Objective To investigate the clinical characteristics,treatment methods,and prognosis of a-cute leukemia patients with extramedullary infiltration.Methods The clinical characteristics and treatment methods of 47 acute leukemia patients with extramedullary infiltration admitted to the Affiliated Hospital of Guizhou Medical University from April 2014 to April 2023 were retrospectively analyzed.Subgroup analysis was performed according to whether there was extramedullary infiltration before transplantation,and whether there was isolated extramedullary recurrence after transplantation.Based on this analysis,the patients were di-vided into the pre-transplantation radiotherapy group and pre-transplantation non-radiotherapy group,the post-transplantation radiotherapy group and post-transplantation non-radiotherapy group.According to the treatment methods of central nervous system leukemia(CNSL),the patients were divided into the intrathecal injection group(n=12)and combination of intrathecal injection and radiotherapy group(n=13).The local remission situation,survival duration,and toxic and side effects of radiotherapy and chemotherapy were com-pared.Results For acute leukemia patients with extramedullary infiltration,the overall survival time(OS)in the radiotherapy group was better than that in the non-radiotherapy group(median OS:706 d vs.151 d,P=0.015).Subgroup analysis showed that the OS of the pre-transplantation radiotherapy group was better than that of the pre-transplantation non-radiotherapy group(median OS:592 d vs.386 d,P=0.035).For CNSL,the combination of intrathecal injection and radiotherapy group had a better OS than the intrathecal injection group(median OS:547 d vs.388 d,P=0.045).The event-free survival time(EFS)of the radiotherapy group was better than that of the non-radiotherapy group(median EFS:175 d vs.50 d,P=0.005).The COX pro-portional-hazards model showed that treatment with or without radiotherapy had a significant impact on the OS of acute leukemia patients with extramedullary infiltration.The risk of death in the pre-transplantation non-radiotherapy group was 2.231 times higher than that in the pre-transplantation radiotherapy group(HR=3.231,95％CI:1.021-10.227,P=0.046).Compared with the non-radiotherapy group,the radiother-apy group had a higher local remission and a lower risk of haematological toxicity,infection,and haemorrhage.Conclusion Radiotherapy can rapidly alleviate the local symptoms of acute leukemia complicated with extr-amedullary infiltration,prolong the survival time of these patients,and reduce the risk of hematologic toxicity,infection,and haemorrhage.

Objective To investigate the influence of peripheral blood neutrophil-to-lymphocyte ratio (NLR),monocyte-to-lymphocyte ratio (MLR) and platelet-to-lymphocyte ratio (PLR) on the prognosis in the patients with multiple myeloma (MM).Methods A total of 159 newly diagnosed MM admitted and treated in the Affiliated Hospital of Guizhou Medical University from January 2019 to May 2023 were selected as the study subjects.The general clinical data,blood biochemical and marrow routine detection results before the in-itial treatment were collected.NLR,MLR and PLR were calculated.The univariate and multivariate Cox-re-gression model was adopted to analyze the influencing factors.The receiver operating characteristic (ROC) curve was used to analyze the predictive value.The Kaplan-Meier survival curve and Log-Rank test were used to conduct the survival analysis.Results The ROC curve showed that the critical values of NLR,MLR and PLR were 2.682,0.317 and 147.786 respectively.The patients were divided into the high/low NLR groups (n=61,n=98),high/low MLR group (n=76,n=83) and high/low PLR groups (n=59,n=100).The pro-portions of blood calcium<2.5 mmol/L and creatinine<177 μmmol/L in the low NLR group in the low NLR group were higher compared with the high NLR group (P<0.05);the blood calcium,creatinine and DS stage had statistical differences between the low MLR group and high MLR group (P<0.05);blood calcium had statistical difference between the low PLR group and high PLR group (P<0.05).After 3 treatment courses,the complete remission rate in the high NLR group,high MLR group and high PLR group was significantly lower than that in the corresponding low group (P<0.05).The multivariate Cox-regression analysis results showed that hemoglobin<100 g/L and high PLR were the independent risk factors affecting the progress free survival (PFS) stage in the patients with MM (P<0.05).The age>60 years old was the independent risk factors affecting the overall survival (OS) in the patients with MM (P<0.05).Conclusion NLR,MLR and PLR could serve as the assisted tool to evaluate the prognosis in the patients with MM.

