Objective To access the diagnostic value of Prostate Imaging Reporting and Data System (PIRADS version 2)for prostate cancer (PCa) in prostate specific antigen (PSA) grey zone(4-10 ng/mL).Methods Treatment naive PCa and BPH patients with an increase of PSA 4-10 ng/mL from 2200 patients underwent prostate MRI from 2012 to 2016 were included,multiparameter magnetic resonance imaging (mp-MRI) prior biopsy or prostatectomy and clinical data were obtained,mp-MRI were retrospectively analyzed quantitatively by a radiology expert with 15 years experience in urogenital system imaging diagnosis and a doctor with 5 years experience in radiology diagnosis blind to the pathology results according to PIRADS v2,PIRADS v2 score and lesion zone were recorded respectively,in case of disagreement,dicision was made through discuss.TRUS guided biopsy or prostatectomy pathology serves as gold reference.Diagnostic value of PIRADS v2 for PSA grey zone PCa was calculated by receiver operating characteristic (ROC) curve,logistic regression analysis was used to access the risk factors of PCa.Results 15 PCa and 30 BPH patients were in eluded.There was no significant difference between these two groups in age,tPSA,fPSA,f/tPSA,prostate volume and PSA density.The area under ROC curve of PIRADS v2 in diagnosing PCa was 0.932[95 ％ CI 0.822-0.984],P＜0.01.Using a cutoff PIRADS＞4,the diagnosis sensitivity was 88.89 ％,specificity 87.10 ％,and positive predictive value 80 ％,negative predictive value 93.10％,respectively.Logistic regression analysis showed that PIRADS v2 score was an independent risk factor for predicting PCa,with a hazard ratio 17.847[3.745-85.078],P＜0.01.There was a positive correlation between PIRADS v2score and gleason score,r=0.585,P=0.022.Conclusion PIRADS v2 has a significantly high diagnosis value in diagnosing PSA grey zone PCa and a good correlation with pathology results.

Objective The purpose of this study was to compare the image quality of readout-segmented EPI (RS-EPI) and that of standard single-shot echo-planar imaging (SS-EPI) in patients with scrotal diseases. Methods Initial diagnosis of scrotal diseases were included in the prospective study, all patients underwent scrotum routine MRI and RS-EPI, SS-EPI sequence at 3.0 T. A total of 38 patients were recruited qualitative assessment ,and 29 patients proved by operation and pathology (malignant 21 cases and benign 8 cases) were included quantitative analysis.For qualitative comparison of image quality, two readers independently assessed the two sets of DWI, which consisted of identification of structure and geometric distortion of scrotum (epididymis,testes, lesion) using a 5-point Likert scale. For assessment of image parameters, signal-to-noise ratio (SNR), contrast, contrast-to-noise ratio (CNR),apparent diffusion coefficient value of normal testis and testis distortion ratio of anatomical(T2WI)/DWI fusion image were calculated. Inter-observer agreement was assessed with the Kappa statistics, the differences of scores of
RS-EPI and SS-EPI were compared by using Wilcoxon rank-sum test, and image parameters were compared by using paired sample t test. Results There was good reader agreement in the scores, the Kappa value were 0.77, 0.74, 0.80, 0.87. The difference of identification of structure and geometric distortion on RS-EPI and SS-EPI had statistic significance, the RS-EPI was superior to SS-EPI in image quality (all P<0.05).The SNR, contrast of benign lesion for two sequences had no statistic significance(P values were 0.352, 0.124, respectively), but the difference of CNR had statistic significance(P<0.05). The SNR,contrast and CNR of malignant lesion for two sequences had statistic significance (all P<0.05). The mean size of the testis was (35.61 ± 9.78)mm, the mean distance in fusion image of RS-EPI or SS-EPI with T2WI were (3.80 ± 1.32)mm and (7.54 ± 2.62)mm, and the mean distortion ratios of the two set were (11.1 ± 0.6)% and (22.4 ± 19.2)%, respectively, the difference of two sets had statistic significance(P<0.05). There was no significant difference in the ADC obtained by using either DWI method(t=0.396,P=0.796), the mean ADC values of normal testes for RS-EPI and SS-EPI, respectively, were (1.18 ± 0.06) × 10-3mm2/s, (1.24 ± 0.11) × 10-3mm2/s.Conclusion RS-EPI DWI images is a feasible technique in the scrotum for producing high-resolution DWI with reduced geometric distortion and offers potentially superior image quality compared to SS-EPI at 3.0 T.

