Using angiographic parametric imaging-derived radiomics features to predict complications and embolization outcomes of intracranial aneurysms treated by pipeline embolization devices.

Background Pipeline embolization devices (PEDs) have gained widespread popularity in the treatment of intracranial aneurysms (IAs). However, precise predictors of treatment outcomes are still lacking. This study aimed to use angiographic parametric imaging (API)-derived radiomics features to explore whether biomarkers extracted from immediate postprocedural digital subtraction angiography (DSA) were associated with complications and embolization outcomes of IAs treated with PED without adjunctive coils. Methods Radiomic features were extracted from postprocedural DSA by API, and radiomics feature selection and radiomics score calculation were performed by the least absolute shrinkage and selection operator (LASSO) logistic regression. Angiographic findings and clinical characteristics were screened using stepwise multivariable logistic regression analysis to identify significant variables for predicting the complication endpoint. Radiomics feature selection and radiomics risk score (RadRS) calculations were performed by LASSO Cox regression. Univariate and multivariate Cox regression analyses were used to identify significant predictors for the occlusion endpoint. Results We screened 281 observations for complications and 235 observations for embolization outcomes from IAs treated in our center using PED between June 2015 and July 2020. Multivariate regression analysis showed association of the radiomics score (p Conclusions Biomarkers extracted from immediate postprocedural DSA by API could be potential indicators for assessing treatment outcomes of IAs treated by PED without adjunctive coils.