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Objective To explore the application of time series autoregressive integrated moving average (ARIMA) based on seasonal difference to predict the number of syphilis cases in Anhui Province, and to provide a reference for early warning and control of syphilis. Methods Using R 3.6.2 software, the number of syphilis cases in Anhui Province from January 2004 to December 2016 was used for model fitting, and the resulting model was used to predict the incidence from January to December 2017. The difference between the predicted value and actual observed value was compared to evaluate the prediction effect of this model fitting. Results The incidence of syphilis in Anhui Province was on the rise with obvious periodicity. ARIMA(1,1,1)(0,1,2)12 was the optimal model, with the AIC being -264.81 and the BIC being -249.99. Box-Pierce test showed that λ2 value was 1.444(P=0.963), 10.459(P=0.576), and the difference was not statistically significant (P>0.05), indicating that the residual sequence was white noise. The model accuracy effect evaluation showed that the MAE was 0.06, the RMSE was 0.09, and the MAPE was 1.00%, indicating that the model fitting effect was good. The 2017 data was used to test the effect of the model extrapolation, and the results showed MAPE=6.09%, indicating that the model extrapolation effect was good. The actual value fell within 95% confidence interval of the predicted value, and the model prediction effect was relatively ideal. Conclusion The ARIMA(1,1,1)(0,1,2)12 model could better fit and predict the number of syphilis cases in Anhui Province, which may provide a theoretical basis for early warning, prevention and control of syphilis.
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Autoimmune pancreatitis (AIP) is a unique subtype of chronic pancreatitis, which shares many clinical presentations with pancreatic ductal adenocarcinoma (PDA). The misdiagnosis of AIP often leads to unnecessary pancreatic resection. F-FDG positron emission tomography/ computed tomography (PET/CT) could provide comprehensive information on the morphology, density, and functional metabolism of the pancreas at the same time. It has been proved to be a promising modality for noninvasive differentiation between AIP and PDA. However, there is a lack of clinical analysis of PET/CT image texture features. Difficulty still remains in differentiating AIP and PDA based on commonly used diagnostic methods. Therefore, this paper studied the differentiation of AIP and PDA based on multi-modality texture features. We utilized multiple feature extraction algorithms to extract the texture features from CT and PET images at first. Then, the Fisher criterion and sequence forward floating selection algorithm (SFFS) combined with support vector machine (SVM) was employed to select the optimal multi-modality feature subset. Finally, the SVM classifier was used to differentiate AIP from PDA. The results prove that texture analysis of lesions helps to achieve accurate differentiation of AIP and PDA.
Subject(s)
Humans , Adenocarcinoma , Diagnostic Imaging , Algorithms , Autoimmune Diseases , Diagnostic Imaging , Diagnosis, Differential , Fluorodeoxyglucose F18 , Pancreatic Neoplasms , Diagnostic Imaging , Pancreatitis , Diagnostic Imaging , Positron Emission Tomography Computed Tomography , Support Vector MachineABSTRACT
Objective To investigate the correlativity between elasticity modulus and pathological severity in chronic pancreatitis (CP).Methods Twenty-one pigs were divided randomly into experimental group (n=18) and control group (n=3) using random number method.The main pancreatic duct (MPD) was incompletely ligated to establish the CP model.In control group, MPD was not ligated.The animals were killed in batches at 4th, 8th and 12th week after surgery.The pancreatic tissue was taken for elasticity modulus test and pathological examination, and the pigs were classified into control, mild, moderate and severe groups based on the severity of fibrosis.Cell density, fat infiltration and extracellular edema were observed and classified into mild and severe.The difference of elasticity modulus among different groups were compared by Variance analysis, the correlation between pancreatic fibrosis and elastic modulus was analyzed with Spearman correlation analysis, and ROC curve was used to evaluate its efficacy of diagnosing CP.Results Sixteen CP models were established successfully expected for 2 deaths (mild, n=7;moderate, n=2 and severe, n=7).All of the control group (n=3) showed normal pancreas.The elasticity modulus of control, mild and moderate to severe group were 0.4268±0.0566, 0.3203±0.0518 and 0.2235±0.0685, respectively.The difference between the groups was statistically significant (F=13.658,P0.05).Conclusions The elasticity modulus can be used to detect the pathological changes of CP, and evaluate the CP pathologic grades.
