BMC medical imaging · 2025
A scoring model for preoperative differentiation of high-enhancement pancreatic ductal adenocarcinoma from mass-forming chronic pancreatitis.
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Zhou Jiaping, Wang Xiaojie, Zhang Haifeng, Pan Yao, Wang Weilin, Yu Risheng
Аннотация
BACKGROUND: The present study aimed to establish a scoring model for the differential diagnosis of high-enhancement pancreatic ductal adenocarcinoma (hPDAC) versus mass-forming chronic pancreatitis (MFCP).
METHODS: A retrospective analysis was conducted on 81 patients: 40 with MFCP and 41 with hPDAC. Demographic and imaging characteristics were collected. Univariate, ridge regression and binary logistic regression analyses were performed to identify independent predictors and develop diagnostic models. The clinicoradiological model was subsequently converted into a weighted scoring model. Calibration tests, receiver operating characteristic (ROC) curves, area under the ROC curve (AUC), and cut-off points were assessed for both the clinicoradiological and scoring models.
RESULTS: Four independent predictors were included in the clinicoradiological model: lesion size (p = 0.012), carbohydrate antigen 19 - 9 (CA19-9) elevate (p = 0.003), irregular lesion shape (p = 0.024), and pancreatic duct cut-off (p = 0.003). Weighted scores were assigned as follows: CA19-9 elevate, 6 points; smaller lesion size, 2 points; irregular lesion shape, 2 points; and pancreatic duct cut-off, 7 points. The clinicoradiological model and the scoring model exhibited AUC values of 0.986 and 0.940, respectively, revealed no significantly difference observed between the two (p = 0.073, DeLong test). The scoring model was stratified into two ranges: 0-8 points indicating MFCP and 9-17 points indicating hPDAC.
CONCLUSIONS: A concise and practical scoring model for differentiating hPDAC from MFCP was developed, demonstrating strong diagnostic performance. A score of 8 points serves as the key demarcation line in this model.
METHODS: A retrospective analysis was conducted on 81 patients: 40 with MFCP and 41 with hPDAC. Demographic and imaging characteristics were collected. Univariate, ridge regression and binary logistic regression analyses were performed to identify independent predictors and develop diagnostic models. The clinicoradiological model was subsequently converted into a weighted scoring model. Calibration tests, receiver operating characteristic (ROC) curves, area under the ROC curve (AUC), and cut-off points were assessed for both the clinicoradiological and scoring models.
RESULTS: Four independent predictors were included in the clinicoradiological model: lesion size (p = 0.012), carbohydrate antigen 19 - 9 (CA19-9) elevate (p = 0.003), irregular lesion shape (p = 0.024), and pancreatic duct cut-off (p = 0.003). Weighted scores were assigned as follows: CA19-9 elevate, 6 points; smaller lesion size, 2 points; irregular lesion shape, 2 points; and pancreatic duct cut-off, 7 points. The clinicoradiological model and the scoring model exhibited AUC values of 0.986 and 0.940, respectively, revealed no significantly difference observed between the two (p = 0.073, DeLong test). The scoring model was stratified into two ranges: 0-8 points indicating MFCP and 9-17 points indicating hPDAC.
CONCLUSIONS: A concise and practical scoring model for differentiating hPDAC from MFCP was developed, demonstrating strong diagnostic performance. A score of 8 points serves as the key demarcation line in this model.