Objective To investigate the value of MRI diffusion-weighted imaging (DWI) technique in endocrine therapy for prostate cancer (PCa) based on PI-RADSv2.1. Methods A retrospective analysis of 57 patients with pathologically confirmed PCa was conducted. All patients underwent multi-parametric MRI (mpMRI) according to PI-RADS v2.1 technical specifications before biopsy and six months after endocrine therapy. The apparent diffusion coefficient (ADC) values were measured in cancer and non-cancer areas before biopsy and six months after endocrine therapy. Patients were grouped based on the mRECIST criteria and PSA level into responders (n=45) and non-responders (n=12). ROC curves were obtained to assess the correlation between changes in ADC values and PSA values before and after endocrine therapy. Results In the responder group, the ADC value of the cancer areas was increased significantly after endocrine therapy (P<0.001). No statistically significant difference of the ADC value of the cancer areas was found in the non-responder group before and six months after endocrine therapy (P=0.714). The ADC change of responders and non-responder groups were (0.411±0.178)×10^-3 mm²/s and (-0.014±0.125)×10^-3 mm²/s, respectively (P<0.001); the ADC ratio were (60.603±30.201)% and (-1.096±13.175)%, respectively (P<0.001). The cutoff value of the ADC change was 0.165 (AUC=0.974; sensitivity, 88.89%; specificity, 100.00%; PPV, 100.00%; NPV, 70.59%). The cutoff value of ADC ratio was 16.827% (AUC=0.980; sensitivity, 91.11%; specificity, 100.00%; PPV, 100.00%; NPV, 75.00%). The ADC values were negatively correlated with serum PSA before and after endocrine therapy. Conclusion The ADC change and ADC ratio may be facilitated to monitor the efficacy of endocrine therapy for PCa. The ADC values were negatively correlated with serum PSA.

Objective: To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visualscore in evaluating clinical classification of severity of coronavirus disease (COVID-19). Materials and Methods: We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji MedicalCollege from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data werecollected, and based on the clinical classification of severity, patients were divided into groups 1 (mild) and 2 (severe/critical). A semiquantitative visual score was used to estimate the lesion extent. A three-dimensional slicer was used toprecisely quantify the volume and CT value of the lung and lesions. Correlation coefficients of the quantitative CT parameters,semiquantitative visual score, and clinical classification were calculated using Spearman’s correlation. A receiver operatingcharacteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods. Results: There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groupswere not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 hadlarger values for all volume-dependent parameters (p < 0.001). The percentage of lesions had the strongest correlation withdisease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative scorewas 0.349. To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807;95% confidence interval, 0.744–0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher thanthat of the semiquantitative visual score (p = 0.001). Conclusion The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitativevisual score in terms of evaluating the severity of COVID-19.

Objective:To investigate the value of texture analysis based on T 2WI and apparent diffusion coefficient (ADC) maps in discriminating low grade from high grade prostate cancer (PCa). Methods:Retrospective analysis was performed on patients who were confirmed to be PCa by pathology after surgery and underwent MRI examination in the department of radiology,Tongji Hospital,Tongji Medical College, Huazhong University of Science and Technology before radical surgery, including routine T 1WI, T 2WI and diffusion weighted imaging (DWI) sequences. 3D data analysis module of the MaZda software was used to manually draw region of interest (ROIs) slice by slice on T 2WI and ADC images, and generate volume of interest (VOI) of the entire tumor. MaZda software was also used to extract texture features. The independent sample t test or Mann-Whitney U test were used to identify the texture features with statistically significant differences between low and high grade PCa groups. Lasso regression model was used to select the best combination of texture features for identifying low and high grade PCa, and then the model was built. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of the model in both training cohort and test cohort. Results:The best texture feature combination selected by Lasso regression model were the S (1, 0, 0) correlation of T 2WI and the S (1, 0, 0) correlation, S (1, -1, 0) sum entropy and vertical-run length nonuniformity of ADC maps. The area under the ROC curve (AUC) of the model in training cohort was 0.823, and the sensitivity and specificity were 70.4% and 80.8%, respectively, which were better than the single texture feature. The AUC of the model in test cohort was 0.714, which was worse than training cohort. Conclusion:The texture analysis of T 2WI and ADC maps is valuable for the identification of low and high grade PCa.