ABSTRACT
Objective To evaluate the gender differences in fat water fraction(FWF)related to fat metabolism in supraclavicular region of neck with iterative decomposition of water and fat with echo asymmetry and least square estimation iron quantification(IDEAL-IQ)sequence quantitatively.Methods Twenty healthy female and twenty healthy male volunteers were selected for a MRI examination with IDEAL-IQ,then the FWF of R2*,brown adipose tissue(BAT)and white adipose tissue(WAT)were obtained by post-processing.The differences of FWF between the two groups were compared by Mann-Whitney U test.Results There was sig-nificant difference in the FWF of BAT and WAT between the two groups(P＜0.05).The FWF of BAT in the female was higher than that the male,and the FWF of WAT in the male was higher than that the female,there was no significant difference in the R2*between the two groups(P＞0.05).Conclusion IDEAL-IQ sequence can be used to evaluate the FWF in supraclavicular region of neck quantitatively,and classify BAT and WAT,then provide clinical according to the quantitative study of fat content.
ABSTRACT
Objective:To investigate the value of radiomics based on three-dimensional high resolution MR vessel wall imaging (3D HRMR-VWI) for identifying culprit plaques in symptomatic patients with middle cerebral atherosclerosis.Methods:The clinical and imaging features of 117 patients (139 middle cerebral artery plaques) with cerebrovascular diseases in Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from October 2018 to October 2020 were respectively reviewed. Stratified random sampling was used to divide 139 plaques into training set (97 plaques) and validation set (42 plaque) at the ratio of 7∶3. The plaques were divided into 69 culprit plaques and 70 non-culprit plaques based on plaque MR features and clinical symptoms. The clinical and imaging characteristics of culprit plaques and non-culprit plaques were compared by independent sample t-test, Mann-Whitney U test and χ 2 test, and factors with significant difference between two groups in univariate analysis were further analyzed by multivariate logistic regression to find out the independent predictors of culprit plaques. Radiomics features were extracted, screened and radiomics model was constructed using pre-and post-contrast 3D HRMR-VWI based on the training set. The combined model was constructed by combining the independent predictors and radiomics model. Receiver operating characteristic curve and area under curve (AUC) were used to evaluate the efficacy of each model, and DeLong test was used to compare the efficacy of different models. Results:Significant difference was found in intraplaque hemorrhage, lumen area of stenosis, stenosis diameter, stenosis rate, plaque burden and enhancement rate between culprit and non-culprit plaques (all P<0.05). Multivariate logistic regression analysis confirmed that only intraplaque hemorrhage was the independent predictor for culprit plaques (OR=7.045,95%CI 1.402-35.397, P=0.018). In the validation set, the AUC of the pre-contrast 3D HRMR-VWI model was lower than that of the post-contrast 3D HRMR-VWI model ( Z=-2.01, P=0.044). The AUC of pre+post-contrast 3D HRMR-VWI model was not significantly different from that of post-contrast 3D HRMR-VWI model ( Z=0.79, P=0.427). The AUC showed no significant difference between combined model and pre+post-contrast 3D HRMR-VWI model ( Z=-0.59, P>0.05). The combined model showed the best performance in predicting culprit plaques of middle cerebral artery (AUC=0.939), with the sensitivity, specificity and accuracy of 95.24%, 76.19% and 85.71%. Conclusion:Radiomics based on 3D HRMR-VWI has potential values in identifying culprit plaques in symptomatic patients with middle cerebral atherosclerosis.