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Objective:To develop and verify a predictive model based on CT characteristics for predicting infected walled-off necrosis (IWON) in MSAP and SAP patients.Methods:The clinical and CT data of 1 322 patients diagnosed as MSAP and SAP according to the 2012 Atlanta revised diagnostic criteria in the First Affiliated Hospital of Naval Medical University from January 2015 to December 2020 were continuously collected. Finally, 126 patients who underwent enhanced CT scans within 3 days after admission and percutaneous catheter drainage of WON during hospitalization were enrolled. Among them, there were 63 MSAP and 63 SAP patients. According to the results of the culture from drainage fluid, the patients were divided into sterile walled-off necrosis group (SWON group, n=31) and infected walled-off necrosis group (IWON group, n=95). Patients were divided into training set (18 patients with SWON and 74 patients with IWON from January 2015 to December 2018) and validation set (13 patients with SWON and 21 patients with IWON from January 2019 to December 2020). Univariate and multivariate logistic regression analysis were performed to establish a model for predicting IWON. The model was visualized as a nomogram. The receiver operating characteristic curve (ROC) was drawn. The predictive efficacy of the model was evaluated by the area under the curve (AUC), sensitivity, specificity and accuracy, and the clinical application value was judged by decision curve analysis (DCA). Results:Univariate regression analysis showed that age, etiology, WON with bubble sign and the lowest CT value of WON were significantly associated with IWON. Multivariate logistic regression analysis showed that older age, biliary acute pancreatitis, WON with bubble sign, and the greater minimum CT value of WON were independent predictors for IWON. The formula for the prediction model was 0.12+ 0.01 age-0.75 hyperlipidemia-1.62 alcoholic-2.62 other causes+ 19.18 WON bubble sign+ 0.10 minimum CT value of WON. The AUC, sensitivity, specificity, and accuracy of the model were 0.85 (95% CI 0.76-0.94), 67.57%, 88.89%, and 71.74% in the training set and 0.78(95% CI0.62-0.94), 66.67%, 84.62%, and 73.53% in the validation set, respectively. The decision analysis curve showed that when the nomogram differentiated IWON from SWON at a rate greater than 0.38, using the nomogram could benefit the patients. Conclusions:The prediction model established based on CT characteristics might non-invasively and accurately predict the presence or absence of IWON in MSAP and SAP patients, and provide a basis for guiding treatment and evaluating prognosis.
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Objective:To observe any relationship between corticospinal tract integrity and the upper limb motor function of stroke survivors treated with repetitive transcranial magnetic stimulation (rTMS).Methods:Bilateral corticospinal tracts (CSTs) were reconstructed in ischemic or hemorrhagic stroke survivors with upper limb motor dysfunction using diffusion tensor imaging (DTI). Thirty patients with good CST integrity (rFA>0.5) and 30 with rFA≤0.5 were further divided into a high frequency rTMS group (HF, n=10), a low frequency group (LF, n=10), and a control group ( n=10). All groups were given routine rehabilitation, while the high and low frequency groups were additionally provided with 5Hz and 1Hz rTMS respectively applied over the M1 area of the contralesional hemisphere. Before and after 3 weeks of treatment, all of the subjects were evaluated using the Fugl-Meyer upper extremity scale (F-M UE), the Wolf Motor Function Test (WMFT) and the Modified Barthel Index (MBI). Results:For the high CST integrity group, significant improvement was observed in the average scores of all measurements, with the average FMA-UE, WMFT and MBI scores of the LF group [(38.10±5.71), (43.20±5.32) and (78.00±11.35)] significantly better than those of the other 2 groups. Among the low CST integrity group, the HF subgroup showed greater improvement than the other 2 on average.Conclusions:For patients with good CST integrity, LF-rTMS over the contralesional cortex is superior to HF-rTMS in promoting upper limb motor function, while for patients with low CST integrity HF-rTMS over the contralesional cortex has a better effect than LF-rTMS or sham stimulation in terms of improving upper limb motor function after a stroke.
