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Objective:To investigate the value of artificial intelligence (AI)-assisted quantitative measurement in evaluation of the dynamic changes of CT for COVID-19 pneumonia.Methods:The clinical and chest CT dynamic imaging data of 99 patients with confirmed COVID-19 pneumonia who were hospitalized in Wuhan Central Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 15, 2020 to March 10, 2020 were retrospectively analyzed. According to the definitive diagnosis, the 99 patients were classified into common ( n=36), severe ( n=33) and critical ( n=30) type, the CT imaging findings of each type were analyzed, including CT basic signs, total volume of pneumonia lesions and percentage of pneumonia lesions of the total lung volume (volume ratio). AI software was used to quantitatively evaluate the dynamic changes of chest CT images. The quantitative indicators included CT peak time of lesions, total volume of lesions peak, volume ratio of lesions peak, maximum growth rate of total volume and maximum growth rate of volume ratio. Kruskal-Wallis rank sum test was used to compare the difference of quantitative indexes between the 3 types, and χ 2 test or Fisher exact probability test was used to compare the difference of qualitative indexes between the 3 types. Sequence measurement and scatter plots were used to show the evolution trend of the volume ratio of the three types of COVID-19 pneumonia lesions. The ROC curve was used to analyze the value of the volume ratio of pneumonia lesions and its maximum growth rate in predicting the conversion of common pneumonia to severe or critical pneumonia. Results:There were statistically significant differences in age and gender distribution among patients with common, severe and critical COVID-19 ( P<0.05), the age of severe and critical types were significantly higher than that of common type ( P<0.01). Compared with common [2.5 (1.0, 5.0) d] and critical type[2.5 (1.0, 4.0) d], the time from onset to the first chest CT scan of severe type was prolonged [5.0 (2.5, 8.0) d, P<0.01]. There were statistically significant differences in involvement of multiple lung lobes (20 cases, 29 cases, 25 cases, χ2=10.403, P=0.006) in patients with common, severe and critical COVID-19 at the first scan, the incidence of the involvement of multiple lung lobes in severe and critical types was significantly higher than that of common type ( P=0.002). The volume ratios of patients with common, severe and critical COVID-19 at the first scan were statistically significant [1.0% (0.2%, 4.7%), 9.30% (1.63%, 26.83%), 2.10% (0.64%, 8.61%), Z=14.236, P=0.001], and the volume ratio of severe type was significantly higher than that of common type ( P<0.001), there was no statistically significant difference between common type and critical type ( P=0.062). Follow-up CT showed that the pneumonia lesions showed a dynamic transformation of progress and recovery, and it was seen that the coexistence of multiphase lesions. The trend line in the scatter plot of the three types of COVID-19 pneumonia lesions showed that the lesions in the advanced stage developed from less to more. The lesion peak volume ratios of the common, severe and critical types were 9.75% (4.83%, 13.18%), 29.80% (23.99%, 42.36%) and 61.81% (43.73%, 72.82%), respectively, the difference was statistically significant ( Z=74.147, P<0.001). The maximum growth rates of lesion volume ratio were 1.27% (0.50%, 1.81%)/d, 4.39% (3.16%, 5.54%)/d and 6.02% (4.77%, 9.96%)/d, respectively, the difference was statistically significant ( Z=52.453, P<0.001). The peak times of lesions were 12.0 (9.0, 15.0) d, 13.0 (10.0, 16.0) d and 16.5 (12.0, 25.0)d, respectively, the difference was statistically significant ( Z=9.524, P=0.009). Taking the volume ratio of pneumonia lesion 22.60% and the maximum growth rate of the volume ratio 1.875%/d as the boundary value, the sensitivity of diagnosing common type to severe or critical type was 92.10% and 96.83%, and the specificity was 100% and 80.56%, respectively. The area under the curve was 0.987 and 0.925, respectively. Conclusions:The lesions of COVID-19 pneumonia show a similar parabolic change on CT imaging. The use of AI technology to dynamitcally and accurately measure the CT pneumonia lesion volume ratio is helpful to evaluate the severity of the disease and predict the development trend of the disease. Patients with a rapid growth of volume ratio are more likely to become severe or critical type.
