BACKGROUND:Radiation-induced brain injury has recently become an increasing area of research, in particular in animal experimental studies. Domestic and international researches show that there have been no uniform scanning parameters used for examination of animal models of radiation-induced brain injury by magnetic resonance imaging. In this study, we performed magnetic resonance imaging in rabbits to determine related sequence parameters. OBJECTIVE:To establish the New Zealand rabbit models of radiation-induced brain injury, and obtain the brain magnetic resonance images of rabbits using LOOP7 coil, so as to provide experimental evidence for diagnosis of radiation-induced brain injury by magenetic resonance imaging. METHODS:Each of T2-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy and magnetic susceptibility-weighted imaging were performed several times through the use of LOOP7 coil, to determine the optimal scanning parameters for each sequence. Rabbit models of radiation-induced brain injury were established and then their right hemispheres were irradiated using 6 MV X-rays at a single dose of 40, 80 and 120 Gy. The daily performance and dynamic magnetic resonance signs of rabbits were observed. The brain tissue was taken for pathological examination once abnormal magnetic resonance findings were observed or after 20 weeks of folow-up. RESULTS AND CONCLUSION:Only one rabbit model in the 40 Gy group had subdural hemorrhage. In the 80 Gy group, abnormal T2-weight imaging signals were observed in al rabbit models, which were pathologicaly confirmed as scattered degenerated neurons and infiltrated neutrophils. The abnormal signals that gradualy expanded over time were seen in rabbits from the 120 Gy group by magnetic resonance imaging and were pathologicaly confirmed as radiation-induced brain injury loci. The results confirm that establishing rat models of radiation-induced brain injury using radiation therapy system can better simulate the pathological process of radiation-induced brain injury; moreover, this model can be applied to receive routine magnetic resonance examination with LOOP7 coil.

Objective To discuss the application of routine CT three-phase perfusion parameter,that is arterial enhancement fraction (AEF) value,in evaluating the curative effect of transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma (HCC).Methods The clinical data of a total of 30 patients with pathologically proved HCC were enrolled in this study.Routine CT three-phase perfusion scan was performed 1-3 days before as well as 30-40 days after TACE in all patients.AEF value was calculated by using CT Kinetics software (GE Healthcare).The formula for calculating AEF value was as follows:AEF value=(arterial phase CT value-plain scan CT value)÷(portal phase CT value-plain scan CT value).The results were statistically analyzed.Results Effective treatment group had 17 patients,and ineffective treatment group had 13 patients.The postoperative AEF values in the effective treatment group and the ineffective treatment group were (0.351±0.090) and (0.438±0.050) respectively,the difference between the two groups was statistically significant (P＜0.05).Taking postoperative AEF value of 0.392 as the critical value to predict the postoperative effect of TACE,the sensitivity and specificity were 86.7％ and 73.2％ respectively,and the area under the curve was 0.876 (P＜0.001).Conclusion The routine CT three-phase perfusion parameter (AEF) can quantitatively reflect the hemodynamic changes of HCC after TACE,which is helpful for making early evaluation of TACE effect,meanwhile,no additional radiation dose will be added.

Objective To explore the value of CT radiomics model in predicting three-year survival time in patients with primary hepatocellular carcinoma (HCC). Methods Eighty one patients pathologically or clinically confirmed HCC and B stageof Barcelona clinical liver cancer before transcatheter arterial chemoembolization (TACE) in Zhejiang Cancer Hospitalwere retrospectively enrolled from January 2010 to June 2014.A primary cohort consisted of 64 patients and an independent validation cohort consisted of 17 patients. The patients were divided into survival group of 39 cases and death groupof 42 cases duringthree-year follow-up. All the patients underwentnon-enhanced and contrast-enhanced CTimages scan before TACE. Three hundered and seventy six quantization radiomics features were extracted from the arterial phase and portal phase CTimages of target lesion. LASSO regression model was used for data dimension reduction. Logistic regression was used to develop the prediction model. The predictive ability of the model was validated using the area under the curve (AUC) of receiver operating characteristic(ROC) analysis. Results The radiomics features selected from the arterial and portal phase were 8 and 5, respectively. The arterial prediction model showed AUC=0.833, sensitivity=83.9％(26/31), specificity=81.8％(27/33), accuracy=82.8％(53/64)in primary datasetand AUC=0.861, sensitivity=75.0％(6/8), specificity=100.0％(9/9), accuracy=88.2％(15/17)in independent validation dataset.The portal prediction model showed AUC=0.858, sensitivity=83.3％(25/30), specificity=85.3％(29/34), accuracy=84.4％(54/64)in primary dataset and AUC=0.750, sensitivity=75.0％(6/8), specificity=100.0％(9/9), accuracy=88.2(15/17)in independent validation dataset. Conclusion This study shows CT radiomics model can be conveniently used to facilitate the preoperative individualized prediction of three-year survival time in patients with HCC.