Clinical Value of Mean Platelet Volume to Platelet Ratio (MPR) in Distinguishing Mass-Forming Chronic Pancreatitis and Pancreatic Cancer.

BACKGROUND: Correctly distinguishing mass-forming chronic pancreatitis (MFCP) from pancreatic cancer (PC) is of clinical significance to determine optimal therapy and improve the prognosis of patients. According to research, inflammation status in PC is different from that in MFCP. Mean platelet volume/platelet ratio (MPR) is a platelet-related inflammation index which has been proven to be valuable in the diagnosis and prognosis of various malignant cancers due to the change in mean platelet volume and platelet count under abnormal inflammatory conditions caused by tumors. Thus, we conducted this study to investigate the clinical value of MPR in distinguishing MFCP from PC. METHODS: We retrospectively analyzed the data of 422 patients who were suspected to have PC during imaging examination at our department from January 2012 to December 2021. Included patients were divided into the PC (n = 383) and MFCP groups (n = 39), according to their pathological diagnosis. Clinical data including MPR were compared within these two groups and the diagnostic value was explored using logistic regression. The ROC curve between MPR and PC occurrence was drawn and an optimal cut-off value was obtained. Propensity score matching was applied to match MFCP patients with PC patients according to their age and carbohydrate antigen 19-9 (CA19-9). Differences in MPR between groups were compared to verify our findings. RESULTS: The area under the ROC curve between MPR and PC occurrence was 0.728 (95%CI: 0.652-0.805) and the optimal cut-off value was 0.045 with a 69.2% sensitivity and 68.0% accuracy. For all the included patients, MPRs in the MFCP and PC groups were 0.04 (0.04, 0.06) and 0.06 (0.04, 0.07), respectively (p = 0.005). In patients with matching propensity scores, MPRs in the MFCP and PC groups were 0.04 (0.03, 0.06) and 0.06 (0.05, 0.08), respectively (p = 0.005). Multiple logistic regression in all included patients and matched patients confirmed MPR and CA19-9 as independent risk markers in distinguishing PC. Combining CA19-9 with MPR can increase the sensitivity and accuracy in diagnosing PC to 93.2% and 89.5%, respectively. CONCLUSION: MPR in PC patients is significantly higher than that in MFCP patients and may be adopted as a potential indicator to distinguish MFCP and PC. Its differential diagnosis capacity can be improved if combined with CA19-9.

Mass-Forming Chronic Pancreatitis: Diagnostic Performance of PET/CT.

Mass-forming chronic pancreatitis and pancreatic ductal adenocarcinoma are most commonly located in the head of pancreas, and there is a marked overlap in clinical features and imaging findings that makes it diagnostically challenging, although prognosis and management of both these entities differ. Differentiation is made even more difficult when surgical exploratory biopsy is obtained. Radical surgical resection remains the standard of care for pancreatic ductal adenocarcinoma and conservative treatment is effective for mass-forming chronic pancreatitis. Misdiagnosis of mass-forming chronic pancreatitis as pancreatic ductal adenocarcinoma results in unnecessary surgical intervention, and misdiagnosis of pancreatic ductal adenocarcinoma as mass-forming chronic pancreatitis results in delay in surgical intervention when required. Fluorodeoxyglucose-positron emission tomography/computed tomography can reliably be used for tissue characterization of mass-forming chronic pancreatitis and for monitoring disease response following treatment. Although differentiation of mass-like lesions of pancreas is reliably made on histopathology, significant false-negative rate is a major drawback that has a negative effect on diagnosis. This case report describes a rare presentation of mass-forming chronic pancreatitis with florid dystrophic calcifications in a 60-year-old male.

Development and validation of a novel model incorporating MRI-based radiomics signature with clinical biomarkers for distinguishing pancreatic carcinoma from mass-forming chronic pancreatitis.

PURPOSE: It is difficult to make a clear differential diagnosis of pancreatic carcinoma (PC) and mass-forming chronic pancreatitis (MFCP) via conventional examinations. We aimed to develop a novel model incorporating an MRI-based radiomics signature with clinical biomarkers for distinguishing the two lesions. METHODS: A total of 102 patients were retrospectively enrolled and randomly divided into the training and validation cohorts. Radiomics features were extracted from four different sequences. Individual imaging modality radiomics signature, multiparametric MRI (mp-MRI) radiomics signature, and a final mixed model based on mp-MRI and clinically independent risk factors were established to discriminate between PC and MFCP. The diagnostic performance of each model and model discrimination were assessed in both the training and validation cohorts. RESULTS: ADC had the best predictive performance among the four individual radiomics models, but there were no significant differences between the pairs of models (all p > 0.05). Six potential radiomics features were finally selected from the 960 texture features to formulate the radiomics score (rad-score) of the mp-MRI model. In addition, the boxplot results of the distributions of rad-scores identified the rad-score as an independent predictive factor for the differentiation of PC and MFCP (p< 0.001). Notably, the nomogram integrating rad-score and clinically independent risk factors had a better diagnostic performance than the mp-MRI and clinical models. These results were further confirmed by the validation group. CONCLUSION: The mixed model was developed and preliminarily validated to distinguish PC from MFCP, which may benefit the formulation of treatment strategies and nonsurgical procedures.

