Summary
- A total of 166 patients with intracerebral hemorrhage (ICH) received conservative treatment at a hospital from 2019 to 2022.
- Patients were included if they were over 18 years old, had supratentorial ICH, and had a pre-morbid mRS score of 0.
- Imaging analysis was performed on the baseline NCCT images of the patients using 3D Slicer software.
- Radiomics features were extracted from hematoma and surrounding tissues to predict the prognosis of ICH patients.
- The random forest algorithm was used for model construction and validation to evaluate the performance of the prognostic model.
Researchers at the Second Affiliated Hospital of Dalian Medical University recently conducted a study on 166 patients who were treated conservatively for intracerebral hemorrhage (ICH) between January 2019 and June 2022. The study was approved by the hospital’s Ethics Committee, and patients who met certain criteria were included in the analysis.
The study focused on patients over 18 years old who had a baseline NCCT examination within 24 hours of the onset of ICH. Patients with specific conditions, such as intracranial hemorrhage due to tumors or trauma, were excluded from the study. The researchers assessed the patients’ clinical outcomes using the modified Rankin Scale (mRS) at 90 days after the onset of ICH.
The researchers analyzed imaging data from the patients to evaluate the relationship between the size and location of the hemorrhage and the patients’ prognosis. They used advanced software to extract radiomics features from the images and selected important features to predict patient outcomes accurately.
The study found that certain radiomics features were associated with the patients’ prognosis, and a predictive model was developed to assess the likelihood of a good or poor outcome for ICH patients. The researchers used a machine learning algorithm to validate the model and evaluate its performance.
Overall, this study highlights the importance of using advanced imaging techniques to improve the prognostic evaluation of ICH patients. The findings have the potential to enhance clinical decision-making and ultimately improve patient outcomes in the future.
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Radiology, Neurology, Critical Care