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Objective ToassessthevalueofGdGEOBGDTPAenhancedT1ρimaginginevaluatingtheseverityandinflammation gradeinnonalcoholicsteatohepatitis(NASH)rabbitsmodel.Methods NASH modelswereestablishedin26adultrabbitsbyfeeding withthehighGfat,highGcholesteroldietinavarieddurations (0,4,8,12 weeks).T1ρ,T1ρinthehepatobiliaryphase (HBP)and changeofT1ρ(Δ%)werecomparedamongthedifferentgroupswhichweredeterminedbydifferentnonGalcoholicfattyliverdisease activityscore(NAS)andinflammationgrades.SpearmancorrelationanalysiswasusedtoassessthecorrelationsofT1ρ,T1ρ(HBP) withNASscoresandinflammationgrades.ROCcurvewasperformedtoevaluatethediagnosticvalueofT1ρ,T1ρ(HBP)inpredicting NASHandadvancedinflammation.Results T1ρandT1ρ(HBP)werepositivelyassociatedwithNASandinflammationscores.The differencesofT1ρ(HBP)amongNASH,nonalcoholicfattyliver(NAFL)andnormalliverwerestatisticallysignificant(P＜0.05). T1ρ(HBP)wassignificantlydifferentintherabbitswithgrade3inflammationfromintherabbitswithgrade0,grade1andgrade2 inflammation (P＜0.05).AUCsofT1ρandT1ρ(HBP)fordifferentiatingNASH were0.849and0.949,respectively.AUCofT1ρand T1ρGHBPfordiagnosinggrade2andgrade3inflammationwere0.925and0.922,respectively.Fibrosisandinflammationwerethe mainindependentfactorsaffectingT1(HBP).Conclusion GdGEOBGDTPAenhancedT1ρimagingcanreflecttheseverityofNASH anddegreeofinflammation.T1ρ(HBP)mightbeamoresuperiornoninvasiveimagingbiomarkerthannonGenhancedT1ρforassessmentof NASHactivityandinflammationgrading.
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Objective To explore the values of metrics on intravoxel incoherent motion (IVIM) and gadoxetic acid enhanced T1ρ imaging for staging of non?alcoholic fatty liver disease activity scores (NAS) and inflammation in nonalcoholic steatohepatitis (NASH) rabbits model. Methods NASH rabbits model was established by feeding with a varied duration (4, 8, 12 weeks) of high?fat, high?cholesterol diet. IVIM and gadolinium?ethoxybenzyl?diethylenetriamine pentaacetic acid (Gd?EOB?DTPA) enhanced T1ρ images were performed by a 3.0 T MR scanner. The inter?class correlation coefficients (ICC) and Bland?Altman analysis were applied to evaluate the reproducibility of the IVIM and Gd?EOB?DTPA enhanced T1ρ mapping measurers. Spearman correlation analysis were used to assess the correlation between MR metrics, including ADC, D, D*, f, T1ρ, T1ρ (hepatobiliary phase, HBP), and NAS score and inflammation grades respectively with reference to histopathology. ROC curve analysis was used to evaluate the diagnostic performance of T1ρ and IVIM parameters for NASH, inflammation grade, and hepatic fibrosis. Multiple linear regression equations were used to analyze the independent influence factors of T1ρ (HBP). Results The f value was negatively correlated with the NAS score (r=-0.530, P<0.01). The f value of the fibrosis S1?2 was significantly lower than that of the S0 (P<0.01). There was no statistical difference in D, D*, ADC among NASH score, inflammation, and fibrosis stage. T1ρ and T1ρ (HBP) values were positively correlated with NAS scores and inflammation grades. The area under curve (AUC) for the diagnosis of NASH for T1ρ, T1ρ(HBP), ADC, D, D*, and f values were 0.849, 0.949, 0.728, 0.596, 0.522, and 0.871, respectively. The AUCs of T1ρ (HBP)+f in the diagnosis of NASH, G2?3 inflammation, and F1?2 fibrosis were 0.971, 0.935, and 0.903, respectively. Fibrosis (R2=0.624, P=0.002) and inflammation (R2=0.746, P=0.002) were major independent factors of T1ρ (HBP). Conclusion Gd?EOB?DTPA enhanced T1ρ imaging can reflect the severity of NASH and degree of inflammation. IVIM measurements are not accurate enough to stage liver inflammatory activity of NASH. T1ρ (HBP)+f might be a superior noninvasive imaging biomarker than either non?enhanced T1ρ or IVIM for NASH activity and inflammation assessments.