Radiomics Model Based on MR Images to Discriminate Pancreatic Ductal Adenocarcinoma and Mass-Forming Chronic Pancreatitis Lesions.

BACKGROUND: It is difficult to identify pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions through conventional CT or MR examination. As an innovative image analysis method, radiomics may possess potential clinical value in identifying PDAC and MFCP. To develop and validate radiomics models derived from multiparametric MRI to distinguish pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions. METHODS: This retrospective study included 119 patients from two independent institutions. Patients from one institution were used as the training cohort (51 patients with PDAC and 13 patients with MFCP), and patients from the other institution were used as the testing cohort (45 patients with PDAC and 10 patients with MFCP). All the patients had pathologically confirmed results, and preoperative MRI was performed. Four feature sets were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and the artery (A) and portal (P) phases of dynamic contrast-enhanced MRI, and the corresponding radiomics models were established. Several clinical characteristics were used to discriminate PDAC and MFCP lesions, and clinical model was established. The results of radiologists' evaluation were compared with pathology and radiomics models. Univariate analysis and the least absolute shrinkage and selection operator algorithm were performed for feature selection, and a support vector machine was used for classification. The receiver operating characteristic (ROC) curve was applied to assess the model discrimination. RESULTS: The areas under the ROC curves (AUCs) for the T1WI, T2WI, A and, P and clinical models were 0.893, 0.911, 0.958, 0.997 and 0.516 in the primary cohort, and 0.882, 0.902, 0.920, 0.962 and 0.649 in the validation cohort, respectively. All radiomics models performed better than clinical model and radiologists' evaluation both in the training and testing cohorts by comparing the AUC of various models, all P<0.050. Good calibration was achieved. CONCLUSIONS: The radiomics models based on multiparametric MRI have the potential ability to classify PDAC and MFCP lesions.

A nomogram based on CT characteristics for differentiating mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma patients with chronic pancreatitis history / 中华胰腺病杂志

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.

Mass-forming pancreatitis versus pancreatic ductal adenocarcinoma: CT and MR imaging for differentiation.

Various inflammatory abnormalities of the pancreas can mimic pancreatic ductal adenocarcinoma (PDAC) at cross-sectional imaging. Misdiagnosis of PDAC at imaging may lead to unnecessary surgery. On the other hand, chronic pancreatitis (CP) bears a greater risk of developing PDAC during the course of the disease. Thus, differentiation between mass-forming chronic pancreatitis (MFCP) and PDAC is important to avoid unnecessary surgery and not to delay surgery of synchronous PDAC in CP.Imaging features such as the morphology of the mass including displacement of calcifications, presence of duct penetrating, sign appearance of duct stricturing, presence or absence of vessel encasement, apparent diffusion coefficient (ADC) value and intravoxel incoherent motion (IVIM) at diffusion-weighted imaging (DWI), fluorodeoxyglucose (FDG) uptake in PET/CT, and mass perfusion parameters can help to differentiate between PDAC and MFCP. Correct interpretation of imaging features can appropriately guide biopsy and surgery, if necessary. This review summarizes the relevant computed tomography (CT) and magnetic resonance imaging (MRI) features that can help the radiologist to come to a confident diagnosis and to guide further management in equivocal cases.

Pancreatitis and PDAC: association and differentiation.

The discrimination of mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) is a central diagnostic dilemma. It is important to differentiate these entities since they have markedly different prognoses and management. Importantly, the appearance of these two entities significantly overlaps on a variety of imaging modalities. However, there are imaging features that may be suggestive of one entity more than the other. MFCP and PDAC may show different enhancement patterns on perfusion computed tomography (CT) and/or dynamic contrast-enhanced MRI (DCE-MRI). The duct-penetrating sign on magnetic resonance cholangiopancreatography (MRCP) is more often associated with MFCP, whereas abrupt cutoff with upstream dilatation of the main pancreatic duct and the double-duct sign (obstruction/cutoff of both the common bile duct and pancreatic duct) are more often associated with PDAC. Nevertheless, tissue sampling is the most reliable method to differentiate between these entities and is currently generally necessary for management.

Multi-modality imaging features distinguish pancreatic carcinoma from mass-forming chronic pancreatitis of the pancreatic head.

