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Clinical Article
Nomogram model based on clinical manifestations and MRI features to early predict the prognosis of peripancreatic collections in acute pancreatitis
LUO Jiang  LIU Tingting  ZHANG Xueying  JIANG Donglin  ZHANG Xiaoming 

Cite this article as: LUO J, LIU T T, ZHANG X Y, et al. Nomogram model based on clinical manifestations and MRI features to early predict the prognosis of peripancreatic collections in acute pancreatitis[J]. Chin J Magn Reson Imaging, 2023, 14(11): 68-76. DOI:10.12015/issn.1674-8034.2023.11.012.

[Abstract] Objective To explore the prognostic factors of acute pancreatitis (AP) and build a nomogram model based on clinical manifestations and MRI features to predict the prognosis of peripancreatic collections (PPCs) in early stages of AP.Materials and methods We conducted a retrospective study involving 102 patients with peripancreatic collections of AP admitted to our hospital from January 2016 to February 2023. Patients were categorized into two groups based on clinical and imaging follow-up outcomes: good prognosis and poor prognosis. A multifactorial logistic regression analysis was performed to establish a nomogram based on clinical manifestations and MRI features for early prognosis prediction. The nomogram's performance was evaluated by calculating the area under the curve (AUC) of receiver operating characteristic (ROC), bootstrap resampling, and visual inspection of the calibration curve. Additionally, decision curve analysis (DCA) was used to assess the nomogram's clinical utility.Results Of the 102 AP patients with peripancreatic collections, 77 had a good prognosis, while 25 had a poor prognosis. Compared to the good prognosis group, indicators associated with poor prognosis, such as complications of AP, Extrapancreatic Inflammation on MRI (EPIM), Bedside Index for Severity in AP (BISAP), the number of peripancreatic spaces related to PPCs, MR Severity Index (MRSI), the maximum dimensional area of PPCs, classification of PPCs, the diffusion range grading of PPCs involving sub-peritoneal spaces, and involvement of the abdominal wall and peripancreatic vessels, showed a significant increase in proportion (P<0.05). Multifactorial prognostic analysis revealed that MRSI, EPIM, maximal dimensional area of PPCs, and BISAP score were independent prognostic factors for early prognosis prediction of PPCs in AP. The nomogram demonstrated excellent performance, with an AUC of 0.946 (95% CI: 0.905-0.988) and excellent agreement between predicted and observed probabilities, as indicated by calibration curves. The DCA curve further confirmed its clinical utility.Conclusions A nomogram model based on clinical manifestations and MRI features can effectively predict the early prognosis of PPCs in AP.
[Keywords] acute pancreatitis;magnetic resonance imaging;peripancreatic collections;nomogram;predict;prognosis

LUO Jiang   LIU Tingting   ZHANG Xueying   JIANG Donglin   ZHANG Xiaoming*  

Sichuan Key Laboratory of Medical Imaging, Department of Radiology, the Affiliated Hospital of North Sichuan Medical College, Nanchong 637001, China

Corresponding author: ZHANG X M, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS 2022 North Sichuan Medical College Affiliated Hospital Research and Development Programme (Unveiling and Hanging) Project (No. 2022JB001); Provincial Key Laboratory and Special Cultivation Fund of North Sichuan Medical College in 2022 (No. CBY22-PT01).
Received  2023-07-04
Accepted  2023-10-27
DOI: 10.12015/issn.1674-8034.2023.11.012
Cite this article as: LUO J, LIU T T, ZHANG X Y, et al. Nomogram model based on clinical manifestations and MRI features to early predict the prognosis of peripancreatic collections in acute pancreatitis[J]. Chin J Magn Reson Imaging, 2023, 14(11): 68-76. DOI:10.12015/issn.1674-8034.2023.11.012.

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