The role of imaging in predicting 3-month prognosis of primary intracerebral hemorrhage: a single-center, prospective observational study in tertiary care hospital

Abstract

Background: Due to the high morbidity and mortality of primary intracerebral hemorrhage (ICH), several non-contrast computed tomography (NCCT) imaging markers were proposed to determine the prognosis of affected patients. We prospectively evaluated the predictive accuracy of certain imaging features and established a predictive model composed of highly relevant imaging and clinical features to identify the 3-month functional outcome in primary ICH patients Methods: Patients admitted for primary ICH to a tertiary care center (Al-Zahra Hospital, Isfahan, Iran) were prospectively included from September 2021 to October 2023. Inclusion criteria were defined as: Patients aged >= 18 years with primary or spontaneous ICH confirmed on NCCT at the time of admission. The baseline NCCT was conducted in the early stage of ICH (within 6 hours from symptom onset). The initial NCCT images were obtained within 6 hours from symptom onset. After 3 months, functional outcome of patients was assessed using the modified Rankin Scale (mRS); with mRS >= 3 as poor prognosis and mRS <= 2 as favorable prognosis. The Chi-squared and Logistic regression tests were used for determining the association between clinical and imaging features in differentiating patients' prognosis. Machine learning algorithm support vector machine (SVM) was also used to determine the importance rate of each relevant imaging sign in predicting prognosis. Results: A total of 203 primary ICH patients were included, among which 119 patients (58.6%) had unfavorable prognosis at 3 months. Age, diastolic blood pressure, and Glasgow Coma Scale (GCS) score at admission were significantly associated with prognosis. Among imaging features, hemorrhage volume 95% confidence interval (CI): 0.972-0.991, P<0.001, the presence of midline shift (95% CI: 2.038-7.911, P<0.001), blend sign (95% CI: 1.081-3.760, P=0.026), satellite sign (95% CI: 1.451-4.764, P=0.001), and blackhole sign (95% CI: 2.262-12.714, P<0.001) were significantly different among 2 groups. SVM algorithm showed hemorrhage volume the most important prognostic imaging feature (importance rate: 100%), along with black hole (63.1%), midline shift (54%), satellite (20.4%), and blend sign (15.6%); with decreasing order of importance. Conclusions: Using certain radiological and clinical features, we established a model with considerable prognostication in management of patients with primary ICH in emergency departments.