Objective:To investigate the relationship between telomere length of bone marrow mononuclear cells and prognosis of patients with acute myeloid leukemia (AML) who received allogeneic hematopoietic stem cell transplantation (allo-HSCT).Methods:Telomere length of bone marrow mononuclear cells before transplantation, after transplantation and before donor mobilization as well as information related to follow-up of 33 AML patients who received allo-HSCT in the Affiliated Hospital of Guizhou Medical University between June 2020 and June 2021 were retrospectively analyzed. Telomere length was detected by using telomeric terminal restriction fragment (TRF) method. Telomere length was compared among patients with different prognoses. The recurrence within 1 year was treated as the gold standard and receiver operating characteristic (ROC) curve was used to analyze the effect of telomere length before transplantation or before donor mobilization in the judgement of the recurrence within 1 year after transplantation. The patients were stratified according to the optimal threshold value of telomere length for patients or donors, and Kaplan-Meier method was used to compare the progression-free survival (PFS) of patients with different stratification, and log-rank test was performed.Results:The median age of 33 patients was 34 years (14-61 years), and there were 17 males and 16 females; 31 patients were initially diagnosed with AML, 1 patient transferred from myelodysplastic syndrome (MDS) to AML, and 1 patient transferred from chronic granulocytic leukemia (CML) to AML; 14 received identical sibling transplantation and 19 received haploidentical sibling transplantation. The median age of the donors was 30 years (20-65 years), including 24 males and 9 females. Telomere length of bone marrow mononuclear cells before mobilization in 33 donors was longer than that in patients before transplantation (33 cases) and at +30 d after transplantation (31 cases) [(6.67±0.31) kb, (6.40±0.33) kb, (6.48±0.33) kb, respectively; all P < 0.05], and the difference between patients before and at +30 d after transplantation was not statistically significant ( t = 0.89, P = 0.378), and the telomere length of bone marrow mononuclear cells in 11 patients +180 d after transplantation was (6.66±0.18) kb. The incidence of acute graft-versus-host disease (aGVHD) after transplantation was 45.5% (15/33), the incidence of infection with clear imaging and pathogenic basis was 39.4% (13/33), the mortality rate within 1 year after transplantation was 3.0% (1/33), and the recurrence rate within 1 year after transplantation was 15.2% (5/33). There were no statistically significant differences in telomere length of donor pre-mobilization bone marrow mononuclear cells between the groups with and without aGVHD and between the infected and non-infected groups (all P > 0.05).Compared with patients who had not relapsed within 1 year after transplantation, telomere length of donor pre-mobilization bone marrow mononuclear cells was shorter in patients who relapsed within 1 year after transplantation [(6.39±0.19) kb vs. (6.72±0.30) kb, t = -3.23, P = 0.011], telomere length was longer in patients before transplantation [(6.75±0.16) kb vs. (6.35±0.36) kb, t = 4.17, P = 0.001]. ROC curve analysis showed that the optimal threshold values for telomere length of pre-transplantation and donor pre-mobilization bone marrow mononuclear cells were 6.48 and 6.42 kb, respectively for patients who relapsed within 1 year after transplantation. PFS in patients with pre-transplantation bone marrow mononuclear cells telomere length < 6.48 kb was better than that in patients with telomere length ≥ 6.48 kb ( P = 0.003); PFS in patients with pre-mobilization bone marrow mononuclear cells telomere length>6.42 kb was better than that in patients with telomere length ≤ 6.42 kb ( P < 0.001). Conclusions:In allo-HSCT for AML, patients have an increased risk of relapse within 1 year after transplantation when their pre-transplantation bone marrow mononuclear cells telomere length is long and the donor bone marrow mononuclear cells telomere length is short.