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Objective@#To explore the values of metrics on intravoxel incoherent motion (IVIM) and gadoxetic acid enhanced T1ρ imaging for staging of non-alcoholic fatty liver disease activity scores (NAS) and inflammation in nonalcoholic steatohepatitis (NASH) rabbits model.@*Methods@#NASH rabbits model was established by feeding with a varied duration (4, 8, 12 weeks) of high-fat, high-cholesterol diet. IVIM and gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced T1ρ images were performed by a 3.0 T MR scanner. The inter-class correlation coefficients (ICC) and Bland-Altman analysis were applied to evaluate the reproducibility of the IVIM and Gd-EOB-DTPA enhanced T1ρ mapping measurers. Spearman correlation analysis were used to assess the correlation between MR metrics, including ADC, D, D*, f, T1ρ, T1ρ (hepatobiliary phase, HBP), and NAS score and inflammation grades respectively with reference to histopathology. ROC curve analysis was used to evaluate the diagnostic performance of T1ρ and IVIM parameters for NASH, inflammation grade, and hepatic fibrosis. Multiple linear regression equations were used to analyze the independent influence factors of T1ρ (HBP).@*Results@#The f value was negatively correlated with the NAS score (r=-0.530, P<0.01). The f value of the fibrosis S1-2 was significantly lower than that of the S0 (P<0.01). There was no statistical difference in D, D*, ADC among NASH score, inflammation, and fibrosis stage. T1ρ and T1ρ (HBP) values were positively correlated with NAS scores and inflammation grades. The area under curve (AUC) for the diagnosis of NASH for T1ρ, T1ρ(HBP), ADC, D, D*, and f values were 0.849, 0.949, 0.728, 0.596, 0.522, and 0.871, respectively. The AUCs of T1ρ (HBP)+f in the diagnosis of NASH, G2-3 inflammation, and F1-2 fibrosis were 0.971, 0.935, and 0.903, respectively. Fibrosis (R2=0.624, P=0.002) and inflammation (R2=0.746, P=0.002) were major independent factors of T1ρ (HBP).@*Conclusion@#Gd-EOB-DTPA enhanced T1ρ imaging can reflect the severity of NASH and degree of inflammation. IVIM measurements are not accurate enough to stage liver inflammatory activity of NASH. T1ρ (HBP)+f might be a superior noninvasive imaging biomarker than either non-enhanced T1ρ or IVIM for NASH activity and inflammation assessments.
