Prediction of small intracranial aneurysm rupture status based on combined Clinical-Radiomics model.

Background: Accumulating small unruptured intracranial aneurysms are detected due to the improved quality and higher frequency of cranial imaging, but treatment remains controversial. While surgery or endovascular treatment is effective for small aneurysms with a high risk of rupture, such interventions are unnecessary for aneurysms with a low risk of rupture. Consequently, it is imperative to accurately identify small aneurysms with a low risk of rupture. The purpose of this study was to develop a clinically practical model to predict small aneurysm ruptures based on a radiomics signature and clinical risk factors. Methods: A total of 293 patients having an aneurysm with a diameter of less than 5 mm, including 199 patients (67.9 %) with a ruptured aneurysm and 94 patients (32.1 %) without a ruptured aneurysm, were included in this study. Digital subtraction angiography or surgical treatment was required in all cases. Data on the clinical risk factors and the features on computed tomography angiography images associated with the aneurysm rupture status were collected simultaneously. We developed a clinical-radiomics model to predict aneurysm rupture status using multivariate logistic regression analysis. The combined clinical-radiomics model was constructed by nomogram analysis. The diagnostic performance, clinical utility, and model calibration were evaluated by operating characteristic curve analysis, decision curve analysis, and calibration analysis. Results: A combined clinical-radiomics model (Area Under Curve [AUC], 0.85; 95 % confidence interval [CI], 0.757-0.947) showed effective performance in the operating characteristic curve analysis. In the validation cohort, the performance of the combined model was better than that of the radiomics model (AUC, 0.75; 95 % CI, 0.645-0.865; Delong's test p-value = 0.01) and the clinical model (AUC, 0.74; 95 % CI, 0.625-0.851; Delong's test p-value <0.01) alone. The results of the decision curve, nomogram, and calibration analyses demonstrated the clinical utility and good fitness of the combined model. Conclusion: Our study demonstrated the effectiveness of a clinical-radiomics model for predicting rupture status in small aneurysms.

Analysis of the Performance of Gadoxetic Acid Disodium MRI in Predicting Microvascular Invasion of Hepatocellular Carcinoma.

Objective: This study aimed to evaluate the predictive value of gadoxetic acid disodium magnetic resonance imaging (MRI) in the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: 87 HCC patients (2019-01-2022-01) admitted to the hospital were selected for retrospective analysis, gadoxetic acid disodium MRI scan was performed before surgery, and the patients were divided into two groups according to whether the MVI occurred, including the invasion group (n = 47) and the non-invasion group (n = 40). The influencing factors of MVI in HCC patients were explored, independent risk factors were determined, and the correlation between independent risk factors and MVI in HCC patients was analyzed. Results: There were significant differences in tumor margin, peritumoral low signal (hepatobiliary phase), peritumoral enhancement (arterial phase), and peritumoral hyperintensity ring (arterial phase) between the two groups (P < 0.05). Logistic regression analysis showed that unsmooth tumor margin, peritumoral low signal (hepatobiliary phase), peritumoral enhancement (arterial phase), and peritumoral hyperintensity ring (arterial phase) were independent risk factors for MVI in HCC patients (P < 0.05). The results of Spearman correlation analysis showed that unsmooth tumor margin was negatively correlated with MVI in HCC patients (r = -0.66, P=0.037). Moreover, peritumoral low signal (hepatobiliary phase), peritumoral enhancement (arterial phase), and peritumoral hyperintensity ring (arterial phase) were positively correlated with MVI in HCC patients (r 1 = 0.63, r 2 = 0.68, r 3 = 0.72, P 1= 0.030, P 2 = 0.023, P 3 = 0.017). Conclusion: Unsmooth tumor margin, peritumoral low signal (hepatobiliary phase), peritumoral enhancement (arterial phase), and peritumoral hyperintensity ring (arterial phase) are significantly correlated with MVI in patients with HCC, which can provide a reference for the formulation and implementation of clinical interventions.

The Correlation between Osteoporosis and Blood Circulation Function Based on Magnetic Resonance Imaging.

In order to investigate the relationship between changes in blood circulation and bone mineral density (BMD) loss, the characteristic parameters reflecting the function of tissue oxygen metabolism are obtained by means of blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI), image processing and semi-quantitative analysis. The correlation and variance analysis of the characteristic parameters of different BMD groups are carried out, and the physiological parameters of bone marrow blood perfusion are obtained by dynamic enhanced MRI (DCE-MRI). Multivariate logistic regression analysis is carried out with the physiological parameters of blood oxygen metabolism function and bone marrow blood perfusion as independent variables and BMD as dependent variables. It is found that there are significant differences in oxygen metabolism between individual muscles in different BMD groups and between skeletal muscles of different types of muscle fibers. Age, total volume of bone marrow and oxygen metabolism ability of tibial anterior muscle have significant independent effects on osteoporosis. It shows that the changes of blood circulation in bone marrow and surrounding muscle tissue are indeed one of the causes of osteoporosis.