Zheng1, Mou Li2
1Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective:
Among several novel predictors on noncontrast computed tomography (CT) for hematoma expansion in spontaneous intracerebral hemorrhage (sICH), shape irregularity grade, satellite sign, and island sign are all related to irregular shape of hematoma. This study is aimed to compare the accuracy of these imaging markers for predicting hematoma expansion in the same cohort of sICH patients.
Methods:
This retrospective study enrolled sICH patients who underwent diagnostic computed tomography (CT) scans within 6 hours after onset and another follow-up CT scan within 24 hours after initial CT scan. Shape irregularity grade, satellite sign, and island sign were assessed according to the definitions in previous studies. The accuracy of these imaging indicators for predicting hematoma expansion was analyzed using receiver operator analysis.
Results:
Finally, a total of 196 patients were included. Shape irregularity grade ≥3 was found in 87 (44.39%) patients, satellite sign was identified in 76 (38.78%) patients, and island sign was shown in only 41 (20.92%) patients. Only island sign remained an independent predictor for hematoma expansion in multivariate logistic regression. The sensitivity values of shape irregularity grade ≥3, satellite sign, and island sign were 0.52, 0.63, and 0.48, respectively. By contrast, the specificity values of these 3 predictors were 0.58, 0.69, and 0.85, respectively. Shape irregularity grade ≥3 had the smallest area under the curve (0.597), and island sign had the largest (0.676).
Conclusions:
Island sign seems to be the optimal shape-related predictor for hematoma expansion in sICH patients and could be included in the future predictive model for hematoma expansion.
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