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Objective To investigate the correlativity between secretin-stimulated magnetic resonance cholangiopancreatography (sMRCP) findings and pathological severity in a swine chronic pancreatitis (CP) model. Methods Thirty-nine swine were divided randomly into control group (n=12) and experimental group (n= 27). In experimental group, the main pancreatic duct (MPD) was incompletely ligated to establish the model of obstructive CP. In control group, laparotomy was performed but without ligating the MPD. At the 4th, 8th and 12th week after modeling, one third swine of each group were undergone a series of dynamic sMRCP scans before (0 min) and at 1, 3, 5, 7, 9, 11 min after administration of secretin (0.6 μg/kg). And the MPD diameter and duodenum filling (DF) degree were measured. All survivals were sacrificed to pathological examination including HE and Van Gieson staining for histopathological grading. According to pathological severity, swine were divided into normal group, mild CP group and moderate to severe CP group. MRI features and indexes, including baselined diameter (BD), end diameter (ED), maximum diameter (MD), the largest expansion rate (LER), time to peak (Tpeak) and end change rate of pancreatic duct and duodenal filling (DF) scores were measured. The relationships between pathological grading and sMPCP indexes were analysed. The comparison of sMRCP data among the 3 groups were used ariance analysis, χ2 test and U test. Correlations between sMPCP indexes and pathological severity were tested using Spearman rank correlation coefficients. The diagnostic efficiency of sMRCP indexes were evaluated by ROC method. Results (1) In experimental group, 22 CP models were established and 19 CP swine (mild CP, n= 8; moderate and severe CP, n=11) were performed sMRCP successfully. Eleven swine in normal group were obtained satisfactory MRCP images. (2) sMRCP results:BD of 3 groups were (1.56 ± 0.46),(2.95 ± 1.17),(7.41 ± 1.91) mm, respectively. ED were (1.49 ± 0.31),(2.96 ± 1.17) and (7.37±1.90) mm, respectively. MD were (2.39±0.43),(3.91±1.27) and (7.86±1.87)mm, respectively. The median of LER were 42.10%, 34.85% and 6.58%, respectively. The median of DF scores were 3, 3, 2, respectively. The differences of above indexes have statistically significance (P values were all0.05),and no correlation with pathological severity(P values were all>0.05).For differential diagnosis between normal and mild CP, the area under ROC of BD, ED, MD, LER and DFscores were 0.915, 0.977, 0.926, 0.778 and 0.472, respectively and differential diagnosis between mild CP and moderate to severe CP group, the area under ROC were 0.966,0.966,0.960,1.000 and 0.915, respectively. Conclusions sMRCP findings of CP have characteristics and could be used for in vivo evaluation on the CP pathologic grades.
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Objective To evaluate 99mTc-ciprofloxacin (Infecton) scintigraphy as a method for detecting secondary infections associated with ANP in swine,in comparison with CT.MethodsTwenty-eight healthy swine were randomly assigned to control group (n =6),non-infected ANP (n =6) and infected ANP group( n =16).ANP model was induced by retrograde injection of sodium taurocholate and pancreatic protease mixture into the biliary and pancreatic duct.Two days after ANP induction,swine in infected ANP group were injected with 3 x 108 E.coli into pancreatic tissue,while swine in non-infected ANP group were injected with inactivated E.coli.At 7 d after inoculation,at 0.5,1,2,3,4,and 6 h after intravenous administration of 370 MBq of Infecton,SPECT scan was performed.Then 64-slice spiral CT scan was performed.Then swine were sacrificed,and histopathology examination and bacterial culture of pancreatic tissue were performed.The sensitivity,specificity,accuracy,positive predictive value and negative predictive value of the two methods to detect secondary infections were determined.ResultsThere were no abnormality in the normal pancreas and the bacterial culture was negative.There were pancreatic necrosis in the non-infected ANP group,but the bacterial culture was negative.There were pancreatic necrosis and infection in the infected ANP group and the bacterial culture was positive.The sensitivity,specificity,accuracy,positive predictive value and negative predictive value of the Infecton method were 93.8％ ( 15/16 ),91.7％ ( 11/12 ),92.9％ ( 26/28 ),93.8 ％(15/16) and 91.7％ ( 11/12),whereas these values for CT were 12.5％ (2/16),100.0％ ( 12/12),50.0％(14/28),100.0％ (2/2) and 46.2％ (12/26),respectively.The sensitivity,accuracy,and negative predictive value of the Infecton method were significantly higher than those in CT group (P ＜0.01 ).ConclusionsInfecton scintigraphy may be a better procedure for detecting ANP secondary infections than CT.