A nomogram based on multiparametric magnetic resonance imaging radiomics for prediction of acute pancreatitis activity

Abstract

Purpose: In acute pancreatitis (AP), disease activity is defined as the reversible manifestation of the disease. The aim of this study was to develop a nomogram for predicting disease activity in AP based on multiparametric magnetic resonance imaging (MRI) radiomics.

Methods: This retrospective study included 310 patients with first-episode AP from two medical centers in China. Patients from the first medical center were randomly divided into a training cohort (n = 122) and an internal validation cohort (n = 123) in a 5:5 ratio. Patients from the second medical center were used as the external independent validation cohort (n = 65). Radiomics features were extracted from multiparametric MRI images based on pancreatic parenchymal regions. The least absolute shrinkage and selection operator (LASSO) was used for feature screening, logistic regression was used to establish radiomic feature, and statistically significant laboratory parameters were incorporated to construct the nomogram. The area under the receiver operator characteristic curve assessed the predictive performance of the nomogram. Furthermore, decision curve analysis (DCA) was used to assess the clinical utility of the nomogram, and the disease activity was validated against follow-up clinical outcomes (e.g., organ failure progression, ICU admission) and imaging-confirmed changes within one-week after MRI.

Results: The AUCs of the radiomic signature were 0.808 (training cohort), 0.789 (internal validation cohort), and 0.783 (external validation cohort). Radiomic signature, extrapancreatic inflammation on MRI (EPIM) scores, and WBC count were identified as independent risk factors for the activity of AP and were therefore included in the nomogram. The AUC of the nomogram were 0.881 (training cohort), 0.922 (internal validation cohort) and 0.912 (external validation cohort). Additionally, the nomogram model obtained the greatest net benefit, according to the results of decision curves Based on the follow-up results, we also found that AP patients with higher disease activity were more likely to experience exacerbations.

Conclusions: This nomogram can accurately predict the activity of AP patients, thus providing objective monitoring of the patient's course and potentially improving patient prognosis.

Keywords: Acute pancreatitis; Disease activity; Magnetic resonance imaging; Radiomic nomogram.

Fig. 1

ROC curve for the activity of AP patients to evaluate the performance of the radiomics signature in the training cohort (a), the internal validation cohort (b), and the external validation cohort (c)

Fig. 2

The nomogram model incorporating the Rad-score, the EPIM scores, and WBC

Fig. 3

ROC curve for the activity of AP patients to evaluate the performance of the radiomic nomogram in the training cohort (a), the internal validation cohort (b), and the external validation cohort (c)

Fig. 4

A patient with a peripancreatic effusion on a T2WI image on the day of admission (a, b). The risk of disease activity is less than 20%, as assessed by the radiomic nomogram. During our follow-up, the patient’s T2WI images 6 days after admission showed almost absorption of the peripancreatic effusion (c, d) and gradual stabilization of clinical symptoms and laboratory indices

Fig. 5

A patient’s T2WI images within 2 days of admission show pancreatic parenchymal necrosis and peripancreatic necrotic fluid collection (a, b). The disease activity risk was > 80% as assessed by the radiomic nomogram. Contrast-enhanced computed tomography scan 7 days after MRI examination shows enlarged peripancreatic necrotic fluid collection (c, d). And during follow-up, the patient developed persistent respiratory failure