Objective:To investigate the effect of centrosome protein 55 (CEP55) on the proliferation of bladder cancer cells and its related molecular mechanism.Methods:Western blot was used to detect the expression of CEP55 and H3K9me3 in normal bladder tissue cells (SV-HUC-1) and bladder cancer cells (T24) . The bladder cancer cells T24 were divided into experimental group and control group. The experimental group cells were transfected with siRNA-CEP55, and the control group cells were transfected with siRNA-MOCK. The expression levels of CEP55, H3K9 and H3K9me3 in each group of cells were detected by Western blot. The proliferation ability of each group of cells was detected by CCK8 assay.Results:Western blot assay showed that the expression of CEP55 and H3K9me3 in T24 cells was 0.83±0.15 and 1.01±0.19 respectively. The expressions of CEP55 and H3K9me3 in bladder epithelial SV-HUC-1 cells were 0.35±0.09 and 0.44±0.10 respectively. The expressions of CEP55 and H3K9me3 in bladder cancer cells were higher than those in normal bladder cells (all P<0.05) . siRNA-CEP55 successfully reduced the expression of T24 CEP55 in bladder cancer cells. The absorbance of T24 cells in the experimental group was 1.109±0.105, which was significantly lower than that in the control group (2.208±0.104) . Low expression of CEP55 reduced the proliferation ability of T24 cells ( P<0.05) . Western blot results showed that H3K9 was not significantly changed in T24 cells in the experimental group, and H3K9me3 expression decreased significantly ( P<0.05) . Conclusion:CEP55 can inhibit the proliferation of bladder cancer cells by reducing the trimethylation of H3K9.

Objective:To evaluate the effectiveness of deep learning reconstruction (DLR) compared with hybrid iterative reconstruction (Hybrid IR) in improving the image quality in chest low-dose CT (LDCT).Methods:Seventy-seven patients who underwent LDCT scan for physical examination or regular follow-up in Peking Union Medical College Hospital from October 2020 to March 2021 were retrospectively included. The LDCT images were reconstructed with Hybrid IR at standard level (Hybrid IR Stand) and DLR at standard and strong level (DLR Stand and DLR Strong). Regions of interest were placed on pulmonary lobe, aorta, subscapularis muscle and axillary fat to measure the CT value and image noise. The signal to noise ratio (SNR) and contrast to noise ratio (CNR) were calculated. Subjective image quality was evaluated using Likert 5-score method by two experienced radiologists. The number and features of ground-glass nodule (GGN) were also assessed. If the scores of the two radiologists were inconsistent, the score was determined by the third radiologist. The objective and subjective image evaluation were compared using the Kruskal-Wallis test, and the Bonferroni test was used for multiple comparisons within the group.Results:Among Hybrid IR Stand, DLR Stand and DLR Strong images, the CT value of pulmonary lobe, aorta, subscapularis muscle and axillary fat had no significant differences (all P>0.05), but the image noise and SNR of pulmonary lobe, aorta, subscapularis muscle and axillary fat had significant differences(all P<0.05), and the CNR of images had significant difference( P<0.05), too. The CNR of Hybrid IR Stand images, DLR stand images and DLR strong images were 0.71 (0.49, 0.88), 1.06 (0.78, 1.32) and 1.14 (0.84, 1.48), respectively. Compared with Hybrid IR images, DLR images had lower objective and subjective image noise,higher SNR and CNR (all P<0.05). The scores of DLR images were superior to Hybrid IR images in identifying lung fissures, pulmonary vessels, trachea and bronchi, lymph nodes, pleura, pericardium and GGN (all P<0.05). Conclusions:DLR significantly reduced the image noise, and DLR images were superior to Hybrid IR images in identifying GGN in chest LDCT while maintaining superior image quality at relatively low radiation dose levels. Thus DLR images can improve the safety of lung cancer screening and pulmonary nodule follow-up by CT.