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Objective:To explore the differential diagnosis of pancreatic acinar cell carcinoma (PACC) and pancreatic ductal adenocarcinoma (PDAC) based on multidetector computed tomography (MDCT) features.Methods:The clinical, pathological and MDCT imaging data of 26 patients with pathologically confirmed PACC and 145 patients with pathologically confirmed PDAC who underwent MDCT from November 2013 to April 2021 were retrospectively studied. The differences of MDCT features including tumor location, tumor size, common pancreatic duct and bile duct dilatation, pancreatitis, lymph node metastasis, cyst, pancreatic parenchyma atrophy, duodenal involvement, bile ductal and vascular involvement between the two groups were compared. Univariate analysis and multivariate analysis by logistic regression models were performed to identify the independent predictive factors for PACC.Results:The tumor size, bile duct dilatation, lymph node metastasis, pancreatic parenchyma atrophy and vascular involvement were significantly different between PACC group and PDAC group (all P value<0.05). Multivariate analysis revealed that the tumor size ( OR=1.07, 95% CI 1.028-1.15, P=0.001), lymph node metastasis ( OR=0.23, 95% CI 0.065-0.800, P=0.02), pancreatic parenchyma atrophy ( OR=0.15, 95% CI 0.048-0.490, P=0.002) were closely associated with PACC. Conclusions:The tumor size, bile duct dilatation, lymph node metastasis, pancreatic parenchyma atrophy and vascular involvement evaluated by MDCT had a certain value in differentiating PACC from PDAC, and the tumor size, lymph node metastasis and pancreatic parenchyma atrophy were independent predictors for the diagnosis of PACC.
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Objective:To investigate the relationship between the perineural invasion score based on multidetector computed tomography (MDCT) and extrapancreatic perineural invasion (EPNI) in pancreatic ductal adenocarcinoma (PDAC).Methods:The clinical, radiological, and pathological data of 374 patients pathologically diagnosed as pancreatic cancer who underwent radical resection in the First Affiliated Hospital of Naval Medical University from March 2018 to May 2020 were analyzed retrospectively. Patients were divided into EPNI negative group ( n=111) and EPNI positive group (n=263) based on the pathological presence of EPNI. The perineural invasion score was performed for each patient based on radiological images. Univariate and multivariate logistic regression models were used to analyze the association between the perineural invasion score based on MDCT and EPNI in PDAC. Results:There were significant statistical differences between EPNI negative group and positive group on both pathological characteristics (T stage, N stage, invasion of common bile duct, and positive surgical margin) and radiological characteristics (tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, parenchymal atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct) (all P value <0.05). Univariate analysis revealed that the tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, pancreatic atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct were independently associated with EPNI. Multivariate analyses revealed that the perineural invasion based on MDCT was an independent risk factor for EPNI in pancreatic cancer (score=1, OR=2.93, 95% CI 1.61-5.32, P<0.001; score=2, OR=5.92, 95% CI 2.68-13.10, P<0.001). Conclusions:The perineural invasion score based on MDCT was an independent risk factor for EPNI in pancreatic cancer and can be used as an evaluation indicator for preoperative prediction of EPNI in PDAC.
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Objective:To develop and validate a visualized computed tomography nomogram for differentiating focal-type autoimmune pancreatitis (fAIP) from pancreatic ductal adenocarcinoma (PDAC).Methods:This retrospective review included 42 consecutive patients with fAIP diagnosed according to the International Consensus Diagnostic Criteria and 242 consecutive patients with PDAC confirmed by pathology between January 2011 and December 2018 in the First Affiliated Hospital of Naval Medical University. Among them, 209 consecutive patients (25 fAIP and 184 PDAC) were enrolled in the development cohort; Seventy-five consecutive patients (17 fAIP and 58 PDAC) were enrolled in the validation cohort. CT image characteristics, including lesion location, size, enhancement mode and degree of mass enhancement in portal vein phase, pancreatic parenchymal atrophy, main pancreatic duct dilation, common bile duct dilation, cyst, acute obstructive pancreatitis, and vascular invasion were compared. Univariate and multivariate analysis were used to screen the independent predictive factors for fAIP and PDAC, based on which the nomogram was constructed and visualized. The