The application value of CT radiomics features in predicting pressure amplitude correlation index in patients with severe traumatic brain injury - Liu, Jiaqi; Shan, Yingchi; Gao, Guoyi (Frontiers in Neurology, 2022)
To explore the application value of a machine learning model based on CT radiomics features in predicting the pressure amplitude correlation index (RAP) in patients with severe traumatic brain injury（sTBI）. Retrospectively analyzed the clinical and imaging data in 36 patients with sTBI. All patients underwent surgical treatment, continuous ICP monitoring, and invasive arterial pressure monitoring. The pressure amplitude correlation index (RAP) was collected within 1h after surgery. Three volume of interest (VOI) was selected from the craniocerebral CT images of patients 1h after surgery, and a total of 93 radiomics features were extracted from each VOI. Three models were established to be used to evaluate the patients’ RAP level. The result shows CT radiomics can predict RAP level in patients with sTBI, which has the potential to establish a method of noninvasive intracranial pressure (NI-ICP) monitoring.