Objective:To explore the effect of deep learning reconstruction (DLR) on radiation dosage reduction and image quality of CTPA compared with hybrid iterative reconstruction (HIR).Methods:A total of 100 patients with suspected pulmonary embolism (APE) or indications for CTPA due to other pulmonary artery diseases in Peking Union Medical College Hospital from December 2020 to April 2021 were prospectively enrolled and divided into HIR group and DLR group according to block randomization, with 50 cases in each group. The patient′s gender, age and body mass index (BMI) were recorded. HIR group and DLR group underwent standard deviation (SD)=8.8 and SD=15 CTPA protocols in combination with HIR and DLR algorithm respectively. Other scanning parameters and contrast medium injection plan were the same. The effective dose (ED) and size-specific dose estimate (SSDE) were calculated. Regions of interest (ROIs) were drawn in the lumen of Grade 1-3 pulmonary arteries and bilateral paravertebral muscles. The corresponding CT and SD values were recorded to acquire signal to noise ratio (SNR) and contrast noise ratio (CNR). Based on a double-blind method, two radiologists evaluated the subjective noise, visualization of pulmonary arteries, and diagnostic confidence of the two groups by 5-point Likert scales. The inconsistent results were judged comprehensively by the third radiologist. Independent samples t-test was used to compare the demographic data, radiation dosage and quantitative image quality of the two groups. Mann-Whitney U test was used to compare the subjective noise, visualization of pulmonary arteries and diagnostic confidence between the two groups. Linear weighted Kappa coefficient was calculated to analyze the consistency of the qualitative scores between the two radiologists. Results:There were no significant differences in gender, age and BMI between the two groups ( P>0.05). The CT values of Grade1-3 pulmonary arteries and paravertebral muscle had no significant differences ( P>0.05). Compared with HIR group, the ED and SSDE in DLR group decreased by about 35% to 1.3 mSv and 4.20 mGy respectively, while the SNR (30±5) and CNR (26±5) of CTPA images were higher in DLR group than those in HIR group (23±5 and 20±5, with t=-6.60 and -5.90, respectively, both P<0.001). The subjective noise score was higher in DLR group than that in HIR group ( Z=-7.34, P<0.001). In addition, two radiologists showed excellent interobserver agreement in DLR group (Kappa=0.847, 95%CI 0.553-1.000). No significant differences were found in visualization of pulmonary arteries and diagnostic confidence between the two groups ( P>0.05). Conclusion:DLR further reduced the radiation dosage and improved the image quality of CTPA, with no detriment to diagnostic confidence. Thus DLR is worthy of clinical promotion.

Objective:To investigate the feasibility of chest ultra-low dose CT (ULDCT) using deep learning reconstruction (DLR) for lung cancer screening, and to compare its image quality and nodule detection rate with ULDCT iterative reconstruction (Hybrid IR) and conventional dose CT (RDCT) Hybrid IR.Methods:The patients who underwent chest CT examination for pulmonary nodules in Peking Union Medical College Hospital from October 2020 to March 2021 were prospectively included and underwent chest RDCT (120 kVp, automatic tube current), followed by ULDCT (100 kVp, 20 mA). The RDCT images were reconstructed with Hybrid IR (adaptive iterative dose reduction 3D,AIDR 3D), and ULDCT was reconstructed with AIDR3D and DLR. Radiation dose parameters and nodule numbers were recorded. Image quality was assessed using objective noise, signal-to-noise ratio (SNR) of the main trachea and left upper lobe, subjective image scores of the lung and nodules. Subjective scores were scored by 2 experienced radiologists on a Likert 5-point scale. The difference of radiation dose was compared with paired t-test between ULDCT and RDCT.The differences of quantitative indexes, objective image noise and subjective scores of the three reconstruction methods were compared with one-way analysis of variance or Friedman test. Results:Forty-five patients were enrolled, including 17 males and 28 females, aged from 32 to 74 (55±11) years. The radiation dose of ULDCT was (0.17±0.01) mSv, which was significantly lower than that of RDCT [(1.35±0.41) mSv, t=15.46, P<0.001]. There were significant differences in the image noise and SNR in the trachea and lung parenchyma and in the CT value of the trachea among ULDCT-AICE, ULDCT-AIDR 3D and RDCT-AIDR 3D images ( P<0.05). Image noise in the trachea and lung parenchyma and CT value in the trachea of ULDCT-AICE were significantly lower than those of ULDCT-AIDR 3D ( P<0.05) and comparable to RDCT-AIDR 3D ( P>0.05). There were significant differences in subjective image scores of the lung and nodules among ULDCT-AICE, ULDCT-AIDR 3D and RDCT-AIDR 3D images (χ2=50.57,117.20, P<0.001). Subjective image scores of the lung and nodules for ULDCT-AICE were significantly higher than those of ULDCT-AIDR 3D ( P<0.05), and non-inferior to RDCT-ADIR 3D ( P>0.05). All 72 clinically significant nodules detected on RDCT-ADIR 3D were also noted on ULDCT-AICE and ULDCT-AIDR 3D images. Conclusions:Chest ULDCT using DLR can significantly reduce the radiation dose, and compared with Hybrid IR, it can effectively reduce the image noise and improve SNR, and display the pulmonary nodules well. The image quality and nodule detection are not inferior to RDCT Hybrid IR routinely used in clinical practice.