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Objective To explore the predictive value of CT image texture analysis for early enlargement of hypertensive intracerebral hemorrhage.Methods One hundred and eight patients with hypertensive intracerebral hemorrhage were divided into enlarged hematoma group (positive group)and non-enlarged hematoma group (negative group),according to whether the volume of hematoma on 24 h follow up CT scan was more than 30% or 6 mL of the baseline CT.Phillis Radiomics Tool V93 software was used to segment the hematoma on CT plain scan images of two groups,four features of first-order and three of gray-level co-occurrence matrix (GLCM),thirteen of gray-level size zone matricx (GLSZM)and eleven of gray-level run-length matricx (GLRLM)were obtained.The differences of thirty-one texture features between the two groups were compared.The ROC curves of the features with statistical differences were analyzed.The independent predictors of early enlargement of intracerebral hemorrhage were screened by Logistic multivariate regression model.Results Among the one hundred and eight patients,twenty-eight were positive group and eighty were negative group.Skewness and long run low gray-level emphasis (LRLGE)in positive group were significantly higher than those in negative group (P＜0.05).There was no significant difference in the remaining twenty-nine features between the two groups (P＞0.05).ROC curve analysis showed that the AUC of Skewness,LRLGE and their combined diagnosis were 0.634,0.814 and 0.828,respectively.The independent variables were screened by stepwise regression analysis.The LRLGE (OR＝1.238,95%CI＝1.009－1.51 9,P＜0.05)was selected as the regression model, suggesting that LRLGE was an independent predictor of the early enlargement of intracerebral hemorrhage.Conclusion Texture analysis of CT images is helpful to predict the early enlargement of hypertensive intracerebral hemorrhage,and LRLGE based on GLRLM algorithm can be used as an independent predictor.
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Objective To investigate the MRI manifestations and diagnostic value of adenomatoid tumor (AT)of epididymis. Methods The MRI features of 5 patients with AT of epididymis were analyzed retrospectively,which were confirmed by histopathology,and some relevant medical literatures were reviewed.Results The epididymal tumor was manifested as moderate signal on T1 WI and T2 WI,similar to adjacent testicule,and as moderate signal with slightly high rim-enhancement on enhanced T1 WI in 4 cases.Secondary infarction and chronic granulomatous inflammation in 1 patient was found and presented unevenly moderate signal on T1 WI,slight hypointensity on T2 WI, hyperintensity on DWI and rim-enhancement on dynamic enhancement MRI.Few hydrocele was detected in all 5 patients.Conclusion AT of epididymis is a rare benign neoplasm with some characteristic MRI features which is helpful for the preoperative diagnosis.
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Objective:To investigate the correlation between the breast cancer MRI schedule of reinforcement and the shrinkage pattern of tumor after neo-adjuvant chemotherapy, and its clinical significance in the guidance of formulating operation plan. Methods:Dynamic contrast-enhanced MRI scan was performed before chemotherapy and before surgery after a whole-range N-Acety-L-Cysteine (NAC) treatment in 55 patients with loco-regionally advanced breast cancer who received the neo-adjuvant chemotherapy. MRI sched-ule of reinforcement and the shrinkage pattern of tumor after neo-adjuvant chemotherapy were obtained in the treatment, and the corre-lation between the two was analyzed. Results:Of the 55 patients, the unilateral breast mass was found in 54 and the bilateral lesion in 1. There were 56 neo-plastic foci in these patients. The mass-like enhanced image was seen in 24 of the total cases (43%), of which 23 presented with a centripetal shrinkage, 1 with an annular decline, (P0.05). There were 11 of the total cases with non-tu-mor-like enhancement (20%), in which 4 assumed a centripetal shrinkage and 7 a honeycombed multifocal shrinkage (P<0.01). Conclu-sion:The tumor shrinking pattern and its accurate radiological image evaluation are the keys to the selection of breast-conserving sur-gery and the control of local recurrence after treatment of NAC regimen. We can predict the shrinking pattern through the type of the le-sion on baseline before NAC, which is important for the patients and surgeon to get a reasonable expectation in the subsequent treat-ments.