The present study retrospectively analyzed computerized tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography-computerized tomography (PET/CT) data to identify features that may distinguish pancreatic carcinoma (PC) from mass-forming chronic pancreatitis (MFCP) of the pancreatic head. The mean diameter of the lesions was larger in the MFCP patients (n=24) than in the PC patients (n=30; 5.44±27 vs. 3.34±1.23 cm; P<0.001). PC lesions showed increased lobulation when compared with the MFCP cases (83.33 vs. 12.5%; P<0.001). Lesions in the MFCP patients exhibited diffuse and marginally distributed calcification. MFCP patients showed increased exudation around the lesion (83.33 vs. 13.33%), pseudocyst formation (58.33 vs. 10%) and thickening of the right renal fascia (83.33 vs. 13.33%) than in the PC patients. MFCP patients also exhibited visible remnants of normal pancreatic tissue within the lesions. MFCP and PC patients could be distinguished by a cutoff value of 4.40 cm for lesion size [area under the curve (AUC): 0.894; 95% confidence interval (CI): 0.810-0.978)], 21.85 Hu for net-increased value in the arterial phase (AUC, 0.799; 95% CI, 0.670-0.928), 37.70 Hu for net-increased value in the portal phase (AUC, 0.798; 95% CI, 0.919-0.677), 4.85 for early standardized uptake value (SUV) of 18F-deoxyglucose (18F-FDG; AUC, 0.934; 95% CI, 0.850-1.018) and 4.90 for delayed SUV of 18F-FDG (AUC, 0.958; 95% CI, 0.878-1.038). These findings demonstrated that the integration of data from dynamic contrast-enhanced CT, MRI and PET/CT imaging may distinguish MFCP from PC.

The value of calcification and cystic lesion of CT findings in differentiating pancreatic head ductal carcinoma from mass-forming chronic pancreatitis of the pancreatic head / 实用放射学杂志

Objective To investigate the diagnostic value of calcification and cystic lesion of CT findings in differentiating pancreatic head ductal carcinoma (PHDA)from mass-forming chronic pancreatitis (MFCP)of the pancreatic head.Methods The clinic data and CT findings of 30 cases with PHDA and 24 cases with MFCP of the pancreatic head,which were confirmed by surgery and pathology were analyzed retrospectively.The images were reviewed independently by two expert radiologists with a double-blind method.An independent sample t test and chi-square test were used to compare the data of imaging findings between two groups.Results ① Calcification was found in 14 cases (58.33%)with MFCP and in 3 cases (10%)with PHDA (P＜0.001).The percentage of patchy,punctate and mixed calcification were 28.57% (n=4),14.29% (n=2)and 57.14% (n=8)in MFCP,0% (n=0),66.67% (n=2)and 33.33% (n=1) in PHDA,respectively.② Necrotic cyst was founded in 7 cases (29.17%)with MFCP and 18 cases (60%)with PHDA(P＜0.05). Pseudocysts were demonstrated in 14 cases (58.33%)with MFCP and in 3 cases (10%)with PHDA (P＜0.001).Honeycombed change with tension within or around the lesion were demonstrated only in patients with MFCP.In addition,normal tissue of the pancreas was found within the lesion in 11 cases (45.83%)of MFCP and none in PHDA,which showed significant difference between two groups.Conclusion Mixed calcification and honeycomb with tension of CT findings are of significant value in differentiating PHDA from MFCP of the pancreatic head.

Pancreatic ductal adenocarcinoma and chronic mass-forming pancreatitis: Differentiation with dual-energy MDCT in spectral imaging mode.

OBJECTIVE: To investigate the value of dual-energy MDCT in spectral imaging in the differential diagnosis of chronic mass-forming chronic pancreatitis (CMFP) and pancreatic ductal adenocarcinoma (PDAC) during the arterial phase (AP) and the pancreatic parenchymal phase (PP). MATERIALS AND METHODS: Thirty five consecutive patients with CMFP (n=15) or PDAC (n=20) underwent dual-energy MDCT in spectral imaging during AP and PP. Iodine concentrations were derived from iodine-based material-decomposition CT images and normalized to the iodine concentration in the aorta. The difference in iodine concentration between the AP and PP, contrast-to-noise ratio (CNR) and the slope K of the spectrum curve were calculated. RESULTS: Normalized iodine concentrations (NICs) in patients with CMFP differed significantly from those in patients with PDAC during two double phases (mean NIC, 0.26±0.04 mg/mL vs. 0.53±0.02 mg/mL, p=0.0001; 0.07±0.02 mg/mL vs. 0.28±0.04 mg/mL, p=0.0002, respectively). There were significant differences in the value of the slope K of the spectrum curve in two groups during AP and PP (K(CMFP)=3.27±0.70 vs. K(PDAC)=1.35±0.41, P=0.001, and K(CMFP)=3.70±0.17 vs. K(PDAC)=2.16±0.70, p=0.003, respectively). CNRs at low energy levels (40-70 keV) were higher than those at high energy levels (80-40 keV). CONCLUSION: Individual patient CNR-optimized energy level images and the NIC can be used to improve the sensitivity and the specificity for differentiating CMFP from PDAC by use of dual-energy MDCT in spectral imaging with fast tube voltage switching.