ObjectiveTo observe the characteristics of magnetic resonance angiography of (MRA) ophthalmic artery in patients with diabetic retinopathy (DR).MethodsA total of 36 eyes of DR patients (DR group) diagnosed by clinical examination were included in the study. Among them, there were 42 eyes in 21 males and 15 eyes in 15 females. The average age was 55.2 years old. The average duration of diabetes was 7.56 years. All eyes were examined by MRA and fluorescein fundus angiography (FFA) in the ophthalmic artery. At the same time, 24 eyes of 12 patients were examined by computed tomography angiography (CTA). Twenty-two healthy volunteers with age and gender matching were selected as the control group. Among them, there were 13 males and 9 females. All patients underwent MRA examination of the ophthalmic artery; at the same time, 5 eyes of 5 eyes were examined by CTA. MRA and CTA were classified into three grades according to the development condition and shape change of the ophthalmic artery. 0 grade : no abnormality; grade Ⅰ: mild lesion; grade Ⅱ: obvious lesion. According to the results of FFA examination, it was divided into no obvious disease stage, background stage, proliferative stage, proliferative stage. The morphological features of the MRA of the ophthalmic artery in the DR group and the control group were compared. The relationship between the MRA grading of the ophthalmic artery and the FFA staging was observed in the DR group. The consistency analysis between the MRA and CTA grades of the ophthalmic artery in the DR group was performed by Kappa test; the relationship between the MRA grade and the FFA staging of the ophthalmic artery was analyzed by Spearson correlation analysis of the same data with two-way ordered attributes.ResultsIn 44 eyes of the control group, the MRA in grade 0 and Ⅰ of the ophthalmic artery were 41 and 3 eyes, respectively; all eyes of the CTA examination of the ophthalmic artery were grade 0. In 72 eyes of the DR group, the MRA in grade 0, Ⅰ, and Ⅱ of the ophthalmic artery were 28, 28, and 16 eyes, respectively. Among the 24 eyes examined by CTA, there were 13, 6, and 5 eyes in grade 0, Ⅰ, and Ⅱ, respectively. In the DR group, the classification of MRA and CTA of the ophthalmic artery was highly consistent (Kappa value = 0.86). There were significant differences in the number of eyes with different grades of MRA in the DR group and the control group (Z=-5.74, P=0.000). In 72 eyes of the DR group, there were 8, 12, 22, and 30 eyes in no obvious disease stage, background stage, proliferative stage, and proliferative stage, respectively. Correlation analysis showed that there was a significant correlation between MRA grading and FFA staging in the DR group (r=0.405, P=0.000).ConclusionsMRA can show the changes of ophthalmic artery morphology and reflect DR staging to a certain extent. It has a high consistency with FFA vascular changes.
In order to solve the pathological grading of hepatocellular carcinomas (HCC) which depends on biopsy or surgical pathology invasively, a quantitative analysis method based on radiomics signature was proposed for pathological grading of HCC in non-contrast magnetic resonance imaging (MRI) images. The MRI images were integrated to predict clinical outcomes using 328 radiomics features, quantifying tumour image intensity, shape and text, which are extracted from lesion by manual segmentation. Least absolute shrinkage and selection operator (LASSO) were used to select the most-predictive radiomics features for the pathological grading. A radiomics signature, a clinical model, and a combined model were built. The association between the radiomics signature and HCC grading was explored. This quantitative analysis method was validated in 170 consecutive patients (training dataset: n = 125; validation dataset, n = 45), and cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Through the proposed method, AUC was 0.909 in training dataset and 0.800 in validation dataset, respectively. Overall, the prediction performances by radiomics features showed statistically significant correlations with pathological grading. The results showed that radiomics signature was developed to be a significant predictor for HCC pathological grading, which may serve as a noninvasive complementary tool for clinical doctors in determining the prognosis and therapeutic strategy for HCC.