Abstract

Early identification of the etiology of spontaneous acute intracerebral hemorrhage is essential for appropriate management. This study aimed to develop an imaging model to identify cavernoma-related hematomas. Patients 1-55 years of age with acute (≤7 days) spontaneous intracerebral hemorrhage were included. Two neuroradiologists reviewed CT and MR imaging data and assessed the characteristics of hematomas, including their shape (spherical/ovoid or not), their regular or irregular margins, and associated abnormalities including extralesional hemorrhage and peripheral rim enhancement. Imaging findings were correlated with etiology. The study population was randomly split to provide a training sample (50%) and a validation sample (50%). From the training sample, univariate and multivariate logistic regression was performed to identify factors predictive of cavernomas, and a decision tree was built. Its performance was assessed using the validation sample. Four hundred seventy-eight patients were included, of whom 85 had hemorrhagic cavernomas. In multivariate analysis, cavernoma-related hematomas were associated with spherical/ovoid shape (P < .001), regular margins (P = .009), absence of extralesional hemorrhage (P = .01), and absence of peripheral rim enhancement (P = .002). These criteria were included in the decision tree model. The validation sample (n = 239) had the following performance: diagnostic accuracy of 96.1% (95% CI, 92.2%-98.4%), sensitivity of 97.95% (95% CI, 95.8%-98.9%), specificity of 89.5% (95% CI, 75.2%-97.0%), positive predictive value of 97.7% (95% CI, 94.3%-99.1%), and negative predictive value of 94.4% (95% CI, 81.0%-98.5%). An imaging model including ovoid/spherical shape, regular margins, absence of extralesional hemorrhage, and absence of peripheral rim enhancement accurately identifies cavernoma-related acute spontaneous cerebral hematomas in young patients.

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