receiver operating characteristic curve (ROC) was drawn and area under the curve (AUC) was calculated to evaluate the differential efficacy of the nomogram. The clinical usefulness of the nomogram was evaluated by decision curve analysis.Results:There were statistically significant differences on common bile duct dilation and the mode and degree of enhancement in portal phase between fAIP group and PDAC group in training set and validation set ( P<0.05). Univariate regression analysis showed that common bile duct dilation and degree of mass enhancement in portal vein were closely correlated with fAIP and PDAC phase between the two groups in training set and validation set; mass enhancement mode in portal vein phase and main pancreatic duct dilation were closely correlated with fAIP and PDAC in training set. Multivariate logistic regression analysis showed that common biliary duct dilatation ( OR=0.26, 95% CI 0.06-1.10, P=0.07), main pancreatic duct dilation ( OR=9.46, 95% CI 1.60-56.04, P<0.01) and mass mild hyper-enhancing in portal vein phase ( OR=0.003, 95% CI 0.0003-0.0278, P<0.0001) were the three independent predictors for fAIP and PDAC. Thus, the equation for predicting the probability of PDAC was 4.51-1.33× no dilatation of the common bile duct+ 2.25× the main pancreatic duct dilated-5.84× mass mild hyper-enhancing during the portal phase. The individualized prediction nomogram using these predictors of the fAIP achieved an AUC of 0.97 (95% CI 0.95-0.99) in the development set and 0.97(95% CI0.94-1.00) in the validation set. The sensitivity, specificity and accuracy of the model were 87.5%, 100% and 89% in the training set; and 94.83%, 94.12% and 94.67% in the validation set, respectively. The decision curve analysis demonstrated that the nomogram was clinically useful when the nomogram differentiated fAIP and PDAC at a rate of >0.2. Conclusions:The nomogram based on common bile duct dilation, main pancreatic duct dilation and mass enhancement in portal vein phase can be used as a useful tool for predicting fAIP and PDAC and provide valuable evidence for clinical decision.
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Objective:To develop a visualized nomogram with a predictive value to differentiate mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) patients with chronic pancreatitis (CP) history.Methods:The clinical and radiological data of 5 433 CP patients acoording to the Asia-Pacific Diagnostic Criteria between February 2011 and February 2021 in the First Affiliated Hospital of Naval Medical University were retrospectively analyzed, and 71 PDAC patients with CP history and 67 MFCP who underwent surgery or biopsy and pathologically confirmed were eventually enrolled. The training set included 44 patients with MFCP and 59 patients with PDAC who were diagnosed between February 2011 and April 2018. The validation set consisted of 23 patients with MFCP and 12 patients with PDAC who were diagnosed between May 2018 and February 2021. Univariate and multivariate logistic regression analyses were performed to develop a prediction model for PDAC and MFCP, and the model was visualized as a nomogram. ROC was used to evaluate the predictive efficacy of the nomogram, and the clinical usefulness was judged by decision curve analysis.Results:The univariate analysis showed that a significant association with pancreatic cancer were observed for the duct-to-parenchyma ratio ≥0.34, pancreatic duct cut-off, pancreatic portal hypertension, arterial CT attenuation, portal venous CT attenuation, delayed CT attenuation, and vascular invasion in both the training and validation cohorts, but the duct-penetrating sign in the training cohort only. The multivariable logistic regression analysis showed that statistically significant differences (all P value <0.05) existed in cystic degeneration, a duct-to-parenchyma ratio ≥0.34, the duct-penetrating sign, pancreatic portal hypertension and arterial CT attenuation between the two cohorts. The above parameters were selected for the logistic regression model. The predicted model=3.65-2.59×cystic degeneration+ 1.26×duct-to-parenchyma ratio≥0.34-1.40×duct-penetrating sign+ 1.36×pancreatic portal hypertension-0.05×arterial CT attenuation. Area under the curve, sensitivity, specificity and accuracy of the model-based nomogram were 0.87 (95 CI 0.80-0.94), 89.0%, 75.0% and 83.5% in the training cohort, and 0.94 (95 CI 0.82-0.99), 91.7%, 100% and 97.1% in the validation cohort, respectively. Decision curve analysis showed that when the nomogram differentiated MFCP from PDAC patients with CP history at a rate of 0.05-0.85, the application of the nomogram could benefit the patients. Conclusions:The nomogram based on CT radiological features accurately differentiated MFCP from PDAC patients with CP history and provide reference for guiding the treatment and judging the prognosis.