Objective:To analyze the MRI findings of solid pseudopapilloma of the pancreas (SPTs) and nonfunctional pancreatic neuroendocrine tumors (PNETs), and to establish and verify the prediction model of SPTs and PNETs.Methods:The clinical and MRI data of 142 patients with SPTs and 137 patients with PNETs who underwent surgical resection and were confirmed by pathology in the First Affiliated Hospital of Naval Medical University from January 2013 to December 2020 were collected continuously. Age, gender, body mass index (BMI), lesion size, location, shape, boundary, cystic change, T 1WI signal, T 2WI signal, enhancement peak phase, whether the enhancement degree was higher than that of pancreatic parenchyma in the enhancement peak phase, enhancement pattern, whether pancreatic duct and common bile duct were dilated, whether the pancreas shrank, and whether it invaded adjacent organs and vessels were recorded. According to the international consensus on prediction model modeling, patients were divided into training set (106 SPTs and 100 PNETs between January 2013 and December 2018), and validation set (36 SPTs and 37 PNETs between January 2019 and December 2020). The above characteristics of patients in training and validation set were analyzed by univariate and multivariate logistic regression, and a prediction model was established to distinguish SPTs and PNETs, and then visualized as a nomogram. The receiver operating characteristic curve (ROC) of the nomogram of training set and verification set was drawn, and the area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the prediction efficiency of the model, and the clinical application value of the prediction model was evaluated by decision curve analysis (DCA). Results:Univariate regression analysis showed that there were significant differences on age, gender, lesion size, shape, cystic change, T 1WI signal, peak phase of enhancement, degree of enhancement in peak phase, pattern of enhancement and invasion of adjacent organs between SPTs group and PNETs group (all P value <0.05). Multivariate regression analysis showed that the older age, male patients, the smaller lesion, no high signal on T 1WI, the enhancement peak phase located in arterial phase or venous phase, and the enhancement degree in peak phase higher than that of pancreatic parenchyma were the six independent predictors of PNETs. The prediction model was established by using these six factors and visualized as a nomogram. The formula for predicting PNETs probability was 4.31+ 1.13×age+ 1.31×tumor size-1.29×female-4.18×high T 1WI signal+ 1.28×the enhancement degree higher than that of pancreatic parenchyma -4.69 ×enhancement peak in delay phase. The prediction model was visualized as a nomogram. The AUC values in the training set and validation set were 0.99(95% CI0.977-1.000) and 0.97 (95% CI 0.926-1.000), respectively. The sensitivity, specificity and accuracy in the training set are 98.00%, 94.34% and 96.12% and in the validation set were 86.49%, 97.22% and 91.78% respectively. The results of decision curve analysis show that the prediction model can accurately diagnose SPTs and PNETs. Conclusions:The prediction model established in this study can accurately differentiate SPTs from PNETs, and can provide important information for clinical decision and prognosis.

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.

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.