Noninvasive Prediction for Intracranial Pressure Related Parameters in Patients with Traumatic Brain Injury Using Computed Tomography Radiomic Features

Current intracranial pressure (ICP)-related parameters monitoring is invasive and tends to cause complications, which limit their use to predict patients’ intracranial status and prognosis. To utilize post-operative computed tomography (CT) images radiomic features techniques to predict abnormal ICP-related parameter levels consisting of an index of cerebrospinal compensatory reserve (RAP) and a pressure reactivity index (PRx) in patients with traumatic brain injury (TBI) noninvasively, 60 patients were enrolled and randomized to training ( n = 42) and test ( n = 18) sets. Data of 20 patients from another hospital were used to validate the model. A total of 107 radiomic features were extracted from each patient’s CT image. Their clinical and imaging data were collected and analyzed to establish prediction models of RAP and PRx, respectively. Univariate regression analysis and least absolute shrinkage and selection operator method were used for feature selection, and multivariate logistic regression was used to develop the predictive models. The nomogram was assessed with respect to its calibration and clinical usefulness. The RAP model showed a good discrimination with the area under the receiver operating characteristic curve (AUC) of training and test sets was 0.789 (95% confidence interval [CI]: 0.635–0.944) and 0.818 (95% CI: 0.578–0.998). The performance of PRx model was inferior to the RAP model, but still had a significant discrimination with the AUCs of training and test were 0.713 (95% CI: 0.676–0.920) and 0.667 (95% CI: 0.554–0.803). Application of the nomogram and calibration curve also showed that the two models had excellent model predictions and clinical usefulness. The external validation results of RAP and PRx showed a good discrimination with an AUC of 0.813 (95% CI: 0.586–1) and 0.781 (95% CI: 0.565–0.997). The study illustrated that CT radiomic features as a clinical aid may have the ability to predict ICP-related parameters to reflect the intracranial condition of patients with TBI noninvasively given its potential for clinical treatment guidance and prognosis indication.