Purpose: Circumferential enhancement on MR vessel wall imaging has been proposed as a biomarker of a higher risk of rupture in intracranial aneurysms. Focal enhancement is frequently encountered in unruptured aneurysms, but its implication for risk stratification and patient management remains unclear. This study investigates the association of focal wall enhancement with hemodynamic and morphological risk factors and histologic markers of wall inflammation and degeneration. Methods: Patients with an unruptured middle cerebral artery aneurysm who underwent 3D rotational angiography and 3T MR vessel wall imaging showing focal wall enhancement were included. Hemodynamic parameters were calculated based on flow simulations and compared between enhanced regions and the entire aneurysm surface. Morphological parameters were semiautomatically extracted and quantitatively associated with wall enhancement. Histological analysis included detection of vasa vasorum, CD34, and myeloperoxidase staining in a subset of patients. Results: Twenty-two aneurysms were analyzed. Enhanced regions were significantly associated with lower AWSS, lower maxOSI, and increased LSA. In multivariate analysis, higher ellipticity index was an independent predictor of wall enhancement. Histologic signs of inflammation and degeneration and higher PHASES score were significantly associated with focal enhancement. Conclusion: Focal wall enhancement is colocalized with hemodynamic factors that have been related to a higher rupture risk. It is correlated with morphological factors linked to rupture risk, higher PHASES score, and histologic markers of wall destabilization. The results support the hypothesis that focal enhancement could serve as a surrogate marker for aneurysm instability.

Background: Parameters of body composition have prognostic potential in patients with oncologic diseases. The aim of the present study was to analyse the prognostic potential of radiomics‐based parameters of the skeletal musculature and adipose tissues in patients with advanced hepatocellular carcinoma (HCC).Methods: Radiomics features were extracted from a cohort of 297 HCC patients as post hoc sub‐study of the SORAMIC randomized controlled trial. Patients were treated with selective internal radiation therapy (SIRT) in combination with sorafenib or with sorafenib alone yielding two groups: (1) sorafenib monotherapy (n = 147) and (2) sorafenib and SIRT (n = 150). The main outcome was 1‐year survival. Segmentation of muscle tissue and adipose tissue was used to retrieve 881 features. Correlation analysis and feature cleansing yielded 292 features for each patient group and each tissue type. We combined 9 feature selection methods with 10 feature set compositions to build 90 feature sets. We used 11 classifiers to build 990 models. We subdivided the patient groups into a train and validation cohort and a test cohort, that is, one third of the patient groups.Results: We used the train and validation set to identify the best feature selection and classification model and applied it to the test set for each patient group. Classification yields for patients who underwent sorafenib monotherapy an accuracy of 75.51% and area under the curve (AUC) of 0.7576 (95% confidence interval [CI]: 0.6376–0.8776). For patients who underwent treatment with SIRT and sorafenib, results are accuracy = 78.00% and AUC = 0.8032 (95% CI: 0.6930–0.9134).Conclusions: Parameters of radiomics‐based analysis of the skeletal musculature and adipose tissue predict 1‐year survival in patients with advanced HCC. The prognostic value of radiomics‐based parameters was higher in patients who were treated with SIRT and sorafenib.