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Objective To compare the image quality of chest low dose CT (LDCT) using automatic exposure control (AEC) and constant current control (CCC) and explore a more reasonable scanning protocol. Methods Two hundred and eighty participants were examined with 64 CT scanner at 7 centers in China. All were divided into 4 groups. Two groups underwent LDCT using AEC with standard deviation set at 25 (A1) and 30 (A2) respectively and the tube current ranged from 10 mA to 80 mA. The other two groups underwent LDCT using CCC with tube current set at 40 mA (C1) and 50 mA (C2) respectively. The axial and MPR images were evaluated by two radiologists who were blinded to the scanning protocols.The radiation dose, noise and the image quality of the 4 groups were compared and analyzed statistically.Differences of radiation dose and noise among groups were determined with variance analysis and t test,image quality with Mann-Whitney test and the consistency of diagnosis with Kappa test. Results There was a significant lower DLP in AEC group than in CCC group [(82.62±40.31)vs ( 110.81±18.21) mGy·cm (F =56. 88 ,P ＜ 0. 01 )], whereas no significant difference was observed between group A2 and group A1 0. 05]. The noisy of AEC group was higher than that of CCC group both on lung window(41.50±9.58 vs 40.86±7.03) and mediastinum window (41.19±7.83 vs 40.92±9.89), but there was no significant difference( Flung =0.835, P=0.476, Fmediastinum =1.910, P=0.128).The quality score of axial image in AEC group was higher than that in CCC group (superior margin of the brachiocephalic vein level: 4.49±0.56 vs4.38±0.64,superior margin of the aortic arch: 4.86±0.23 vs 4.81±0.32,the right superior lobar bronchus Level:4.87±0.27 vs 4. 84 ± 0. 22, the right middle lobar bronchus Level: 4.90±0.25 vs 4.88±0.21) except on the right inferior pulmonary vein level(4. 92 ±0. 25 vs 4. 93 ±0. 17) and superior margin of the left diaphragmatic dome level (4. 91±0.27 vs 4.93±0.22) on lung window, but no significant differences (F=0.076-1.748, P＞0.05) were observed. A significant higher score in AEC group was observed on mediastinum window compared with CCC group on superior margin of brachiocephalic vein level (2.57±0.77 vs 2. 46 ± 0. 59, F = 8. 459, P ＜ 0. 05 ), however, the score of AEC group was lower than that of CCC group on other levels without significant differences (superior margin of the aortic arch:3.36 ±0. 63 vs 3.45 ±0. 60,the right superior lobar bronchus level: 3.94 ±0. 56 vs 3. 95 ±0. 51 ,the right middle lobar bronchus Level: 3.80 ±0. 58 vs 3. 87 ±0. 50,the right inferior pulmonary vein level: 3.72 ±0. 56 vs 3.78 ±0. 53, superior margin of the left diaphragmatic dome level: 3.58 ± 0.63 vs 3.68±0.56,F=0.083-3.380,P ＞ 0.05 ). The MPR image quality of AEC group was better than that of CCC group both on lung window and mediastinum window (Zlung =-2.258, Zmedlastinum=-1.330, P＞0.05). For all participants including the underweighted group, the normal group and the overweighted group, the image quality of A1 group was better than that of A2 group without significant differences (the underweighted group: Zlung=0.000, P=1.000, Zmedastinum= 0.000, P=1.000;the normal group: Zlung =-0.062, P=0.950, Zmediastinum =-0.746, P = 0.456; the overweighted group: Zlung = - 1.177, P = 0.239,Zmediastinum =-1.715, P=0.144) both on lung and mediastinum windows, and for the higher BMI participants, a better image quality was obtained in A1 group than in A2 group on the mediastinum window (Z = -1. 715, P = 0. 144). Conclusions The total radiation exposure dose of AEC group is significantly lower than that of CCC group, but no statistical significant differences are observed between both groups in image quality and noise level. The AEC technique is highly recommended in thoracic LDCT scan for screening program, and the SD25 ( SD value = 25) scan protocol is suggested for higher BMI population while the SD30 (SD value = 30) scan protocol for lower BMI population.
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Objective To investigate ~1H-MRS findings of brain tumor and the clinical application of ~1H-MRS.Methods 80patients with brain tumors clinically or pathologically-proved underwent ~1H-MRS.Normal opposite hemispheres in 30 cases were used as control group.Single voxel spectroscopy(SVS) or 2D-MRS imaging was performed with excited echo sequence.The mean ratio of metabolisms with difference was compared.Results Compared with control group,NAA of tumor decreased in certain degree(P