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Objective:To investigate the MRI features of intraductal papillary mucinous tumor (IPMN) of the pancreas and establish a prediction model for predicting the malignancy risk.Methods:The clinical data of 260 IPMN patients who underwent MRI and pathological confirmed in the First Affiliated Hospital of Naval Medical University from October 2012 to April 2020 were retrospectively analyzed. According to the pathological results, all patients were divided into benign group (including IPMN with low-grade dysplasia) and malignant group (including IPMN with high grade dysplasia and invasive carcinoma). According to international consensus of prediction model modeling, patients were divided into training set and validation set in chronological order. A prediction model was developed based on a training set consisting of 193 patients (including 117 patients with benign IPMN and 76 patients with malignant IPMN) between October 2012 and April 2019, and the model was validated in 67 patients (including 40 patients with benign IPMN and 27 patients with malignant IPMN) between May 2019 and April 2020. The multivariable logistic regression model was adopted to identify the independent predictive factors for IPMN malignancy and establish and visualized a nomogram. The ROC was drawn and AUC was calculated. The decision curve analysis was used to evaluate its clinical usefulness.Results:The IPMN type, cyst size, thickened cyst wall, mural nodule size, diameter of main pancreatic duct (MPD) and the abrupt change in the caliber of the MPD with distal pancreatic atrophy in the training set and validation set, and jaundice and lymphadenopathy in the training set were significantly different between benign group and malignant group ( P<0.05). The multivariable logistic regression model of characteristics included the jaundice, cyst size, mural nodule size ≥5 mm, the abrupt change in caliber of the MPD with distal pancreatic atrophy were independent risk factors for IPMN maligancy. The model for predicting IPMN malignancy was -0.35+ 2.28×(jaundice)+ 1.57×(mural nodule size ≥5 mm)+ 2.92×(the abrupt change in caliber of the MPD with distal pancreatic atrophy)-1.95×(cyst <3 cm)-1.05×(cyst≥3 cm). The individualized prediction nomogram using these predictors of the malignant IPMN achieved an AUC of 0.85 (95% CI 0.79-0.91) in the training set and 0.84 (95% CI 0.74-0.94) in the validation set. The sensitivity, specificity and accuracy of the training set were 72.37%, 85.47% and 80.31%, respectively. The sensitivity, specificity and accuracy of the validation set were 81.48%, 75.00% and 77.61%, respectively. The decision curve analysis demonstrated that when the IPMN malignancy rate was >0.16, the nomogram diagnosing IPMN could benefit patients more than the strategy of considering all the patients as malignancy or non-malignancy. Conclusions:The nomogram based on MRI features can accurately predict the risk of malignant IPMN, and can be used as an effective predictive tool to provide more accurate information for personalized diagnosis and treatment of patients.
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ObjectiveTo investigate the expression levels of the red blood cell surface receptors and oxidative stress of patients with hemodialysis,evaluate the immune function of the red blood cells,and identify the cause of infection and high prevalence of tumor in patients with hemodialysis.MethodsForty-five long-term hemodialysis patients from our blood purification center was chosen as the treatment group.Forty-five healthy individuals conducting physical examination at the same period was chosen as the control group.The flow cytometric method was used to detect CD35 surface receptors numbers of the red blood cell.The red blood cells wreath experiments were used to measure the adhesive function.The ELASA method was used to test the changes of oxidative stress index:SOD,MDA,CAT and GSH-PX.ResultsCompared to the normal control group,the treatment group had significantly lower levels of CD35 [ ( 28.62 ±6.95 ) AU vs.( 19.71 4.89) AU,t =5.441,P ＜0.01 ],impaired adhesive function red blood cells[ (0.63 ±0.07) vs.(0.44 ±0.04),t =0.41,P ＜0.05].For the levels of oxidative stress index,MDA [ ( 6.18 ± 0.16 ) μmol/L vs ( 13.47 ± 0.39 ) μmol/L ] was significantly higher in the treatment group than in the normal control group( t =13.14,P ＜ 0.05 ),and SOD( 34 202.00 ± 1634.00) U/( g · Hb),CAT ( 21.70 ± 0.84 ) U/ml and GSH-PX ( 444.00 ± 10.31 ) U/ml were significantly lower in the treatment group than in the normal control group [ SOD:(24 652.00 ± 2179.00)U/( g · Hb),CAT:( 14.80 ± 1.13 ) U/ml,GSH-PX:( 217.89 ± 13.70 ) U,t =20.246,9.496,27.195,P ＜0.05 ].ConclusionPatients with hemodialysis had lower numbers of red blood cell surface receptors CD35 and impaired immune function of adhesion,and higher oxidative stress levels.This may be the cause of infection and tumor of patients with hemodialvsis.